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Temperature measurement plays a central role in determining pediatric patients' disease risk and management. However, current pediatric temperature thresholds may be outdated and not applicable to children.To characterize pediatric temperature norms and variation by patient characteristics, time of measurement, and thermometer route.In this cross-sectional study, we analyzed 134,641 well-child visits occurring between 2014-2019 at primary care clinics that routinely measured temperature. We performed bivariate and multivariable quantile regressions with clustered standard errors to determine temperature percentiles and variation by age, sex, time of measurement, and thermometer route. We performed sensitivity analyses: 1) using a cohort that excluded visits with infectious diagnoses that could explain temperature aberrations and 2) including clinic as a fixed effect.The median rectal temperature for visits of infants ≤12 months old was 37.2˚C, which was 0.4˚C higher than the median axillary temperature. The median axillary temperature for children 1-18 years old was 36.7˚C, which was 0.1˚C lower than the median values of all other routes. The 99th percentile for rectal temperatures in infants was 37.8˚C and the 99.9th percentile for axillary temperatures in children was 38.5˚C. Adjusted analyses did not demonstrate clinically significant variation in temperature by sex, age, or time of measurement.These updated temperature norms can serve as reference values in clinical practice and should be considered in the context of thermometer route used and the clinical condition being evaluated. Variations in temperature values by sex, age, and time of measurement were not clinically significant.

Objective: We investigated a decrease in antibiotic prescribing for respiratory illnesses in 2 academic urgent-care clinics during the coronavirus disease 2019 (COVID-19) pandemic using semistructured clinician interviews. Methods: We conducted a quality-improvement project from November 2020 to May 2021. We investigated provider antibiotic decision making using a mixed-methods explanatory design including interviews. We analyzed transcripts using a thematic framework approach to identify emergent themes. Our performance measure was antibiotic prescribing rate (APR) for encounters with respiratory diagnosis billing codes. We extracted billing and prescribing data from the electronic medical record and assessed differences using run charts, p charts and generalized linear regression. Results: We observed significant reductions in the APR early during the COVID-19 pandemic (relative risk [RR], 0.20; 95% confidence interval [CI], 0.17–0.25), which was maintained over the study period (P < .001). The average APRs were 14% before the COVID-19 pandemic, 4% during the QI project, and 7% after the project. All providers prescribed less antibiotics for respiratory encounters during COVID-19, but only 25% felt their practice had changed. Themes from provider interviews included changing patient expectations and provider approach to respiratory encounters during COVID-19, the impact of increased telemedicine encounters, and the changing epidemiology of non–COVID-19 respiratory infections. Conclusions: Our findings suggest that the decrease in APR was likely multifactorial. The average APR decreased significantly during the pandemic. Although the APR was slightly higher after the QI project, it did not reach prepandemic levels. Future studies should explore how these factors, including changing patient expectations, can be leveraged to improve urgent-care antibiotic stewardship.

Background and Purpose The purpose is to determine the impact of an academic neurohospitalist service on clinical outcomes. Methods We performed a retrospective, quasi-experimental study of patients discharged from the general neurology service before (August 2010–July 2014) and after implementation of a full-time neurohospitalist service (August 2016–July 2018) compared to a control group of stroke patients. Primary outcomes were length of stay and 30-day readmission. Using the difference-in-difference approach, the impact of introducing a neurohospitalist service compared to controls was assessed with adjustment of patients’ characteristics. Secondary outcomes included mortality, in-hospital complications, and cost. Results There were 2706 neurology admissions (1648 general; 1058 stroke) over the study period. The neurohospitalist service was associated with a trend in reduced 30-day readmissions (ratio of ORs: .52 [.27, .98], P = .088), while length of stay was not incrementally changed in the difference-in-difference model (-.3 [-.7, .1], P = .18). However, descriptive results demonstrated a significant reduction in mean adjusted LOS of .7 days (4.5 to 3.8 days, P < .001) and a trend toward reduced readmissions (8.9% to 7.6%, P = .42) in the post-neurohospitalist cohort despite a significant increase in patient complexity, shift to higher acuity diagnoses, more emergent admissions, and near quadrupling of observation status patients. Mortality and in-hospital complications remained low, patient satisfaction was stable, and cost was not incrementally changed in the post-neurohospitalist cohort. Conclusions Implementation of a neurohospitalist service at an academic medical center is feasible and associated with a significant increase in patient complexity and acuity and a trend toward reduced readmissions.

BackgroundPoint-of-care ultrasound (POCUS) machines may utilize artificial intelligence (AI) to enhance image interpretation and acquisition. This study investigates whether AI-enabled devices improve competency among POCUS novices.MethodsWe conducted a randomized controlled trial at a single academic institution from 2021-2022. Internal medicine trainees (N=43) with limited POCUS experience were randomized to receive a POCUS device with (Echonous, N=22) or without (Butterfly, N=21) AI-functionality for two weeks while on an inpatient rotation. The AI-device provided automatic labeling of cardiac structures, guidance for optimal probe placement to acquire cardiac views, and ejection fraction estimations. Participants were allowed to use the devices at their discretion for patient-related care.The primary outcome was the time to acquire an apical 4-chamber (A4C) image. Secondary outcomes included A4C image quality using the modified Rapid Assessment for Competency in Echocardiography (RACE) scale, correct identification of pathology, and participant attitudes. Measurements were performed at the time of randomization and at two-week follow-up. All scanning assessments were performed on the same standardized patient.ResultsBoth AI and non-AI groups had similar scan times and image quality scores at baseline. At follow-up, the AI group had faster scan times (72 seconds [IQR 38-85] vs. 85 seconds [IQR 54-166]; p=0.01), higher image quality scores (4.5 [IQR 2-5.5] vs. 2 [IQR 1-3]; pConclusionsPOCUS devices with AI features may improve image acquisition and interpretation by novices. Future studies are needed to determine the extent that AI impacts POCUS learning.

ImportanceStudies show that ChatGPT, a general purpose large language model chatbot, could pass the multiple-choice US Medical Licensing Exams, but the model’s performance on open-ended clinical reasoning is unknown.ObjectiveTo determine if ChatGPT is capable of consistently meeting the passing threshold on free-response, case-based clinical reasoning assessments.DesignFourteen multi-part cases were selected from clinical reasoning exams administered to pre-clerkship medical students between 2019 and 2022. For each case, the questions were run through ChatGPT twice and responses were recorded. Two clinician educators independently graded each run according to a standardized grading rubric. To further assess the degree of variation in ChatGPT’s performance, we repeated the analysis on a single high-complexity case 20 times.SettingA single US medical schoolParticipantsChatGPTMain Outcomes and MeasuresPassing rate of ChatGPT’s scored responses and the range in model performance across multiple run throughs of a single case.Results12 out of the 28 ChatGPT exam responses achieved a passing score (43%) with a mean score of 69% (95% CI: 65% to 73%) compared to the established passing threshold of 70%. When given the same case 20 separate times, ChatGPT’s performance on that case varied with scores ranging from 56% to 81%.Conclusions and RelevanceChatGPT’s ability to achieve a passing performance in nearly half of the cases analyzed demonstrates the need to revise clinical reasoning assessments and incorporate artificial intelligence (AI)-related topics into medical curricula and practice.

Background The reported incidence of adverse reactions following Coronavirus disease 2019 (COVID‐19) convalescent plasma (CCP) transfusion has generally been lower than expected based on the incidence of transfusion reactions that have been observed in studies of conventional plasma transfusion. This raises the concern for under‐reporting of adverse events in studies of CCP that rely on passive surveillance strategies. Materials and Methods Our institution implemented a protocol to actively identify possible adverse reactions to CCP transfusion. In addition, we retrospectively reviewed the charts of inpatients who received CCP at Stanford Hospital between May 13, 2020 and January 31, 2021. We determined the incidence of adverse events following CCP transfusion. Results A total of 49 patients received CCP. Seven patients (14%) had an increased supplemental oxygen requirement within 4 h of transfusion completion, including one patient who was intubated during the transfusion. An additional 11 patients (total of 18, 37%) had increased oxygen requirements within 24 h of transfusion, including 3 patients who were intubated. Six patients (12%) fulfilled criteria for transfusion‐associated circulatory overload (TACO). Conclusion Using an active surveillance strategy, we commonly observed adverse events following the transfusion of CCP to hospitalized patients. It was not possible to definitively determine whether or not these adverse events are related to CCP transfusion. TACO was likely over‐diagnosed given overlap with the manifestations of COVID‐19. Nevertheless, these results suggest that the potential adverse effects of CCP transfusion may be underestimated by reports from passive surveillance studies.

To capture and compare the perspectives of parents and their transgender and gender expansive (TGE) adolescents during pivotal moments of gender identity development and to report the level of adjustment during these parental experiences.We utilized a mixed-methods approach and interviewed 36 parents and 23 TGE adolescents at our Gender Clinic. Parents retrospectively identified "pivotal moments" in their child's gender identity development and rated their levels of support and adjustment. Adolescents independently rated their parent's level of support during these moments to allow for comparative analyses.The supportive behavior most frequently identified by parents was connecting the adolescent to services, while adolescents considered their parents' use of the affirmed name or pronouns to be most supportive. We found a positive correlation between the parents' perceptions of support and those of TGE adolescents during pivotal moments (r = 0.4, p0.001). Adolescents rated the degree of parental support to be 3.73 points (95% confidence interval: [2.67,4.8], p0.001) higher on a Likert scale than corresponding ratings provided by parents in a generalized estimating equation model. Parents experienced moderate need for adjustment during these moments.Providers may use these findings to guide parents toward gender affirmative behaviors that may protect against negative mental health outcomes.

OBJECTIVE The only effective treatment for ischemic moyamoya disease (iMMD) is cerebral revascularization by an extracranial to intracranial bypass. The preferred revascularization method remains controversial: direct versus indirect bypass. The purpose of this study was to test the hypothesis that method choice should be personalized based on angiographic, hemodynamic, and clinical characteristics to balance the risk of perioperative major stroke against treatment efficacy. METHODS Patients with iMMD were identified retrospectively from a prospectively maintained database. Those with mild to moderate internal carotid artery or M1 segment stenosis, preserved cerebrovascular reserve, intraoperative M4 segment anterograde flow ≥ 8 ml/min, or the absence of frequent and severe transient ischemic attacks (TIAs) or stroke had been assigned to indirect bypass. The criteria for direct bypass were severe ICA or M1 segment stenosis or occlusion, impaired cerebrovascular reserve or steal phenomenon, intraoperative M4 segment retrograde flow or anterograde flow < 8 ml/min, and the presence of frequent and severe TIAs or clinical strokes. The primary study endpoint was MRI-confirmed symptomatic stroke ≤ 7 days postoperatively resulting in a decline in the modified Rankin Scale (mRS) score from preoperatively to 6 months postoperatively. As a secondary endpoint, the authors assessed 6-month postoperative DSA-demonstrated revascularization, which was classified as < 1/3, 1/3–2/3, or > 2/3 of the middle cerebral artery territory. RESULTS One hundred thirty-eight patients with iMMD affecting 195 hemispheres revascularized in the period from March 2016 to June 2018 were included in this analysis. One hundred thirty-three hemispheres were revascularized with direct bypass and 62 with indirect bypass. The perioperative stroke rate was 4.7% and 6.8% in the direct and indirect groups, respectively (p = 0.36). Degree of revascularization was higher in the direct bypass group (p = 0.03). The proportion of patients improving to an mRS score 0–1 (from preoperatively to 6 months postoperatively) tended to be higher in the direct bypass group, although the difference between the two bypass groups was not statistically significant (p = 0.27). CONCLUSIONS The selective use of an indirect bypass procedure for iMMD did not decrease the perioperative stroke rate. Direct bypass provided a significantly higher degree of revascularization. The authors conclude that direct bypass is the treatment of choice for iMMD.

Metabolic response assessment for oropharyngeal squamous cell carcinoma (OPSCC) aids in identifying locoregional persistence/recurrence (LRR). The Hopkins Criteria are a standardized qualitative response assessment system using posttreatment FDG-PET/CT.We conducted a retrospective cohort study of patients with node-positive OPSCC treated with definitive (chemo)radiotherapy. We assessed Hopkins Criteria performance for LRR, then developed and validated a competing-risks model.Between 2004 and 2018, 259 patients were included with median follow-up of 43 months. The Hopkins Criteria sensitivity, specificity, negative predictive value, and accuracy were 68%, 88%, 95%, and 85%. The 36-month cumulative incidence of LRR was greater with positive scores (45% vs. 5%, HR 12.60, p 0.001). PET/CTs performed ≤10 weeks after radiotherapy were associated with a four-fold increase in pathologically negative biopsies/surgeries (36% vs. 9%, p = 0.03). The AUC for LRR was 0.89 using a model integrating the Hopkins score.The Hopkins Criteria predict LRR with high accuracy for OPSCC response assessment.

Deficits in social skills are common in children with Autism Spectrum Disorder (ASD), and there is an urgent need for effective social skills interventions, especially for improving interactions with typically developing peers. This study examined the effects of a naturalistic behavioral social skills intervention in improving social initiations to peers through a randomized controlled trial. Analyses of multimethod, multi-informant measures indicated that children in the active group (SIMI) demonstrated greater improvement in the types of initiations which were systematically prompted and reinforced during treatment (i.e., behavior regulation). Generalization to joint attention and social interaction initiation types, as well as collateral gains in broader social functioning on clinician- and parent-rated standardized measures were also observed.

Background Internal medicine residents face numerous career options after residency training. Little is known about when residents make their final career choice. Objective We assessed the timing and predictive factors of final career choices among internal medicine residents at graduation, including demographics, pre-residency career preferences, and rotation scheduling. Methods We conducted a retrospective study of graduates of an academic internal medicine residency program from 2014 to 2017. Main measures included demographics, rotation schedules, and self-reported career choices for residents at 5 time points: recruitment day, immediately after Match Day, end of postgraduate year 1 (PGY-1), end of PGY-2, and at graduation. Results Of the 138 residents eligible for the study, 5 were excluded based on participation in a fast-track program for an Accreditation Council for Graduate Medical Education subspecialty fellowship. Among the remaining 133 residents, 48 (36%) pursued general internal medicine fields and 78 (59%) pursued fellowship training. Career choices from recruitment day, Match Day, and PGY-1 were only weakly predictive of the career choice. Many choices demonstrated low concordance throughout training, and general medicine fields (primary care, hospital medicine) were frequently not decided until after PGY-2. Early clinical exposure to subspecialty rotations did not predict final career choice. Conclusions Early career choices before and during residency training may have low predictability toward final career choices upon graduation in internal medicine. These choices may continue to have low predictability beyond PGY-2 for many specialties. Early clinical exposure may not predict final career choice for subspecialties.

Purpose We describe the design of a longitudinal cohort study to determine SARS-CoV-2 incidence and prevalence among a population-based sample of adults living in six San Francisco Bay Area counties. Methods Using an address-based sample, we stratified households by county and by census-tract risk. Risk strata were determined by using regression models to predict infections by geographic area using census-level sociodemographic and health characteristics. We disproportionately sampled high and medium risk strata, which had smaller population sizes, to improve precision of estimates, and calculated a desired sample size of 3400. Participants were primarily recruited by mail and were followed monthly with PCR testing of nasopharyngeal swabs, testing of venous blood samples for antibodies to SARS-CoV-2 spike and nucleocapsid antigens, and testing of the presence of neutralizing antibodies, with completion of questionnaires about socio-demographics and behavior. Estimates of incidence and prevalence will be weighted by county, risk strata and sociodemographic characteristics of non-responders, and will take into account laboratory test performance. Results We enrolled 3842 adults from August to December, 2020, and completed follow-up March 31, 2021. We reached target sample sizes within most strata. Conclusions Our stratified random sampling design will allow us to recruit a robust general population cohort of adults to determine the incidence of SARS-CoV-2 infection. Identifying risk strata was unique to the design and will help ensure precise estimates, and high-performance testing for presence of virus and antibodies will enable accurate ascertainment of infections.

OBJECTIVES Reproductive health is an important issue in the care of adolescents and young adults (AYA). Unfortunately, many AYAs, particularly those with chronic medical conditions, may not regularly access primary care to address these issues. This study evaluates the impact of an inpatient reproductive health consult service on reproductive health care. METHODS A reproductive health-focused screening consult service was initiated in June 2017 at an academic teaching hospital. Patients aged 15 to 26 admitted to pediatric ward teams were eligible for screening. A retrospective chart review was conducted from December 2016 to June 2019 to determine the effect of the consult service on the primary outcome, documentation of a psychosocial assessment, and reproductive health concerns. RESULTS Nine hundred twenty-nine encounters were analyzed (345 preintervention and 584 during intervention), representing 675 patients. The proportion of encounters with a documented psychosocial assessment increased from 14.8% to 41.3% during the intervention (P < .001); a reproductive health screening consult was responsible for 37.3% (109 of 292) of the documented assessments. There were high self-reported rates of sexual activity (38%), substance use (47%), and mood concerns (48%) among hospitalized AYA; all behaviors were documented at statistically significant increased frequencies (P < .001) during the intervention compared with preintervention. CONCLUSIONS Initiation of an inpatient reproductive health screening consult service led to increased documentation of psychosocial assessments, including increased documentation of sexual health history and other risk factors. With improved screening of reproductive and psychosocial needs, targeted interventions can meet underrecognized needs among hospitalized AYA.

Background Preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2_ infections in healthcare workers (HCWs) is critical for healthcare delivery. We aimed to estimate and characterize the prevalence and incidence of coronavirus disease 2019 (COVID-19) in a US HCW cohort and to identify risk factors associated with infection. Methods We conducted a longitudinal cohort study of HCWs at 3 Bay Area medical centers using serial surveys and SARS-CoV-2 viral and orthogonal serological testing, including measurement of neutralizing antibodies. We estimated baseline prevalence and cumulative incidence of COVID-19. We performed multivariable Cox proportional hazards models to estimate associations of baseline factors with incident infections and evaluated the impact of time-varying exposures on time to COVID-19 using marginal structural models. Results A total of 2435 HCWs contributed 768 person-years of follow-up time. We identified 21 of 2435 individuals with prevalent infection, resulting in a baseline prevalence of 0.86% (95% confidence interval [CI], .53%–1.32%). We identified 70 of 2414 incident infections (2.9%), yielding a cumulative incidence rate of 9.11 cases per 100 person-years (95% CI, 7.11–11.52). Community contact with a known COVID-19 case was most strongly correlated with increased hazard for infection (hazard ratio, 8.1 [95% CI, 3.8–17.5]). High-risk work-related exposures (ie, breach in protective measures) drove an association between work exposure and infection (hazard ratio, 2.5 [95% CI, 1.3–4.8). More cases were identified in HCWs when community case rates were high. Conclusions We observed modest COVID-19 incidence despite consistent exposure at work. Community contact was strongly associated with infections, but contact at work was not unless accompanied by high-risk exposure.

1AbstractCOVID-19 has caused tremendous death and suffering since it first emerged in 2019. In response, models were developed to help predict the course of various disease metrics, and these models have been relied upon to help guide public health policy. Here we present a method called COVIDNearTerm to “forecast” hospitalizations in the short term, two to four weeks from the time of prediction. COVIDNearTerm is based on an autoregressive model and utilizes a parametric bootstrap approach to make predictions. We evaluated COVIDNearTerm on San Francisco Bay Area hospitalizations and compared it to models from the California COVID Assessment Tool (CalCAT). We found that that COVIDNearTerm pre-dictions were more accurate than the CalCAT ensemble predictions for all comparisons and any CalCAT component for a majority of comparisons. For instance, at the county level our 14-day hospitalization median absolute percentage errors ranged from 16% to 36%. For those same comparisons the CalCAT ensemble errors were between 30% and 59%. COVIDNearT-erm is also easier to use than some other methods. It requires only previous hospitalization data and there is an open source R package that implements the algorithm.

OBJECTIVES To determine the (1) frequency and visit characteristics of routine temperature measurement and (2) rates of interventions by temperature measurement practice and the probability of incidental fever detection. METHODS In this retrospective cohort study, we analyzed well-child visits between 2014–2019. We performed multivariable regression to characterize visits associated with routine temperature measurement and conducted generalized estimating equations regression to determine adjusted rates of interventions (antibiotic prescription, and diagnostic testing) and vaccine deferral by temperature measurement and fever status, clustered by clinic and patient. Through dual independent chart review, fever (≥100.4°F) was categorized as probable, possible, or unlikely to be incidentally detected. RESULTS Temperature measurement occurred at 155 527 of 274 351 (58.9%) well-child visits. Of 24 clinics, 16 measured temperature at >90% of visits (“routine measurement clinics”) and 8 at CONCLUSIONS Temperature measurement occurs at more than one-half of well-child visits and is a clinic-driven practice. Given the impact on subsequent interventions and vaccine deferral, the harm–benefit profile of this practice warrants consideration.

Surgical comanagement (SCM), in which surgeons and hospitalists share responsibility of care for surgical patients, has been increasingly utilized. In August 2012, we implemented SCM in Orthopedic and Neurosurgery services in which the same Internal Medicine hospitalists are dedicated year round to each of these surgical services to proactively prevent and manage medical conditions. In this article, we evaluate if SCM was associated with continued improvement in patient outcomes between 2012 and 2018 in Orthopedic and Neurosurgery services at our institution. We conducted regression analysis on 26,380 discharges to assess yearly change in our outcomes. Since 2012, the odds of patients with ≥1 medical complication decreased by 3.8% per year (P = .01), the estimated length of stay decreased by 0.3 days per year (P < .0001), and the odds of rapid response team calls decreased by 12.2% per year (P = .001). Estimated average direct cost savings were $3,424 per discharge.

As a newly recognized subspecialty, understanding programmatic models for pediatric hospital medicine (PHM) programs is vital to lay the groundwork for a sustainable field. Although variability has been described within university-based PHM programs, there remains no national benchmark for community-based PHM programs. In this report, we describe the workload, clinical services, employment, and perception of sustainability of 70 community-based PHM programs in 29 states through a survey of community site leaders. The median hours for a full-time hospitalist was 1,882 hours/year with those employed by community hospitals working 8% more hours/year and viewing appropriate morning pediatric census as 20% higher than those employed by university institutions. Forty-three out of 70 (63%) site leaders perceived their programs as sustainable, with no significant difference by employer structure. Future studies should further explore root causes for workload discrepancies between community and academic employed programs along with establishing potential standards for PHM program development.

Importance Surveys in the US have found that Black and Latinx individuals have more reservations than their white counterparts about COVID-19 vaccination. However, little is known about the degree to which racial-ethnic differences in COVID-19 vaccination intentions are explained by differences in beliefs or perceptions about COVID-19 vaccines. Objective To compare intention to receive COVID-19 vaccination by race-ethnicity, to identify perceptional factors that may mediate the association between race-ethnicity and intention to receive the vaccine, and to identify the demographic and perceptional factors most strongly predictive of intention to receive a vaccine. Design Cross-sectional survey conducted from November, 2020 to January, 2021, nested within two longitudinal cohort studies of prevalence and incidence of SARS CoV-2 among the general population and healthcare workers. Setting Six San Francisco Bay Area counties. Study Cohort 3,161 participants in the Track COVID cohort (a population-based sample of adults) and 1,803 participants in the CHART Study cohort (a cohort of employees at three large medical centers). Results Rates of high vaccine willingness were significantly lower among Black (45.3%), Latinx (62.5%), Asian (65%), multi-racial (67.2%), and other race (61.0%) respondents than among white respondents (77.6%). Black, Latinx, and Asian respondents were significantly more likely than white respondents to endorse reasons to not get vaccinated, especially lack of trust. Participants’ motivations and concerns about COVID-19 vaccination only partially explained racial-ethnic differences in vaccination willingness. Being a health worker in the CHART cohort and concern about a rushed government vaccine approval process were the two most important factors predicting vaccination intention. Conclusions and Relevance Special efforts are required to reach historically marginalized racial-ethnic communities to support informed decision-making about COVID-19 vaccination. These campaigns must acknowledge the history of racism in biomedical research and health care delivery that has degraded the trustworthiness of health and medical science institutions among non-white population and may continue to undermine confidence in COVID-19 vaccines. Highlights Black, Latinx, Asian, Multi-racial, and Other race respondents were significantly less likely than white respondents to have high willingness to receive COVID-19 vaccination when surveyed around the time that the first COVID-19 vaccines received Emergency Use Authorization in the US. Racial-ethnic differences in vaccination intention were present for both health workers and the general population. Motivations and concerns about COVID-19 vaccination only partially explained racial-ethnic differences in COVID-19 vaccine willingness. The most important factors explaining COVID-19 vaccination intention were being a health worker, concern about government rushing the vaccine process, concern about having a bad reaction to the vaccine, motivation to protecting one’s self and family from COVID-19, and concern about getting COVID from the vaccine

IntroductionPoint-of-care ultrasound (POCUS) may detect the cardiopulmonary manifestations of COVID-19 and expediently predict patient outcomes.MethodsWe conducted a prospective cohort study at four medical centers from 3/2020-1/2021 to evaluate POCUS findings and clinical outcomes with COVID-19. Our inclusion criteria included adult patients hospitalized for COVID-19 who received cardiac or lung POCUS with a 12-zone protocol. Images were interpreted by two reviewers blinded to clinical outcomes. Our primary outcome was ICU admission incidence. Secondary outcomes included intubation and supplemental oxygen usage.ResultsN=160 patients (N=201 scans) were included. Scans were collected a median 23 hours (IQR:7-80) from emergency department triage. Triage POCUS findings associated with ICU admission included B-lines (OR 4.41 [95% CI:1.71-14.30]; pConsolidations present on triage were associated with the need for oxygen at discharge (OR 2.16 [95% CI: 1.01-4.70]; p=0.047). A normal lung triage scan was protective for ICU admission (OR 0.28 [95% CI:0.09-0.75; pDiscussionLung POCUS findings detected early in the hospitalization may provide expedient risk stratification for important COVID-19 clinical outcomes, including ICU admission, intubation, or need for oxygen on discharge. A normal admission scan appears protective against adverse outcomes, which may aid in triage decisions of patients.

Background: Rotating medical consultants, hospitalists or geriatricians, are involved in the care of patients with hip fracture, often after medical complications have already occurred. In August 2012, we implemented a unique surgical comanagement (SCM) model in which the same Internal Medicine hospitalists are dedicated year-round to the orthopaedic surgery service. We examine whether this SCM model was associated with a decrease in medical complications, length of stay, and inpatient mortality in patients with hip fracture admitted at our institution, compared with the previous model. Methods: We included 2,252 admissions to the orthopaedic surgery service with a hip fracture between 2009 and 2018 (757 pre-SCM and 1495 post-SCM). We adjusted for age, Charlson comorbidity score, and operating time in all regression analyses. Results: Mean Charlson comorbidity score (1.6 versus 1.2) and median case mix index (2.1 versus 1.9) were higher in the post-SCM group. A 32% decrease was observed in the odds of having ≥1 medical complication(s) (odds ratio, 0.68 [95% confidence interval, 0.50 to 0.91], P = 0.009) post-SCM. No change was observed in length of stay or inpatient mortality despite an increase in medical complexity post-SCM. Conclusion: Having dedicated orthopaedic hospitalists may contribute to fewer medical complications in patients with hip fracture.

BackgroundHealthcare personnel (HCP) are prioritized for earliest SARS-CoV-2 vaccine administration, yet relatively few data exist on HCP’s knowledge, motivations, concerns, and intentions regarding COVID-19 vaccines.MethodsWe conducted a cross-sectional survey Nov.16-Dec.8, 2020 among HCP enrolled in a cohort study at three Northern California medical centers serving diverse roles including COVID-19 patient care. Eligible HCP were adult (age≥18) on-site employees of the University of California, San Francisco, San Francisco General Hospital, and Stanford Healthcare. A one-time electronically-administered survey was sent to cohort HCP on November 16, 2020 and responses analyzed.ResultsOverall, among 2,448 HCP invited, 2,135 completed the COVID-19 vaccine survey (87.2% response rate). HCPs had mean age 41 years, were 73% female, and had diverse jobs including COVID-19 patient contact. Enthusiasm for vaccination was overall strong, and more HCP (1,453, 69%) said they would definitely/likely receive vaccine if formally FDA-approved versus if approved via emergency use authorization only (785, 35%). While 541 (25%) respondents wanted to be among the earliest to receive vaccine, more desired vaccination after the first round (777, 36%) or >2 months after vaccinations began (389, 18%). Top factors increasing motivation for vaccination included perceiving risk from COVID-19 to self (1,382, 65%) or to family/friends (1355, 63%). Top concerns were vaccine side effects, cited by 596 (28%), and concerns about political involvement in FDA’s approval process (249, 12%).ConclusionsHCP were enthusiastic about COVID-19 vaccination for individual protection and protecting others, but harbored concerns about vaccine side effects. Our data may inform emerging vaccine education campaigns.Key PointsAmong 2,135 healthcare personnel surveyed, we found enthusiasm for COVID-19 vaccination both for individual benefit and protecting others. However, healthcare personnel rated their knowledge of COVID-19 vaccines as only moderate and harbored concerns about vaccine side effects. Education raising awareness of vaccine efficacy and side effects may help maximize vaccine uptake.

Objective This study compared the percent change in systolic blood pressure and the incidence of adverse cardiac events (ACEs; defined as cardiac arrest, cardiopulmonary resuscitation, arrhythmias, or ST-segment changes) during anesthesia induction in patients with Williams syndrome (WS) before and after implementation of a perioperative management strategy. Design Retrospective observational cohort study. Setting Single quaternary academic referral center. Participants The authors reviewed the records of all children with WS at the authors’ institution who underwent general anesthesia for cardiac catheterization, diagnostic imaging, or any type of surgery between November 2008 and August 2019. The authors identified 142 patients with WS, 48 of whom underwent 118 general anesthesia administrations. A historic group (HG) was compared with the intervention group (IG). Interventions Change in perioperative management (three-stage risk stratification: preoperative intravenous hydration, intravenous anesthesia induction, and early use of vasoactives). Measurements and Main Results The authors determined event rates within 60 minutes of anesthesia induction. Standardized mean difference (SMD) was calculated (SMD >0.2 suggests clinically meaningful difference). Sixty-seven general anesthesia encounters were recorded in the HG (mean age, 4.8 years; mean weight, 16.3 kg) and 51 in the IG (mean age, 6.0 years; mean weight, 18.2 kg). The change in systolic blood pressure was –17.5% (–30.0, –5.0) in the HG versus –9% (–18.0, 5.0) in the IG (p = 0.015; SMD = 0.419), and the incidence of ACEs was 6% in the HG and 2% in the IG (p = 0.542; SMD = 0.207). Conclusions Preoperative risk stratification, preoperative intravenous hydration, intravenous induction, and early use of continuous vasoactives resulted in greater hemodynamic stability, with a 2% incidence of ACEs.

More than 3000 clinical trials related to COVID-19 have been registered through clinicaltrials.gov. With so many trials, there is a risk that many will be inconclusive due to being underpowered or due to an inability to recruit patients. At academic medical centers, multiple trials are competing for the same resources; the success of one may come at the expense of another. The COVID-19 Outpatient Pragmatic Protocol Study (COPPS) is a flexible phase 2, multi-site, randomized, blinded trial based at Stanford University designed to overcome these issues by simultaneously evaluating multiple COVID-19 treatments in the outpatient setting in one common platform with shared controls. This approach reduces the overall number of patients required for statistical power, while improving the likelihood that any enrolled patient receives active treatment. The platform study has two main domains designed to evaluate COVID-19 treatments by assessing their ability to reduce viral shedding (Viral Domain), measured with self-collected nasal swabs, or improve clinical outcomes (Clinical Domain), measured through self-reported symptomology data. Data are collected on both domains for all participants enrolled. Participants are followed over a 28-day period. COPPS has the advantage of pragmatism created around its workflow that is also appealing to potential participants because of a lower probability of inactive treatment. At the conclusion of this clinical trial we expect to have identified potentially effective therapeutic strategy/ies for treating COVID-19 in the outpatient setting, which will have a transformative impact on medicine and public health.

Standard hypnotizability scales require physical contact or direct observation by tester and participant. The authors addressed this limitation by developing and testing the remote Hypnotic Induction Profile (rHIP), a hypnotizability test derived from the Hypnotic Induction Profile that is completed by telephone. To assess the validity of the rHIP, 56 volunteers naïve to hypnotizability testing completed both the HIP and the rHIP, with order of testing randomized. Results indicate a strong correlation between HIP and rHIP scores

Background Self-help group (SHG) interventions have been widely studied in low and middle income countries. However, there is little data on specific impacts of health layering, or adding health education modules upon existing SHGs which were formed primarily for economic empowerment. We examined three SHG interventions from 2012-2017 in Bihar, India to test the hypothesis that health-layering of SHGs would lead to improved health-related behaviours of women in SHGs. Methods A model for health layering of SHGs – Parivartan – was developed by the non-governmental organisation (NGO), Project Concern International, in 64 blocks of eight districts. Layering included health modules, community events and review mechanisms. The health layering model was adapted for use with government-led SHGs, called JEEViKA+HL, in 37 other blocks of Bihar. Scale-up of government-led SHGs without health layering (JEEViKA) occurred contemporaneously in 433 other blocks, providing a natural comparison group. Using Community-based Household Surveys (CHS, rounds 6-9) by CARE India, 62 reproductive, maternal, newborn and child health and nutrition (RMNCHN) and sanitation indicators were examined for SHGs with health layering (Pavivartan SHGs and JEEViKA+HL SHGs) compared to those without. We calculated mean, standard deviation and odds ratios of indicators using surveymeans and survey logistic regression. Results In 2014, 64% of indicators were significantly higher in Parivartan members compared to non-members residing in the same blocks. During scale up, from 2015-17, half (50%) of indicators had significantly higher odds in health layered SHG members (Parivartan or JEEViKA+HL) in 101 blocks compared to SHG members without health layering (JEEViKA) in 433 blocks. Conclusions Health layering of SHGs was demonstrated by an NGO-led model (Parivartan), adapted and scaled up by a government model (JEEViKA+HL), and associated with significant improvements in health compared to non-health-layered SHGs (JEEViKA). These results strengthen the evidence base for further layering of health onto the SHG platform for scale-level health change. Study registration ClinicalTrials.gov number NCT02726230

Background The Government of Bihar (GoB) in India, the Bill and Melinda Gates Foundation and several non-governmental organisations launched the Ananya program aimed to support the GoB to improve reproductive, maternal, newborn and child health and nutrition (RMNCHN) statewide. Here we summarise changes in indicators attained during the initial two-year pilot phase (2012-2013) of implementation in eight focus districts of approximately 28 million population, aimed to inform subsequent scale-up. Methods The quasi-experimental impact evaluation included statewide household surveys at two time points during the pilot phase: January-April 2012 (“baseline”) including an initial cohort of beneficiaries and January-April 2014 (“midline”) with a new cohort. The two arms were: 1) eight intervention districts, and 2) a comparison arm comprised of the remaining 30 districts in Bihar where Ananya interventions were not implemented. We analysed changes in indicators across the RMNCHN continuum of care from baseline to midline in intervention and comparison districts using a difference-in-difference analysis. Results Indicators in the two arms were similar at baseline. Overall, 40% of indicators (20 of 51) changed significantly from baseline to midline in the comparison districts unrelated to Ananya; two-thirds (n = 13) of secular indicator changes were in a direction expected to promote health. Statistically significant impact attributable to the Ananya program was found for 10% (five of 51) of RMNCHN indicators. Positive impacts were most prominent for mother’s behaviours in contraceptive utilisation. Conclusions The Ananya program had limited impact in improving health-related outcomes during the first two-year period covered by this evaluation. The program’s theories of change and action were not powered to observe statistically significant differences in RMNCHN indicators within two years, but rather aimed to help inform program improvements and scale-up. Evaluation of large-scale programs such as Ananya using theory-informed, equity-sensitive (including gender), mixed-methods approaches can help elucidate causality and better explain pathways through which supply- and demand-side interventions contribute to changes in behaviour among the actors involved in the production of population-level health outcomes. Evidence from Bihar indicates that deep structural constraints in health system organisation and delivery of interventions pose substantial limitations on behaviour change among health care providers and beneficiaries. Study registration ClinicalTrials.gov number NCT02726230.

Background: Prolonged symptoms after SARS-CoV-2 infection are well-documented. However, which factors influence development of long-term symptoms, how symptoms vary across ethnic groups, and whether long-term symptoms correlate with serologic biomarkers remain elusive. Methods: Adult inpatient and outpatient SARS-CoV-2 RT-PCR positive patients were recruited at Stanford from March 2020 to February 2021. Study participants were seen for in-person visits at diagnosis and every 1-3 months for up to one year after diagnosis; they completed symptom surveys and underwent sampling procedures (blood draw and nasal swab) at each visit. Findings: Our cohort (n=617) ranged from asymptomatic to critical COVID-19 infections. 40% of participants reported at least one symptom associated with COVID-19 six months after diagnosis. Median time from diagnosis to first resolution of all symptoms was 44 days, median time from diagnosis to sustained symptom resolution with no recurring symptoms for one month or longer was 214 days. Serum anti-nucleocapsid IgG level in the first week of infection was predictive of time to symptom resolution. A prior diagnosis of lung disease was associated with longer time to symptom resolution. COVID-19 disease severity, ethnicity, sex, cytomegalovirus (CMV) seropositivity, and remdesivir use did not affect time to sustained symptom resolution. More than 90% of participants had SARS-CoV-2-specific antibody>1000 AU/mL nine months after diagnosis. Interpretation: Our findings showed that all disease severities had a similar risk of developing post-COVID-19 syndrome in an ethnically diverse population. Comorbid lung disease and lower levels of initial IgG response to SARS-CoV-2 nucleocapsid antigen were associated with longer symptom duration. Trial Registration: National clinical trial database NCT04664309. Funding: NIH CTSA grant, U54 NIH Grant, R21 NIEHS, Sean N Parker Center for Allergy and Asthma Research at Stanford University, the Sunshine Foundation, the Crown Foundation, and the Parker Foundation. Declaration of Interest: Dr. Boyd received support for the current manuscript from Meso Scale Discovery and NIH; 418 received consulting fees by Regeneron for expert testimony, has stocks or stock options in 419 AbCellera Biologics; Dr. Chinthrajah reports grants from NIAID, CoFAR, Aimmune, DBV 420 Technologies, Astellas, Regeneron, Stanford Maternal and Child Health Research Institute 421 (MCHRI), and FARE. She is an Advisory Board Member at Alladapt Therapeutics, Novartis, 422 Genentech, Sanofi, Allergenis, and Nutricia; Dr. Manisha Desai received support from Chan 423 Zuckerberg Foundation; Dr. Maecker received grants or contracts from NIH, Bill & Melinda 424 Gates Foundation, Ionis Corporation, Amgen Corporation; Consulting fees from Magarray Corp; 425 payment or honoraria from UCLA, UC Davis; leadership or fiduciary role at Cytek SAB; stocks 426 or stock options at BD Biosciences; Dr. Nadeau reports grants from National Institute of Allergy and Infectious Diseases (NIAID), National Heart, Lung, and Blood Institute (NHLBI), National Institute of Environmental Health Sciences (NIEHS), and Food Allergy Research & Education (FARE); Director of World Allergy Organization (WAO) , Advisor at Cour Pharma, Consultant for Excellergy, Red tree ventures, and Phylaxis, Co-founder of Before Brands, Alladapt, Latitude, and IgGenix; and National Scientific Committee member at Immune Tolerance Network (ITN), and National Institutes of Health (NIH) clinical research centers, outside the submitted work; patents include, “Mixed allergen composition and methods for using the same”, “Granulocyte-based methods for detecting and monitoring immune system disorders”, “Methods and Assays for Detecting and Quantifying Pure Subpopulations of White Blood Cells in Immune System Disorders,” and “Methods of isolating allergen-specific antibodies from humans and uses thereof”; Dr. Benjamin Pinsky received grants or contracts for the present manuscript from MesoScale Diagnostics; Dr. Angele Rogers was a Clinical Trials Advisory Board Member for Merck; Dr. Sindher reports support for the present manuscript from the NIH, Regeneron, DBV Technologies, Aimmune, Novartis, CoFAR, FARE, participated on a DSMB for Astra Zeneca, DBV, and received payment or honorarium from FARE; Neera Ahuja, Maja Artandi, Linda Barman, Catherine Blish, Andra Blomkalns, William Collins, MacKenzie Cox, Linda Geng, Xiaolin Jia, Megan Mahoney, Monali Manohar, Ruth O’hara, Rajan Puri, Katharina Roltgen, Laura Vaughan, Samuel Yang, Shu Cao, Iris Chang, Hena Din, Evan Do, Andrea Fernandez, Alexandra Lee, Natasha Purington, Yael Rosenberg-Hasson, Theo Snow, Daniel Solis, Michelle Verghese, and Yingjie Weng have no conflict of interest. Ethical Approval: This study was reviewed and approved by the Stanford Administrative Panel on Human Subjects in Medical Research.

Supplemental material, sj-pdf-1-ctj-10.1177_1740774520988298 for Clinical trials in a COVID-19 pandemic: Shared infrastructure for continuous learning in a rapidly changing landscape by Haley Hedlin, Ariadna Garcia, Yingjie Weng, Ziyuan He, Vandana Sundaram, Bryan Bunning, Vidhya Balasubramanian, Kristen Cunanan, Kristopher Kapphahn, Santosh Gummidipundi, Natasha Purington, Mary Boulos and Manisha Desai in Clinical Trials