The Skeptics Guide to Emergency Medicine

Dr. Chris Bond, an emergency medicine physician and assistant professor at the University of Calgary, discusses the impact of microaggressions in the emergency department. He addresses how subtle discrimination affects patient care outcomes, focusing on a case study of a Chinese woman with chest pain. The conversation highlights how language barriers exacerbate these issues and the role of implementation science in improving healthcare interactions. Bond also emphasizes the need for training to foster better communication and understanding in diverse patient populations.

Date: November 20, 2023 Reference: Jones et al. Time to reflect on open-label placebos and their value for clinical practice. PAIN October 2023 Caitlin Jones PhD Guest Skeptic: Dr. Caitlin Jones is a Postdoctoral Research Associate at Sydney University’s institute for Musculoskeletal Health. Her research evaluates the benefits and harms of treatments for musculoskeletal conditions with a particular interest in high-risk treatment options such as opioid medicines and spinal cord stimulators for pain. She has a goal to improve patient outcomes and reduce harm from inappropriate treatments. We have an interesting back story on how we met. Dr. Sergey Motov and I did a structured critical appraisal of the OPAL trial (SGEM#419). You were the lead author on that study. You pointed out we missed some details in our review and provided some additional information. We were happy to hear from you and updated the SGEM episode based upon your comments. Not everyone has been so receptive to your study and your feedback. Thanks for appraising OPAL and for engaging with me about it. There were lots of varied responses to OPAL. Most were positive and interested. Some had opinions that the trial doesn’t reflect their practice or their patients, so it’s not relevant to them (reasonable position). Some are furious that we would even suggest that opioids don't work and they are certain this is part of a corrupt evil agenda (I don’t engage with this stance because nothing I can say will change their minds). I do engage when it’s just a genuine misunderstanding, or someone has missed some details.Everyone is free to make up their own mind about how they will or won’t apply these findings into their clinical practice, but I do feel an obligation to correct misunderstandings when I see them. After our exchange I looked up some of your other publications. One of them caught my eye as being very thought-provoking. It looked at open label placebo being used in clinical trials. The title of the paper was Time to reflect on open-label placebos and their value for clinical practice [1]. What got you interested in that topic? A lot of my research compares treatments for MSK pain to placebo to establish efficacy (how well it works). In my field we often find, sadly, that some of the treatments used for decades in clinical practice don’t show effects above that of the placebo when someone finally tests them properly. There’s been increasing chatter about OLPs with a few editorials written in big journals, and an increase in publications on the topic, so it is clearly gaining traction in the clinical and research community. A lot of my work so far has been about testing treatments that have been used for decades without proper testing, and then when we finally test them, we discover we were doing more harm than good all this time. Open label placebos as a clinical treatment are new enough that there is time to intervene and advocate for some thorough testing before they become common place in clinical care. I don’t want this to be another thing where we realize in 50 years’ time that we were harming not helping. SGEM listeners are probably familiar with the placebo effect, but can you give us a brief definition or description? The placebo effect is the positive effect on outcomes stemming from positive expectations around receiving a treatment, but not the treatment itself. Placebo in a research context is the gold standard comparison in efficacy trials that can provide an estimate of the treatment effect, filtering out all the biases and contextual effects that aren’t directly caused by the treatment of interest, so we are left with an estimate of the direct effects of the treatment itself. Then along came some research which caused some excitement. They reported that you could elicit a placebo effect without deceiving the patients (ie telling them it is a placebo) [2]. Yes, some very interesting research came out that even when you tell people they are getting a placebo, they still seemed to cause some positive effects. That was really appealing to a lot of people who believed in the power of placebo, but felt the main barrier to usage was with unethical element of deception – suddenly no deception seemed necessary. Open Label I love talking nerdy and the methods section is my favourite section of a publication. So, what were the fundamental misunderstandings of the open label placebo (OLP) and research methodology? Mismeasuring / over inflating the placebo effect by confusing response for effect Lack of blinding in trials, plus positive preamble, overinflates OLP group and deflates control group effects. Sampling bias, advertising for mind-body treatments and having participants self-select(only examining people with a pre-existing belief or interest). Not including co-design or input from the people who we think would be most likely to receive this (conditions hard to diagnose and treatg. chronic pain, chronic fatigue) I understand there were some experts opining that open label placebos should be part of clinical care [3.4]? Yes, some are calling for OLPs in clinical care. Some are overlooking the limitations of the current research, taking these effect sizes at face value, and assuming there are no harms, so why not? That sounds better than a lot of the genuine treatments we regularly use. There are even some clinicians who report on surveys as to prescribing placebos. Surveys from 2008, 2010, and 2019 conducted in primary care settings in Australia and the United States found that many doctors have prescribed a placebo at least once (from 55% to 80%). Yes, a lot of doctors are willing to admit in surveys they’ve used something they knew wouldn’t likely beeffective but did it anyway to illicit the placebo effect. One of the problems here is that the American Medical Association’s code of ethics warns against using placebos to “mollify” a “difficult” patient. It says that they can be considered if the patient is aware that it is a placebo and can therefore provide informed consent. This has given rise to the potential use of OLPs. Do you think open-label placebos are the answer? Definitely not yet, and possible not ever unless we find a way to ascertain that the benefits outweigh the risk of causing harm. I believe this is true even for patients with conditions where there is no effective treatment. This is a tough ask, because there is enormous pressure on clinicians to “do something”, and they want to reach for a treatment where the risks are low. This is perceived to be the case with OLPs although we don’t actually know that yet and I suspect there I substantial risk of stigmatizing and alienated patients. We have mentioned intervention bias many times on the SGEM. My mentor and Legend of EM, Dr. Jerry Hoffman, would frequently say…don’t just do something, stand there. In fact, that is the title of one of my favourite articles (Don't just do something, stand there! The value and art of deliberate clinical inertia [6]. That is true in so many clinical settings, but I would imagine especially so in the ED? People didn’t wait 14 hours to be seen and then receive no treatment. The pressure must be huge. Let’s look at the research on OLP. What is the quality in this area? Like much of the evidence from open-label trials, research into OLPs lack unbiased, convincing evidence of their efficacy. Studies of OLPs do not properly control for the positive preamble delivered alongside the placebo pill.Perhaps an even more pressing issue with OLP research is that patients have not been involved in co-designing this program of research. Increasingly, medical funding calls for patients’ contributions to shift from merely passive recipients to active co-designers of research programs. Dr. Steven Novella from the Skeptics Guide to the Universe (SGU) who has been on an SGEM Xtra and writes for Science Based Medicine has argued that it is unethical to knowing prescribe a placebo. Do you think it is ethical to offer patients placebos? I am not sure I would say it is unethical in all circumstances. In the context of conditions where there is no known effective treatment, proposing OLPs as an option in the shared decision-making process is a gamble with unfavourable odds, when we do not know yet whether patients would likely find this stigmatising and offensive. If it is for a patient where the clinician feels they have a good relationship, and the person has shown interest in this sort of thing before then maybe the odds are more favourable. But you are risking destroying that trusting relationship if the suggestion offends them. Also, to offer it honestly, a clinician would have to be honest about the limitations of the research – it isn’t ethical to present it as a powerful and proven remedy, because it isn’t. It is, at best, still a question mark. Do you think it is there any utility in conducting properly designed studies that have involved patient input? I have seen a survey where research recruits said in the majority that if it “works” then they would be happy to take an OLP. But we don’t really know if it works yet, so how can we ask patients if they would be willing to take it, when whether it works or not is probably the lynchpin in that decision. I think the first step would be to ask the people who are most likely to receive an OLP – those with hard to diagnose and treat conditions, like chronic pain and chronic fatigue – whether this is an avenue they would like to see taxpayer dollars spent on. Only if the answer to that is yes is it worth investing time and money into the puzzle that is how you would design an unbiased trial. What was the goal of publishing this article?

Dr. Alasdair Munro, a clinical research fellow in pediatric infectious disease, joins to dissect the nuances of pediatric sinusitis. They analyze a case of a 4-year-old with yellow nasal discharge and fever, questioning if antibiotics are warranted. The conversation highlights the challenges of differentiating between viral and bacterial infections, discusses recent guidelines, and challenges assumptions about nasal discharge color. They also delve into the importance of evidence-based treatment while promoting shared decision-making in pediatric care.

Date: November 22, 2023 Reference: Stopyra et al. Delayed First Medical Contact to Reperfusion Time Increases Mortality in Rural EMS Patients with STEMI. AEM November 2023. Guest Skeptic: Dr. Lauren Westafer an Assistant Professor in the Department of Emergency Medicine at the University of Massachusetts Medical School – Baystate. She is the cofounder of FOAMcast and a pulmonary embolism and implementation science researcher. Dr. Westafer serves as the Social Media Editor and a research methodology editor for Annals of Emergency Medicine. Case: A 72-year-old man with a history of high blood pressure and diabetes calls emergency medical services (EMS) for chest pressure and dyspnea that started 1 hour ago. Upon EMS arrival, they find the patient is sweaty with normal vital signs. A 12-lead electrocardiogram (ECG) demonstrates ST elevations in leads II, III, and aVF with ST depressions in leads I and aVL and the team begins transport to the nearest percutaneous coronary intervention (PCI) capable hospital. Background: We have covered the issue of heart attacks several times on the SGEM. These include looking at the HEART score, troponin testing and cardiovascular disease in women. One aspect we have not addressed is rural. SGEM#151: Groove is in the HEART Pathway SGEM#160: Oh Baby, You’re Too Sensitive – High Sensitivity Troponin SGEM#280: This Old Heart of Mine and Troponin Testing SGEM#370: Listen to your HEART (Score) SGEM#400: A Little Bit of Heart and Sport and Sports Related Sudden Cardiac Arrest in Women SGEM Xtra: Unbreak My Heart – Women and Cardiovascular Disease Current guidelines target a time between first medical contact (FMC) like EMS on-scene and stent or balloon deployment (PCI) of 90 minutes or less. If time from FMC to PCI is anticipated to be greater than 120 minutes, the guidelines recommend systemic thrombolysis rather than PCI [1]. I’ve published on this issue with a project we called “barn door-to-needle time” [2]. We looked at 101 STEMI patients from two rural EDs. The median door-to-ECG time was 6 minutes, door-to-physician time was 8 minutes and DTN time was 27 minutes; 58% of patients received thrombolytics within 30 minutes. Regional systems of care have been designed to rapidly recognize patients with STEMI and direct STEMI patients to timely reperfusion. Many hospitals do not provide PCI, prolonging transportation times, which disproportionately affects rural patients. There are several distinct time intervals in the care of patients with STEMI and it is unclear which steps in pre-PCI care of patients contribute to avoidable delays. Clinical Question: Is there an association between in-hospital mortality and time between first medical contact and primary percutaneous coronary intervention in rural patients who present with a STEMI? Reference: Stopyra et al. Delayed First Medical Contact to Reperfusion Time Increases Mortality in Rural EMS Patients with STEMI. AEM November 2023. Population: Patients ≥ 18 years of age who were transported to one of three tertiary care hospitals by a rural EMS agency and received primary percutaneous coronary intervention (PCI) for STEMI. Rural agency was defined by US census codes (2014) Excluded: Patients <18, those who had prehospital cardiac arrest, and those who were transferred between hospitals Exposure: 90-minute first medical contact to PCI goal (defined as time between the time recorded as EMS personnel arrival on scene and the time the angioplasty or stent was deployed Comparison: Greater than 90 minute first medical contact to PCI Outcome: Primary Outcome: All-cause in-hospital mortality during the index hospitalization Secondary Outcomes: Prehospital time intervals stratified by index hospitalization mortality. Type of Study: A retrospective cohort study from eight rural North Carolina EMS agencies between January 2016 to March 2020. Dr. Michael Supples This is an SGEMHOP episode, and it is my pleasure to introduce Dr. Michael Supples. He is an assistant professor of emergency medicine and faculty within the emergency medical services fellowship at Wake Forest School of Medicine in North Carolina. He is double boarded in EM and EMS and focuses on prehospital research. Responds Authors’ Conclusions: “Death among rural patients with STEMI was four times more likely when they did not receive PCI within 90 minutes.” 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? Unsure Was the follow up of subjects complete enough? Yes How precise are the results? Not very 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? Grant from the National Center For Advancing Translational Sciences of the National Institutes of Health Results: There was a total of 365 rural patients with STEMIs included in the study. The mean age was 63 years of age, 70% were male, 46% smoked, 69% had hypertension, 61% had hypercholesterolemia and 29% had diabetes. PCI was performed <90 minutes 61% of the time and <120 minutes in 89%. The overall in-hospital mortality was 3% (11/365) Key Results: Patients receiving PCI within 90 minutes were associated with less in-hospital mortality. Primary Outcome: All-cause in-hospital mortality during the index hospitalization 1.4% (3/221) if treated <90 min vs 5.6% (8/144) if treated >90 min p= 0.03 (95% CI; 0.3% to 8.8%) Meeting the 90-min time goal yielded a 98.6% (95% CI; 96.1% to 99.7%) negative predictive value (NPV) A 78-min FMC to PCI time was the optimal cut point for rural STEMI patients, yielding a NPV of 99.3% (95% CI; 96.1% to 100%) for index death Area under the receiver operating curve (AUC) = 0.752 (95%CI: 0.581, 0.922) Secondary Outcomes: Prehospital time intervals stratified by index hospitalization mortality. This is an observational study so we can only make conclusions of associations. We also already mentioned there were only 11 deaths which gives wide 95% confidence intervals. Have a listen to the podcast to hear Michael answer our five nerdy questions. 1) Confounding – According to Table 1, the patients who experienced in-hospital mortality were older by about a decade and more patients had key cardiovascular comorbidities (hypertension, hypercholesterolemia, diabetes, and prior MI or CABG). A confounder is a variable that it is associated with the primary exposure of interest and the disease outcome of interest. Can you discuss the decision to adjust/not adjust for potential confounders in this study? 2) Causal Inference - It seems like the bulk of the first medical contact time to PCI time between those who lived and those who died in-hospital was in the door to PCI time. This differed by 30 minutes between groups, whereas most other time points (e.g. dispatch time, response time, scene time etc.) only differed by a median of 0-1 minutes. Activation time was longer in the group that died, but by a shorter length of time. To me, this suggests that there is something about the presentation of the patient or delivery of in-hospital care that is different or more complicated. What are your thoughts on this and the role of prehospital transport? 3) Clustering – Clusters are common in medicine – EMS agencies that treat patients, the hospital to which a patient presents, or even the treating clinician. The outcome of interest may vary less within the cluster than it does in the entire dataset. Can you tell us more about your (appropriate) decision to adjust for clusters? 4) Generalizability – In this study, the median response time was 9 minutes, the median transport time was 27 minutes, and the median total EMS time was 41 minutes. Thus, although these patients were classified as rural, access to a PCI center was relatively timely (i.e. not remote rural locations). How do you think this could impact results? 5) Selection Bias – This study included individuals who had a STEMI and received PCI. There may be circumstances in which a patient has an occlusive myocardial infarction (including STEMI) but does not receive PCI (e.g. patient died – possibility for immortal time bias) [3]. How do you think this could impact results? Comment on Authors’ Conclusion Compared to SGEM Conclusion: Timely care of patients with occlusive myocardial infarction is imperative and geographic disparities likely exist. However, there are likely several patient-level confounders that also influence time to PCI. SGEM Bottom Line: Higher in-hospital mortality for rural STEMI patients is associated with longer time from first medical contact to percutaneous coronary intervention. Case Resolution: EMS activates the local STEMI pathway immediately the patient is given aspirin and nitroglycerin and transported to the nearest PCI-capable hospital. Dr. Lauren Westafer Clinical Application: Decreasing unnecessary delays in the prehospital and emergency department settings are important in the care of patients with occlusive myocardial infarction. There is likely potential in rural settings to optimize care to meet recommended benchmarks or provide alternative therapy when necessary. What Do I Tell My Patient? You are having a heart attack. We are bypassing the closest hospital and transporting you to the nearest hospital that will be able to relieve the blockage in your heart. Things will move very quickly to take the best care of you.

Dr. Matt Schmitz, an Orthopaedic Surgeon transitioning from a 20-year Air Force career to Clinical Professor at UC San Diego, tackles the tricky world of scaphoid fractures. He sheds light on the flaws of X-rays in diagnosis, discussions about the significance of clinical exams, and the implications of misdiagnosis. The conversation extends to surgical techniques, patient communication, and even a quirky contest. Packed with insights, this episode explores how to improve outcomes while navigating the complexities of wrist injuries.

Dr. Damian Roland, a Consultant in Paediatric Emergency Medicine at the University of Leicester NHS Trust, shares his expertise in managing pediatric sepsis. He discusses the critical need for early detection and effective interventions. The conversation dives into the complexities of diagnosing sepsis, questioning the effectiveness of current screening methods and lab tests. Roland critiques the misuse of 'sepsis screening' terminology, arguing it's more about clinical judgment and timing than standard tests. He highlights the challenges of pediatric fever assessments in emergency settings.

Dr. Sergey Motov, an Emergency Physician and leading pain management researcher, shares insights on back pain management. He discusses a recent clinical case of severe back pain and the complexities of patient treatment choices. The conversation highlights the limited efficacy of opioids compared to placebo, emphasizing non-opioid alternatives for safer management. Dr. Motov critiques treatment guidelines versus real-world prescribing, shedding light on the importance of evidence-based approaches in emergency medicine.

Dr. Kirsty Challen, an Emergency Medicine Consultant at Lancaster Teaching Hospitals, and Dr. Angela Cai, a Clinical Assistant Professor at the University of Pennsylvania, delve into the nuances of diagnosing spinal epidural abscesses. They discuss staggering misdiagnosis rates and the crucial role of clinical management tools in improving detection. The conversation highlights how these tools can streamline diagnostic processes while navigating the complexities of emergency practices. Their insights reveal the challenges of achieving substantial patient outcome improvements despite implementing evidence-based approaches.

Dr. Vicki Currie, a pediatric emergency medicine registrar and editor for Don’t Forget the Bubbles, shares vital insights on pediatric vital signs and their evolving reference ranges. The discussion starts with a poignant case of a boy suspected of having sepsis, emphasizing the critical need for understanding these signs. Dr. Currie critiques recent research, revealing potential discrepancies in heart rates compared to established guidelines. She advocates for individual assessments in pediatric care, arguing that patient outcomes should take precedence over strict numerical values.

Date: September 28, 2023 Reference: Jarman et al. Sex Differences in Guideline-Consistent Diagnostic Testing for Acute Pulmonary Embolism Among Adult Emergency Department Patients Aged 18-49. AEM September 2023 Guest Skeptic: Dr. Corey Heitz is an emergency physician in Roanoke, Virginia. He is also the CME editor for Academic Emergency Medicine. Case: During a shift in the emergency department (ED), you see two patients with pleuritic chest pain, one female and one male. Pulmonary embolism (PE) is a diagnosis you are considering for both. After d-dimer testing your female patient, you order a CT scan of the chest for the male patient. One of the nurses on shift asks you why you didn’t order a d-dimer for the male, like you did the female patient. Background: PE is commonly considered during ED workups for chest pain and shortness of breath (1). We have covered the topic of PE more than ten times on the SGEM: SGEM#51: Home (Discharging Patients with Acute Pulmonary Emboli Home from the Emergency Department) SGEM#118: I Hope you Had a Negative D-dimer (ADJUST PE Study) SGEM#126: Take me to the Rivaroxaban – Outpatient treatment of VTE SGEM#163: Shuffle off to Buffalo to Talk Thrombolysis for Acute Pulmonary Embolism SGEM#184: We Weren’t Born to Follow-Up – The PEITHO Long-Term Follow-up Study SGEM#219: Shout, Shout, PERC Rule Them Out SGEM#276: FOCUS on PE in Patients with Abnormal Vital Signs SGEM#277: In the Pregnant YEARS – Diagnosing Pulmonary Embolism SGEM#282: It’s All ‘bout that Bayes, ‘Bout that Bayes- No Trouble – In Diagnosing Pulmonary Embolism SGEM#295: Teacher, Teacher – Tell Me How to Do It (Diagnose a PE) SGEM#323: Mama I’m Comin’ Home – For Outpatient Treatment of a Pulmonary Embolism Many patients may be able to have PE ruled out without imaging, after risk stratification with one of several decision tools (2). A very common clinical decision instrument is the Well’s Criteria. It has seven items with each item having a weighting from 1 to 3. The score is added up and then can be applied in a three-tiered model (low, moderate, or high risk) two-tiered model (PE is unlikely or likely). Another common tool is the revised Geneva Score (rGS). It is an eight-item clinical decision instrument for risk stratification. Each item in this tool also has different weight assigned to the items. Patients are considered low, intermediate, or high-risk depending on their total score. Neither of these two scores considers the sex of the patient for risk stratification. However, sex differences exist in the workup of PE, with females receiving more diagnostic testing, but with a lower diagnostic yield. Female patients are also more likely to undergo diagnostic imaging, and females who undergo imaging are less likely to be diagnosed with PE (3-5). Clinical Question: Are male and female patients equally likely to receive care consistent with guidelines for suspected PE? Reference: Jarman et al. Sex Differences in Guideline-Consistent Diagnostic Testing for Acute Pulmonary Embolism Among Adult Emergency Department Patients Aged 18-49. AEM September 2023 Population: Patients 18-49 years of age presenting with chest pain, shortness of breath, hemoptysis, or syncope alone or in combination Excluded: Pregnancy or incomplete ED visits Exposure: Objective testing for PE Comparison: Sex (male or female) Outcome: Primary Outcome: Receipt of guideline-consistent care based on revised Geneva Score (rGS) Secondary Outcomes: Rates of d-dimer testing, d-dimer positivity, rates of CT-pulmonary artery scanning (CTPA), overall yield of testing. Type of Study: A retrospective cohort study conducted at two U.S. academic tertiary care hospitals Dr. Angela Jarman This is an SGEMHOP episode which means we have the lead author on the show.  Dr. Angela Jarman is an Assistant Professor and the Director of Sex & Gender in Emergency Medicine at UC Davis. She joined the faculty there after completing a two-year fellowship in Sex & Gender in Emergency Medicine at Brown University, where she also earned a Master of Public Health degree. Authors’ Conclusions: “In this cohort, females were more likely than males to receive care consistent with current guidelines and less likely to be diagnosed with PE.” 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? Seem precise where CIs are provided Do you believe the results? Yes Can the results be applied to the local population? Probably Do the results of this study fit with other available evidence? Yes Funding of the Study. It was supported by three grants (American Heart Association, National Center for Advancing Translational Science, and the Office of Research on Women’s Health. The authors all declared no conflicts of interest Results: They identified 1,991 patient encounters that met inclusion criteria. The mean age was 36 years, 63% were female and the majority had a chief complaint of chest pain. The revised GS was calculated to be low, intermediate, or high risk 36%, 62% or 2% of the time respectively. Key Result: Female patients were more likely to receive guideline-consistent care. Primary Outcome: Receipt of guideline-consistent care based on rGS was 70% female vs. 63% male, p = 0.003 Secondary Outcomes: Rates of d-dimer testing, d-dimer positivity, rates of CT-pulmonary artery scanning (CTPA), overall yield of testing. Listen to the podcast to hear Angela answer our five nerdy questions. 1. Revised Geneva Score vs Well’s Criteria: Your group decided to use the rGS rather than Well’s criteria. My experience is that Well’s is used more often than rGS. Can you explain your decision not to use Well’s Criteria? 2. Female Sex as a Risk: I have heard several times when asking residents and other clinicians what risk factors someone has for PE. Female sex is often cited as being a risk factor. Can you address this seeming misconception? 3. Guideline-Inconsistent Care: What do you think drives clinicians not to follow the guidelines? 4. Clinical Gestalt: Let’s talk a little about the finding that the plurality of PEs diagnosed were in patients who did not receive guideline consistent care. Do you think this is where clinician gestalt becomes important? 5. Guidelines are Not GODlines: At the end of the day, we are talking about concordance with guidelines. Guidelines should guide our care but not dictate our care. You identified an association between how closely guidelines are followed and the sex of the patients. What this research does not tell us is what is the correct percent PE guidelines should be followed. We know it is not 0% and I think we can agree it is not 100%. So, what is the correct number and why? Comment on Authors’ Conclusion Compared to SGEM Conclusion: We agree with the authors’ conclusions. SGEM Bottom Line: When working patients up for a PE, consider the guideline and risk stratify with validated decision tools or clinical gestalt to avoid over testing and overuse of advanced imaging. Case Resolution: The male patient was getting a CTPA without d-dimer testing. The female patient had an elevated d-dimer, and therefore also underwent CTPA imaging. Neither patient was diagnosed with a PE. Dr. Corey Heitz Clinical Application: Understanding our own biases is important. One tool to try to avoid a bias in this case is to consider using a validated risk-stratification tools to help our decision-making processes. What Do I Tell the Patient? You explain to your nurse that when you utilized risk-stratification tools, the female patient was low risk, while the male was high, and this explains the difference in initial workups. Keener Kontest: Last episode’s winner was Dr. Matheus Cunha from Brazil. He is a first-year resident of Emergency Medicine at the Federal University of São Paulo, and apparently absolutely loves the SGEM. Matheus knew the protagonist's mother in the Squid Game had Diabetes and suffered from its complications! Listen to this weeks' episode to hear the keener contest question. If you think you know the answer, send an email to TheSGEM@gmail.com with “Keener” in the subject line. The first correct answer will receive a cool skeptical prize. SGEMHOP: Now it is your turn SGEMers. What do you think of this episode on sex and guideline directed PE workups? What questions do you have for Angela and her team? Tweet your comments using #SGEMHOP or post your feedback on the SGEM blog. The best social media feedback will be published in AEM. Remember to be skeptical of anything you learn, even if you heard it on the Skeptics’ Guide to Emergency Medicine. References Kline JA. Diagnosis and Exclusion of Pulmonary Embolism. Thromb Res 2018;163:207-220. DOI: 10.1016/j.thromres.2017.06.002. Konstantinides SV, Meyer G, Becattini C, et al. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS): The Task Force for the diagnosis and management of acute pulmonary embolism of the European Society of Cardiology (ESC). Eur Respir J 2019;54(3). DOI: 10.1183/13993003.01647-2019. van Mens TE, van der Pol LM, van Es N, et al. Sex-specific performance of pre-imaging diagnostic algorithms for pulmonary embolism. J Thromb Haemost 2018;16(5):858-865. (In eng). DOI: 10.1111/jth.13984. Robert-Ebadi H, Le Gal G,