The Skeptics Guide to Emergency Medicine

Date: January 6, 2026  Guest Skeptic: Darren McKee is an author and speaker. He has served as a senior policy advisor and policy analyst for over 17 years. Darren hosts the international award-winning podcast, The Reality Check. He is also the author of an excellent, thought-provoking book called Uncontrollable: The Threat of Artificial Superintelligence and the Race to Save the World (2023). The book lays out what AI is, why advanced systems could pose real risks, and what individuals and institutions can do to increase AI safety.  We have discussed AI on the SGEM a few times: SGEM Xtra: Rock, Robot Rock – AI for Clinical Research SGEM#459: Domo Arigato Misuta Roboto – Using AI to Assess the Quality of the Medical Literature SGEM#460: Why Do I Feel Like, Somebody’s Watching Me – CHARTWatch to Predict Clinical Deterioration SGEM#472: Together In Electric Dreams – Or Is It Reality? AI already touches the emergency medicine world through triage, documentation (AI scribes), imaging, and patient communications. You argue in the book that we’re in exponential times, AI capabilities may accelerate, and that simple rules won’t reliably constrain advanced systems. All of which has implications for safety, bias, reliability, and public trust in healthcare.  The book is divided into three sections. I expanded on that so I could ask Daren questions about five different areas. Listen to the SGEM Xtra podcast to hear his responses: Five Questions for Darren Origin Story & Stakes: The book's introduction contrasts the confident historical skepticism about nuclear power with the speed with which reality overtook it. Give us a brief history of nuclear power. Then the book pivots to today’s AI and uses an analogy of humanity’s "smoke detector " moment. Explain what that is and why you decided now was the time to write this book. Part I: What is Happening? In the first part of the book, you build a narrative from AI to AGI to ASuperI. Can you provide some definitions of those terms and explain why they matter? Can you walk us through how current systems (large language models and image models) work at a high level? Why did emergent capabilities surprise even their builders, and why don’t we fully understand what’s happening under the hood of these machines? Part II: What are the Problems? You outline six core challenges: exponential progress, uncertain timelines (and expert disagreement), the alignment problem, why simple rules (à la “Three Laws”) fail, how control erodes as tech integrates into our lives, and how all this aggregates into societal risk. We are not going to go through all six, but could you explain the alignment problem? The other topic I wanted to expand on was the Three Laws. Part III: What Can We Do? The last two chapters get practical and discuss what institutions can do for safe AI innovation and what individuals can do to increase AI safety. Give us your top 2 or 3 institutional moves (transparency, evaluation, guardrails). How about your top 2 to 3 personal moves that listeners can do?  AI in the Emergency Department: Bring it home for us in the emergency department if you can. When an AI-enabled tool is proposed for triage, documentation, or image support, what are the three questions every emergency clinician or leader should ask before adoption?  The SGEM will be back next episode with a structured critical appraisal of a recent publication. Our goal is to reduce the knowledge translation (KT) window from over 10 years to less than 1 year using the power of social media. So, patients get the best care, based on the best evidence.   Remember to be skeptical of anything you learn, even if you heard it on the Skeptics’ Guide to Emergency Medicine.

Reference: Aronson PL, et al. Prediction Rule to Identify Febrile Infants 61–90 Days at Low Risk for Invasive Bacterial Infections. Pediatrics. September 2025 Date: January 6, 2026 Dr. Jillian Nickerson Guest Skeptic: Dr. Jillian Nickerson is a pediatric emergency medicine attending at Children’s National Hospital and Assistant Professor of Pediatrics and Emergency Medicine at The George Washington University School of Medicine and Health Sciences in Washington, DC. Prior to completing her PEM fellowship, she completed an emergency medicine residency at Mount Sinai in New York. Now she is also the associate program director for the pediatric emergency medicine fellowship program at Children’s National Hospital. Background: Fever is a common complaint that we encounter in the emergency department. In general, we want to be careful in our counseling and our practice not to perpetuate many of the myths and misconceptions that contribute to fever phobia. But there are certain populations where fever does get us a bit worried. When infants present with fever, we have to think about evaluating for other sources of infection such as bacteremia or meningitis, termed invasive bacterial infections (IBI). Fortunately, the prevalence of IBI tends to be low, but missing one could lead to significant morbidity or mortality. How do we determine whom to test and what tests to perform? We’ve covered multiple clinical decision rules for risk-stratifying febrile infants before on the SGEM: SGEM #171: Step-by-Step Approach to the Febrile Infant SGEM#296: She’s Got the Fever but Does She Need an LP, Antibiotics or an Admission? SGEM#341: Are the AAP Guidelines for the Evaluation and Management of the Well-Appearing Febrile Infant SGEM#387: Lumbar Punctures in Febrile Infants with Positive Urinalysis SGEM #474: Help! Which Clinical Decision Aid Should I Use to Risk Stratify Febrile Infants? Some of these clinical decision rules like Step by Step can be applied to infants up to 90 days. Others like the 2021 American Academy of Pediatrics (AAP) clinical practice guideline and the Pediatric Emergency Care Applied Research Network (PECARN) clinical decision rule, only include infants up to 60 days. Clinical Question: Is there an accurate prediction rule to identify well-appearing febrile infants 61–90 days old who are at low risk for invasive bacterial infection (IBI)? Reference: Aronson PL, et al. Prediction Rule to Identify Febrile Infants 61–90 Days at Low Risk for Invasive Bacterial Infections. Pediatrics. September 2025 Population: Non-ill-appearing febrile infants 61–90 days who had evaluation with both urinalysis/urine dipstick and blood culture Excluded: infants who were critically ill (ESI level 1, intubated, received vasoactive medication), death in the ED, prematurity ≤32 weeks, substantial pre-existing medical or surgical conditions, skin or soft tissue infections, home antibiotic use before ED visit Intervention: Derivation of a clinical prediction rule using urinalysis, temperature, ANC, ± procalcitonin. Comparison: none Outcome: Primary Outcome: Accuracy of the prediction rule to identify infants at low risk for IBI, defined as bacteremia or bacterial meningitis. Secondary Outcomes: none Trial: Retrospective cohort study Dr. Nathan Kuppermann Dr. Paul Aronson Authors: Dr. Paul Aronson is a pediatric emergency medicine attending and Professor of Pediatrics and Emergency Medicine at Yale School of Medicine. He is the Deputy Director of the Pediatric Residency Program and leads the Research Track. Dr. Nathan Kuppermann is executive vice president, chief academic officer of Children's National Hospital and director of the Children's National Research Institute. He also serves as chair of the Department of Pediatrics and associate dean of Pediatric Academic Affairs at the George Washington University School of Medicine and Health Sciences. Dr. Kuppermann is a pediatric emergency medicine physician, clinical epidemiologist and leader in emergency medical services for children. Authors’ Conclusions: We derived two accurate clinical prediction rules to identify febrile infants 61–90 days at low risk for invasive bacterial infections when urine and blood testing are obtained. Prospective validation is needed. Quality Checklist for Clinical Decision Rules: The study population included or focused on those in the ED. Yes Where was the study conducted (external validity). Conducted across 17 EDs in the PECARN Registry over 10 health systems (with many pediatric EDs). The patients were representative of those with the problem. Unsure. All important predictor variables and outcomes were explicitly specified. Yes This is a prospective, multicenter study including a broad spectrum of patients and clinicians (level II). No Clinicians interpret individual predictor variables and score the clinical decision rule reliably and accurately. Yes Is this an impact analysis of a previously validated CDR (level I study)? No For Level I studies, impact on clinician behavior and patient-centric outcomes is reported. N/A The follow-up was sufficiently long and complete. Yes The effect was large enough and precise enough to be clinically significant. Unsure. Funding of the Study: Eunice Kennedy Shriver National Institute of Child Health and Human Development. No financial conflicts of interest. Did the authors declare any conflicts of interest? The authors reported no conflicts of interest to disclose. Results: They included 4,952 infants. The median age was 72 days, and 54% male. Median maximum qualifying temperature was 38.7°C. Urinalysis was positive in 18%, LP/CSF testing was performed in 10%, antibiotics were given in 26%, and 34% were hospitalized. Approximately 100 (2%) tested positive for IBI with 95 cases of bacteremia and 5 cases of bacterial meningitis. A little bit over half (57%) with bacteremia also had UTI. Of those infants 1207 (24%) had procalcitonin and absolute neutrophil count (ANC) measured. That group had 27 with IBIs with 2 being bacterial meningitis.  Low risk predictors: Procalcitonin <0.24 ng/mL ANC < 10,710 cells/mm3 Key Results: This clinical prediction rule for risk-stratifying febrile infants 61-90 days based on urine and temperature >38.9°C had a sensitivity of 86%, specificity of 58.9%, NPV of 99.5%, and -LR of 0.24, but still needs external validation. This decision rule missed 14 infants with IBIs (13 with bacteremia and one with Group B Strep meningitis). There was a second decision rule that included procalcitonin ≤0.24 ng/mL and ANC  ≤10,710 cells/mm3. The derivation sensitivity was 100% but dropped to 85.2% on cross-validation. The specificity was around 65-68%. NPV ranged from 99.5-100%, Negative likelihood ratio was 0.22. Tune in to the podcast to hear Drs. Aronson and Kuppermann answer our nerdy questions. Selection Bias This secondary analysis included only febrile infants aged 61-90 days who underwent both urine and blood testing. A total of 20,211 infants in that age range had fevers, but only 30% of them had urine and blood cultures obtained. It’s also mentioned that the included infants had higher maximum qualifying temperatures, more assigned ESI triage level 2, and received parenteral antibiotics or were hospitalized. It’s possible that these infants may have been deemed sicker than those who did not undergo testing. The study was unable to capture the clinical decision-making that determined which infants underwent testing and which did not. How do you think this selection bias could impact your results? Overfitting the Data  The PCT and ANC rule showed perfect sensitivity in derivation but lower sensitivity on cross-validation (4 false negatives). This is a pattern that may represent model instability especially when dealing with uncommon outcomes. Increasing model complexity can improve apparent performance in the derivation set but worsen performance in validation because of overfitting. What steps did you take to try to limit overfitting and what changes if any do you anticipate in making to this CDR for external validation? The “Original” PECARN  Although this new clinical decision rule has a high NPV, we must also recognize the limitation that the prevalence of IBI is low. As disease prevalence decreases, NPV increases. The study team did look at this with the “original” PECARN rule’s rounded cutoffs of procalcitonin ≤0.5 and ANC ≤4000 without urinalysis. The sensitivity was 100% (95% CI 87.2-100) and specificity was 49.7% (95% CI 46.8-52.6). This was in the supplemental section. While we’re waiting for external validation of this new clinical decision rule, why not use the tried-and-true existing clinical decision rule? One less thing with new cutoffs for inflammatory markers to remember right? 90 Days and Beyond!  The clinical decision rule in this study, if and when externally validated, would apply to infants up to 90 days. What about beyond that? There’s quite a bit of variation in practice when it comes to workup for infants 2-6 months presenting with fever to the emergency department. How do you approach the workup of infants over 90 days?  Prematurity Many of the existing clinical decision rules exclude infants born prematurely. In reality, we also encounter these patients in the ED. How do you approach the workup of a febrile premature infant?  Bonus Question: Respiratory Virus Testing You report that you were unable to assess the results of respiratory viral testing as a predictor because of missing data, but we do know that febrile infants with viral infections do seem to have lower prevalence of IBI compared to those without. In your clinical practice, how do you manage infants with viral symptoms?

Date: January 17, 2026 Reference:  Casey et al. RSI Investigators and the Pragmatic Critical Care Research Group. Ketamine or Etomidate for Tracheal Intubation of Critically Ill Adults. NEJM. 2025 Dec Guest Skeptic: Dr. Scott Weingart is an ED Intensivist from New York. He did fellowships in Trauma, Surgical Critical Care, and ECMO. Scott is best known for talking to himself about Resuscitation and Critical Care on the podcast EMCrit, which has been downloaded more than 50 million times. Scott and I will both be presenting at Incrementum 2026 in Spain.  Case:  You’re working an evening shift in a busy tertiary-care emergency department (ED). Emergency Medical Services (EMS) rolls in a 62-year-old woman with a history of hypertension and type 2 diabetes. She’s febrile at 39.2°C, tachycardic at 125 beats/min, hypotensive at 86/52 mm Hg despite 2 L of crystalloid and breathing 32/min on a non-rebreather with oxygen saturation of 88%. Chest X-ray shows a right‑lower‑lobe infiltrate; lactate is 5.6 mmol/L. She’s now on a norepinephrine infusion at 0.15 µg/kg/min and still looks exhausted and altered. You decide she needs emergent rapid sequence intubation (RSI) for worsening work of breathing and impending respiratory failure. The respiratory therapist is at the bedside, the pharmacist has arrived with the RSI box, and your resident says: “For induction, should we go with ketamine because she’s septic and hypotensive, or etomidate because we’re worried about pushing her over the edge?” Background: Intubating critically ill patients can be one of those high-stakes, high-adrenaline things we do often in emergency medicine (EM), but the physiology is stacked against us. These patients are often hypoxic, hypotensive, acidotic and catecholamine-depleted before we even reach for the laryngoscope. Emergency airway registries and multicentre cohorts consistently report serious peri-intubation complications (profound hypotension, hypoxemia, cardiac arrest, failed or difficult intubation) in roughly 10% to 20% of critically ill adult intubations in the ED and ICU [1].  Even a single episode of severe hypotension or hypoxemia during intubation is associated with increased mortality and organ failure in the ICU population [2].  So, the choice of induction agent seems to matter. Etomidate became the darling of emergency RSI because it has a rapid onset, short duration, and relatively preserved hemodynamics compared with agents like thiopental or high‑dose propofol [3].  The flip side is adrenal suppression: a single dose transiently inhibits 11‑β hydroxylase and measurably blunts cortisol production for 24–72 hours. Observational studies and post‑hoc analyses in septic shock raised alarms that etomidate might increase mortality by worsening relative adrenal insufficiency, leading some guidelines and regulators to discourage or even remove etomidate in sepsis [4]. But those were mostly non-randomized data, and prior RCTs comparing etomidate with other agents were small and gave conflicting signals about mortality. Ketamine, by contrast, is a dissociative NMDA antagonist with a very different vibe. It provides profound amnesia and analgesia, maintains airway reflexes to some degree, and has sympathomimetic properties that can increase heart rate and blood pressure by catecholamine release [5]. Those properties have made ketamine attractive in shocked patients where we’re worried that propofol or midazolam will “tank the pressure”. However, in catecholamine-depleted septic shock, ketamine’s direct myocardial depressant effects may become more apparent, and registry data suggest its hemodynamic advantage over etomidate is not as clear as many of us were taught on shift.  Old concerns that ketamine raises intracranial pressure have largely been debunked in modern neurocritical care literature, further widening its appeal.  Other agents are still in the mix. Propofol remains widely used in operating theatre practice and some EDs because of its familiarity and ease of titration, but it predictably causes vasodilation and negative inotropy, making it a frequent offender in peri‑intubation hypotension among critically ill patients [6]. Benzodiazepines (midazolam) have a slower onset, a more variable effect and a longer half‑life, and when used as primary induction agents in shock, they’ve been associated with more hypotension and delirium compared with etomidate or ketamine. Fentanyl and other opioids are often layered on for analgesia or “blunting” the sympathetic surge, but they can also precipitate abrupt hypotension and apnea in the already fragile patient. So for years we’ve been stuck between the theoretical adrenal toxicity of etomidate and the hoped‑for hemodynamic benefits of ketamine, without a large, definitive randomized trial in ED/ICU patients powered for patient‑important outcomes like mortality. Clinical Question: In critically ill adults undergoing emergency tracheal intubation in the ED or ICU, which induction agent is better, ketamine or etomidate? Reference:  Casey et al. RSI Investigators and the Pragmatic Critical Care Research Group. Ketamine or Etomidate for Tracheal Intubation of Critically Ill Adults. NEJM. 2025 Dec Population: Critically ill adults (≥18 years) undergoing or planned to undergo tracheal intubation in an ED or ICU, where the treating clinician intended to use either ketamine or etomidate for induction, conducted at six EDs and eight ICUs in the US. Excluded: Known or suspected pregnancy, prisoners. acute trauma as the primary indication for intubation, immediate “crash” intubations where there was no time for randomization, known or suspected allergy or contraindication to either ketamine or etomidate, situations where the treating clinician believed that either ketamine or etomidate was specifically required or contraindicated (strong clinician preference), or patients previously enrolled in the trial. Intervention: The Ketamine group received 1.0–2.0 mg/kg given immediately before intubation.  Treating clinicians chose neuromuscular blocking agents, pre‑ and post‑intubation vasopressors, fluids, and other medications according to local practice. Comparison: The Etomidate group received 0.2–0.3 mg/kg. Again, all other aspects of airway management and resuscitation were at the clinician's discretion. Outcomes: Primary Outcome: In-hospital death by day 28 after randomization.  Secondary Outcomes: A composite of “cardiovascular collapse” during the interval between induction of anesthesia and 2 minutes after tracheal intubation, defined as any of: Systolic BP <65 mm Hg, or A new vasopressor started or an increase in vasopressor dose, or Cardiac arrest.  Exploratory Outcomes Type of Study: A therapeutic, parallel‑group, multicenter randomized controlled trial Authors’ Conclusions: “Among critically ill adults undergoing tracheal intubation, the use of ketamine to induce anesthesia did not result in a significantly lower incidence of in-hospital death by day 28 than etomidate.” Quality Checklist for Randomized Clinical Trials: Did the study population include or focus on ED patients? Yes Were patients adequately randomized? Yes  Was the randomization process concealed? Yes Were patients analyzed in the groups to which they were randomized (intention‑to‑treat)? Yes Were patients recruited consecutively (no selection bias)? Unsure Were both groups similar with respect to prognostic factors? Yes Were all participants (patients, clinicians, outcome assessors) blinded? No Were all groups treated equally except for the intervention? Unsure Was follow‑up complete (≥80% in both groups)? Yes Were all patient‑important outcomes considered? Yes Was the treatment effect large enough and precise enough to be clinically significant? No Who funded the trial? The trial was funded by the Patient-Centred Outcomes Research Institute (PCORI), the US National Heart, Lung, and Blood Institute, and the US Department of Defence, among others; the funders had no role in study design, conduct, analysis, or manuscript preparation.  Did the authors declare any conflicts of interest? Several authors reported research funding and consulting fees from various organizations (NIH, DoD, Octapharma, monitoring companies), although none were manufacturers of ketamine or etomidate. Results: They randomized 2,365 patients with a median age of 60 years, ~42% female, and ~56% intubated in the ED.  Nearly half had sepsis or septic shock, the median APACHE II score was 18, and about 22% were receiving vasopressors in the hour before intubation.   Key Result: For critically ill adults undergoing emergency tracheal intubation in the ED/ICU, ketamine and etomidate produced similar 28-day in-hospital mortality, but ketamine was associated with more cardiovascular collapse and hypotension around the time of intubation. Primary Outcome: In-hospital death by day 28: Ketamine 28.1% vs Etomidate 29.1% Risk difference adjusted for trial site: −0.8% (95% CI: −4.5% to 2.9%). Secondary Outcomes: Open Label Open‑label: This was an open-label trial, with neither clinicians nor research staff being masked to assignment. The lack of blinding can bias both cointerventions (performance bias) and outcome measurement (detection bias), especially for outcomes that rely on clinician judgment. The primary outcome (death by day 28) may not be impacted by this, but the key secondary outcome, like cardiovascular collapse, is partly defined by starting or escalating vasopressors, which is inherently a clinician’s decision. If clinicians believed ketamine was safer or more pressure-friendly, they might delay vasopressors or, conversely, might treat etomidate patients more aggressively with prophylactic pressors, biasing the composite in either direction.

Date: January 5, 2026 Reference: Robblee et al. 2025 guideline update to acute treatment of migraine for adults in the emergency department: The American Headache Society evidence assessment of parenteral pharmacotherapies. Headache 2025 Dec Happy New Year, SGEMers! What better way to start 2026 than with an SGEM Xtra about migraine headaches? We were originally scheduled to record this episode in December, but circumstances changed. This is another SGEM Xtra and not the typical structured critical appraisal with a checklist. It will be a conversation about what we should be doing and should stop doing when treating migraine patients in the ED based on the new American Headache Society (AHS) guidelines. However, you will find a standard SGEM nerdy critical appraisal at the end of this blog post. Migraine is one of the most common causes of headache visits to the ED, representing ~¼ of the 3.5 million annual headache-related visits in the US. Despite prior guidelines, ED practice is still all over the map, and patients sometimes leave without much relief. The AHS has just released the 2025 guideline update on parenteral pharmacotherapies and nerve blocks for adult ED migraine. To help us understand these new guidelines, we are joined by two neurologists who literally wrote the guidelines. Dr. Jennifer Robblee Dr. Jennifer Robblee (lead guideline author) is a Board‑certified neurologist and headache specialist at Barrow Neurological Institute in Phoenix. Her practice focuses on refractory migraine and status migrainosus. She trained at the University of Toronto (MD, neurology residency, MSc) and completed a headache fellowship at the Mayo Clinic Scottsdale.  Jennifer is the third eurologist to be on the SGEM. We’ve had Dr. Jeff Saver and Dr. Ravi Garg discuss thrombolytics and stroke. This will be an example that not all of neurology and emergency medicine intersect over stroke care.  Dr. Serena Orr Dr. Serena Orr (senior guideline author) is a pediatric neurologist, headache subspecialist, and director of the pediatric headache program at Alberta Children’s Hospital in Calgary. Serena has a strong interest in acute treatment of migraine, tech‑based treatment solutions, and psychosocial factors affecting migraine in kids and teens. The AHS guideline committee uses a 5-year update cycle for guidelines. Since 2016, 26 new RCTs and 20 injectable treatments, including nerve blocks (GONB, SONB, SPG) and eptinezumab.  Unfortunately, ED migraine outcomes are still not great. Only ~37% of ED patients achieve headache freedom at discharge. These new guidelines were trying to answer two questions.  Which injectable meds are effective in adults with migraine in the ED? Are nerve blocks effective in adults with migraine in the ED?  Top 5 things ED should know about the 2025 AHS Migraine Guidelines Listen to the SGEM podcast to hear Jennier and Serena discuss the top five things emergency physicians should know about the 2025 migraine guidelines. 1. Prochlorperazine IV & Greater Occipital Nerve Blocks (GONB) Are Now Level A “Must Offer” IV prochlorperazine and greater occipital nerve blocks (GONB) are Level A - must offer or adults presenting to the ED with a migraine attack requiring parenteral therapy (if no contraindications).  Questions: This is a big upgrade from 2016. Why did prochlorperazine and GONB earn Level A status in 2025? Practically, what does that look like in an ED order set? Are you imagining that everyone gets prochlorperazine? For the EM docs who have not been performing occipital nerve blocks, how steep is the learning curve? 2. Hydromorphone Is Level A “Must NOT Offer” Hydromorphone IV: Level A - Must NOT offer for migraine in the ED.  Questions: Let’s talk about opioids. Hydromorphone is now ‘must NOT offer’, what tipped the scale to Level A harm/no benefit? “Must NOT offer” seems like a strong statement (thou shalt not), is there not a potential clinical situation where an opioid still should be offered? How do we balance real‑world pressures, patient expectations, throughput, Press Ganey scores with an anti‑opioid, evidence‑based stance? It’s going to impact ED docs and not neurologists. 3. The Level B Recommendations:  Level B - “Should offer” for headache requiring parenteral therapy (Dexketoprofen IV, ketorolac IV, metoclopramide IV, subcutaneous sumatriptan, and supraorbital nerve blocks [SONB]).  Dexamethasone IV remains Level B “should offer” for recurrence prevention from the 2016 guidance.  Questions: If Level A is your starting lineup, who’s on the bench as your Level B ‘should offer’ options, and when do you pull them in? Is there a preferred sequence – dopamine antagonist first, then NSAID, then triptan, or is it more patient‑specific? How should ED clinicians think about dexamethasone? Is it still a routine add‑on, or more selective? 4. Nerve Blocks Are Mainstream GONB: Level A - Must offer. SONB: Level B - May/should offer when GONB is insufficient or not possible.  Questions: For a busy ED, how realistic is it to integrate occipital and supraorbital nerve blocks into standard migraine care? What’s the pragmatic advice on training?   Can EM doctors become competent with blocks via bedside teaching and FOAMed resources> 5. Big Evidence Gaps No meta‑analyses were possible because of significant heterogeneity in methods and outcomes. Additional ED-specific outcomes, such as pain relief at 1 hour. Asking about patient-oriented outcomes (POO) such as “Would you want this treatment again on your next ED visit?” Need ED‑specific data on eptinezumab (currently Level U for general ED use despite strong outpatient data).  Questions: If you had unlimited funding for one ED migraine randomized control trial, what would you test, and what outcome would you choose? You recommended a 1‑hour endpoint for ED trials. How does that change how we design and interpret future studies? I love the idea of the patient-centred outcome: ‘Would you want this again?’ How do we make sure future trials include that kind of measure? Five Limitations of the AHS Migraine Guideline The goal here is not to dunk on the guideline; there are limitations to any study.  This is just a nerdy conversation about how the next cycle could be improved. Listen to the SGEM Xtra podcast to hear Jennifer and Serena respond.  Limitation 1: Risk of Bias Tool & Study Quality Nuances Question: “You explicitly say that some ‘class I’ RCTs had small sample sizes or weird time points that made you less confident. From an EBM standpoint, how did you reconcile the AAN RoB categories with what we’d call imprecision and indirectness in GRADE?” Limitation 2: External Validity - Not All RCTs Were ED RCTs Question: “Many of the trials you had to work with weren’t actually done in ED settings – eptinezumab and SPG blocks being two examples. How worried should we be about extrapolating outpatient data into the ED, where patients are often later in the attack, more distressed, and maybe have different comorbidities?” Limitation 3: Active Comparators of Unclear Significance Question: “You call out trials that compare against ‘iffy’ active controls (valproate, dexamethasone, etc). In EBM terms, this muddies the signal. If you beat a weak comparator, is your drug actually good? How did you handle that when grading evidence and crafting recommendations?” Limitation 4: No Meta‑Analyses; Reliance on Narrative Synthesis Question: “From a methodological point of view, the fact that you couldn’t meta‑analyze anything limits precision and makes it hard to quantify effect sizes. How should EM clinicians interpret Level A or B recommendations that rest on narrative synthesis instead of pooled estimates?” Limitation 5: Broader Biases - Publication, Selection, and the ED Reality Question: “Zooming way out, every guideline sits on top of the published RCT iceberg. How much do you worry about publication bias, selection bias, and the fact that ED patients we see at 3 am rarely look like the trial population?” Remember to be skeptical of anything you learn, even if you heard it on the Skeptics’ Guide to Emergency Medicine.  Critical Appraisal Reference: Robblee et al. 2025 guideline update to acute treatment of migraine for adults in the emergency department: The American Headache Society evidence assessment of parenteral pharmacotherapies. Headache 2025 Dec Background: Migraine is one of the most common reasons people roll into the ED with a headache, and it’s not just “a bad headache.” It’s a chronic neurologic disorder that affects over a billion people globally and is consistently among the top causes of years lived with disability, especially in young and middle-aged adults [1.2].  In the ED specifically, migraine accounts for about one‑quarter of the ~3.5 million headache-related visits per year in the US. That’s a lot of stretchers tied up with photophobic patients in dark rooms. Clinically, migraine is defined by the International Classification of Headache Disorders (ICHD‑3). Typical attacks last 4 to 72 hours and are moderate to severe, often unilateral, pulsating, and worsened by routine physical activity. They’re commonly accompanied by nausea and/or vomiting and photophobia/phonophobia [3]. Migraine without aura is the most common type; migraine with aura adds transient focal neurologic symptoms (usually visual) that precede or accompany the headache. Diagnosis in the ED is clinical: apply ICHD‑3 criteria, look for a typical migraine phenotype, and screen for red flags (fever, meningeal signs, focal deficits, thunderclap onset, immunocompromise, anticoagulation, etc.) to rule out secondary causes. Outside the ED,

Date: December 23, 2025 Reference: Todd et al. Antihypertensive prescription is associated with improved 30-day outcomes for discharged hypertensive emergency department patients. J Am Coll Emerg Physicians Open. 2024 Guest Skeptic: Dr. Mike Pallaci is a Professor of Emergency Medicine at Northeast Ohio Medical University and a Clinical Professor of Emergency Medicine at Ohio University Heritage College of Osteopathic Medicine. He currently serves as Core Faculty for the USACS EM Residency at Summa Health System in Akron, OH where he is also Medical Director for the Virtual Care Simulation Lab, Director for the Simulation Medicine Fellowship and Vice Chair for Faculty and Resident Development. Over the course of his 24-year career in EM (15 in academics), he has worked in EDs with volumes ranging from 6,000 to 85,000 per year in urban and rural areas, in community and academic institutions, and has served as Program Director for two EM residencies. He has given lectures and published podcasts and articles in all areas of Emergency Medicine, including at the ACOEP Scientific Assembly, on the EM:RAP platform and right here on the SGEM. Prior research has resulted in book chapters, journal publications and presentations at multiple regional, national and international conferences on numerous topics including medical education, chest pain, pain management, gender bias, documentation, wellness, medicolegal issues, emergency ultrasound, hypertension and others. Case: A 47-year-old male presents to the emergency department (ED) with an ankle sprain. Admitting vital signs include a blood pressure of 210/130, which is similar on repeat measurements. He has no complaints except for ankle pain. He is in good health, has no known medical history, and has a primary care doctor whom he hasn't seen in about 6 or 7 years. Background: Hypertension is one of the most common “incidental” findings in the ED. In the US, there are over 900,000 annual ED visits with elevated blood pressure, and that number is climbing each year. Up to a third of these patients have no prior diagnosis of hypertension. Chronic uncontrolled blood pressure is strongly associated with myocardial infarction, stroke, heart failure, renal failure, and death, so these “incidental” readings are not benign. Standard outpatient care focuses on confirming the diagnosis with repeated measurements and then starting long-term therapy (lifestyle plus medications) to reduce cardiovascular events and mortality over the years, with randomized trial and meta-analytic evidence that treating hypertension reduces composite cardiovascular events and death. The ED, however, sits at an awkward intersection between chronic disease and acute care. Many patients we see with elevated blood pressure are asymptomatic or have nonspecific complaints, with no clear end-organ damage. Guidelines generally allow ED physicians considerable discretion about whether to initiate oral antihypertensives at discharge versus simply arranging follow-up. In 2025, the American College of Emergency Physicians (ACEP) published an updated policy regarding patients with asymptomatic markedly elevated blood pressure. They asked whether ED medical intervention reduces rates of adverse outcomes. They provided a Level C Recommendation that said: In patients with asymptomatic markedly elevated blood pressure, routine ED medical intervention is not required. In select patient populations (eg, poor follow-up), emergency physicians may treat markedly elevated blood pressure in the ED and/or initiate therapy for long-term control. [Consensus recommendation] Patients with asymptomatic markedly elevated blood pressure should be referred for outpatient follow-up. [Consensus recommendation] Previous work suggests that starting antihypertensives from the ED is safe and improves short-term blood pressure control in high-risk populations. Still, there has been very little evidence about patient-oriented short-term outcomes (myocardial infarction, stroke, heart failure, death, and ED revisits). Clinical Question: Among adult ED patients discharged with a diagnosis of hypertension and not on antihypertensive therapy, is an ED discharge prescription for an oral antihypertensive medication associated with a lower 30-day risk of severe hypertension-related adverse events, death, or ED revisits? Reference: Todd et al. Antihypertensive prescription is associated with improved 30-day outcomes for discharged hypertensive emergency department patients. J Am Coll Emerg Physicians Open. 2024 Population: Adult patients (≥18 years) seen and discharged from an ED within a single hospital system with a primary or secondary ED discharge diagnosis of essential (primary) hypertension and hypertensive urgency without prior treatment for hypertension during the previous 18 months. Excluded: Patients admitted to the hospital or to ED observation. Those who died in the ED. Patients without documented elevated blood pressure (BP <140/90). Pregnant patients. ED stay >48 hours. Anyone prescribed an antihypertensive in the 18 months prior. Patients with a severe adverse event (AE) that were already present at ED discharge. Visits with missing gender or race data. Exposure: Receiving a prescription for an oral antihypertensive medication at ED discharge. Comparison: Discharged hypertensive ED patients meeting the same inclusion/exclusion criteria who did not receive an antihypertensive prescription at ED discharge. Outcome: Primary Outcome: Severe composite adverse events from hypertension within 30 days of ED discharge (Acute aortic catastrophe, Acute heart failure, Myocardial infarction, Hemorrhagic stroke, Ischemic stroke or Hypertensive encephalopathy) Secondary Outcomes: All-cause death within 30 days of ED discharge and ED revisit within 30 days of ED discharge. Type of Study: Retrospective observational cohort study Authors’ Conclusions: “Prescription antihypertensive therapy for discharged ED patients is associated with a 30-day decrease in severe adverse events and ED revisit rate.” Quality Checklist for Observational Study: Did the study address a clearly focused issue? YES Did the authors use an appropriate method to answer their question? YES Was the cohort recruited in an acceptable way? YES Was the exposure accurately measured to minimize bias? UNSURE Was the outcome accurately measured to minimize bias? UNSURE Have the authors identified all important confounding factors? NO Was the follow-up of the subjects sufficient? UNSURE How precise are the results? YES Do you believe the results? YES Can the results be applied to the local population? YES Do the results fit with other available evidence? YES Who funded the trial? The study is explicitly described as unfunded research. Did the authors declare any conflicts of interest? NO Results: After applying the inclusion and exclusion criteria, they had 93,512 ED visits with a discharge diagnosis of hypertension. The mean age was 59 years, 57% female, 59% white, 10% received antihypertensive treatment in the ED before discharge, and 5% received an antihypertensive prescription at ED discharge. Patients prescribed antihypertensives at discharge were younger, more often male and Black, had higher systolic and diastolic blood pressure, lower comorbidity burden, were more likely to have received antihypertensives in the ED, and less likely to have prior heart failure. Key Result: One in 20 hypertensive ED patients received an antihypertensive prescription at discharge; among those who did, the adjusted odds of severe 30-day adverse events and ED revisits were substantially lower, with no difference in 30-day mortality compared with those who did not receive a prescription. Primary Outcome: Severe adverse events within 30 days 0.7% untreated vs 0.2% treated aOR 0.224 (95% CI; 0.106 to 0.416, p<0.001) Number needed to treat (NNT) 183 (95% CI; 161 to 247) to prevent one adverse event. Secondary Outcomes All cause death at 30 days: No statistical difference between groups (5 deaths in treated vs 105 untreated, aOR 1.445, 95% CI; 0.476–3.583, p=0.467). ED revisit within 30 days: Fewer in the treated group (10% vs 16%). Adjusted aOR 0.610 (95% CI; 0.547 to 0.678, p<0.001). NNT 18 (95% CI 16 to 23) to prevent one ED revisit. Individual Adverse Events: Antihypertensive therapy was significantly associated with decreased odds of acute heart failure (aOR 0.183, 95% CI; 0.056 to 0.441). No statistical difference in aortic catastrophe, MI, ischemic stroke, hemorrhagic stroke, and hypertensive encephalopathy, with some components having zero events in the treated group. 1. Residual Confounding: This is an observational treatment study, not a randomized trial, so the decision to prescribe is influenced by physician judgment and patient factors. Treated patients were younger, had less comorbidity, and were more likely to have received antihypertensives in the ED and to get follow-up prescriptions later. This suggests that they differed systematically from untreated patients. Even with multivariable adjustment and inverse probability weighting, unmeasured factors such as medication adherence, health literacy, or clinician concern could both drive the decision to treat and influence the likelihood of good outcomes. 2. Composite Endpoint: Death, severe adverse event or....ED revisit. That's kind of like a composite endpoint of you die, you have a myocardial infarction, or you sprain your ankle. As you would expect, the vast majority of patients who met one of these criteria (14,208 out of 14,978, almost 95%) had repeat ED visits. There was no significant difference in deaths. While there was a statistically significant difference in severe adverse events, the NNT to prevent one was 183,

Date: November 27, 2025  Guest Skeptic: Dr. Justin Morgenstern is an emergency physician and the creator of the #FOAMed project called www.First10EM.com Case: You are looking after a 65-year-old man who appears to be in septic shock. He presented after five days of fever and cough, and is now severely lethargic and hypotensive on arrival. You give him antibiotics and IV fluids immediately, but an hour later, his lactate comes back at 5, and you need to start norepinephrine to keep his MAP above 65. You put in a call to the intensive care unit (ICU) to get him transferred, and the intensivist asks you whether you have started personalized hemodynamic resuscitation targeting capillary refill time. You don’t want to sound dumb, but what the heck is personalized hemodynamic resuscitation protocol targeting capillary refill time? Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is the most severe end of that spectrum. Patients with sepsis have persistent hypotension requiring vasopressors to maintain MAP ≥65 mm Hg and a lactate >2 mmol/L despite adequate volume resuscitation (Sepsis‑3). In high-income countries, mortality has fallen but remains substantial.  In many settings, mortality can be between 30% to 70%. High-quality ED care requires early recognition, IV antibiotics, source control, hemodynamically directed fluids, and vasopressors. The management of septic shock has changed dramatically since the time that Ken and I started practice. We went through a period in which a very aggressive bundle of care was proposed, based on work by Dr. Emanuel Rivers, published in the NEJM in 2001. Then, we ran big trials on the components of that bundle, and found that none of them helped individually (ARISE, ProCESS & ProMISe). It was clear that these patients benefited from close attention and clinical reassessments, but aside from early antibiotics, the exact interventions needed were unclear. For a while, many people focused on trending lactate levels. We then saw the original ANDROMEDA SHOCK study, which showed that a resuscitation strategy focused on clinical assessments of capillary refill time was at least as good as a strategy focused on trending lactates. We have been left with the question of exactly how to improve capillary refill and which other targets are important. There has been a question about whether a higher MAP target might help (SGEM#90), especially in elderly patients with more baseline hypertension.  But the recent OPTRESS study showed worse outcomes with a higher MAP target in elderly septic shock patients. Therefore, aside from the consensus that providing early antibiotics is a good idea, there remain many questions about the ideal initial resuscitation strategy for septic shock patients. Clinical Question: In adult patients with septic shock, can death, duration of vital support, and/or hospital length of stay be improved by a “personalized hemodynamic resuscitation protocol targeting capillary refill time? Reference:  Hernandez et al. Personalized Hemodynamic Resuscitation Targeting Capillary Refill Time in Early Septic Shock: The ANDROMEDA-SHOCK-2 Randomized Clinical Trial. JAMA. 2025 Oct Population: Adults (≥18 y) with septic shock per Sepsis‑3 (vasopressors after ≥1 L IV fluid and lactate >2 mmol/L), within 4 hours of shock onset. Key Exclusions: >4 h from shock onset; anticipated surgery or dialysis within 6 h; expected survival <90 days; refractory shock; DNAR; Child‑Pugh B/C; severe ARDS; active bleeding; pregnancy; inability to assess CRT (peripheral vascular disease, hypothermia, very dark skin tone, Raynaud phenomenon). Intervention: A personalized hemodynamic resuscitation protocol targeting capillary refill time (CRT) using a 6-hour stepwise algorithm (see below). Comparison: Usual care per local protocols/guidelines. Outcome: Primary Outcome: A hierarchical composite tested with a stratified win ratio of: (1) 28-day all-cause mortality, then (2) duration of vital support (time requiring cardiovascular, respiratory, or kidney support) through day 28, then (3) hospital length of stay through day 28. Secondary Outcomes: Secondary outcomes were each of the three components of the primary outcome. Trial: This is a pragmatic, multi-center, open-label, randomized controlled trial. Authors’ Conclusions: “Among patients with early septic shock, a personalized hemodynamic resuscitation protocol targeting capillary refill time was superior to usual care for the primary composite outcome, primarily due to a lower duration of vital support.” Quality Checklist for Randomized Clinical Trials: The study population included or focused on those in the emergency department. No The patients were adequately randomized. Yes The randomization process was concealed. Yes The patients were analyzed in the groups to which they were randomized. Yes The study patients were recruited consecutively (i.e. no selection bias). Yes The patients in both groups were similar with respect to prognostic factors. Yes All participants (patients, clinicians, outcome assessors) were unaware of group allocation. No All groups were treated equally except for the intervention. Unsure Follow-up was complete (i.e. at least 80% for both groups). Yes All patient-important outcomes were considered. Unsure The treatment effect was sufficiently large and precise to be clinically significant. Unsure Financial conflicts of interest. The researchers at each study site had to get their own fund, so this was truly researcher-driven. Although a few of these researchers have ties to industry, they do not seem to have any obvious financial conflicts of interest that would be relevant to this protocol. Results: They randomized 1,501 patients and were able to analyze 1,467. The median age was ~66 years, and 43% were female. The severity of sepsis was an APACHE II of ~18 and a SOFA of 8. Sources of infection were ~48% abdominal, ~20% respiratory, and ~20% urinary. Baseline supports included invasive ventilation ~48%, norepinephrine 100% (median ~0.21 to 0.23 µg/kg/min). Lactate median ~3.6 mmol/L. Median time from shock criteria to randomization was 2 hours (IQR 1 to 3). Key Results: Compared with usual care, CRT‑PHR produced a statistically significant advantage on the hierarchical composite, driven mainly by shorter duration of vital support, while 28‑day mortality was nearly identical between groups. Primary Outcome: Based on their stratified win ratio analysis of their composite outcome, there were 131,131 wins for the CRT-PHR group and 112,787 wins for the usual care group, resulting in a win ratio of 1.16 (95% CI 1.01-1.33, p=0.04) Secondary Outcomes:  No statistical difference in mortality (26.5% vs 26.6%, p=0.91). There was a statistical decrease of 1 day in mean vital support free days (16.5 vs 15.4). Vital sign support free days is also a composite outcome. They don’t report the specific components of this outcome, but based on the supplementary material, there doesn’t seem to be any real difference in the use of mechanical ventilation or vasopressors, and so the entire difference in this trial might come down to a 1-day difference in renal replacement therapy. There was no statistical difference in hospital length of stay (15.3 vs 16.2). 1. Unmasked Trial with Subjective Outcome Changes: Open-label trials increase the risk of performance bias. Mortality is an objective outcome and was completely unchanged here. The part of the component outcome that changed was “vital support free days”. However, treatment decisions are highly subjective and can be influenced by treatments the patient has already received. Therefore, this outcome is at high risk of bias in an unmasked trial. 2. Composite Outcomes: Composite outcomes have been discussed on the SGEM several times. They are endpoints in clinical research that combine multiple individual events. In this trial, they combined all-cause mortality, vital support and length of stay into a single measure to capture the overall effect of the intervention. Composite outcomes can be useful when individual events are too rare to provide adequate statistical power, allowing researchers to detect treatment effects with smaller sample sizes or shorter follow-up. However, composite outcomes must be interpreted cautiously because the components may vary greatly in clinical importance or frequency [1,2,3].  In addition, the trial’s reported benefit may be driven largely by less important or more common components rather than the outcomes that matter most to patients.  In this ANDROMEDA SHOCK-2 trial, there was no 28-day mortality benefit (26.5% vs 26.6%; HR 0.99), but there was a statistical difference in fewer days of vital support. Performing a hierarchical composite analysis gave a win ratio was 1.16 (95% CI 1.02–1.33; P=0.04). This means a net advantage for the CRT‑personalized resuscitation strategy. 3. Lipstick on a Pig? One of the criticisms of composite outcomes is that each outcome is valued the same. Changing the analysis into a hierarchical model with pre-specified outcomes of importance attempts to address this limitation (death first, then major morbidity and then resource utilization). Analysis typically compares each patient in the intervention arm with each patient in the control arm (or matched pairs) and determines a “win,” “loss,” or “tie” based on the highest‑priority endpoint on which the pair differs. Only if tied at that level does the comparison proceed to the next level in the hierarchy. The net effect is summarized as a win ratio (or a “stratified win ratio,” if stratified by baseline risk). The number of wins for the intervention divided by the number of wins for control (values >1 favour the intervention).

Date: Dec 17, 2025 Reference: Pagnini F, et al. Unexpected events and prosocial behavior: the Batman effect. npj Mental Health Research. November 2025 Guest Skeptic: Dr. Dennis Ren is a pediatric emergency medicine physician at Children’s National in Washington, DC. You may also know him as the host of SGEM Peds. Case: It’s been a dark, cold day in Gotham City. You’re finally on the metro heading home after a long shift. The train is packed, and you’re standing, crammed uncomfortably among all the other citizens eager to get home. Outside, you see the holiday lights and decorations, trying valiantly to shine through the flurries of snow. At the next stop, you see a visibly pregnant passenger board the crowded train car. She shuffles in and stands, holding the rail. No one around her moves. No one gets up to offer their seat. Hardly anyone even notices. You pull your coat a bit tighter around you and wonder: What’s it going to take to nudge people to be a little more helpful? Background: Prosocial behaviour is something we rely on every shift but hardly ever discuss explicitly. Psychologists typically define it as voluntary actions aimed at helping others. Examples include holding a door open, donating money, giving up your seat, or stepping in to assist a stranger. It’s an umbrella term that covers everything from simple everyday kindness to extraordinary acts of altruism. The world just saw an extraordinary example of prosocial behaviour in the Bondi Beach attack ‘hero’, Ahmed Al Ahmed. Motivations vary: empathy and concern for others, a desire to follow social norms, expectations of reciprocity, and even a wish to avoid guilt all influence prosocial behaviour. Prosocial behaviour has traditionally been studied in several primary ways. In the lab, researchers use economic games (such as dictator, ultimatum, and public goods games), staged helping tasks (such as picking up dropped pens or assisting with a “broken” computer), or vignette-based scenarios (“Would you stop to help?”). In real-world settings, classic bystander studies explore whether people intervene when someone seems in need and what situational factors (crowding, diffusion of responsibility, perceived danger) influence their decision to act or remain passive. Throughout all approaches, a key theme is that context plays a crucial role: the same individual may assist in one situation but ignore someone in another. Over the past decade, there has been increasing interest in how subtle environmental cues influence prosocial behaviour. Mindfulness research indicates that when people focus on the present moment, they may be more inclined to notice others’ needs and respond accordingly, although the evidence remains modest and not definitive. Another area of study examines "social primes." For example, images of superheroes can temporarily boost helping intentions and small acts of assistance. A related body of research on the “pique technique” demonstrates that unusual, unexpected events or requests can disrupt automatic “no” responses and increase compliance or helping, likely by pulling people out of autopilot. The “Batman effect” study we explore today extends these ideas into real-world scenarios. Could an unexpected disruption, such as a person dressed as Batman, increase a specific prosocial behaviour? For an emergency physician accustomed to crowded waiting rooms and chaotic departments, it’s an intriguing yet potentially significant question: can small, harmless environmental “shocks” encourage people to do the right thing a little more often without anyone ever having to take a mandatory module on ethics? Clinical Question: Among passengers on a crowded metropolitan subway, does the presence of an unexpected event (a person dressed as Batman) increase the likelihood that someone offers their seat to a pregnant-appearing woman, compared with no Batman present? Reference: Pagnini F, et al. Unexpected events and prosocial behavior: the Batman effect. npj Mental Health Research. November 2025 Population: Passengers in crowded cars on the Milan underground metro. Intervention: Presence of someone dressed as Batman (~3 meters away, no interaction with an experimenter pretending to be a visibly pregnant woman). Comparison: Identical set-up without Batman Outcome: Whether the seated passenger offered their seat to the (pretend) pregnant woman during a single-stop ride Type of Study: Quasi-experimental, non-randomized controlled field study. Both conditions were conducted simultaneously in different train cars and different areas of the platforms. Authors’ Conclusion: “This study suggests that unexpected events can increase prosocial behavior by momentarily disrupting automatic attention patterns and fostering situational awareness. These findings open new avenues for understanding the environmental and cognitive mechanisms underlying prosociality, and suggest potential applications for promoting kindness and cooperation in everyday settings—extending the “Batman effect” to nonsuperheroes as well.” Quality Checklist for Quasi-Experimental Studies: Is it clear what is the ‘cause’ and what is the ‘effect’? Yes Were the participants included in any comparisons similar? Unsure  Were participants in any comparisons receiving similar treatment/care other than the exposure? Yes Was there a control group? Yes Were there multiple measurements of the outcome both pre and post the intervention/exposure? No Was follow-up complete, and if not, were differences adequately described and analyzed? Yes Were the outcomes of participants in any comparisons measured in the same way? Yes Were outcomes measured in a reliable way? Unsure  Was appropriate statistical analysis used? Yes Results: They conducted 138 observations (70 control and 68 experimental with Batman). Most who offered up their seat were women (~68%) with a mean age of approximately 42 years. Key Result: Passengers were roughly three times more likely to give up their seat for a pregnant-appearing woman when Batman was present on the train compared with when he was not. Primary Outcome: Offering a seat to the pregnant woman 38% control vs 67% Batman Odds ratio (OR) = 3.39, p < 0.001 They also conducted brief follow-up interviews with the passengers who gave up their seats and asked whether they had seen Batman. Many spoke about recognizing pregnancy, social norms, education or safety. Nobody directly admitted to giving up their seat because Batman was there. In fact, 44% of those interviewed stated they didn’t see Batman at all. 1. Hawthorne Effect: When discussing this type of field experiment, it is important to mention the Hawthorne effect, which is the idea that people change their behaviour simply because they know they are being observed. In this study, a designated observer recorded whether passengers offered their seat to the pregnant woman. It is not specified how the observer tried (or did not try) to blend into the environment. It is possible that some passengers realized they were being observed, which could have influenced their actions. 2. Confounding: We applaud the authors for attempting to avoid confounding by concurrently conducting experiments with two research teams in different train cars and areas of the platform. The train cars also had to have all seats occupied with no more than five people standing between seats. Ultimately, this was not a randomized experiment. While they looked at Batman vs No Batman scenarios, that may not be the only thing that differs amongst the groups represented in their respective train cars, which was not measured or reported. In an exaggerated example, what if the car with Batman was full of nuns while the other car had a more heterogeneous smattering of society? Did people give up their seats because Batman was there or because they were or were not nuns (assuming that nuns are more charitable)? We also don’t know if the behaviour of the “pregnant” experimenter changed at all between scenarios. Did she always choose to stand in the same place? Did she make or avoid eye contact with the people around her? Were there other environmental factors that made her easier or more difficult to notice? 3. Outcome Measurement: The outcome of interest was the number of people who gave up their seats to the pregnant woman. Based on the methods, it looks like there was only one observer. The study findings may have been more robust if they had more than one observer and reported inter-rater reliability. I’m reminded of the selective attention test, where the viewer is tasked with counting how many times players pass a ball without noticing the gorilla that walks in and out of the frame. 4. Loss to Follow Up: Among the 138 observations, 70 instances of prosocial behaviour were observed. Of those, only 52 (74%) were interviewed during follow-up. This makes us wonder: What about the people who weren’t interviewed? Would they have provided us with more insight or breadth about their reasons for giving up the seat? Would some of the people who weren’t interviewed in the experimental design have stated that they saw Batman? 5. Generalizability: The experiment was conducted in the Milan metro system. There are likely differences in cultural or societal norms that make the findings of this study less generalizable to all transit systems worldwide. One example may be that the number of stops or the distance between stops varies. Shorter distances between stops and more frequent stops could encourage more people to give up their seats to pregnant women as their stop approaches. Is it actually the Batman Effect? This threat to validity hurts me a little bit to admit…because my confirmation bias says “Of course it was the presence of Batman who was responsible for people doing good!” But I mean, who is Batman?

Reference: Binder ZW et al. “Ultrasound-Guided Nerve Block for Pediatric Femur Fractures in the Emergency Department: A Prospective Multi-Center Study.” Academic Emergency Medicine, 2025. Date: November 24, 2025 Dr. Lauren Westafer Guest Skeptic: Dr. Lauren Westafer is an Associate Professor in the Department of Emergency Medicine at the University of Massachusetts Medical School, Baystate. She is the co-founder of FOAMcast and a researcher in pulmonary embolism and implementation science.  Dr. Westafer serves as the research methodology editor for Annals of Emergency Medicine.  Case: A 9-year-old boy presents to the emergency department after a trampoline injury. He was at a party with his friends and they were all bouncing together and competing to see who could bounce the highest. The boy fell down on his right leg and a friend accidentally landed on it. On your exam, the boy is in significant pain and has a deformity of his right leg. You do not note any additional injuries. X-rays confirm a mid-shaft femur fracture. You administer some IV morphine, but the boy is still whimpering in pain. One of the other attending physicians on shift who happens to be an ultrasound enthusiast, suggests using an ultrasound-guided nerve block as a way to manage the boy's pain. The boy’s parents ask “What is that?” Background: Femur fractures are one of the most painful injuries in pediatric patients and frequently require hospital admission for definitive treatment, often with long ED stays prior to operative management. Traditional pain management for these injuries relies heavily on IV opioids, which have well-documented side effects including nausea, respiratory depression, and sedation. Increasing public awareness of the opioid crisis has also led to growing parental concern over opioid exposure in children. There is growing interest in opioid-sparing pain control methods. The fascia iliaca compartment nerve block (FICNB) is a regional anesthesia technique that targets the femoral nerve and adjacent sensory nerves to provide localized pain relief. While landmark-based FICNB techniques have been used successfully in adult patients, recent studies suggest that ultrasound guidance improves the accuracy and safety of these procedures. However, evidence on the effectiveness and safety of ultrasound-guided FICNB in pediatric patients, particularly when performed by emergency physicians in real-world ED settings, remains limited.  Clinical Question: In children with femur fractures, is ultrasound-guided FICNB more effective at reducing pain compared to systemic analgesia? Reference: Binder ZW et al. “Ultrasound-Guided Nerve Block for Pediatric Femur Fractures in the Emergency Department: A Prospective Multi-Center Study.” Academic Emergency Medicine, 2025. Population: Children aged 4–17 years presenting to the ED with isolated, acute femur fractures. Excluded:  Patient with neurovascular compromise, multi-trauma, GCS ≤13, bilateral fractures, allergy to anesthetics, prisoners, pregnancy. Intervention: Ultrasound-guided fascia iliaca compartment nerve block (FICNB) performed with ropivacaine or bupivacaine Comparison: Systemic analgesia administered at discretion of ED treating team Outcome: Primary Outcome: Reduction in pain intensity at 60 minutes using the Faces Pain Scale–Revised (FPS-R). Secondary Outcomes: Reduction in pain at 240 minutes, opioid consumption (oral morphine equivalents per hour), occurrence of adverse events, and emergency department (ED) length of stay. Trial: Prospective multi-center observational study conducted at 12 pediatric emergency departments in the US and Australia. Some sites performed FICNB. Other sites did not. Dr. Zachary Binder Guest Author: Dr. Zachary Binder is a pediatric emergency medicine attending physician at UMass Memorial Health and Associate Professor at UMass Chan Medical School. He is the Director of Point-of-Care Ultrasound for the Department of Pediatrics and the medical school. Authors’ Conclusions: Children who received FICNB had greater reductions in pain intensity and required less opioid medication than those who did not. This is the largest prospective study evaluating the ultrasound-guided FICNB performed on children in the ED, and its findings support the procedure’s use for pediatric femur fracture pain management. Quality Checklist for Observational Study: Did the study address a clearly focused issue? Yes Did the authors use an appropriate method to answer their question? Yes Was the cohort recruited in an acceptable way? Yes.  Was the exposure accurately measured to minimize bias? Yes Was the outcome accurately measured to minimize bias? Yes Have the authors identified all-important confounding factors? Yes Was the follow up of subjects complete enough? Yes.  How precise are the results? Fairly precise Do you believe the results? Yes Can the results be applied to the local population? Unsure Do the results of this study fit with other available evidence? Yes.  Funding of the Study: No financial conflicts of interest Results: They included a total of 114 participants (54 in the FICNB group and 60 in the non-FICNB group).  The mean age was ~10 years old, with ~20% female. Fractures were mostly displaced (91% vs 83%), while open fractures were rare (~2%). Most had received opioids before enrollment (96% vs 88%).  FICNBs were performed by attendings (37%), fellows (33%), or residents (30%) under supervision. Half were performed or supervised by attendings with advanced POCUS training. Key Results: Children who received FICNB had greater reduction in pain compared to those who did not, without more adverse events or longer ED LOS. Primary Outcome (Pain reduction at 60 min) There was a mean decrease of 3.8 points (95% CI, 3.1 to 4.6) in the FICNB group compared to a decrease of 0.8 points in the non-FICNB group (95% CI, -0.2 to 1.9).  That was a difference of 3.0 (95% CI, 1.7 to 4.3).  Secondary Outcomes When it came to pain reduction at 240 min, there was a mean decrease of 3.6 points (95% CI, 2.6 to 4.5) in the FICNB group vs. 1.7 points (95% CI, 0.7 to 2.7) in the non-FICNB group. That was a difference of 1.9; (95% CI, 0.5 to 3.2). The FICBN also received less opioids after enrollment measured as oral morphine equivalents per hour (OME/hr). This was 0.3 in the FICBN group vs. 1.1 in the non-FICBN group). This was a difference of 0.8 (95% CI, 0.4 to 1.1). ED length of stay in both groups was 6.1 hours with overlapping 95% CI. There was not much difference in adverse events between the two groups (5.6% FICNB vs 8.3% non-FICNB), with no serious complications attributable to FICNB. One patient in the FICNB group had apnea but had also received ketamine, fentanyl and midazolam.    Listen to the SGEM podcast to hear Zack respond to our five nerdy points. Selection Bias Twelve sites were included. The proportion of physicians able to perform the nerve block ranged from 25-100% of the faculty. There were four sites that did not routinely perform FICNB. For the sites that did perform the nerve block, it was only performed when someone trained to do it was on shift (which makes sense). Patients may also have been missed for other reasons such as maybe it was too busy on shift or there was a fast disposition from ED to the operating room. However, this also means that there is a group of eligible kids that may have been missed with this convenience sampling. How do you think this selection bias may have impacted the results of the study? Performing FICNB We can’t imagine that a young child is going to be thrilled seeing a long needle being introduced to the leg that is already broken. How do you do this practically? Are you having to give any additional medications for anxiolysis prior to this? Are you worried about the patient moving during this process? Any tips on how to fit this into the workflow of a busy ED shift? One other thing that we were looking for was whether or not all of these blocks were successfully placed on the first attempt or did some require multiple attempts? Ultrasound Training and Competencies We were impressed that in this study, the nerve block was performed by a mix of attending physicians (37%) and fellows and residents under supervision. What does it take to train someone to perform this nerve block? How do you determine they are capable enough to be credentialed? Generalizability It’s mentioned in the paper that four of the 12 sites involved in this project did not routinely perform FICNB. It’s also mentioned that at some of these sites, not performing FICNB would be considered substandard care. This is quite a variation even amongst academic children’s hospitals which may make this practice less generalizable to the community or rural settings.  What do you think are some of the biggest barriers and challenges in having this practice be adopted more widely? Is it the lack of trained staff? Buy-in from orthopedic colleagues? Patient and Family Experience While the primary outcome of pain reduction was very patient-oriented, we can’t help but wonder, did you collect any additional data about the experience of patients or families? Were they overall satisfied with the care they received nerve block or not? Did any express preference for nerve block or systemic analgesia? Comment on Authors’ Conclusion Compared to SGEM Conclusion: We agree with the authors’ conclusion. SGEM Bottom Line: Ultrasound-guided fascia iliaca compartment nerve blocks were associated with clinically meaningful pain reduction and less opioid use for pediatric femur fractures in the ED without prolonging length of stay.

Date: December 4, 2025 Guest Skeptic: Dr. Jestin Carlson – Long-time listener, second-time guest.   Reference: Reinaud et al. Reporting of Noninferiority Margins on ClinicalTrials.gov: A Systematic Review. JAMA Netw Open. 2025 Case: You are working with a resident who asks you about a new thrombolytic they heard about on the SGEM for acute ischemic stroke.  This new treatment was found not to be inferior to the existing thrombolytic, but they are not sure how the paper reached that conclusion.  You start to discuss noninferiority margins when the resident asks you, “Are the noninferiority margins reported on ClinicalTrials.gov consistent with the final publications?” Background: A non-inferiority (NI) trial asks whether a new strategy is “not unacceptably worse” than an established, effective strategy by more than a pre-specified amount. The non-inferiority margin (Δ) or delta is the largest loss of effectiveness we would tolerate in exchange for another advantage (lower cost, easier logistics, fewer adverse effects). Regulators and methods groups emphasize that Δ must be clinically justified, pre-specified, and not chosen after seeing the data. The Δ is then tested using a one-sided hypothesis procedure or, equivalently, by checking whether the confidence interval for the treatment difference stays within Δ. For example, a new medicine to treat hypertension lowers patients’ systolic blood pressure by 1 point more than the standard treatment but causes gastrointestinal (GI) upset in 50% of patients.  That difference may be statistically significant, but clinically it doesn’t result in a net benefit for the patients since so many of them get GI upset.  Ideally, the noninferiority margins should be set up before the trial is conducted to minimize bias.  Many modern ED trials rely on NI logic (TNK vs tPA for stroke, non-operative treatment of appendicitis, Simple Aspiration versus Drainage for Complete Pneumothorax, etc).  However, prior work suggested poor reporting of noninferiority margins with reporting rates as low as 2.6% for studies published between 2012 and 2014.  That was over 10 years ago...hopefully we have improved since then.  Clinical Question: What proportion of registered noninferiority randomized trials report the noninferiority margin at registration, and how consistent are margins between ClinicalTrials.gov and corresponding publications? Reference: Reinaud et al. Reporting of Noninferiority Margins on ClinicalTrials.gov: A Systematic Review. JAMA Netw Open. 2025 Population: All registered non‑inferiority trials on ClinicalTrials.gov with primary completion 2010–2015 (Stage 1) and all first‑posted 2022–2023 (Stage 2). Excluded: Nonrandomized, single-arm, phase 1–2/2–3, diagnostic/screening trials where noninferiority was only a secondary outcome. Exposure: Presence of a prespecified noninferiority margin reported on ClinicalTrials.gov (at registration / during enrollment / after primary completion / in posted results). Comparison: Descriptive contrasts across timepoints and between the registry and corresponding publications (consistency). Outcome: Primary Outcome: Proportion reporting the noninferiority margin at registration on ClinicalTrials.gov. Secondary Outcomes: Timing of first reporting (registration, during enrollment, after completion, or in posted results); proportion reporting margin in posted results; proportion reporting margin in the corresponding publication; justification of margin; consistency between registry and publication; reporting of primary analysis population and Type I Error. Type of Study: A systematic review of registered randomized trials’ methods reporting. Authors’ Conclusions: “Reporting of the noninferiority margin on ClinicalTrials.gov was low (3.0% in 2010–2015 sample, 9.2% in 2022-2023 sample). Because margins are central to design and interpretation, mandatory reporting of trial design and the noninferiority margin at registration would improve transparency and reliability of noninferiority trial results.” Quality Checklist for Systematic Review: Was the main question clearly stated? Yes Was the search detailed and exhaustive? Yes  Were the inclusion criteria appropriate? Yes Included studies sufficiently valid? Yes Results similar from study to study? Yes Any financial conflicts of interest? Authors do not report any financial conflicts of interest. Results: In the 2010 to 2015 cohort (n=266), 60% were industry‑funded; most evaluated drugs/biologics (~67%); parallel‑arm designs predominated (94%); open‑label was common (49%); adults‑only accounted for 74%; and the median planned sample size was 304 (IQR 63 to 545). The 2022 to 2023 cohort (n=327) showed similar patterns with more adult-only studies (83%) and a median planned sample size 228 (IQR 50 to 406). Key Result: Very few trials pre-specified a Δ at registration, a super majority reported a Δ in their publication and registry‑to‑publication consistency could only be evaluated in a handful of studies. 2010 to 2015 sample (n=266) Only 8 trials (3%) reported the planned noninferiority margin at registration. 31 trials (11.7%) first reported a margin after registration (11 during enrollment; 20 after primary completion). Of 132 trials with results posted on ClinicalTrials.gov, 79 (59.8%) reported the noninferiority margin in the posted results. Corresponding publications were found for 208 trials (2010–2015 sample); 196/208 (94.2%) publications reported the noninferiority margin, and 86/196 (41.3%) justified it. 2022 to 2023 sample (n=327) 30 trials (9%) reported the margin at registration (a modest improvement but still low); only 6 of these justified. When margins were reported in both the registry and the publication, they were identical in the 5 trials that reported margins at registration and in publication; margins in posted results and publications were consistent for all but 1 of 63 trials. Registry Transparency: ClinicalTirals.gov lacks a mandatory, structured field for trial design type and noninferiority margin. The authors suggest mandatory fields to prevent untraceable post-hoc margin changes. Building and maintaining trust in the scientific literature depends on ensuring we are honest and transparent in the scientific process.  This includes transparency in registration.  Potential for Bias: Post-hoc or late specification of margins can bias conclusions. A margin change after seeing the data can turn a noninferior result from “fail” to “pass”. This would be like p-hacking or HARKing (hypothesizing after results are known). Overinterpreting Non-inferiority Trials: The goal of non-inferiority trials is exactly that...to determine if one treatment is not inferior to another. It does not prove whether the treatment is effective.  In addition, even if margins are pre-specified, they can be clinically meaningless. Readers still need to appraise whether the Δ represent something the patient would consider non-inferior.  Single Trial Registry: This study used a single registry (ClinicalTrials.gov) and did not search the study protocols. There are many registries where clinical trials can be registered, including the Australian New Zealand Clinical Trials Registry, the Chinese Clinical Trial Registry and EU Clinical Trials Register, to name a few.  How these results generalize to other registries is unknown. Ensuring Consistency with Reporting: FDA guidance and the CONSORT extension for noninferiority trials emphasize pre-specification and justification of margins. We should expect this in both registration and publication.  In addition, journals, editors, and reviewers may insist that the author report not only the margins at the time of publication but also whether the margins were published at the time of registration.  Comment on the Authors’ Conclusion Compared to the SGEM Conclusion: We generally agree with the authors’ conclusions.  SGEM Bottom Line: Non-inferiority margins need to be pre-specified, justified, and clinically acceptable, and this new review shows we often can’t verify that from the trial registry alone. Case Resolution: You tell the resident that when you read a noninferiority trial, check the publication for margin justification, when possible, verify pre-specification in the trial registry or protocol and reflect on whether the margin is clinically relevant. Treat noninferiority claims cautiously if the margin is not prospectively registered. Clinical Application: Be skeptical when reading the results of a non-inferiority trial and cross-check them against what is reported on clinicaltrials.gov if it was registered there.  What Do I Tell the Patient? N/A Keener Kontest: Last week’s winner was Brad Roney. He knew the pain was defined by the International Association for the Study of Pain (IASP) as: “An unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage.” Listen to the SGEM podcast for this week’s question. If you know, then send an email to thesgem@gmail.com with “keener” in the subject line. The first correct answer will receive a shoutout on the next episode. Other FOAMed: First10EM - You Don't Understand Non-Inferiority Trials (and neither do I) Remember to be skeptical of anything you learn, even if you heard it on the Skeptics’ Guide to Emergency Medicine.   Additional Readings & Resources: D'Agostino RB Sr, Massaro JM, Sullivan LM. Non-inferiority trials: design concepts and issues - the encounters of academic consultants in statistics. Stat Med. 2003 Jan 30;22(2):169-86. doi: 10.1002/sim.1425. PMID: 12520555. Kaul S, Diamond GA. Good enough: a primer on the analysis and interpretation of noninferiority trials. Ann Intern Med. 2006 Jul 4;145(1):62-9.

Date: November 26, 2025 Reference: Ray et al. Emergency Department Visit Frequency Among Adults with Chronic Abdominal Pain: Findings From the 2023 US National Health Interview Survey. AEM November 2025. Guest Skeptic: Dr. Kirsty Challen is a Consultant in Emergency Medicine in the UK and an evidence-based medicine advocate. She's a seasoned knowledge translator with her PaperinaPic infographics.   Case: You are mid-shift in what feels like the never-ending winter of emergency medicine, and you hear the sigh as your resident picks up the chart of the next patient to be seen. Wondering if the resident requires coffee or support, you ask what is wrong. “I’m good, it’s just this is the third patient with acute worsening of abdominal pain they’ve had for years that I’ve seen this week. What’s going on?” Background: Abdominal pain is a frequent reason for presentation to the emergency department (ED), generating over 13 million visits in the US in 2022. As emergency care providers, we are taught to think of the worst-case diagnoses (aneurysmal, ischaemic, an ectopic pregnancy, appendicitis, etc). Once the “bad stuff” is excluded, it’s tempting to breathe a sigh of relief and “not my concern”. However, there is an estimated population prevalence of chronic abdominal pain of around 22 per 1,000 person-years. According to the International Association for the Study of Pain, this is defined as abdominal pain without a clear diagnostic explanation that lasts for 3 months or more. Often, patients with these symptoms have been diagnosed with “functional” abdominal pain, although more recent terminology uses “Disorders of Gut-Brain Interaction”. Managing patients with acute-on-chronic pain syndromes in the ED can be very challenging, particularly if continuity of care is lacking for their chronic condition. This has been addressed to some extent by the GRACE-2 guidance on managing recurrent low-risk abdominal pain, which de-emphasizes repeated routine imaging and recommends opioid-minimizing strategies for symptom management. Clinical Question: Do people with chronic abdominal pain have higher rates of ED utilization than those without? Reference: Ray et al. Emergency Department Visit Frequency Among Adults with Chronic Abdominal Pain: Findings From the 2023 US National Health Interview Survey. AEM November 2025. Population: Adult respondents to the National Health Interview Survey 2023 who completed the question on demographics, pain, healthcare seeking behaviours, disability, mental health, past medical history and social determinants of health. Exclusion: The entire survey excludes people without a permanent household address, active-duty military personnel or civilians on military bases, and residents of long-term care facilities. For this study, the authors also excluded people reporting a history of cancer, Crohn’s disease and ulcerative colitis and those who were pregnant. Exposure: Chronic abdominal pain (CAP) was defined by the authors as reporting pain “most days” or “every day” over the prior three months, and being “bothered by” abdominal, pelvic or genital pain “somewhere between a little and a lot” or “a lot” over the prior three months. Comparison: Adults without chronic abdominal pain. Outcomes: Primary Outcome: ED visits in the prior 12 months. Secondary Outcomes: Mental health status, physical comorbidities, disability, and social determinants of health. Type of Study: Secondary analysis of a cross-sectional interview study. Dr. Michael Ray This is an SGEMHOP, and we are pleased to have the lead author on the episode. Dr. Michael Ray is an Assistant Research Professor, Department of Emergency Medicine at George Washington University School of Medicine & Health Sciences. Known as a pain researcher. Clinically practiced as a chiropractor in an outpatient setting, which led to an interest in chronic pain and transition to academia. Authors’ Conclusions: This nationally representative analysis suggests that individuals with CAP have significantly higher ED utilization and face greater burdens of disability, mental health conditions, comorbidities, and SDOH-­related barriers. These findings highlight the potential value of addressing BioPsychoSocial factors to reduce ED reliance and support comprehensive care for CAP patients. Quality Checklist for Observational Study: Did the study address a clearly focused issue? Yes Did the authors use an appropriate method to answer their question? Yes Was the cohort recruited in an acceptable way? Unsure Was the exposure accurately measured to minimize bias? Unsure Was the outcome accurately measured to minimize bias? Unsure Have the authors identified all important confounding factors? Unsure Was the follow-up of subjects complete enough? N/A How precise are the results? The numbers are large, so they are likely to be reasonably precise, but formal measures of uncertainty, such as credible intervals, aren’t presented in the paper. Do you believe the results? Yes  Can the results be applied to the local population? Yes Do the results of this study fit with other available evidence? Yes Funding of the Study? National Research Scientist Award via George Washington University, and the Authors declared no conflicts of interest. Results: Just over 4.5 million (2.8%) of the nearly 163 million respondents reported Chronic Abdominal Pain. The chronic abdominal pain group had higher proportions of female sex (66% vs 50%) and age 55 to 64 (23% vs 15%), with similar race/ethnicity distribution. Key Result: Reporting Chronic Abdominal Pain was associated with an increased frequency of ED attendance. Primary Outcome: 1% of people with CAP reported one ED visit over the last 12 months, compared to 11.7% of people without. 16.9% had visited 2 to 4 times compared with 5.2%. Secondary Outcomes: Chronic abdominal pain was associated with increased incidence of anxiety, depression, physical comorbidities, challenges accessing healthcare, economic instability and limitations in social and employment function. Recall Bias: By conducting a secondary analysis of the US National Health Interview Survey, you are obviously limited by how the original survey's designers chose to collect the data. Much of the data depends on patients’ recollections, which we know can be flawed. People who go to the ED with their pain may well remember the days of pain more clearly than those who did not or could not seek healthcare. Do you have any information or a sense of how the NHIS measures up against other cohorts where the data can be triangulated Exclusions & Missing Data: The dataset includes many potential confounding factors, such as comorbidities and some social determinants of health. However, the entire survey excludes people without a permanent household address, and there doesn’t seem to be information around alcohol or substance use, which could plausibly be associated with chronic pain and contact with healthcare. How much do you think that challenges your findings? Outcome Measurement: The NHIS does not link ED visits to a specific presenting complaint, so some “excess” ED use among chronic abdominal pain respondents may reflect unrelated issues. In addition, modelling excluded asthma and injury. Excluding injury makes sense, but why exclude asthma? Multiple Comparisons: You acknowledge in the paper that the multiple comparisons you have done increase your risk of Type 1 error. This is where you find something that meets the criteria for statistical significance purely by chance. However, you deliberately chose not to apply a statistical adjustment, such as a Bonferroni correction. Could you talk us through that? Residual & Bidirectional Confounding: Although models adjusted for demographics, disability, mental health, PMH, and SDOH, unmeasured or imperfectly measured factors (access to specialty care, pain catastrophizing, prior imaging availability) could partly explain the associations. You note complex bidirectional relationships among CAP, mental health, disability, and SDOH that a cross-sectional model cannot fully resolve, which is an inherent limitation of observational designs. What do you think its implications might be for the individual patient and care provider? Comment on Authors’ Conclusion Compared to SGEM Conclusion: We broadly agree with the authors’ conclusions, but would emphasize the need to be very cautious about inferring causation in either direction. SGEM Bottom Line: Adults reporting chronic abdominal pain report more ED attendances than those without, and report higher levels of physical, psychological and social comorbidities. Dr. Kirsty Challen Case Resolution: You empathize with your resident, noting that it can be frustrating when patients present to the ED with chronic problems. However, you help her frame this in the context of the impact on multiple areas of the patient’s life of chronic pain. Clinical Application: ED providers should recognize that people presenting with chronic abdominal pain are more likely to have physical and psychological comorbidities and be disadvantaged in terms of social determinants of health. What Do I Tell the Patient? We know that patients with chronic abdominal pain often have challenges in other parts of their lives. Is there anything else we can help with? Keener Kontest: The last episode’s winner was Scott Luce. He gave four examples of c-collars with geographic locations from the US (Aspen, Philly, Miami Jr and NY Ortho). Listen to the SGEM podcast for this week’s question. If you know, then send an email to thesgem@gmail.com with “keener” in the subject line. The first correct answer will receive a shoutout on the next episode. Now it is your turn, SGEMers. What do you think of this episode on chronic abdominal pain and ED utilization?