Two Weeks Versus One Week of Maximal Patient-Intensivist Continuity for Adult Medical Intensive Care Patients: A Two-Center Target Trial Emulation.

OBJECTIVES: To compare outcomes for 2 weeks vs. 1 week of maximal patient-intensivist continuity in the ICU. DESIGN: Retrospective cohort study. SETTING: Two U.S. urban, teaching, medical ICUs where intensivists were scheduled for 2-week service blocks: site A was in the Midwest and site B was in the Northeast. PATIENTS: Patients 18 years old or older admitted to a study ICU between March 1, 2017, and February 28, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We applied target trial emulation to compare admission during an intensivist's first week (as a proxy for 2 wk of maximal continuity) vs. admission during their second week (as a proxy for 1 wk of maximal continuity). Outcomes included hospital mortality, ICU length of stay, and, for mechanically ventilated patients, duration of ventilation. Exploratory outcomes included imaging, echocardiogram, and consultation orders. We used inverse probability weighting to adjust for baseline differences and random-effects meta-analysis to calculate overall effect estimates. Among 2571 patients, 1254 were admitted during an intensivist's first week and 1317 were admitted during a second week. At sites A and B, hospital mortality rates were 25.8% and 24.2%, median ICU length of stay were 4 and 2 days, and median mechanical ventilation durations were 3 and 3 days, respectively. There were no differences in adjusted mortality (odds ratio [OR], 1.01 [95% CI, 0.96-1.06]) or ICU length of stay (-0.25 d [-0.82 d to +0.32 d]) for 2 weeks vs. 1 week of maximal continuity. Among mechanically ventilated patients, there were no differences in adjusted mortality (OR, 1.00 [0.87-1.16]), ICU length of stay (+0.06 d [-0.78 d to +0.91 d]), or duration of mechanical ventilation (+0.37 d [-0.46 d to +1.21 d]) for 2 weeks vs. 1 week of maximal continuity. CONCLUSIONS: Two weeks of maximal patient-intensivist continuity was not associated with differences in clinical outcomes compared with 1 week in two medical ICUs.

Mortality of Patients With Sepsis Administered Piperacillin-Tazobactam vs Cefepime.

Importance: Experimental and observational studies have suggested that empirical treatment for bacterial sepsis with antianaerobic antibiotics (eg, piperacillin-tazobactam) is associated with adverse outcomes compared with anaerobe-sparing antibiotics (eg, cefepime). However, a recent pragmatic clinical trial of piperacillin-tazobactam and cefepime showed no difference in short-term outcomes at 14 days. Further studies are needed to help clarify the empirical use of these agents. Objective: To examine the use of piperacillin-tazobactam compared with cefepime in 90-day mortality in patients treated empirically for sepsis, using instrumental variable analysis of a 15-month piperacillin-tazobactam shortage. Design, Setting, and Participants: In a retrospective cohort study, hospital admissions at the University of Michigan from July 1, 2014, to December 31, 2018, including a piperacillin-tazobactam shortage period from June 12, 2015, to September 18, 2016, were examined. Adult patients with suspected sepsis treated with vancomycin and either piperacillin-tazobactam or cefepime for conditions with presumed equipoise between piperacillin-tazobactam and cefepime were included in the study. Data analysis was conducted from December 17, 2022, to April 11, 2023. Main Outcomes and Measures: The primary outcome was 90-day mortality. Secondary outcomes included organ failure-free, ventilator-free, and vasopressor-free days. The 15-month piperacillin-tazobactam shortage period was used as an instrumental variable for unmeasured confounding in antibiotic selection. Results: Among 7569 patients (4174 men [55%]; median age, 63 [IQR 52-73] years) with sepsis meeting study eligibility, 4523 were treated with vancomycin and piperacillin-tazobactam and 3046 were treated with vancomycin and cefepime. Of patients who received piperacillin-tazobactam, only 152 (3%) received it during the shortage. Treatment groups did not differ significantly in age, Charlson Comorbidity Index score, Sequential Organ Failure Assessment score, or time to antibiotic administration. In an instrumental variable analysis, piperacillin-tazobactam was associated with an absolute mortality increase of 5.0% at 90 days (95% CI, 1.9%-8.1%) and 2.1 (95% CI, 1.4-2.7) fewer organ failure-free days, 1.1 (95% CI, 0.57-1.62) fewer ventilator-free days, and 1.5 (95% CI, 1.01-2.01) fewer vasopressor-free days. Conclusions and Relevance: Among patients with suspected sepsis and no clear indication for antianaerobic coverage, administration of piperacillin-tazobactam was associated with higher mortality and increased duration of organ dysfunction compared with cefepime. These findings suggest that the widespread use of empirical antianaerobic antibiotics in sepsis may be harmful.

The Lung Microbiome Predicts Mortality and Response to Azithromycin in Lung Transplant Recipients with Chronic Rejection.

Rationale: Chronic lung allograft dysfunction (CLAD) is the leading cause of death after lung transplant, and azithromycin has variable efficacy in CLAD. The lung microbiome is a risk factor for developing CLAD, but the relationship between lung dysbiosis, pulmonary inflammation, and allograft dysfunction remains poorly understood. Whether lung microbiota predict outcomes or modify treatment response after CLAD is unknown. Objectives: To determine whether lung microbiota predict post-CLAD outcomes and clinical response to azithromycin. Methods: Retrospective cohort study using acellular BAL fluid prospectively collected from recipients of lung transplant within 90 days of CLAD onset. Lung microbiota were characterized using 16S rRNA gene sequencing and droplet digital PCR. In two additional cohorts, causal relationships of dysbiosis and inflammation were evaluated by comparing lung microbiota with CLAD-associated cytokines and measuring ex vivo P. aeruginosa growth in sterilized BAL fluid. Measurements and Main Results: Patients with higher bacterial burden had shorter post-CLAD survival, independent of CLAD phenotype, azithromycin treatment, and relevant covariates. Azithromycin treatment improved survival in patients with high bacterial burden but had negligible impact on patients with low or moderate burden. Lung bacterial burden was positively associated with CLAD-associated cytokines, and ex vivo growth of P. aeruginosa was augmented in BAL fluid from transplant recipients with CLAD. Conclusions: In recipients of lung transplants with chronic rejection, increased lung bacterial burden is an independent risk factor for mortality and predicts clinical response to azithromycin. Lung bacterial dysbiosis is associated with alveolar inflammation and may be promoted by underlying lung allograft dysfunction.

Using Multi-Modal Electronic Health Record Data for the Development and Validation of Risk Prediction Models for Long COVID Using the Super Learner Algorithm.

BACKGROUND: Post-Acute Sequelae of COVID-19 (PASC) have emerged as a global public health and healthcare challenge. This study aimed to uncover predictive factors for PASC from multi-modal data to develop a predictive model for PASC diagnoses. METHODS: We analyzed electronic health records from 92,301 COVID-19 patients, covering medical phenotypes, medications, and lab results. We used a Super Learner-based prediction approach to identify predictive factors. We integrated the model outputs into individual and composite risk scores and evaluated their predictive performance. RESULTS: Our analysis identified several factors predictive of diagnoses of PASC, including being overweight/obese and the use of HMG CoA reductase inhibitors prior to COVID-19 infection, and respiratory system symptoms during COVID-19 infection. We developed a composite risk score with a moderate discriminatory ability for PASC (covariate-adjusted AUC (95% confidence interval): 0.66 (0.63, 0.69)) by combining the risk scores based on phenotype and medication records. The combined risk score could identify 10% of individuals with a 2.2-fold increased risk for PASC. CONCLUSIONS: We identified several factors predictive of diagnoses of PASC and integrated the information into a composite risk score for PASC prediction, which could contribute to the identification of individuals at higher risk for PASC and inform preventive efforts.

Characteristics of Facilities With Early and Rapid Ustekinumab Adoption for Patients With Inflammatory Bowel Disease.

INTRODUCTION: To examine which facility characteristics, including teamwork, are associated with early or rapid inflammatory bowel disease-related ustekinumab adoption. METHODS: We examined the association between ustekinumab adoption and the characteristics of 130 Veterans Affairs facilities. RESULTS: Mean ustekinumab adoption increased by 3.9% from 2016 to 2018 and was higher in urban compared with rural facilities (ß = 0.03, P = 0.033) and among facilities with more teamwork (ß = 0.11, P = 0.041). Compared with nonearly adopters, early adopters were more likely be high-volume facilities (46% vs 19%, P = 0.001). DISCUSSION: Facility variation in medication adoption provides an opportunity for improving inflammatory bowel disease care through targeted dissemination strategies to improve medication uptake.

External Validation and Comparison of a General Ward Deterioration Index Between Diversely Different Health Systems.

OBJECTIVES: Implementing a predictive analytic model in a new clinical environment is fraught with challenges. Dataset shifts such as differences in clinical practice, new data acquisition devices, or changes in the electronic health record (EHR) implementation mean that the input data seen by a model can differ significantly from the data it was trained on. Validating models at multiple institutions is therefore critical. Here, using retrospective data, we demonstrate how Predicting Intensive Care Transfers and other UnfoReseen Events (PICTURE), a deterioration index developed at a single academic medical center, generalizes to a second institution with significantly different patient population. DESIGN: PICTURE is a deterioration index designed for the general ward, which uses structured EHR data such as laboratory values and vital signs. SETTING: The general wards of two large hospitals, one an academic medical center and the other a community hospital. SUBJECTS: The model has previously been trained and validated on a cohort of 165,018 general ward encounters from a large academic medical center. Here, we apply this model to 11,083 encounters from a separate community hospital. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The hospitals were found to have significant differences in missingness rates (> 5% difference in 9/52 features), deterioration rate (4.5% vs 2.5%), and racial makeup (20% non-White vs 49% non-White). Despite these differences, PICTURE's performance was consistent (area under the receiver operating characteristic curve [AUROC], 0.870; 95% CI, 0.861-0.878), area under the precision-recall curve (AUPRC, 0.298; 95% CI, 0.275-0.320) at the first hospital; AUROC 0.875 (0.851-0.902), AUPRC 0.339 (0.281-0.398) at the second. AUPRC was standardized to a 2.5% event rate. PICTURE also outperformed both the Epic Deterioration Index and the National Early Warning Score at both institutions. CONCLUSIONS: Important differences were observed between the two institutions, including data availability and demographic makeup. PICTURE was able to identify general ward patients at risk of deterioration at both hospitals with consistent performance (AUROC and AUPRC) and compared favorably to existing metrics.

Social Network Diversity and the Daily Burden of Inflammatory Bowel Disease.

INTRODUCTION: To examine the association between social network, daily inflammatory bowel disease (IBD) burden, and related cognitive factors such as loneliness and psychological well-being. METHODS: Using survey data, we compared the relationship between social network diversity and daily IBD burden with multivariable linear regression. RESULTS: Patients with IBD with higher social network diversity reported a lower daily IBD burden. This association was more common among those who reported a higher degree of loneliness than those with a low degree of loneliness. DISCUSSION: We should consider diverse social connections as an indicator of risk for higher IBD burden, especially among lonely patients.

Assessment of Symptom, Disability, and Financial Trajectories in Patients Hospitalized for COVID-19 at 6 Months.

Importance: Individuals who survived COVID-19 often report persistent symptoms, disabilities, and financial consequences. However, national longitudinal estimates of symptom burden remain limited. Objective: To measure the incidence and changes over time in symptoms, disability, and financial status after COVID-19-related hospitalization. Design, Setting, and Participants: A national US multicenter prospective cohort study with 1-, 3-, and 6-month postdischarge visits was conducted at 44 sites participating in the National Heart, Lung, and Blood Institute Prevention and Early Treatment of Acute Lung Injury Network's Biology and Longitudinal Epidemiology: COVID-19 Observational (BLUE CORAL) study. Participants included hospitalized English- or Spanish-speaking adults without severe prehospitalization disabilities or cognitive impairment. Participants were enrolled between August 24, 2020, and July 20, 2021, with follow-up occurring through March 30, 2022. Exposure: Hospitalization for COVID-19 as identified with a positive SARS-CoV-2 molecular test. Main Outcomes and Measures: New or worsened cardiopulmonary symptoms, financial problems, functional impairments, perceived return to baseline health, and quality of life. Logistic regression was used to identify factors associated with new cardiopulmonary symptoms or financial problems at 6 months. Results: A total of 825 adults (444 [54.0%] were male, and 379 [46.0%] were female) met eligibility criteria and completed at least 1 follow-up survey. Median age was 56 (IQR, 43-66) years; 253 (30.7%) participants were Hispanic, 145 (17.6%) were non-Hispanic Black, and 360 (43.6%) were non-Hispanic White. Symptoms, disabilities, and financial problems remained highly prevalent among hospitalization survivors at month 6. Rates increased between months 1 and 6 for cardiopulmonary symptoms (from 67.3% to 75.4%; P = .001) and fatigue (from 40.7% to 50.8%; P < .001). Decreases were noted over the same interval for prevalent financial problems (from 66.1% to 56.4%; P < .001) and functional limitations (from 55.3% to 47.3%; P = .004). Participants not reporting problems at month 1 often reported new symptoms (60.0%), financial problems (23.7%), disabilities (23.8%), or fatigue (41.4%) at month 6. Conclusions and Relevance: The findings of this cohort study of people discharged after COVID-19 hospitalization suggest that recovery in symptoms, functional status, and fatigue was limited at 6 months, and some participants reported new problems 6 months after hospital discharge.

Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 Infection (PASC) in a Large Academic Medical Center in the US.

BACKGROUND: A growing number of Coronavirus Disease-2019 (COVID-19) survivors are affected by post-acute sequelae of SARS CoV-2 infection (PACS). Using electronic health record data, we aimed to characterize PASC-associated diagnoses and develop risk prediction models. METHODS: In our cohort of 63,675 patients with a history of COVID-19, 1724 (2.7%) had a recorded PASC diagnosis. We used a case-control study design and phenome-wide scans to characterize PASC-associated phenotypes of the pre-, acute-, and post-COVID-19 periods. We also integrated PASC-associated phenotypes into phenotype risk scores (PheRSs) and evaluated their predictive performance. RESULTS: In the post-COVID-19 period, known PASC symptoms (e.g., shortness of breath, malaise/fatigue) and musculoskeletal, infectious, and digestive disorders were enriched among PASC cases. We found seven phenotypes in the pre-COVID-19 period (e.g., irritable bowel syndrome, concussion, nausea/vomiting) and sixty-nine phenotypes in the acute-COVID-19 period (predominantly respiratory, circulatory, neurological) associated with PASC. The derived pre- and acute-COVID-19 PheRSs stratified risk well, e.g., the combined PheRSs identified a quarter of the cohort with a history of COVID-19 with a 3.5-fold increased risk (95% CI: 2.19, 5.55) for PASC compared to the bottom 50%. CONCLUSIONS: The uncovered PASC-associated diagnoses across categories highlighted a complex arrangement of presenting and likely predisposing features, some with potential for risk stratification approaches.

A Quantitative Study of Decision Thresholds for Initiation of Antibiotics in Suspected Sepsis.

BACKGROUND: Clinicians' decision thresholds for initiating antibiotics in patients with suspected sepsis have not been quantified. We aimed to define an average threshold of infection likelihood at which clinicians initiate antibiotics when treating a patient with suspected infection and to evaluate the influence of severity of illness and clinician-related factors on the threshold. DESIGN: This was a prospective survey of 153 clinicians responding to 8 clinical vignettes constructed from real-world data from 3 health care systems in the United States. We treated each hour in the vignette as a decision to treat or not treat with antibiotics and assigned an infection probability to each hour using a previously developed infection prediction model. We then estimated decision thresholds using regression models based on the timing of antibiotic initiation. We compared thresholds across categories of severity of illness and clinician-related factors. RESULTS: Overall, the treatment threshold occurred at a 69% probability of infection, but the threshold varied significantly across severity of illness categories-when patients had high severity of illness, the treatment threshold occurred at a 55% probability of infection; when patients had intermediate severity, the threshold for antibiotic initiation occurred at an infection probability of 69%, and the threshold was 84% when patients had low severity of illness (P < 0.001 for group differences). Thresholds differed significantly across specialty, highest among infectious disease and lowest among emergency medicine clinicians and across years of experience, decreasing with increasing years of experience. CONCLUSIONS: The threshold infection probability above which physicians choose to initiate antibiotics in suspected sepsis depends on illness severity as well as clinician factors. IMPLICATIONS: Incorporating these context-dependent thresholds into discriminating and well-calibrated models will inform the development of future sepsis clinical decision support systems. Clinician-related differences in treatment thresholds suggests potential unwarranted variation and opportunities for performance improvement. HIGHLIGHTS: Decision making about antibiotic initiation in suspected sepsis occurs under uncertainty, and little is known about clinicians' thresholds for treatment.In this prospective study, 153 clinicians from 3 health care systems reviewed 8 real-world clinical vignettes representing patients with sepsis and indicated the time that they would initiate antibiotics.Using a model-based approach, we estimated decision thresholds and found that thresholds differed significantly across illness severity categories and by clinician specialty and years of experience.

Understanding clinician connections to inform efforts to promote high-quality inflammatory bowel disease care.

BACKGROUND: Highly connected individuals disseminate information effectively within their social network. To apply this concept to inflammatory bowel disease (IBD) care and lay the foundation for network interventions to disseminate high-quality treatment, we assessed the need for improving the IBD practices of highly connected clinicians. We aimed to examine whether highly connected clinicians who treat IBD patients were more likely to provide high-quality treatment than less connected clinicians. METHODS: We used network analysis to examine connections among clinicians who shared patients with IBD in the Veterans Health Administration between 2015-2018. We created a network comprised of clinicians connected by shared patients. We quantified clinician connections using degree centrality (number of clinicians with whom a clinician shares patients), closeness centrality (reach via shared contacts to other clinicians), and betweenness centrality (degree to which a clinician connects clinicians not otherwise connected). Using weighted linear regression, we examined associations between each measure of connection and two IBD quality indicators: low prolonged steroids use, and high steroid-sparing therapy use. RESULTS: We identified 62,971 patients with IBD and linked them to 1,655 gastroenterologists and 7,852 primary care providers. Clinicians with more connections (degree) were more likely to exhibit high-quality treatment (less prolonged steroids beta -0.0268, 95%CI -0.0427, -0.0110, more steroid-sparing therapy beta 0.0967, 95%CI 0.0128, 0.1805). Clinicians who connect otherwise unconnected clinicians (betweenness) displayed more prolonged steroids use (beta 0.0003, 95%CI 0.0001, 0.0006). The presence of variation is more relevant than its magnitude. CONCLUSIONS: Clinicians with a high number of connections provided more high-quality IBD treatments than less connected clinicians, and may be well-positioned for interventions to disseminate high-quality IBD care. However, clinicians who connect clinicians who are otherwise unconnected are more likely to display low-quality IBD treatment. Efforts to improve their quality are needed prior to leveraging their position to disseminate high-quality care.

Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 infection (PASC) in a Large Academic Medical Center in the US.

Objective: A growing number of Coronavirus Disease-2019 (COVID-19) survivors are affected by Post-Acute Sequelae of SARS CoV-2 infection (PACS). Using electronic health records data, we aimed to characterize PASC-associated diagnoses and to develop risk prediction models. Methods: In our cohort of 63,675 COVID-19 positive patients, 1,724 (2.7 %) had a recorded PASC diagnosis. We used a case control study design and phenome-wide scans to characterize PASC-associated phenotypes of the pre-, acute-, and post-COVID-19 periods. We also integrated PASC-associated phenotypes into Phenotype Risk Scores (PheRSs) and evaluated their predictive performance. Results: In the post-COVID-19 period, known PASC symptoms (e.g., shortness of breath, malaise/fatigue) and musculoskeletal, infectious, and digestive disorders were enriched among PASC cases. We found seven phenotypes in the pre-COVID-19 period (e.g., irritable bowel syndrome, concussion, nausea/vomiting) and 69 phenotypes in the acute-COVID-19 period (predominantly respiratory, circulatory, neurological) associated with PASC. The derived pre- and acute-COVID-19 PheRSs stratified risk well, e.g., the combined PheRSs identified a quarter of the COVID-19 positive cohort with an at least 2.9-fold increased risk for PASC. Conclusions: The uncovered PASC-associated diagnoses across categories highlighted a complex arrangement of presenting and likely predisposing features, some with a potential for risk stratification approaches.

Consensus elements for observational research on COVID-19-related long-term outcomes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its long-term outcomes may be jointly caused by a wide range of clinical, social, and economic characteristics. Studies aiming to identify mechanisms for SARS-CoV-2 morbidity and mortality must measure and account for these characteristics to arrive at unbiased, accurate conclusions. We sought to inform the design, measurement, and analysis of longitudinal studies of long-term outcomes among people infected with SARS-CoV-2. We fielded a survey to an interprofessional group of clinicians and scientists to identify factors associated with SARS-CoV-2 infection and subsequent outcomes. Using an iterative process, we refined the resulting list of factors into a consensus causal diagram relating infection and 12-month mortality. Finally, we operationalized concepts from the causal diagram into minimally sufficient adjustment sets using common medical record data elements. Total 31 investigators identified 49 potential risk factors for and 72 potential consequences of SARS-CoV-2 infection. Risk factors for infection with SARS-CoV-2 were grouped into five domains: demographics, physical health, mental health, personal social, and economic factors, and external social and economic factors. Consequences of coronavirus disease 2019 (COVID-19) were grouped into clinical consequences, social consequences, and economic consequences. Risk factors for SARS-CoV-2 infection were developed into a consensus directed acyclic graph for mortality that included two minimally sufficient adjustment sets. We present a collectively developed and iteratively refined list of data elements for observational research in SARS-CoV-2 infection and disease. By accounting for these elements, studies aimed at identifying causal pathways for long-term outcomes of SARS-CoV-2 infection can be made more informative.

Characteristics and Outcomes of US Patients Hospitalized With COVID-19.

BACKGROUND: Understanding COVID-19 epidemiology is crucial to clinical care and to clinical trial design and interpretation. OBJECTIVE: To describe characteristics, treatment, and outcomes among patients hospitalized with COVID-19 early in the pandemic. METHODS: A retrospective cohort study of consecutive adult patients with laboratory-confirmed, symptomatic SARS-CoV-2 infection admitted to 57 US hospitals from March 1 to April 1, 2020. RESULTS: Of 1480 inpatients with COVID-19, median (IQR) age was 62.0 (49.4-72.9) years, 649 (43.9%) were female, and 822 of 1338 (61.4%) were non-White or Hispanic/Latino. Intensive care unit admission occurred in 575 patients (38.9%), mostly within 4 days of hospital presentation. Respiratory failure affected 583 patients (39.4%), including 284 (19.2%) within 24 hours of hospital presentation and 413 (27.9%) who received invasive mechanical ventilation. Median (IQR) hospital stay was 8 (5-15) days overall and 15 (9-24) days among intensive care unit patients. Hospital mortality was 17.7% (n = 262). Risk factors for hospital death identified by penalized multivariable regression included older age; male sex; comorbidity burden; symptoms-to-admission interval; hypotension; hypoxemia; and higher white blood cell count, creatinine level, respiratory rate, and heart rate. Of 1218 survivors, 221 (18.1%) required new respiratory support at discharge and 259 of 1153 (22.5%) admitted from home required new health care services. CONCLUSIONS: In a geographically diverse early-pandemic COVID-19 cohort with complete hospital folllow-up, hospital mortality was associated with older age, comorbidity burden, and male sex. Intensive care unit admissions occurred early and were associated with protracted hospital stays. Survivors often required new health care services or respiratory support at discharge.

Association of Surge Conditions with Mortality Among Critically Ill Patients with COVID-19.

OBJECTIVE: To determine whether surge conditions were associated with increased mortality. DESIGN: Multicenter cohort study. SETTING: U.S. ICUs participating in STOP-COVID. PATIENTS: Consecutive adults with COVID-19 admitted to participating ICUs between March 4 and July 1, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The main outcome was 28-day in-hospital mortality. To assess the association between admission to an ICU during a surge period and mortality, we used two different strategies: (1) an inverse probability weighted difference-in-differences model limited to appropriately matched surge and non-surge patients and (2) a meta-regression of 50 multivariable difference-in-differences models (each based on sets of randomly matched surge- and non-surge hospitals). In the first analysis, we considered a single surge period for the cohort (March 23 - May 6). In the second, each surge hospital had its own surge period (which was compared to the same time periods in matched non-surge hospitals).Our cohort consisted of 4342 ICU patients (average age 60.8 [sd 14.8], 63.5% men) in 53 U.S. hospitals. Of these, 13 hospitals encountered surge conditions. In analysis 1, the increase in mortality seen during surge was not statistically significant (odds ratio [95% CI]: 1.30 [0.47-3.58], p = .6). In analysis 2, surge was associated with an increased odds of death (odds ratio 1.39 [95% CI, 1.34-1.43], p < .001). CONCLUSIONS: Admission to an ICU with COVID-19 in a hospital that is experiencing surge conditions may be associated with an increased odds of death. Given the high incidence of COVID-19, such increases would translate into substantial excess mortality.

Development and Retention of Early-Career Clinician-Scientists through a Novel Peer Mentorship Program: Multidisciplinary Intensive Care Research Workgroup.

Background: Early-career clinician-scientists often leave academic medicine, but strong mentorship can help facilitate retention. Beyond the traditional dyadic mentor-mentee relationship, formal peer mentoring provides a rich means to augment career development and foster independence. Objective: To describe a model for early-career peer mentorship and the retention of participating early-career clinician-scientists in academic medicine. Methods: In 2015, a multidisciplinary and interprofessional group of early-career clinician-scientists focused on critical care developed a peer mentoring group at the University of Michigan called the MICReW (Multidisciplinary Intensive Care Research Workgroup). We describe the establishment, sustainability, guiding principles, challenges, and successes of MICReW. Results: MICReW was established to be a formal, peer-only mentoring group without the direct participation of senior mentors. The purpose of MICReW was to support and promote the research and career development of early-career clinician-scientists by creating an environment that fostered diverse opinions, constructive feedback, and camaraderie. As a group, we wrote a mission statement and defined our guiding principles. Our sustainability, growth, and adaptability (seamlessly transitioning to all virtual meetings) were possible by the continued investment of our peer members. To date, MICReW has had 30 members, of whom 15 are current members and approximately half are women. Nearly all members (n = 29/30) remain in academic positions, and half (n = 15) have been awarded career development awards. Most members also report significant benefits from being a member of MICReW. Conclusion: The MICReW peer mentorship model is a sustainable and adaptable peer mentoring model whose members continue to be engaged in academic medicine.