Influence of a Large Language Model on Diagnostic Reasoning: A Randomized Clinical Vignette Study.

Importance: Diagnostic errors are common and cause significant morbidity. Large language models (LLMs) have shown promise in their performance on both multiple-choice and open-ended medical reasoning examinations, but it remains unknown whether the use of such tools improves diagnostic reasoning. Objective: To assess the impact of the GPT-4 LLM on physicians' diagnostic reasoning compared to conventional resources. Design: Multi-center, randomized clinical vignette study. Setting: The study was conducted using remote video conferencing with physicians across the country and in-person participation across multiple academic medical institutions. Participants: Resident and attending physicians with training in family medicine, internal medicine, or emergency medicine. Interventions: Participants were randomized to access GPT-4 in addition to conventional diagnostic resources or to just conventional resources. They were allocated 60 minutes to review up to six clinical vignettes adapted from established diagnostic reasoning exams. Main Outcomes and Measures: The primary outcome was diagnostic performance based on differential diagnosis accuracy, appropriateness of supporting and opposing factors, and next diagnostic evaluation steps. Secondary outcomes included time spent per case and final diagnosis. Results: 50 physicians (26 attendings, 24 residents) participated, with an average of 5.2 cases completed per participant. The median diagnostic reasoning score per case was 76.3 percent (IQR 65.8 to 86.8) for the GPT-4 group and 73.7 percent (IQR 63.2 to 84.2) for the conventional resources group, with an adjusted difference of 1.6 percentage points (95% CI -4.4 to 7.6; p=0.60). The median time spent on cases for the GPT-4 group was 519 seconds (IQR 371 to 668 seconds), compared to 565 seconds (IQR 456 to 788 seconds) for the conventional resources group, with a time difference of -82 seconds (95% CI -195 to 31; p=0.20). GPT-4 alone scored 15.5 percentage points (95% CI 1.5 to 29, p=0.03) higher than the conventional resources group. Conclusions and Relevance: In a clinical vignette-based study, the availability of GPT-4 to physicians as a diagnostic aid did not significantly improve clinical reasoning compared to conventional resources, although it may improve components of clinical reasoning such as efficiency. GPT-4 alone demonstrated higher performance than both physician groups, suggesting opportunities for further improvement in physician-AI collaboration in clinical practice.

A parental communication assessment initiative in the paediatric cardiovascular ICU.

OBJECTIVE: Challenges to communication between families and care providers of paediatric patients in intensive care units (ICU) include variability of communication preferences, mismatched goals of care, and difficulties carrying forward family preferences from provider to provider. Our objectives were to develop and test an assessment tool that queries parents of children requiring cardiac intensive care about their communication preferences and to determine if this tool facilitates patient-centred care and improves families' ICU experience. DESIGN: In this quality improvement initiative, a novel tool was developed, the Parental Communication Assessment (PCA), which asked parents with children hospitalised in the cardiac ICU about their communication preferences. Participants were prospectively randomised to the intervention group, which received the PCA, or to standard care. All participants completed a follow-up survey evaluating satisfaction with communication. MAIN RESULTS: One hundred thirteen participants enrolled and 56 were randomised to the intervention group. Participants who received the PCA preferred detail-oriented communication over big picture. Most parents understood the daily discussions on rounds (64%) and felt comfortable expressing concerns (68%). Eighty-six percent reported the PCA was worthwhile. Parents were generally satisfied with communication. However, an important proportion felt unprepared for difficult decisions or setbacks, inadequately included or supported in decision-making, and that they lacked control over their child's care. There were no significant differences between the intervention and control groups in their communication satisfaction results. CONCLUSIONS: Parents with children hospitalised in the paediatric ICU demonstrated diverse communication preferences. Most participants felt overall satisfied with communication, but individualising communication with patients' families according to their preferences may improve their experience.

Adjusting Incidence Estimates with Laboratory Test Performances: A Pragmatic Maximum Likelihood Estimation-Based Approach.

Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge, there are no pragmatic methods to address the bias introduced by the performance of labs in testing for the virus. In the setting of a longitudinal study, we developed a maximum likelihood estimation-based approach to estimate laboratory performance-adjusted incidence using the expectation-maximization algorithm. We constructed confidence intervals (CIs) using both bootstrapped-based and large-sample interval estimator approaches. We evaluated our methods through extensive simulation and applied them to a real-world study (TrackCOVID), where the primary goal was to determine the incidence of and risk factors for SARS-CoV-2 infection in the San Francisco Bay Area from July 2020 to March 2021. Our simulations demonstrated that our method converged rapidly with accurate estimates under a variety of scenarios. Bootstrapped-based CIs were comparable to the large-sample estimator CIs with a reasonable number of incident cases, shown via a simulation scenario based on the real TrackCOVID study. In more extreme simulated scenarios, the coverage of large-sample interval estimation outperformed the bootstrapped-based approach. Results from the application to the TrackCOVID study suggested that assuming perfect laboratory test performance can lead to an inaccurate inference of the incidence. Our flexible, pragmatic method can be extended to a variety of disease and study settings.

Comparative Effectiveness and Cost-Effectiveness of Colorectal Cancer Screening With Blood-Based Biomarkers (Liquid Biopsy) vs Fecal Tests or Colonoscopy.

BACKGROUND & AIMS: Colorectal cancer (CRC) screening is highly effective but underused. Blood-based biomarkers (liquid biopsy) could improve screening participation. METHODS: Using our established Markov model, screening every 3 years with a blood-based test that meets minimum Centers for Medicare & Medicaid Services' thresholds (CMSmin) (CRC sensitivity 74%, specificity 90%) was compared with established alternatives. Test attributes were varied in sensitivity analyses. RESULTS: CMSmin reduced CRC incidence by 40% and CRC mortality by 52% vs no screening. These reductions were less profound than the 68%-79% and 73%-81%, respectively, achieved with multi-target stool DNA (Cologuard; Exact Sciences) every 3 years, annual fecal immunochemical testing (FIT), or colonoscopy every 10 years. Assuming the same cost as multi-target stool DNA, CMSmin cost $28,500/quality-adjusted life-year gained vs no screening, but FIT, colonoscopy, and multi-target stool DNA were less costly and more effective. CMSmin would match FIT's clinical outcomes if it achieved 1.4- to 1.8-fold FIT's participation rate. Advanced precancerous lesion (APL) sensitivity was a key determinant of a test's effectiveness. A paradigm-changing blood-based test (sensitivity >90% for CRC and 80% for APL; 90% specificity; cost ≤$120-$140) would be cost-effective vs FIT at comparable participation. CONCLUSIONS: CMSmin could contribute to CRC control by achieving screening in those who will not use established methods. Substituting blood-based testing for established effective CRC screening methods will require higher CRC and APL sensitivities that deliver programmatic benefits matching those of FIT. High APL sensitivity, which can result in CRC prevention, should be a top priority for screening test developers. APL detection should not be penalized by a definition of test specificity that focuses on CRC only.

Quality improvement project to reduce medicare 1-day write-offs due to inappropriate admission orders.

BACKGROUND: We identified that Stanford Health Care had a significant number of patients who after discharge are found by the utilization review committee not to meet Center for Mediare and Medicaid Services (CMS) 2-midnight benchmark for inpatient status. Some of the charges incurred during the care of these patients are written-off and known as Medicare 1-day write-offs. This study which aims to evaluate the use of a Best Practice Alert (BPA) feature on the electronic medical record, EPIC, to ensure appropriate designation of a patient's hospitalization status as either inpatient or outpatient in accordance with Center for Medicare and Medicaid services (CMS) 2 midnight length of stay benchmark thereby reducing the number of associated write-offs. METHOD: We incorporated a best practice alert (BPA) into the Epic Electronic Medical Record (EMR) that would prompt the discharging provider and the case manager to review the patients' inpatient designation prior to discharge and change the patient's designation to observation when deemed appropriate. Patients who met the inclusion criteria (Patients must have Medicare fee-for-service insurance, inpatient length of stay (LOS) less than 2 midnights, inpatient designation as hospitalization status at time of discharge, was hospitalized to an acute level of care and belonged to one of 37 listed hospital services at the time of signing of the discharge order) were randomized to have the BPA either silent or active over a three-month period from July 18, 2019, to October 18, 2019. RESULT: A total of 88 patients were included in this study: 40 in the control arm and 48 in the intervention arm. In the intervention arm, 8 (8/48, 16.7%) had an inpatient status designation despite potentially meeting Medicare guidelines for an observation stay, comparing to 23 patients (23/40, 57.5%) patients in the control group (p = 0.001). The estimated number of write-offs in the control arm was 17 (73.9%, out of 23 inpatient patients) while in the intervention arm was 1 (12.5%, out of 8 inpatient patient) after accounting for patients who may have met inpatient criteria for other reasons based on case manager note review. CONCLUSION: This is the first time to our knowledge that a BPA has been used in this manner to reduce the number of Medicare 1-day write-offs.

Donor Electrocardiogram Associations With Cardiac Dysfunction, Heart Transplant Use, and Survival: The Donor Heart Study.

BACKGROUND: Potential organ donors often exhibit abnormalities on electrocardiograms (ECGs) after brain death, but the physiological and prognostic significance of such abnormalities is unknown. OBJECTIVES: This study sought to characterize the prevalence of ECG abnormalities in a nationwide cohort of potential cardiac donors and their associations with cardiac dysfunction, use for heart transplantation (HT), and recipient outcomes. METHODS: The Donor Heart Study enrolled 4,333 potential cardiac organ donors at 8 organ procurement organizations across the United States from 2015 to 2020. A blinded expert reviewer interpreted all ECGs, which were obtained once hemodynamic stability was achieved after brain death and were repeated 24 ± 6 hours later. ECG findings were summarized, and their associations with other cardiac diagnostic findings, use for HT, and graft survival were assessed using univariable and multivariable regression. RESULTS: Initial ECGs were interpretable for 4,136 potential donors. Overall, 64% of ECGs were deemed clinically abnormal, most commonly as a result of a nonspecific St-T-wave abnormality (39%), T-wave inversion (19%), and/or QTc interval >500 ms (17%). Conduction abnormalities, ectopy, pathologic Q waves, and ST-segment elevations were less common (each present in ≤5% of donors) and resolved on repeat ECGs in most cases. Only pathological Q waves were significant predictors of donor heart nonuse (adjusted OR: 0.39; 95% CI: 0.29-0.53), and none were associated with graft survival at 1 year post-HT. CONCLUSIONS: ECG abnormalities are common in potential heart donors but often resolve on serial testing. Pathologic Q waves are associated with a lower likelihood of use for HT, but they do not portend worse graft survival.

Stir-up Regimen After General Anesthesia in the Postanesthesia Care Unit: A Nurse Led Stepped Wedge Cluster Randomized Control Trial.

PURPOSE: To implement a standardized Stir-up Regimen (deep breathing, coughing, repositioning, mobilization [moving arms/legs], assessing and managing pain and nausea) within the first 30 minutes of arrival in the postanesthesia care unit (PACU), with a goal of decreasing recovery time in the immediate postanesthesia period (Phase I). DESIGN: A pragmatic stepped wedge cluster randomized control trial. Initially, data were collected on time in Phase I in three PACUs (control). Subsequently, the same three units were randomized to sequentially transition to the Stir-up Regimen (intervention). METHODS: A stepped wedge cluster randomized control trial design was used to implement a standardized Stir-up Regimen in three PACUs in an academic hospital for adult patients who received at least 30 minutes of general anesthesia. The measured outcome was the PACU time in minutes from patient arrival to when the patient met Phase I discharge criteria. Differences between intervention and control groups were evaluated using a generalized mixed-effects model. Nurses were educated about the Stir-up Regimen in team huddles, in-services, video demonstrations, email notifications and reminders, and immediate feedback at the bedside. Implementation science principles were used to assess the adoption of the Stir-up Regimen through a presurvey, postsurvey and spot-check observations in all three PACUs. FINDINGS: A total of 5,809 PACU adult patient admissions were included: control group (n = 2,860); intervention group (n = 2,949); males (n = 2,602), and females (n = 3,206). The intervention was associated with a reduction in overall mean Phase I recovery time of 4.9 minutes (95% CI: -8.4 to -1.4, P = .007). One PACU decreased time by 9.6 minutes (95% CI: -15.3 to -4.0, P < .001). The other units also reduced Phase I recovery time, but this did not reach statistical significance. The spot-check observations confirmed the intervention was adopted by the nurses, as most interventions were nurse-initiated versus patient-initiated during the first 30 minutes in PACU. CONCLUSIONS: Standardization of a Stir-up Regimen within 30 minutes of patient PACU arrival resulted in decreased Phase I recovery time.

Incidence of Neonatal Hypothermia in the Newborn Nursery and Associated Factors.

Importance: Thermoregulation is a key component of well-newborn care. There is limited epidemiologic data on hypothermia in late preterm and term infants admitted to the nursery. Expanding on these data is essential for advancing evidence-based care in a population that represents more than 3.5 million births per year in the US. Objective: To examine the incidence and factors associated with hypothermia in otherwise healthy infants admitted to the newborn nursery following delivery. Design, Setting, and Participants: A retrospective cohort study using electronic health record data from May 1, 2015, to August 31, 2021, was conducted at a newborn nursery at a university-affiliated children's hospital. Participants included 23 549 infants admitted to the newborn nursery, from which 321 060 axillary and rectal temperature values were analyzed. Exposures: Infant and maternal clinical and demographic factors. Main Outcomes and Measures: Neonatal hypothermia was defined according to the World Health Organization threshold of temperature less than 36.5 °C. Hypothermia was further classified by severity (mild: single episode, temperature 36.0-36.4 °C; moderate/severe: persistent or recurrent hypothermia and/or temperature <36.0 °C) and timing (early: all hypothermic episodes occurred within the first 24 hours after birth; late: any episode extended beyond the first 24 hours). Results: Of 23 549 included infants (male, 12 220 [51.9%]), 5.6% were late preterm (35-36 weeks' gestation) and 4.3% were low birth weight (≤2500 g). The incidence of mild hypothermia was 17.1% and the incidence of moderate/severe hypothermia was 4.6%. Late hypothermia occurred in 1.8% of infants. Lower birth weight and gestational age and Black and Asian maternal race and ethnicity had the highest adjusted odds across all classifications of hypothermia. The adjusted odds ratios of moderate/severe hypothermia were 5.97 (95% CI 4.45-8.00) in infants with a birth weight less than or equal to 2500 vs 3001 to 3500 g, 3.17 (95% CI 2.24-4.49) in 35 week' vs 39 weeks' gestation, and 2.65 (95% CI 1.78-3.96) in infants born to Black mothers and 1.94 (95% CI 1.61-2.34) in infants born to Asian mothers vs non-Hispanic White mothers. Conclusions and Relevance: In this cohort study of infants in the inpatient nursery, hypothermia was common, and the incidence varied by hypothermia definition applied. Infants of lower gestational age and birth weight and those born to Black and Asian mothers carried the highest odds of hypothermia. These findings suggest that identifying biological, structural, and social determinants of hypothermia is essential for advancing evidence-based equitable thermoregulatory care.

Chatbot vs Medical Student Performance on Free-Response Clinical Reasoning Examinations.

This study compares performance on free-response clinical reasoning examinations of first- and second-year medical students vs 2 models of a popular chatbot.

Left Ventricular Dysfunction Associated With Brain Death: Results From the Donor Heart Study.

BACKGROUND: Left ventricular dysfunction in potential donors meeting brain death criteria often results in nonuse of donor hearts for transplantation, yet little is known about its incidence or pathophysiology. Resolving these unknowns was a primary aim of the DHS (Donor Heart Study), a multisite prospective cohort study. METHODS: The DHS enrolled potential donors by neurologic determination of death (n=4333) at 8 organ procurement organizations across the United States between February 2015 and May 2020. Data included medications administered, serial diagnostic tests, and transthoracic echocardiograms (TTEs) performed: (1) within 48 hours after brain death was formally diagnosed; and (2) 24±6 hours later if left ventricular (LV) dysfunction was initially present. LV dysfunction was defined as an LV ejection fraction <50% and was considered reversible if LV ejection fraction was >50% on the second TTE. TTEs were also examined for presence of LV regional wall motion abnormalities and their reversibility. We assessed associations between LV dysfunction, donor heart acceptance for transplantation, and recipient 1-year survival. RESULTS: An initial TTE was interpreted for 3794 of the 4333 potential donors by neurologic determination of death. A total of 493 (13%) of these TTEs showed LV dysfunction. Among those donors with an initial TTE, LV dysfunction was associated with younger age, underweight, and higher NT-proBNP (N-terminal pro-B-type natriuretic peptide) and troponin levels. A second TTE was performed within 24±6 hours for a subset of donors (n=224) with initial LV dysfunction; within this subset, 130 (58%) demonstrated reversibility. Sixty percent of donor hearts with normal LV function were accepted for transplant compared with 56% of hearts with reversible LV dysfunction and 24% of hearts with nonreversible LV dysfunction. Donor LV dysfunction, whether reversible or not, was not associated with recipient 1-year survival. CONCLUSIONS: LV dysfunction associated with brain death occurs in many potential heart donors and is sometimes reversible. These findings can inform decisions made during donor evaluation and help guide donor heart acceptance for transplantation.

Antifungal stewardship in practice: Insights from a prospective audit and feedback program.

OBJECTIVE: To identify characteristics of antifungal prospective audit and feedback (PAF) and to compare rates of PAF recommendation and acceptance between antifungal and antibiotic agents. DESIGN: Retrospective cohort study of antifungal and antibiotic audits by a children's hospital antimicrobial stewardship program (ASP) from November 1, 2020, to October 31, 2022. METHODS: Antimicrobial audit data were retrieved from the ASP data warehouse. We characterized antifungal PAF using descriptive statistics. We then compared the overall rates of PAF recommendation and recommendation acceptance between antifungals and antibiotics. We also compared the differences in antifungal and antibiotic PAF recommendation and acceptance rates across various factors, including infectious problem, medical service, and recommendation type. RESULTS: Of 10,402 antimicrobial audits identified during the study period, 8,599 (83%) were for antibiotics and 1,803 (17%) were for antifungals. The highest antifungal recommendation rates were for liposomal amphotericin B, antifungals used for sepsis or respiratory tract infection, and antifungals prescribed in the cardiovascular intensive care unit. The rate of PAF recommendation was higher for antibiotics than for antifungals (29% vs 21%; P < .001); however, the rates of recommendation acceptance were similar. Recommendations to discontinue or for medication monitoring were more common for antifungals. CONCLUSIONS: Our analysis of antifungal PAF identified key opportunities to improve antifungal use, including the optimized use of specific agents and targeted use by certain medical services. Moreover, antifungal PAF, despite identifying fewer recommendations compared to antibiotic PAF, were associated with similarly high rates of acceptance, highlighting a promising opportunity for antifungal stewardship.

Performance of ChatGPT on free-response, clinical reasoning exams.

Importance: Studies 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. Objective: To determine if ChatGPT is capable of consistently meeting the passing threshold on free-response, case-based clinical reasoning assessments. Design: Fourteen 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. Setting: A single US medical school. Participants: ChatGPT. Main Outcomes and Measures: Passing rate of ChatGPT's scored responses and the range in model performance across multiple run throughs of a single case. Results: 12 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 Relevance: ChatGPT'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.

A quality-improvement approach to urgent-care antibiotic stewardship for respiratory tract infections during the COVID-19 pandemic: Lessons learned.

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.

Characteristics associated with diagnostic yield of imaging for deep venous thrombosis and pulmonary embolism in the emergency department, hospital, and office settings: An Optum Clinformatics claims database study (2015-2019).

BACKGROUND: Different patient characteristics influence the decision to order diagnostic imaging for deep venous thrombosis (DVT) and pulmonary embolism (PE) in different settings (emergency department (ED), hospital, and office). Diagnostic yield is defined as the proportion of tests that report positive results. We hypothesize different patient characteristics are associated with higher or lower diagnostic yield of imaging for DVT and PE in different settings. METHODS: We used Optum Clinformatics™ national claims database (2015-2019) to assess the diagnostic yield of imaging for DVT and PE in three settings: (a) ED discharge, (b) Hospitalized, and (c) Office. We studied the patient characteristics associated with diagnostic yield using logistic regression. RESULTS: Diagnostic imaging for DVT and PE was performed in 1,502,417 and 710,263 visits, respectively. Diagnostic yield for DVT and PE was 9.8 ± 0.1 % and 12.7 ± 0.1 %, respectively in the overall cohort. In the ED discharge, hospitalized, and office settings, diagnostic yield for DVT was 10.4 ± 0.1 %, 16.9 ± 0.1 %, and 6.5 ± 0.1 %, respectively, and that for PE 6.4 ± 0.1 %, 18.7 ± 0.1 %, and 8.8 ± 0.2 %, respectively. Of the patients who underwent imaging for DVT, higher diagnostic yield was more likely with thrombophilia, central venous access, and cancer. Of the patients who underwent imaging for PE, higher diagnostic yield was most likely with thrombophilia, respiratory failure, and heart failure or acute myocardial infarction. CONCLUSIONS: In each setting, different patient characteristics influence the diagnostic yield of imaging for DVT and PE and can inform clinical practice. Judicious use of imaging for DVT and PE could reduce costs and avoid exposure to radiation and contrast.

A Cross-sectional Study Characterizing Pediatric Temperature Percentiles in Children at Well-Child Visits.

BACKGROUND: 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. OBJECTIVE: To characterize pediatric temperature norms and variation by patient characteristics, time of measurement, and thermometer route. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Association between Obesity and Length of COVID-19 Hospitalization: Unexpected Insights from the American Heart Association National COVID-19 Registry.

Background: The mechanism for possible association between obesity and poor clinical outcomes from Coronavirus Disease 2019 (COVID-19) remains unclear. Methods: We analyzed 22,915 adult COVID-19 patients hospitalized from March 2020 to April 2021 to non-intensive care using the American Heart Association National COVID Registry. A multivariable Poisson model adjusted for age, sex, medical history, admission respiratory status, hospitalization characteristics, and laboratory findings was used to calculate length of stay (LOS) as a function of body mass index (BMI). We similarly analyzed 5,327 patients admitted to intensive care for comparison. Results: Relative to normal BMI subjects, overweight, class I obese, and class II obese patients had approximately half-day reductions in LOS (-0.469 days, P<0.01; -0.480 days, P<0.01; -0.578 days, P<0.01, respectively). Conclusion: The model identified a dose-dependent, inverse relationship between BMI category and LOS for COVID-19, which was not seen when the model was applied to critically ill patients.

Posttreatment FDG-PET/CT Hopkins criteria predict locoregional recurrence after definitive radiotherapy for oropharyngeal squamous cell carcinoma.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The Hopkins Criteria predict LRR with high accuracy for OPSCC response assessment.

Outcomes of a Neurohospitalist Program at an Academic Medical Center.

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.