Background: Many people living with HIV (PLWH) have comorbidities which are risk factors for severe coronavirus disease 2019 (COVID-19) or have exposures that may lead to acquisition of severe acute respiratory distress syndrome coronavirus 2. There are few studies, however, on the demographics, comorbidities, clinical presentation, or outcomes of COVID-19 in people with HIV. Objective: To evaluate risk factors, clinical manifestations, and outcomes in a large cohort of PLWH with COVID-19. Methods: We systematically identified all PLWH who were diagnosed with COVID-19 at a large hospital from 3 March to 26 April 2020 during an outbreak in Massachusetts. We analyzed each of the cases to extract information including demographics, medical comorbidities, clinical presentation, and illness course after COVID-19 diagnosis. Results: We describe a cohort of 36 PLWH with confirmed COVID-19 and another 11 patients with probable COVID-19. Almost 85% of PLWH with confirmed COVID-19 had a comorbidity associated with severe disease, including obesity, cardiovascular disease, or hypertension. Approximately 77% of PLWH with COVID-19 were non-Hispanic Black or Latinx whereas only 40% of the PLWH in our clinic were Black or Latinx. Nearly half of PLWH with COVID-19 had exposure to congregate settings. In addition to people with confirmed COVID-19, we identified another 11 individuals with probable COVID-19, almost all of whom had negative PCR testing. Conclusion: In the largest cohort to date of PLWH and confirmed COVID-19, almost all had a comorbidity associated with severe disease, highlighting the importance of non-HIV risk factors in this population. The racial disparities and frequent link to congregate settings in PLWH and COVID-19 need to be explored urgently.

Background We sought to develop an automatable score to predict hospitalization, critical illness, or death for patients at risk for COVID-19 presenting for urgent care. Methods We developed the COVID-19 Acuity Score (CoVA) based on a single-center study of adult outpatients seen in respiratory illness clinics (RICs) or the emergency department (ED). Data was extracted from the Partners Enterprise Data Warehouse, and split into development (n = 9381, March 7-May 2) and prospective (n = 2205, May 3-14) cohorts. Outcomes were hospitalization, critical illness (ICU or ventilation), or death within 7 days. Calibration was assessed using the expected-to-observed event ratio (E/O). Discrimination was assessed by area under the receiver operating curve (AUC). Results In the prospective cohort, 26.1%, 6.3%, and 0.5% of patients experienced hospitalization, critical illness, or death, respectively. CoVA showed excellent performance in prospective validation for hospitalization (expected-to-observed ratio (E/O): 1.01, AUC: 0.76); for critical illness (E/O 1.03, AUC: 0.79); and for death (E/O: 1.63, AUC=0.93). Among 30 predictors, the top five were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate. Conclusions CoVA is a prospectively validated automatable score for the outpatient setting to predict adverse events related to COVID-19 infection.

Objective: Evaluate the effect of a virtual coaching program offered to women surgery residents in a surgical society. Background: Randomized controlled experiments evaluating the effect of coaching on trainee well-being and burnout is lacking. Methods: Women surgery residents in the Association of Women Surgeons were recruited to participate in a randomized controlled trial of the effects of a virtual coaching program on trainee well-being. Attending surgeons served as coaches after completing in-person training. Residents (n = 237) were randomized to intervention (three 1:1 coaching sessions over 9 mo) or control (e-mailed wellness resources). Participants were surveyed at baseline and postintervention using validated measures of well-being, burnout, and resilience. Changes in outcome measures between presurvey and postsurvey were compared between study arms. Results: Survey response rates were 56.9% (n = 66) in the control group and 69.4% (n = 84) in the intervention group (P = 0.05). The intervention group showed significant improvement in professional fulfillment (P = 0.021), burnout (0.026), work exhaustion (0.017), self-valuation (0.003), and well-being (P = 0.002); whereas the control group showed significant improvement in self-valuation (P = 0.015) and significant decline in resilience (P = 0.025). The intervention group had a significant improvement in well-being (P = 0.015) and intolerance of uncertainty (P = 0.015) compared to controls. Conclusions: Women surgery residents who participated in a remote coaching program offered by a surgical society demonstrated improvement in aspects of well-being relative to peers who did not receive coaching. Therefore, remote coaching offered by a professional society may be a useful component of initiatives directed at trainee well-being.

BACKGROUND: Coaching has been shown to improve resident well-being; however, not all benefit equally. OBJECTIVE: Assess predictors of changes in resident physician well-being and burnout in a multisite implementation of a Professional Development Coaching Program. DESIGN: Pre-and post-implementation surveys administered to participant cohorts at implementation sites in their intern year. Effect size was calculated comparing pre-and post-intervention paired data. PARTICIPANTS: In total, 272 residents in their intern year at five internal medicine residency programs (Boston

Background This study aimed to determine the impact of pulmonary complications on death after surgery both before and during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Methods This was a patient-level, comparative analysis of two, international prospective cohort studies: one before the pandemic (January–October 2019) and the second during the SARS-CoV-2 pandemic (local emergence of COVID-19 up to 19 April 2020). Both included patients undergoing elective resection of an intra-abdominal cancer with curative intent across five surgical oncology disciplines. Patient selection and rates of 30-day postoperative pulmonary complications were compared. The primary outcome was 30-day postoperative mortality. Mediation analysis using a natural-effects model was used to estimate the proportion of deaths during the pandemic attributable to SARS-CoV-2 infection. Results This study included 7402 patients from 50 countries; 3031 (40.9 per cent) underwent surgery before and 4371 (59.1 per cent) during the pandemic. Overall, 4.3 per cent (187 of 4371) developed postoperative SARS-CoV-2 in the pandemic cohort. The pulmonary complication rate was similar (7.1 per cent (216 of 3031) versus 6.3 per cent (274 of 4371); P = 0.158) but the mortality rate was significantly higher (0.7 per cent (20 of 3031) versus 2.0 per cent (87 of 4371); P < 0.001) among patients who had surgery during the pandemic. The adjusted odds of death were higher during than before the pandemic (odds ratio (OR) 2.72, 95 per cent c.i. 1.58 to 4.67; P < 0.001). In mediation analysis, 54.8 per cent of excess postoperative deaths during the pandemic were estimated to be attributable to SARS-CoV-2 (OR 1.73, 1.40 to 2.13; P < 0.001). Conclusion Although providers may have selected patients with a lower risk profile for surgery during the pandemic, this did not mitigate the likelihood of death through SARS-CoV-2 infection. Care providers must act urgently to protect surgical patients from SARS-CoV-2 infection.

Background. We sought to develop an automatable score to predict hospitalization, critical illness, or death in patients at risk for COVID-19 presenting for urgent care during the Massachusetts outbreak. Methods. Single-center study of adult outpatients seen in respiratory illness clinics (RICs) or the emergency department (ED), including development (n = 9381, March 7-May 2) and prospective (n = 2205, May 3-14) cohorts. Data was queried from Partners Enterprise Data Warehouse. Outcomes were hospitalization, critical illness or death within 7 days. We developed the COVID-19 Acuity Score (CoVA) using automatically extracted data from the electronic medical record and learning-to-rank ordinal logistic regression modeling. Calibration was assessed using predicted-to-observed event ratio (E/O). Discrimination was assessed by C-statistics (AUC). Results. In the development cohort, 27.3%, 7.2%, and 1.1% of patients experienced hospitalization, critical illness, or death, respectively; and in the prospective cohort, 26.1%, 6.3%, and 0.5%. CoVA showed excellent performance in the development cohort (concurrent validation) for hospitalization (E/O: 1.00, AUC: 0.80); for critical illness (E/O: 1.00, AUC: 0.82); and for death (E/O: 1.00, AUC: 0.87). Performance in the prospective cohort (prospective validation) was similar for hospitalization (E/O: 1.01, AUC: 0.76); for critical illness (E/O 1.03, AUC: 0.79); and for death (E/O: 1.63, AUC=0.93). Among 30 predictors, the top five were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate. Conclusions. CoVA is a prospectively validated automatable score to assessing risk for adverse outcomes related to COVID-19 infection in the outpatient setting.

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