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Item Association between microbiome and the development of adverse posttraumatic neuropsychiatric sequelae after traumatic stress exposure(Springer Nature, 2023-11-18) Zeamer, Abigail L.; Salive, Marie-Claire; An, Xinming; Beaudoin, Francesca L.; House, Stacey L.; Stevens, Jennifer S.; Zeng, Donglin; Neylan, Thomas C.; Clifford, Gari D.; Linnstaedt, Sarah D.; Rauch, Scott L.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Swor, Robert A.; Hudak, Lauren A.; Pascual, Jose L.; Seamon, Mark J.; Harris, Erica; Pearson, Claire; Peak, David A.; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O’Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Kessler, Ronald C.; Koenen, Karestan C.; McLean, Samuel A.; Bucci, Vanni; Haran, John P.; Emergency Medicine, School of MedicinePatients exposed to trauma often experience high rates of adverse post-traumatic neuropsychiatric sequelae (APNS). The biological mechanisms promoting APNS are currently unknown, but the microbiota-gut-brain axis offers an avenue to understanding mechanisms as well as possibilities for intervention. Microbiome composition after trauma exposure has been poorly examined regarding neuropsychiatric outcomes. We aimed to determine whether the gut microbiomes of trauma-exposed emergency department patients who develop APNS have dysfunctional gut microbiome profiles and discover potential associated mechanisms. We performed metagenomic analysis on stool samples (n = 51) from a subset of adults enrolled in the Advancing Understanding of RecOvery afteR traumA (AURORA) study. Two-, eight- and twelve-week post-trauma outcomes for post-traumatic stress disorder (PTSD) (PTSD checklist for DSM-5), normalized depression scores (PROMIS Depression Short Form 8b) and somatic symptom counts were collected. Generalized linear models were created for each outcome using microbial abundances and relevant demographics. Mixed-effect random forest machine learning models were used to identify associations between APNS outcomes and microbial features and encoded metabolic pathways from stool metagenomics. Microbial species, including Flavonifractor plautii, Ruminococcus gnavus and, Bifidobacterium species, which are prevalent commensal gut microbes, were found to be important in predicting worse APNS outcomes from microbial abundance data. Notably, through APNS outcome modeling using microbial metabolic pathways, worse APNS outcomes were highly predicted by decreased L-arginine related pathway genes and increased citrulline and ornithine pathways. Common commensal microbial species are enriched in individuals who develop APNS. More notably, we identified a biological mechanism through which the gut microbiome reduces global arginine bioavailability, a metabolic change that has also been demonstrated in the plasma of patients with PTSD.Item Associations of Alcohol and Cannabis Use with Change in Posttraumatic Stress Disorder and Depression Symptoms Over Time in Recently Trauma-exposed Individuals(Cambridge University Press, 2024) Hinojosa, Cecilia A.; Liew, Amanda; An, Xinming; Stevens, Jennifer S.; Basu, Archana; van Rooij, Sanne J. H.; House, Stacey L.; Beaudoin, Francesca L.; Zeng, Donglin; Neylan, Thomas C.; Clifford, Gari D.; Jovanovic, Tanja; Linnstaedt, Sarah D.; Germine, Laura T.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Kurz, Michael C.; Swor, Robert A.; Hudak, Lauren A.; Pascual, Jose L.; Seamon, Mark J.; Datner, Elizabeth M.; Chang, Anna M.; Pearson, Claire; Peak, David A.; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Miller, Mark W.; Pietrzak, Robert H.; Joormann, Jutta; Pizzagalli, Diego A.; Sheridan, John F.; Harte, Steven E.; Elliott, James M.; Kessler, Ronald C.; Koenen, Karestan C.; McLean, Samuel A.; Ressler, Kerry J.; Fani, Negar; Emergency Medicine, School of MedicineBackground: Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians. Methods: In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance. Results: Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12. Conclusions: Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.Item Brain-Based Biotypes of Psychiatric Vulnerability in the Acute Aftermath of Trauma(American Psychiatric Association, 2021) Stevens, Jennifer S.; Harnett, Nathaniel G.; Lebois, Lauren A.M.; van Rooij, Sanne J.H.; Ely, Timothy D.; Roeckner, Alyssa; Vincent, Nico; Beaudoin, Francesca L.; An, Xinming; Zeng, Donglin; Neylan, Thomas C.; Clifford, Gari D.; Linnstaedt, Sarah D.; Germine, Laura T.; Rauch, Scott L.; Lewandowski, Christopher; Storrow, Alan B.; Hendry, Phyllis L.; Sheikh, Sophia; Musey, Paul I., Jr.; Haran, John P.; Jones, Christopher W.; Punches, Brittany E.; Lyons, Michael S.; Kurz, Michael C.; McGrath, Meghan E.; Pascual, Jose L.; Datner, Elizabeth M.; Chang, Anna M.; Pearson, Claire; Peak, David A.; Domeier, Robert M.; O'Neil, Brian J.; Rathlev, Niels K.; Sanchez, Leon D.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Sheridan, John F.; Luna, Beatriz; Harte, Steven E.; Elliott, James M.; Murty, Vishnu P.; Jovanovic, Tanja; Bruce, Steven E.; House, Stacey L.; Kessler, Ronald C.; Koenen, Karestan C.; McLean, Samuel A.; Ressler, Kerry J.; Emergency Medicine, School of MedicineObjective: Major negative life events, such as trauma exposure, can play a key role in igniting or exacerbating psychopathology. However, few disorders are diagnosed with respect to precipitating events, and the role of these events in the unfolding of new psychopathology is not well understood. The authors conducted a multisite transdiagnostic longitudinal study of trauma exposure and related mental health outcomes to identify neurobiological predictors of risk, resilience, and different symptom presentations. Methods: A total of 146 participants (discovery cohort: N=69; internal replication cohort: N=77) were recruited from emergency departments within 72 hours of a trauma and followed for the next 6 months with a survey, MRI, and physiological assessments. Results: Task-based functional MRI 2 weeks after a motor vehicle collision identified four clusters of individuals based on profiles of neural activity reflecting threat reactivity, reward reactivity, and inhibitory engagement. Three clusters were replicated in an independent sample with a variety of trauma types. The clusters showed different longitudinal patterns of posttrauma symptoms. Conclusions: These findings provide a novel characterization of heterogeneous stress responses shortly after trauma exposure, identifying potential neuroimaging-based biotypes of trauma resilience and psychopathology.Item Classification and Prediction of Post-Trauma Outcomes Related to PTSD Using Circadian Rhythm Changes Measured via Wrist-Worn Research Watch in a Large Longitudinal Cohort(IEEE, 2021) Cakmak, Ayse S.; Perez Alday, Erick A.; Da Poian, Giulia; Rad, Ali Bahrami; Metzler, Thomas J.; Neylan, Thomas C.; House, Stacey L.; Beaudoin, Francesca L.; An, Xinming; Stevens, Jennifer S.; Zeng, Donglin; Linnstaedt, Sarah D.; Jovanovic, Tanja; Germine, Laura T.; Bollen, Kenneth A.; Rauch, Scott L.; Lewandowski, Christopher A.; Hendry, Phyllis L.; Sheikh, Sophia; Storrow, Alan B.; Musey, Paul I., Jr.; Haran, John P.; Jones, Christopher W.; Punches, Brittany E.; Swor, Robert A.; Gentile, Nina T.; McGrath, Meghan E.; Seamon, Mark J.; Mohiuddin, Kamran; Chang, Anna M.; Pearson, Claire; Domeier, Robert M.; Bruce, Steven E.; O’Neil, Brian J.; Rathlev, Niels K.; Sanchez, Leon D.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Harte, Steven E.; Elliott, James M.; Kessler, Ronald C.; Koenen, Karestan C.; Ressler, Kerry J.; Mclean, Samuel A.; Li, Qiao; Clifford, Gari D.; Emergency Medicine, School of MedicinePost-Traumatic Stress Disorder (PTSD) is a psychiatric condition resulting from threatening or horrifying events. We hypothesized that circadian rhythm changes, measured by a wrist-worn research watch are predictive of post-trauma outcomes. Approach: 1618 post-trauma patients were enrolled after admission to emergency departments (ED). Three standardized questionnaires were administered at week eight to measure post-trauma outcomes related to PTSD, sleep disturbance, and pain interference with daily life. Pulse activity and movement data were captured from a research watch for eight weeks. Standard and novel movement and cardiovascular metrics that reflect circadian rhythms were derived using this data. These features were used to train different classifiers to predict the three outcomes derived from week-eight surveys. Clinical surveys administered at ED were also used as features in the baseline models. Results: The highest cross-validated performance of research watch-based features was achieved for classifying participants with pain interference by a logistic regression model, with an area under the receiver operating characteristic curve (AUC) of 0.70. The ED survey-based model achieved an AUC of 0.77, and the fusion of research watch and ED survey metrics improved the AUC to 0.79. Significance: This work represents the first attempt to predict and classify post-trauma symptoms from passive wearable data using machine learning approaches that leverage the circadian desynchrony in a potential PTSD population.Item Clinical and Research Considerations for Patients with Hypertensive Acute Heart Failure(Elsevier, 2016-08) Collins, Sean P.; Levy, Phillip D.; Martindale, Jennifer L.; Dunlap, Mark E.; Storrow, Alan B.; Pang, Peter S.; Sawyer, Douglas B.; Fermann, Gregory J.; Lenihan, Daniel J.; Peacock, W. Frank; Albert, Nancy M.; Hollander, Judd E.; Lindenfeld, JoAnn M.; Teerlink, John R.; Felker, G. Michael; Fonarow, Gregg C.; Butler, Javed; Department of Emergency Medicine, IU School of MedicineManagement approaches for patients in the emergency department (ED) who present with acute heart failure (AHF) have largely focused on intravenous diuretics. Yet, the primary pathophysiologic derangement underlying AHF in many patients is not solely volume overload. Patients with hypertensive AHF (H-AHF) represent a clinical phenotype with distinct pathophysiologic mechanisms that result in elevated ventricular filling pressures. To optimize treatment response and minimize adverse events in this subgroup, we propose that clinical management be tailored to a conceptual model of disease based on these mechanisms. This consensus statement reviews the relevant pathophysiology, clinical characteristics, approach to therapy, and considerations for clinical trials in ED patients with H-AHF.Item Current Emergency Department Disposition of Patients With Acute Heart Failure: An Opportunity for Improvement(Elsevier, 2022) Sax, Dana R.; Mark, Dustin G.; Rana, Jamal S.; Reed, Mary E.; Lindenfeld, Joann; Stevenson, Lynne W.; Storrow, Alan B.; Butler, Javed; Pang, Peter S.; Collins, Sean P.; Emergency Medicine, School of MedicineEmergency department (ED) providers play a critical role in the stabilization and diagnostic evaluation of patients presenting with acute heart failure (AHF), and EDs are key areas for establishing current best practices and future considerations for the disposition of and decision making for patients with AHF. These elements include accurate risk assessment; response to initial treatment and shared decision making concerning optimal venue of care; reframing of physicians' risk perceptions for patients presenting with AHF; exploration of alternative venues of care beyond hospitalization; population-level changes in demographics, management and outcomes of HF patients; development and testing of data-driven pathways to assist with disposition decisions in the ED; and suggested outcomes for measuring success.Item Delirium and its association with short-term outcomes in younger and older patients with acute heart failure(Public Library of Science, 2022-07-26) Han, Jin H.; McNaughton, Candace D.; Stubblefield, William B.; Pang, Peter S.; Levy, Phillip D.; Miller, Karen F.; Meram, Sarah; Cole, Mette Lind; Jenkins, Cathy A.; Paz, Hadassah H.; Moser, Kelly M.; Storrow, Alan B.; Collins, Sean P.; Emergency Medicine Research and Outcomes Consortium Investigators; Emergency Medicine, School of MedicineYounger patients (18 to 65 years old) are often excluded from delirium outcome studies. We sought to determine if delirium was associated with short-term adverse outcomes in a diverse cohort of younger and older patients with acute heart failure (AHF). We conducted a multi-center prospective cohort study that included adult emergency department patients with confirmed AHF. Delirium was ascertained using the Brief Confusion Assessment Method (bCAM). The primary outcome was a composite outcome of 30-day all-cause death, 30-day all-cause rehospitalization, and prolonged index hospital length of stay. Multivariable logistic regression was performed, adjusting for demographics, cognitive impairment without delirium, and HF risk factors. Older age (≥ 65 years old)*delirium interaction was also incorporated into the model. Odds ratios (OR) with their 95% confidence intervals (95%CI) were reported. A total of 1044 patients with AHF were enrolled; 617 AHF patients were < 65 years old and 427 AHF patients were ≥ 65 years old, and 47 (7.6%) and 40 (9.4%) patients were delirious at enrollment, respectively. Delirium was significantly associated with the composite outcome (adjusted OR = 1.64, 95%CI: 1.02 to 2.64). The older age*delirium interaction p-value was 0.47. In conclusion, delirium was common in both younger and older patients with AHF and was associated with poorer short-term outcomes in both cohorts. Younger patients with acute heart failure should be included in future delirium outcome studies.Item Derivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision(Elsevier, 2023) Jones, Christopher W.; An, Xinming; Ji, Yinyao; Liu, Mochuan; Zeng, Donglin; House, Stacey L.; Beaudoin, Francesca L.; Stevens, Jennifer S.; Neylan, Thomas C.; Clifford, Gari D.; Jovanovic, Tanja; Linnstaedt, Sarah D.; Germine, Laura T.; Bollen, Kenneth A.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Punches, Brittany E.; Lyons, Michael S.; Kurz, Michael C.; Swor, Robert A.; McGrath, Meghan E.; Hudak, Lauren A.; Pascual, Jose L.; Seamon, Mark J.; Datner, Elizabeth M.; Harris, Erica; Chang, Anna M.; Pearson, Claire; Peak, David A.; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O'Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Miller, Mark W.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Sheridan, John F.; Smoller, Jordan W.; Harte, Steven E.; Elliott, James M.; Koenen, Karestan C.; Ressler, Kerry J.; Kessler, Ronald C.; McLean, Samuel A.; Emergency Medicine, School of MedicineStudy objective: To derive and initially validate a brief bedside clinical decision support tool that identifies emergency department (ED) patients at high risk of substantial, persistent posttraumatic stress symptoms after a motor vehicle collision. Methods: Derivation (n=1,282, 19 ED sites) and validation (n=282, 11 separate ED sites) data were obtained from adults prospectively enrolled in the Advancing Understanding of RecOvery afteR traumA study who were discharged from the ED after motor vehicle collision-related trauma. The primary outcome was substantial posttraumatic stress symptoms at 3 months (Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders-5 ≥38). Logistic regression derivation models were evaluated for discriminative ability using the area under the curve and the accuracy of predicted risk probabilities (Brier score). Candidate posttraumatic stress predictors assessed in these models (n=265) spanned a range of sociodemographic, baseline health, peritraumatic, and mechanistic domains. The final model selection was based on performance and ease of administration. Results: Significant 3-month posttraumatic stress symptoms were common in the derivation (27%) and validation (26%) cohort. The area under the curve and Brier score of the final 8-question tool were 0.82 and 0.14 in the derivation cohort and 0.76 and 0.17 in the validation cohort. Conclusion: This simple 8-question tool demonstrates promise to risk-stratify individuals with substantial posttraumatic stress symptoms who are discharged to home after a motor vehicle collision. Both external validation of this instrument, and work to further develop more accurate tools, are needed. Such tools might benefit public health by enabling the conduct of preventive intervention trials and assisting the growing number of EDs that provide services to trauma survivors aimed at promoting psychological recovery.Item Design and Rationale of a Randomized Trial of a Care Transition Strategy in Patients With Acute Heart Failure Discharged From the Emergency Department: GUIDED-HF (Get With the Guidelines in Emergency Department Patients With Heart Failure).(American Heart Association, 2017-02) Fermann, Gregory J.; Levy, Phillip D.; Pang, Peter; Butler, Javed; Ayaz, S. Imran; Char, Douglas; Dunn, Pat; Jenkins, Cathy A.; Kampe, Christy; Khan, Yosef; Kumar, Vijaya A.; Lindenfeld, JoAnn; Liu, Dandan; Miller, Karen; Peacock, W. Frank; Rizk, Samaa; Robichaux, Chad; Rothman, Russell L.; Schrock, Jon; Singer, Adam; Sterling, Sarah A.; Storrow, Alan B.; Walsh, Cheryl; Wilburn, John; Collins, Sean P.; Emergency Medicine, School of MedicineGUIDED-HF (Get With the Guidelines in Emergency Department Patients With Heart Failure) is a multicenter randomized trial of a patient-centered transitional care intervention in patients with acute heart failure (AHF) who are discharged either directly from the emergency department (ED) or after a brief period of ED-based observation. To optimize care and reduce ED and hospital revisits, there has been significant emphasis on improving transitions at the time of hospital discharge for patients with HF. Such efforts have been almost exclusively directed at hospitalized patients; individuals with AHF who are discharged from the ED or ED-based observation are not included in these transitional care initiatives. Patients with AHF discharged directly from the ED or after a brief period of ED-based observation are randomly assigned to our transition GUIDED-HF strategy or standard ED discharge. Patients in the GUIDED arm receive a tailored discharge plan via the study team, based on their identified barriers to outpatient management and associated guideline-based interventions. This plan includes conducting a home visit soon after ED discharge combined with close outpatient follow-up and subsequent coaching calls to improve postdischarge care and avoid subsequent ED revisits and inpatient admissions. Up to 700 patients at 11 sites will be enrolled over 3 years of the study. GUIDED-HF will test a novel approach to AHF management strategy that includes tailored transitional care for patients discharged from the ED or ED-based observation. If successful, this program may significantly alter the current paradigm of AHF patient care.Item Development and Validation of a Model to Predict Posttraumatic Stress Disorder and Major Depression After a Motor Vehicle Collision(American Medical Association, 2021) Ziobrowski, Hannah N.; Kennedy, Chris J.; Ustun, Berk; House, Stacey L.; Beaudoin, Francesca L.; An, Xinming; Zeng, Donglin; Bollen, Kenneth A.; Petukhova, Maria; Sampson, Nancy A.; Puac-Polanco, Victor; Lee, Sue; Koenen, Karestan C.; Ressler, Kerry J.; McLean, Samuel A.; Kessler, Ronald C.; AURORA Consortium; Stevens, Jennifer S.; Neylan, Thomas C.; Clifford, Gari D.; Jovanovic, Tanja; Linnstaedt, Sarah D.; Germine, Laura T.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Lyons, Michael S.; Murty, Vishnu P.; McGrath, Meghan E.; Pascual, Jose L.; Seamon, Mark J.; Datner, Elizabeth M.; Chang, Anna M.; Pearson, Claire; Peak, David A.; Jambaulikar, Guruprasad; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O'Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Sheridan, John F.; Harte, Steven E.; Elliott, James M.; van Rooij, Sanne J.H.; Emergency Medicine, School of MedicineImportance: A substantial proportion of the 40 million people in the US who present to emergency departments (EDs) each year after traumatic events develop posttraumatic stress disorder (PTSD) or major depressive episode (MDE). Accurately identifying patients at high risk in the ED would facilitate the targeting of preventive interventions. Objectives: To develop and validate a prediction tool based on ED reports after a motor vehicle collision to predict PTSD or MDE 3 months later. Design, setting, and participants: The Advancing Understanding of Recovery After Trauma (AURORA) study is a longitudinal study that examined adverse posttraumatic neuropsychiatric sequalae among patients who presented to 28 US urban EDs in the immediate aftermath of a traumatic experience. Enrollment began on September 25, 2017. The 1003 patients considered in this diagnostic/prognostic report completed 3-month assessments by January 31, 2020. Each patient received a baseline ED assessment along with follow-up self-report surveys 2 weeks, 8 weeks, and 3 months later. An ensemble machine learning method was used to predict 3-month PTSD or MDE from baseline information. Data analysis was performed from November 1, 2020, to May 31, 2021. Main outcomes and measures: The PTSD Checklist for DSM-5 was used to assess PTSD and the Patient Reported Outcomes Measurement Information System Depression Short-Form 8b to assess MDE. Results: A total of 1003 patients (median [interquartile range] age, 34.5 [24-43] years; 715 [weighted 67.9%] female; 100 [weighted 10.7%] Hispanic, 537 [weighted 52.7%] non-Hispanic Black, 324 [weighted 32.2%] non-Hispanic White, and 42 [weighted 4.4%] of non-Hispanic other race or ethnicity were included in this study. A total of 274 patients (weighted 26.6%) met criteria for 3-month PTSD or MDE. An ensemble machine learning model restricted to 30 predictors estimated in a training sample (patients from the Northeast or Midwest) had good prediction accuracy (mean [SE] area under the curve [AUC], 0.815 [0.031]) and calibration (mean [SE] integrated calibration index, 0.040 [0.002]; mean [SE] expected calibration error, 0.039 [0.002]) in an independent test sample (patients from the South). Patients in the top 30% of predicted risk accounted for 65% of all 3-month PTSD or MDE, with a mean (SE) positive predictive value of 58.2% (6.4%) among these patients at high risk. The model had good consistency across regions of the country in terms of both AUC (mean [SE], 0.789 [0.025] using the Northeast as the test sample and 0.809 [0.023] using the Midwest as the test sample) and calibration (mean [SE] integrated calibration index, 0.048 [0.003] using the Northeast as the test sample and 0.024 [0.001] using the Midwest as the test sample; mean [SE] expected calibration error, 0.034 [0.003] using the Northeast as the test sample and 0.025 [0.001] using the Midwest as the test sample). The most important predictors in terms of Shapley Additive Explanations values were symptoms of anxiety sensitivity and depressive disposition, psychological distress in the 30 days before motor vehicle collision, and peritraumatic psychosomatic symptoms. Conclusions and relevance: The results of this study suggest that a short set of questions feasible to administer in an ED can predict 3-month PTSD or MDE with good AUC, calibration, and geographic consistency. Patients at high risk can be identified in the ED for targeting if cost-effective preventive interventions are developed.