Faculty Bibliography

PURPOSE/UNASSIGNED:We aimed to determine whether implementation of clinical decision support (CDS) tool integrated into the electronic health record of a multisite academic medical center increased the proportion of patients with AUA "high-risk" microscopic hematuria (MH) who receive guideline concordant evaluations. MATERIALS AND METHODS/UNASSIGNED:We conducted a two-arm cluster randomized quality improvement project in which 202 ambulatory sites from a large health system were randomized to either have their physicians receive at time of test results an automated CDS alert for patients with "high-risk" MH with associated recommendations for imaging and cystoscopy (intervention) or usual care (control). Primary outcome was met if a patient underwent both imaging and cystoscopy within 180 days from MH result. Secondary outcomes assessed individual completion of imaging, cystoscopy, or placement of imaging orders. RESULTS/UNASSIGNED:= .09). CONCLUSIONS/UNASSIGNED:Implementing an electronic health record-integrated CDS tool to promote evaluation of patients with high-risk MH did not lead to improvements in patient completion of a full guideline-concordant evaluation. The development of an algorithm to trigger a CDS alert was demonstrated to be feasible and effective. Further multilevel assessment of barriers to evaluation is necessary to continue to improve the approach to evaluating high-risk patients with MH.

IMPORTANCE/UNASSIGNED:A substantial number of individuals worldwide experience long COVID, or post-COVID condition. Other postviral and autoimmune conditions have a female predominance, but whether the same is true for long COVID, especially within different subgroups, is uncertain. OBJECTIVE/UNASSIGNED:To evaluate sex differences in the risk of developing long COVID among adults with SARS-CoV-2 infection. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cohort study used data from the National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER)-Adult cohort, which consists of individuals enrolled in and prospectively followed up at 83 sites in 33 US states plus Washington, DC, and Puerto Rico. Data were examined from all participants enrolled between October 29, 2021, and July 5, 2024, who had a qualifying study visit 6 months or more after their initial SARS-CoV-2 infection. EXPOSURE/UNASSIGNED:Self-reported sex (male, female) assigned at birth. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Development of long COVID, measured using a self-reported symptom-based questionnaire and scoring guideline at the first study visit that occurred at least 6 months after infection. Propensity score matching was used to estimate risk ratios (RRs) and risk differences (95% CIs). The full model included demographic and clinical characteristics and social determinants of health, and the reduced model included only age, race, and ethnicity. RESULTS/UNASSIGNED:Among 12 276 participants who had experienced SARS-CoV-2 infection (8969 [73%] female; mean [SD] age at infection, 46 [15] years), female sex was associated with higher risk of long COVID in the primary full (RR, 1.31; 95% CI, 1.06-1.62) and reduced (RR, 1.44; 95% CI, 1.17-1.77) models. This finding was observed across all age groups except 18 to 39 years (RR, 1.04; 95% CI, 0.72-1.49). Female sex was associated with significantly higher overall long COVID risk when the analysis was restricted to nonpregnant participants (RR, 1.50; 95%: CI, 1.27-1.77). Among participants aged 40 to 54 years, the risk ratio was 1.42 (95% CI, 0.99-2.03) in menopausal female participants and 1.45 (95% CI, 1.15-1.83) in nonmenopausal female participants compared with male participants. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this prospective cohort study of the NIH RECOVER-Adult cohort, female sex was associated with an increased risk of long COVID compared with male sex, and this association was age, pregnancy, and menopausal status dependent. These findings highlight the need to identify biological mechanisms contributing to sex specificity to facilitate risk stratification, targeted drug development, and improved management of long COVID.

In 2001, the Centers for Medicare and Medicaid Services established the New Technology Add-On Payment (NTAP) program to incentivize access to costly new technologies for Medicare beneficiaries. These technologies, authorized by the Food and Drug Administration (FDA), must demonstrate "substantial clinical improvement" when compared to existing technologies. However, in FY2021, the FDA introduced two expedited authorization pathways, allowing technologies with either designation to bypass the "substantial clinical improvement" criterion. We describe the services and payments associated with NTAPs following this policy change.

BACKGROUND:Patients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge. OBJECTIVE:To determine risks for post-discharge readmission and death among patients hospitalized with COVID-19. DESIGN/METHODS:Multicenter retrospective observational cohort study, 2020-2021, with 30-day follow-up. PARTICIPANTS/METHODS:Adults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system. MAIN MEASURES/METHODS:Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN). KEY RESULTS/RESULTS:The final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model's AUC for the internal validation set was 0.73 (95% CI 0.71-0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set. CONCLUSIONS:This large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.

Electronic health record (EHR)-embedded tools are known to improve prescribing of guideline-directed medical therapy (GDMT) for patients with heart failure. However, physicians may perceive EHR tools to be unhelpful, and may be therefore hesitant to implement these in their practice. We surveyed cardiologists about two effective EHR-tools to improve heart failure care, and they perceived the EHR tools to be easy to use, helpful, and improve the overall management of their patients with heart failure.

OBJECTIVE:To estimate the prevalence of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) after infection with SARS-CoV-2 during pregnancy and to characterize associated risk factors. METHODS:In a multicenter cohort study (NIH RECOVER [Researching COVID to Enhance Recovery]-Pregnancy Cohort), individuals who were pregnant during their first SARS-CoV-2 infection were enrolled across the United States from December 2021 to September 2023, either within 30 days of their infection or at differential time points thereafter. The primary outcome was PASC , defined as score of 12 or higher based on symptoms and severity as previously published by the NIH RECOVER-Adult Cohort, at the first study visit at least 6 months after the participant's first SARS-CoV-2 infection. Risk factors for PASC were evaluated, including sociodemographic characteristics, clinical characteristics before SARS-CoV-2 infection (baseline comorbidities, trimester of infection, vaccination status), and acute infection severity (classified by need for oxygen therapy). Multivariable logistic regression models were fitted to estimate associations between these characteristics and presence of PASC. RESULTS:Of the 1,502 participants, 61.1% had their first SARS-CoV-2 infection on or after December 1, 2021 (ie, during Omicron variant dominance); 51.4% were fully vaccinated before infection; and 182 (12.1%) were enrolled within 30 days of their acute infection. The prevalence of PASC was 9.3% (95% CI, 7.9-10.9%) measured at a median of 10.3 months (interquartile range 6.1-21.5) after first infection. The most common symptoms among individuals with PASC were postexertional malaise (77.7%), fatigue (76.3%), and gastrointestinal symptoms (61.2%). In a multivariable model, the proportion PASC positive with vs without history of obesity (14.9% vs 7.5%, adjusted odds ratio [aOR] 1.65, 95% CI, 1.12-2.43), depression or anxiety disorder (14.4% vs 6.1%, aOR 2.64, 95% CI, 1.79-3.88) before first infection, economic hardship (self-reported difficulty covering expenses) (12.5% vs 6.9%, aOR 1.57, 95% CI, 1.05-2.34), and treatment with oxygen during acute SARS-CoV-2 infection (18.1% vs 8.7%, aOR 1.86, 95% CI, 1.00-3.44) were associated with increased prevalence of PASC. CONCLUSION/CONCLUSIONS:The prevalence of PASC at a median time of 10.3 months after SARS-CoV-2 infection during pregnancy was 9.3% in the NIH RECOVER-Pregnancy Cohort. The predominant symptoms were postexertional malaise, fatigue, and gastrointestinal symptoms. Several socioeconomic and clinical characteristics were associated with PASC after infection during pregnancy. CLINICAL TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov , NCT05172024.

BACKGROUND/UNASSIGNED:There are currently no validated clinical biomarkers of postacute sequelae of SARS-CoV-2 infection (PASC). OBJECTIVE/UNASSIGNED:To investigate clinical laboratory markers of SARS-CoV-2 and PASC. DESIGN/UNASSIGNED:Propensity score-weighted linear regression models were fitted to evaluate differences in mean laboratory measures by prior infection and PASC index (≥12 vs. 0). (ClinicalTrials.gov: NCT05172024). SETTING/UNASSIGNED:83 enrolling sites. PARTICIPANTS/UNASSIGNED:RECOVER-Adult cohort participants with or without SARS-CoV-2 infection with a study visit and laboratory measures 6 months after the index date (or at enrollment if >6 months after the index date). Participants were excluded if the 6-month visit occurred within 30 days of reinfection. MEASUREMENTS/UNASSIGNED:Participants completed questionnaires and standard clinical laboratory tests. RESULTS/UNASSIGNED:levels was attenuated after participants with preexisting diabetes were excluded. Among participants with prior infection, no meaningful differences in mean laboratory values were found between those with a PASC index of 12 or higher and those with a PASC index of zero. LIMITATION/UNASSIGNED:Whether differences in laboratory markers represent consequences of or risk factors for SARS-CoV-2 infection could not be determined. CONCLUSION/UNASSIGNED:Overall, no evidence was found that any of the 25 routine clinical laboratory values assessed in this study could serve as a clinically useful biomarker of PASC. PRIMARY FUNDING SOURCE/UNASSIGNED:National Institutes of Health.

BACKGROUND:Sodium-glucose cotransporter 2 (SGLT2) inhibitors reduce heart failure (HF) hospitalizations, recurrent cardiovascular events, and chronic kidney disease (CKD) progression, and thus constitute a Class 1a recommendation in people with diabetes and atherosclerotic cardiovascular disease, HF, or CKD and in people with severe albuminuria or HF, regardless of diabetes status. OBJECTIVES/OBJECTIVE:The purpose of this study was to comprehensibly characterize the rate of SGLT2 inhibitor prescriptions among people with a Class 1a recommendation for SGLT2 inhibitor use. METHODS:Among 3,189,827 adults from 28 U.S. health systems within Optum Labs Data Warehouse between April 1, 2022, and March 31, 2023, we assessed SGLT2 inhibitor prescription rates, stratified by presence of diabetes and Class 1a recommendation. RESULTS:Among 716,387 adults with diabetes, 63.4% had a Class 1a recommendation for SGLT2 inhibitor therapy. There was little difference by Class 1a recommendation status (present: 11.9%; 95% CI: 11.9%-12.0% vs absent: 11.4%; 95% CI: 11.3%-11.6%; standardized mean difference: 1.3%). Among 2,473,440 adults without diabetes, 6.2% had a Class 1a recommendation for SGLT2 inhibitor therapy, and 3.1% (3.0%-3.2%) of those received a prescription. Internists/family practitioners initiated SGLT2 inhibitor prescriptions most commonly among people with diabetes, whereas specialists initiated SGLT2 inhibitor prescriptions most commonly among people without diabetes. No health system had >25% SGLT2 inhibitor prescription rate among people with a Class 1a recommendation. Health systems with higher proportions of patients with commercial insurance and lower proportions with Medicare had higher SGLT2 inhibitor prescription rates. CONCLUSIONS:In this analysis of U.S. data from 2022 to 2023, SGLT2 inhibitor prescription among people with a Class 1a recommendation is low. Interventions are needed to increase uptake of guideline-recommended SGLT2 inhibitor use.