REBEL Cast

Salim R. Rezaie, MD

Rational Evidence-Based Evaluation of Literature

  1. 23/05/2024

    ANNEXA-1: Andexanet Alfa Associated with Harm in DOAC Reversal

    Background: In May of 2018, Andexanet alfa gained accelerated approval by the FDA for the reversal direct oral anticoagulants (DOACs) despite a lack of robust evidence for use. The 2022 AHA/ASA guidelines give the drug a level 2A recommendation and recommend it over the use of 4F-PCC (Greenberg 2022). FDA approval alongside guideline endorsement has led to the drug seeing a remarkable growth in use without a single high-quality study to support its use. The available data reports good hemostatic control: a subjective measure that is highly biased by unblinding and selection bias. More importantly, there are no studies comparing andexanet alfa to 4F-PCC or even placebo looking at important, patient-centered outcomes. REBEL Cast WEE – ANNEXA-1 – Andexanet Alfa Associated with Harm in DOAC Reversal Click here for Direct Download of the Podcast. Article: Connolly SJ et al. Andexanet for Factor Xa Inhibitor-Associated Acute Intracerebral Hemorrhage (ANNEXA-1). NEJM 2024; 390(19): 1745-55. PMID: 38749032 Clinical Question: Does the use of andexanet alfa in patients on DOACs with intracerebral hemorrhage improved hemostatic efficacy? Population: Patients > 18 years of age on a factor Xa inhibitor (taken within 15 hours of randomization) with an acute intracerebral hemorrhage. Outcomes: Primary: Hemostatic efficacy assessed at 12 hours after randomization. Hemostatic efficacy was defined as: Excellent hemostatic efficacy: Change in hematoma volume 35 Surgery planned within 12 hours of enrollment Thrombotic event within 2 weeks of enrollment Time from symptom onset > 6 hours Pregnancy Results: Primary results 581 patients were assessed for eligibility across 131 sites over 4 years 31 excluded prior to randomization 20 excluded after randomization due to consent issues 530 analyzed for the safety outcomes 263 patients assigned to andexanet alfa arm 267 patients assigned to usual care arm 452 patients were analyzed for the primary outcome 85.5% (195/228) patients in the usual care arm received 4F-PCC 78.1% (175/224) patients in the andexanet arm received the low-dose regimen Critical Results Andexanet alfa Usual Care Difference (95% CI) P Value Primary Outcome Hemostatic Efficacy 67% (150/224) 53.1% (121/228) 13.4 (4.6 – 22.2) 0.003 NIHSS change 7 points 87.9% (188/214) 83.0% (181/218) 4.6 (-2.0 – 11.2) Secondary Outcome Anti-Factor Xa % Change -94.5% (-96.6 – 88.9) -26.9% (-54.2 – -9.5) Safety Outcome Thrombotic Events 10.3% 5.6% 4.6 (0.1 – 9.2) 0.048 TIA 0 0 Ischemic Stroke 6.5% 1.5% Myocardial Infarction 4.2% 1.5% DVT 0.4% 0.7% PE 0.4% 2.2% Arterial Embolism 1.1% 0.7% Death 27.8% 25.5% 0.51 Strengths: This is the first randomized trial comparing andexanet alfa to standard care in this patient group. Multicenter, multinational study increasing applicability of findings. Outcome assessors were blinded to treatment arm. Hematoma measurements were made with a standard protocol and central site adjudication. 12 hour NIHSS assessments were performed by health care professionals who were unaware of group assignments Limitations: Study funded, designed, and supervised by AstraZeneca Pharmaceuticals the maker of Andexanet alpha.  Although, this does not refute the findings of this study, it should make readers skeptical. Clinicians were not blinded to the treatment arm patients were randomized to. This may introduce bias particularly in terms of subsequent treatments (treatments outside of reversal are not detailed in the study). Primary endpoint is not patient centered. Convenience sample of patients which introduces bias. There are some baseline differences between groups and it’s hard to say how this may have influenced the results. Exclusion criteria are likely to be difficult for clinicians to assess real time leading to protocol violation (particularly items like planned surgery and recent thrombotic event). Dose adjustment for time from ingestion likely to lead to protocol violation as this info difficult to assess. Exclusion criteria: Removed the sickest patients. Discussion: The positive primary and secondary outcomes Both the primary (hematoma expansion) and secondary (anti-factor Xa reduction) outcomes were better in the andexanet group. Unfortunately, these are disease-oriented outcomes instead of patient centered outcomes: the patient doesn’t care if their hematoma expands by 20% or 25% or 30%. They care about clinically important outcomes like disability or death. The authors note that in other studies, hematoma expansion has been associated with worse outcomes, but this was clearly not demonstrated in this study as 90d mRS and death were the same between groups. Bottom line is that there wasn’t even a hint of improved clinical outcomes in the andexanet group. Safety outcomes favored the usual care group In general, larger studies or registries of patients are required to determine safety of a treatment. In this study, however, there is a clear signal for harm even with a small group of patients under ideal circumstances (ie enrolled within a study). Though death was not statistically different, the raw numbers favor usual care. Thrombotic events were clearly increased in the andexanet group. Across a larger group of patients outside of the pristine setting of a study, it is likely that we would see an increase in thrombotic events and death. Only 85.5% of patients in the usual care group received 4F-PCC Though there isn’t abundant evidence for the use of 4F-PCC in this setting, it does represent standard practice. The authors do not report about the subgroup of patients who did not receive 4F-PCC and their outcomes. If this data shows worse outcomes with no reversal treatment, it would suggest that usual care with 4F-PCC may be superior to andexanet alfa for clinical outcomes. If this data shows improved outcomes with no reversal treatment, it would suggest that specific reversal agents aren’t necessary. There were multiple protocol changes during the study. Typically, protocols should not be changed while the study is enrolling patients. This is often done to try to steer the data towards benefit. Initial power calculation was for 900 patients to achieve a 90% power to detect and absolute difference of 10% points in terms of hemostatic efficacy but then made an addendum to the protocol to stop after 450 patients. After this stop point, the safety and monitoring board recommended the trial be stopped. Though the authors state they had no knowledge of the effect prior, there is no clear explanation given for this change and it raises the possibility that the trial was stopped prior to additional data showing harm was collected. Drug cost Andexanet alfa costs between $30 – 50,000/treatment. This only takes into account drug costs (ie not monitoring, nursing costs etc). 4F-PCC costs around $5-6,000/treatment. Author Conclusion: “Among patients with intracerebral hemorrhage who were receiving factor Xa inhibitors, andexanet resulted in better control of hematoma expansion than usual care but was associated with thrombotic events, including ischemic stroke.” Clinical Take Home Point: The authors conclusions are correct. However, they don’t properly stress the findings. Treatment of patients with intracerebral hemorrhage on a DOAC with Anexanet alfa did not improve clinical outcomes when compared to usual care. Based on safety data, andexanet alfa resulted in increased harm to patients. Andexanet alfa should not be part of the standard treatment in this scenario based on the available evidence. References: Greenberg SM et al. 2022 Guidelines for the Management of Patients with Spontaneous Intracerebral Hemorrhage: A Guideline from the American Heart Association/American Stroke Association. Stroke 2022; 53(7). PMID: 35579034 Connolly SJ et al. Andexanet for Factor Xa Inhibitor-Associated Acute Intracerebral Hemorrhage (ANNEXA-1). NEJM 2024; 390(19): 1745-55. PMID: 38749032 For More Thoughts on This Topic Checkout: REBEL EM: ANNEXA-4 – Andexanet Alfa and Factor Xa Inhibitors First10EM: Andexanet Alfa – More Garbage Science in the New England Journal of Medicine EM Lit of Note: Disutility, thy Name is ANEXXA-4 Post Peer Reviewed By: Salim R. Rezaie, MD (Twitter/X: @srrezaie) The post ANNEXA-1: Andexanet Alfa Associated with Harm in DOAC Reversal appeared first on REBEL EM - Emergency Medicine Blog.

  2. 29/05/2024

    REBEL Core Cast 123.0 – Posterior Epistaxis

    Take Home Points: Posterior epistaxis is a rare, life-threatning presentation. The key is in identifying and rapidly gaining control with a posterior pack or foley catheter. These patients often require surgical intervention so get ENT to the bedside and admit to a place with a higher level of monitoring. REBEL Core Cast 123.0 – Posterior Epistaxis Click here for Direct Download of the Podcast. Recognition Typically will have heavy bleeding both anteriorly and posterior into the oropharynx. These patients have a tough time because they’re continually trying to spit out or swallow blood Tachycardia is common and hypotension while not common isn’t unexpected. Very different from anterior epistaxis where VS usually unremarkable or maybe a bit of hypertension Failure of anterior pressure or packing to stop bleeding: apply pressure but still see brisk posterior bleeding or even place b/l pack and see continued posterior bleeding Start with the basics IV, Supp O2, Monitor Consider blood products if the patient appears to be losing a lot of blood or they report heavy blood loss. VS abnormalities can drive this as well Strongly consider reversal of AC (this will typically come after control) Stopping the Bleeding PPE: these things bleed like stink. Anecdote. Gown, gloves and most importantly eye and face protection Ideal: commercial posterior pack Two balloons – one for anterior, one for posterior Place the device (straight back parallel to the floor) Inflate anterior balloon (10-15 cc) of air If still bleeding, inflate posterior balloon (5-10 cc of air) Foley: if no commercial device Place foley catheter just as you would place a nasal tampon When you see the tip of the foley in the posterior pharynx, inflate balloon (5-10 cc) Need to pull back a bit and secure (can do this with tape on the nose) Post Placement Care Antibiotics: standard practice to give cephalexin or amox/clav. Literature doesn’t defend this approach but, the lit is pretty sparse. The idea behind abx is to prevent things like AOM and TSS but neither should be much of an issue with short term placement ICU Admission? Traditional teaching is that these patients are at risk for life-threatening bradydysrhythmias and should go to the ICU Literature here is non-existent. Two oft-cited articles Cassisi Laryngoscope 1971 – no mention of cardiac events in the article but widely cited Zeyyan Laryngoscope 2010 – slightly lower HR in the packing group but no bradydysrhythmias Before throwing ICU out Hypoxia can occur – Cassisi found about a 20 mm Hg drop in PaO2 but all the patients in this publication were sedated so the packing may not have been the issue look at Viducich 1995 Acad Emerg Med – showed that 18% of the 88 patients with posterior epistaxis required a surgical intervention. With that in mind, you want to consider placing patients into a setting where they can be frequently reassessed – perhaps SDU. This will be pretty location specific. If you treat a posterior bleed at a hospital without ENT, I would transfer as surgical intervention is pretty common REBEL EM: Do Patients with Epistaxis Managed by Nasal Packing Require Prophylactic Antibiotics? REBEL EM: Do Patients with Posterior Epistaxis Managed by Posterior Packs Require ICU Admission? EMRAP HD: Epistaxis Posterior Pack References Cassisi NJ et al. Changes in arterial oxygen tension and pulmonary mechanics with the use of posterior packing in epistaxis: a preliminary report. Laryngoscope 1971; 81(8): 1261-6. PMID: 5569677 Zeyyan E et al. The effects on cardiac function and arterial blood gas of totally occluding nasal packs and nasal packs with airway. Laryngoscope 2010; 120: 2325-2330. PMID: 20938948 Loftus BC et al. Epistaxis, medical history and the nasopulmonary reflex: what is clinically relevant. Otolaryngol Head Neck Surg 1994; 110: 363-9. PMID: 8170679 Viducich RA et al. Posterior epistaxis: clinical features and acute complications. Acad Emerg Med 1995; 25(5): 592-6. PMID: 7741333 Corrales CE, Goode RL. Should patients with posterior nasal packing require ICU admission. Laryngoscope 2013; 123: 2928-9. PMID: 24114977 Post Peer Reviewed By: Salim R. Rezaie, MD (Twitter/X: @srrezaie) The post REBEL Core Cast 123.0 – Posterior Epistaxis appeared first on REBEL EM - Emergency Medicine Blog.

    7 min
  3. 12/06/2024

    REBEL Core Cast 124.0 – Hyperinsulinemia Euglycemia Therapy

    Take Home Points Management of severe beta-blocker and calcium-channel blocker toxicity should occur in a stepwise fashion: potential gastric decontamination, multiple lines of access, judicious fluids, calcium, glucagon, and vasopressors as needed. Initiation of high dose insulin therapy requires a tremendous amount of logistical and cognitive resources as it requires cross-disciplinary collaboration and is prone to mismanagement. If the patient doesn’t respond to maximum pharmacologic therapy, venous-arterial ECMO should be considered. REBEL Core Cast 124.0 – Hyperinsulinemia Euglycemia Therapy Click here for Direct Download of the Podcast. Background and Physiology Shock secondary to beta-blocker (BB) or calcium-channel blocker (CCB) toxicity bears a tremendous degree of morbidity and mortality. According to the 2022 Annual Report of the National Poison Data System from America’s Poison Center, CCBs and BBs account for the sixth and seventh largest number of fatalities from overdose.1 Recall that cardiac output is a function of both stroke volume and heart rate. The natural response to diminishing stroke volume is a compensatory rise in heart rate (tachycardia). Keep a low threshold to search a patient’s medication list for BB/CCBs, when a hypotension is seen with a “normal heart rate.” Clinical Manifestations Both BBs and CCBs ultimately cause reduced levels of intracellular calcium within myocytes. Depending on the degree of toxicity, subsequent effects include: decreased systemic vascular resistance, vasodilation, bradycardia, various conduction delays, and ultimately hypotension and cardiogenic shock. In addition to abnormal vital signs, look for surrogates of poor clinical perfusion: acidemia, lactate, decreasing urinary output Traditional Management Consider GI decontamination to reduce systemic absorption: 1g/kg up to 50g of activated charcoal. Patient must be alert or the airway must be secured as to avoid aspiration. Obtain multiple lines of intravenous access (3 PIVs or triple lumen CVC) and provide a judicious amount of fluids. (more on this below) Pharmacotherapy Calcium Gluconate: 1-3g intravenous Glucagon: 3mg-5mg slow intravenous push. Rapid administration may induce nausea and emesis. Vasopressors as a bridge to… HIET Mechanism of action is still not fully elucidated however several factors are implicated: Insulin augments cardiac contractility by activating “reverse-mode” Na-Ca exchange and subsequently increasing calcium concentration in the sarcoplasmic reticulum. 2 At a resting physiologic state, the heart utilize free fatty acids as its primary energy course. Under stressed conditions, glucose is used instead. Insulin helps to facilitate glucose metabolism. HIET Dosing: 1 unit/kg IV bolus. Then infusion starting at 1 unit/kg/hr infusion and titrate q30-60 minutes, keeping in mind that effects are not instant. Relative maximum is ~10 unit/kg/hr. If glucose 250 mg/dL, administer a bolus of dextrose 25-50 g (or 0.5-1 g/kg) IV. Ask pharmacy to concentrate insulin from 1 unit/mL to 10 units/ml. Patients often succumb to volume overload given pre-existing cardiac disease and the volume of medical resuscitation through their hospital stay. Once HIET is initiated, dextrose and potassium infusions should simultaneously be started to obviate hypoglycemia and hypokalemia Dextrose: 0.5-1 g/kg/hr via D50/D20 Replete potassium to a minimum of 3.5mEq/L A central venous catheter (often a triple lumen) is often needed to emergently replete potassium and provide D50/D20 safely (given its high osmolarity) Serial monitoring of dextrose (q15-30 minutes) and potassium (q1 hour) is critical HIET has been demonstrated to improve perfusion without necessarily increasing SVR/MAP – while MAPs may not markedly increase dramatically in the short term, obtain serial blood gases, lactate, and track urinary output to track perfusion. 3 Hyperinsulinemia Euglycemia Therapy (HIET) for BB/CCB Toxicity Management of severe beta-blocker and calcium-channel blocker toxicity should occur in a stepwise fashion: potential gastric decontamination, multiple lines of access, judicious fluids, calcium, glucagon, and vasopressors as needed. Initiation of high dose insulin therapy requires a tremendous amount of logistical and cognitive resources as it requires cross-disciplinary collaboration and is prone to mismanagement. HIET Dosing: 1 unit/kg IV bolus. Then infusion starting at 1 unit/kg/hr infusion and titrate q30-60 minutes, keeping in mind that effects are not instant. Relative maximum is ~10 unit/kg/hr. HIET therapy requires simultaneous dextrose and potassium infusions as insulin will induce hypoglycemia and shift potassium intracellularly. If the patient doesn’t respond to maximum pharmacologic therapy, venous-arterial ECMO should be considered. References Gummin DD, Mowry JB, Beuhler MC, et al. 2022 Annual Report of the National Poison Data System® (NPDS) from America’s Poison Centers®: 40th Annual Report. Clin Toxicol (Phila). 2023;61(10):717-939. doi:10.1080/15563650.2023.226898 von Lewinski D, Bruns S, Walther S, Kögler H, Pieske B. Insulin causes [Ca2+]i-dependent and [Ca2+]i-independent positive inotropic effects in failing human myocardium. Circulation. 2005;111(20):2588-2595. doi:10.1161/CIRCULATIONAHA.104.497461 Holger JS, Engebretsen KM, Fritzlar SJ, Patten LC, Harris CR, Flottemesch TJ. Insulin versus vasopressin and epinephrine to treat beta-blocker toxicity. Clin Toxicol (Phila). 2007;45(4):396-401. doi:10.1080/15563650701285412 Post Peer Reviewed By: Salim R. Rezaie, MD (Twitter/X: @srrezaie) The post REBEL Core Cast 124.0 – Hyperinsulinemia Euglycemia Therapy appeared first on REBEL EM - Emergency Medicine Blog.

    15 min
  4. 26/06/2024

    REBEL Core Cast 125.0 – Hyperkalemia

    Take Home Points Always obtain an EKG in patients with ESRD upon presentation Always obtain an EKG in patients with hyperkalemia as pseudohyperkalemia is the number one cause If the patient with hyperkalemia is unstable or has significant EKG changes (wide QRS, sine wave) rapidly administer calcium salts In patients who are anuric, early mobilization of dialysis resources is critical REBEL Core Cast 125.0 – Hyperkalemia Click here for Direct Download of the Podcast. Definition: A serum potassium level > 5.5 mmol/L Epidemiology Common electrolyte disorder 10% of hospitalized patients (Elliott 2010) Causes Pseudohyperkalemia: extravascular hemolysis Renal failure (potassium is primarily eliminated by the kidneys) Acidosis Massive cell death (tumor lysis syndrome, rhabdomyolysis, burns, crush injuries, hemolysis) Drugs: ACEI, ARBs, Spironalactone, NSAIDs, Succinycholine Clinical Manifestations Mild hyperkalemia often asymptomatic Cardiac Effects Increased potassium raises the resting membrane potential of cardiac myocytes Slows ventricular conduction Decreases length of action potential Increases cardiac myocyte excitability Cardiac effects can manifest in lethal dysrhythmias Neuromuscular Effects Paresthesias Weakness Flaccid paralysis Depressed or absent deep tendon reflexes Diagnosis Suspect hyperkalemia in ALL patients with renal impairment, especially end-stage renal disease (ESRD) Serum potassium Can be artificially elevated by extravascular hemolysis Blood gas results may differ from standard metabolic panels by up to 0.5mmol/L 12-Lead EKG Screening test that can rapidly detect severe cardiac manifestations of hyperkalemia A normal EKG with a significant serum potassium elevation should raise concerns for spurious results (extravascular hemolysis) Sensitivity of EKG to detect hyperkalemia is poor (Wrenn 1991, Aslam 2002, Montague 2008) Classic EKG findings PR prolongation Peaked T waves Loss of P waves Widening of QRS complex Sine wave Ventricular Fibrillation Asystole Note: Hyperkalemia can present with a number of “non-classic” EKG findings including AV blocks and sinus bradycardia (Mattu 2000) Note: Hyperkalemic EKG changes do not necessarily occur in order (i.e. patients can jump from peaked T waves to sine wave) Management Basics: ABCs, IV, O2, Cardiac Monitor and, 12-lead EKG Identify + treat underlying cause of hyperkalemia (i.e. rhabdomyolysis -> hydration) Remove inciting factors (i.e. stop ACEI, NSAIDs etc) Asymptomatic Patients without EKG Changes Eliminate potassium from the body Binding agents (SPS, Sodium zirconium cyclosilicate etc) Enhance renal elimination Intravenous hydration if volume depleted Consider potassium wasting loop diuretics (i.e. furosemide) Dialysis for anuric patients (i.e. ESRD) Symptomatic Patients or Significant EKG Changes Stabilize cardiac myocytes with calcium salts Mechanism: Recreates the electrical gradient leading to rapid reversal of cardiac effects and rapid stabilization Two Options: CaGluconate, CaCl2 No difference in time to onset (1st pass metabolism is a myth) Dose: 1 ampule CaCl2 (270 mg Ca2+) = 3 ampules CaGluconate (90 mg Ca2+/ampule) Onset of action: seconds to minutes Duration: 20-30 minutes Shift potassium into intracellular space (temporary) Insulin (Moussavi 2021) Mechanism: Activation of the Na-K-ATPase Dose: 5-10 units IV Onset of Action: 15 min Effect: Lowers potassium by about 0.6 mmol Duration of action: 30-60 min Give with dextrose (0.5 – 1 g/kg) unless hyperglycemia present Caution: Duration of action of insulin may outlast administered dextrose. Be vigilant for hypoglycemia Beta-adrenoreceptor agonists (i.e. albuterol) Mechanism: Activation of beta receptors Dose: 10-20 mg inhaled (4-8 standard ampules) Onset of Action: 15 min Effect: Lowers potassium by about 0.6 mmol Duration of action: 30-60 min Additive effect with insulin (Allon 1990) Note: Unlikely to have effect in patients taking beta-adrenoreceptor blocker medications Sodium Bicarbonate (NaHCO3) Evidence for the efficacy of NaHCO3 to lower serum potassium is scant and contradictory (Elliott 2010, Weisberg 2008) Eliminate potassium from the body (see above) Asymptomatic Patients with Minor EKG Changes Minimal recommendations on managing this clinical entity Eliminate potassium from the body (see above) Consider calcium salt administration: patients can rapidly progress through EKG changes and calcium administration may prevent this from occurring. However, the effects of calcium are temporary and offer no long-term protection Consider medications to shift potassium intracellularly while waiting for elimination Take Home Points Always obtain an EKG in patients with ESRD upon presentation Always obtain an EKG in patients with hyperkalemia as pseudohyperkalemia is the number one cause If the patient with hyperkalemia is unstable or has significant EKG changes (wide QRS, sine wave) rapidly administer calcium salts In patients who are anuric, early mobilization of dialysis resources is critical References Elliott MJ et al. Management of patients with acute hyperkalemia. CMAJ 2010; 182(15): 1631-5. PMID: 20855477 Wrenn K et al. The ability of physicians to predict hyperkalemia from the ECG. Ann Emerg Med 1991; 20(11): 1229-32. PMID: 1952310 Aslam S et al. Electrocardiography is unreliable in detecting potentially lethal hyperkalaemia in hemodialysis patients. Nephrol Dial Transplant 2002; 17: 1639-42. PMID: 12198216 Montague BT et al. Retrospective review of the frequency of ECG changes in hyperkalemia. Clin J Am Soc Nephrol 2008; 3:324–330. PMID: 18235147 Mattu A et al. Electrocardiographic manifestations of hyperkalemia. Am J Emerg Med 2000; 18: 721-9. PMID: 11043630 Allon M, Copkney C. Albuterol and insulin for treatment of hyperkalemia in hemodialysis patients. Kidney Int 1990; 38:869–872. PMID: 2266671 Weisberg LS. Management of hyperkalemia. Crit Care Med 2008; 36: 3246-51. PMID: 18936701 Moussavi K et al. Reduced alternative insulin dosing in hyperkalemia: a meta-analysis of effects on hypoglycemia and potassium reduction. Pharmacotherapy 2021; 41(7): 598-607. PMID: 33993515 Post Peer Reviewed By: Salim R. Rezaie, MD (Twitter/X: @srrezaie) The post REBEL Core Cast 125.0 – Hyperkalemia appeared first on REBEL EM - Emergency Medicine Blog.

    8 min
  5. 22/07/2024

    A Winning Hand in Cardiology: Queen of Hearts AI Model Enhances OMI Detection

    Background: Cath lab activation based on ST-elevation myocardial infarction (STEMI) criteria is founded on aging data and requires evolution. In the “Occlusive Myocardial Infarction (OMI) Manifesto,” emergency physicians Dr. Steve Smith, Dr. Pendell Meyers, and Dr. Scott Weingart introduced a new paradigm —OMI vs. non-occlusive myocardial infarction (NOMI). The OMI/NOMI paradigm focuses on the presence of coronary occlusion, while STEMI/NSTEMI categorizes myocardial infarctions based on electrocardiogram (ECG) findings. Patients with OMI exhibit higher mortality and worse left ventricular function compared to those with NOMI.1, 2, 3 Detecting OMI is more difficult and necessitates scrutiny of the ECG, which is challenging in a busy emergency department where ED clinicians are interrupted more than ten times per hour.4, 5 Some OMI ECG signs include ST elevation in only one lead, subtle ST elevation with minimal reciprocal changes, isolated ST depressions, and hyperacute T waves. To meet this challenge, Dr. Steve Smith, Dr. Pendell Meyers (Dr. Smith’s ECG Blog), and their team developed The Queen of Hearts, a machine-learning AI model that has the potential to aid in the early detection of subtle OMI ECG changes. Accurately identifying OMI changes in ECG that STEMI criteria might otherwise miss would allow for more timely intervention, potentially salvaging more myocardium. An AI model that is highly sensitive in detecting OMI while maintaining a high degree of specificity would be an ideal tool to support emergency physicians’ clinical decision-making. The performance of this tool is unknown. Click here for Direct Download of the Podcast. Paper: Herman R, Meyers HP, Smith SW, et al. International evaluation of an artificial intelligence-powered electrocardiogram model detecting acute coronary occlusion myocardial infarction. Eur Heart J Digit Health. 2023;5(2):123-133. Published 2023 Nov 28. PMID: 38505483 Clinical question: “Can an AI model detect an OMI lesion using a single 12-lead ECG?” What They Did: Investigators performed a retrospective derivation study followed by validation on an internal data set from the same Acute Coronary Syndrome (ACS) database. Cases eligible for inclusion were randomly assigned to a model development training set (derivation set) and testing set (validation set).   The training set included ECG feature extraction and classification Feature extraction used 60,000 parameters The classification component combined all extracted features and used an additional 150,000 parameters. The validation data set was used for hyperparameter tuning and threshold selection.  Investigators then tested the AI model on two data sets An internal European data set (internal validation set) A separate US data set (external validation set) from the DOMI ARIGATO database. They compared the AI model with the existing criteria for detecting OMI on 12-lead ECGs and analyzed the AI model in various subgroups. Population: Derivation Set: Random selection of ACS patients from the Cardiovascular Centre Aalst in Belgium and ACS patients from an international image database patient. EU Internal Test Set: Random Selection of ACS patients from the Cardiovascular Centre Aalst in Belgium and ACS patients from an international image database patient. US External Test Set: Patients from the DOMI ARIGATO database. Exclusion: ECGs >24 h before CAG and post-CAG ECGs with poor signal quality  ECGs with missing Expert Annotation, undigitizable ECGs, Baseline ECGs (additionally excluded from the US External Database) Intervention: AI-powered ECG model implemented on ECGs from the internal EU and external US datasets. Comparator: Blinded physician annotations of the standard ‘STEMI criteria’ on ECG Blinded subjective ECG expert annotations of OMI Angiographic clinical outcome data Outcomes: Primary Outcome: AI model’s ability to identify patients with angiographically confirmed OMI using only the 12-lead ECG. Secondary Outcomes: OMI AI model performance across demographic and ECG subgroups A comparison of the AI model performance against the existing STEMI criteria for detecting acute coronary occlusion from 12-lead ECGs A sensitivity analysis of AI model performance using various angiographic and laboratory cut-offs of OMI An evaluation of misclassified cases Results: The derivation set used in the AI model development included 18,616 ECGs from 10,543 patients with clinically validated outcomes. The overall test set included 3254 ECGs from 2222 patients   The internal EU testing cohort 2016 ECGs from 1630 patients  The US testing cohort 1238 ECGs from 633 patients  The prevalence of OMI differed between the internal EU and the external US test sets, 16% compared with 36.2%, respectively ( 0.001). The patients in the US test set were younger, had more ECGs recorded before catheterization, and were more likely to present with a STEMI-positive ECG. AI Model Performance: Achieved an Area Under the ROC Curve (AUC) of 0.938 [95% CI: 0.924–0.951]. Accuracy: 90.9% [95% CI: 89.7–92.0]. Sensitivity: 80.6% [95% CI: 76.8–84.0]. Specificity: 93.7% [95% CI: 92.6–94.8]. STEMI Criteria Performance: STEMI criteria accuracy: 83.6% [95% CI: 82.1–85.1]. Sensitivity: 32.5% [95% CI: 28.4–36.6]. Specificity: 97.7% [95% CI: 97.0–98.3]. ECG Experts Performance: Accuracy of ECG experts was 90.8% [95% CI: 89.5–91.9]. Sensitivity: 73.0% [95% CI: 68.7–77.0]. Specificity: 95.7% [95% CI: 94.7–96.6]. OMI AI Model vs. STEMI Criteria: The OMI AI model performs significantly better than the STEMI criteria in sensitivity, Negative Predictive Value (NPV), Matthews correlation coefficient (MCC), and AUC. However, it has lower specificity and Positive Predictive Value (PPV) compared to the STEMI criteria. OMI AI Model vs. ECG Experts: The OMI AI model has higher sensitivity and NPV than ECG experts. It shows equal performance in AUC and is adjudicated as equal overall to ECG experts. Specificity and PPV are lower than ECG experts, and MCC is neutral. ECG Experts vs. STEMI Criteria: ECG experts have higher sensitivity, NPV, MCC, and AUC than STEMI criteria. They perform the same in specificity and PPV compared to STEMI criteria, leading to significantly better adjudication. Strengths: Rigorous Methodological Approach: The study follows a comprehensive methodological approach, encompassing stages of development, validation, and comparison. Large and Diverse Dataset: The model was trained and tested on a substantial dataset of 18,616 ECGs from 10,543 patients with ACS across multiple international cohorts. This diversity enhances the model’s generalizability and robustness. Expert Interpretation and Validation: All cases in the derivation set included expert ECG interpretations alongside clinically validated angiographic outcome data, ensuring high accuracy in the model’s training process. High Agreement Among Experts: Two authors, serving as ECG experts, annotated all tracings for the presence of OMI while being blinded to all clinical data. They achieved a 94% agreement (kappa = 0.849), demonstrating the reliability of the expert annotations. Independent Review: Blinded independent clinical reviewers adjudicated all angiographic data in the EU internal testing set, adding an extra layer of objectivity and reliability to the validation process. Comprehensive Performance Comparison: The study compares the AI model’s performance with existing STEMI criteria and expert ECG interpretations. This sets a quantifiable humanistic standard, highlighting the AI model’s enhanced performance. Limitations: Applicability Limited to ACS Patients: The AI model was developed using patients and ECGs exclusively from ACS databases, restricting its applicability to only those with ACS. Disease-Oriented Outcomes: The outcomes in this study are disease-oriented. While facilitating the diagnosis of OMI may lead to improved patient-oriented outcomes, this was not directly studied. Limited Generalizability to Asymptomatic Patients: The study is not generalizable to a broader population of asymptomatic patients and was not designed to quantify other relevant clinical endpoints such as mortality, in-hospital complications, or major adverse cardiovascular events (MACE). Lack of Prospective Validation: The validation set was analyzed retrospectively, lacking prospective validation to confirm the model’s effectiveness in real-world clinical settings. Randomization Process Not Mentioned: The randomization process used to allocate cases to the derivation or validation set is not mentioned, which may impact the robustness of the findings. Comparison Limited to 12-Lead ECG: The AI model was compared to the 12-lead ECG alone. Some patients undergo emergency angiography without clear STEMI criteria based on the full clinical picture. Therefore, the interpretation of the overall gain is limited without a pragmatic comparison to real-world clinical practices and patient-oriented outcomes. Limited Generalizability to Younger Population and Women: Approximately 10% of ECGs were from patients ≤45 years of age, and three-quarters of the cases were from males, limiting the generalizability to younger populations and women. Inappropriate Use of P-Values: The inclusion of p-values in Tables 1 and 2 is puzzling, as this is not a randomized controlled trial (RCT). Demographic differences between validation sets are expected and desired for external validity. Variability in Care Standards: Significant differences in clinical presentation and management between patients in Europe and the USA (e.g., the USA had younger patients and more ECGs before catheterization) could affect the model’s performance across different healthcare systems. Subjective Outcome Verification: The detection of OMI relied on visual verification of TIMI flow on angiograms, which may be subjective. Conflict o

    45 min

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Rational Evidence-Based Evaluation of Literature

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