Prevalent Metformin Use in Adults With Diabetes and the Incidence of Long COVID: An EHR-Based Cohort Study From the RECOVER Program.

OBJECTIVE: Studies show metformin use before and during SARS-CoV-2 infection reduces severe COVID-19 and postacute sequelae of SARS-CoV-2 (PASC) in adults. Our objective was to describe the incidence of PASC and possible associations with prevalent metformin use in adults with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: This is a retrospective cohort analysis using the National COVID Cohort Collaborative (N3C) and Patient-Centered Clinical Research Network (PCORnet) electronic health record (EHR) databases with an active comparator design that examined metformin-exposed individuals versus nonmetformin-exposed individuals who were taking other diabetes medications. T2DM was defined by HbA1C ≥6.5 or T2DM EHR diagnosis code. The outcome was death or PASC within 6 months, defined by EHR code or computable phenotype. RESULTS: In the N3C, the hazard ratio (HR) for death or PASC with a U09.9 diagnosis code (PASC-U09.0) was 0.79 (95% CI 0.71-0.88; P < 0.001), and for death or N3C computable phenotype PASC (PASC-N3C) was 0.85 (95% CI 0.78-0.92; P < 0.001). In PCORnet, the HR for death or PASC-U09.9 was 0.87 (95% CI 0.66-1.14; P = 0.08), and for death or PCORnet computable phenotype PASC (PASC-PCORnet) was 1.04 (95% CI 0.97-1.11; P = 0.58). Incident PASC by diagnosis code was 1.6% metformin vs. 2.0% comparator in the N3C, and 2.1% metformin vs. 2.5% comparator in PCORnet. By computable phenotype, incidence was 4.8% metformin and 5.2% comparator in the N3C and 24.7% metformin vs. 26.1% comparator in PCORnet. CONCLUSIONS: Prevalent metformin use is associated with a slightly lower incidence of death or PASC after SARS-CoV-2 infection. PASC incidence by computable phenotype is higher than by EHR code, especially in PCORnet. These data are consistent with other observational analyses showing prevalent metformin is associated with favorable outcomes after SARS-CoV-2 infection in adults with T2DM.

Timing to Surgery and Lymph Node Upstaging in Gastric Cancer: An NCDB Analysis.

BACKGROUND: Prior studies have shown tumor specificity on the impact of longer time interval from diagnosis to surgery, however in gastric cancer (GC) this remains unclear. We aimed to determine if a longer time interval from diagnosis to surgery had an impact on lymph node (LN) upstaging and overall survival (OS) outcomes among patients with clinically node negative (cN0) GC. PATIENTS AND METHODS: Patients diagnosed with cN0 GC undergoing surgery between 2004-2018 were identified in the National Cancer Database (NCDB) and divided into intervals between time of diagnosis and surgery [short interval (SI): ≥ 4 days to < 8 weeks and long interval (LI): ≥ 8 weeks]. Multivariable regression analysis evaluated the independent impact of surgical timing on LN upstaging and a Cox proportional hazards analysis and Kaplan-Meier curves evaluated survival outcomes. RESULTS: Of 1824 patients with cN0 GC, 71.8% had a SI to surgery and 28.1% had a LI to surgery. LN upstaging was seen more often in the SI group when compared to LI group (82% versus 76%, p = 0.004). LI to surgery showed to be an independent factor protective against LN upstaging [adjusted odds ratio = 0.62, 95% CI: (0.39-0.99)]. Multivariate Cox regression analysis indicated that time to surgery was not associated with a difference in overall survival [hazard ratio (HR) = 0.91, 95% CI: (0.71-1.17)], however uncontrolled Kaplan-Meier curves showed OS difference between the SI and LI to surgery groups (p = 0.037). CONCLUSION: Timing to surgery was not a predictor of LN upstaging or overall survival, suggesting that additional medical optimization in preparation for surgery and careful preoperative staging may be appropriate in patients with node negative early stage GC without affecting outcomes.

Underrepresentation of blind and deaf participants in the All of Us Research Program.

Blind and deaf individuals comprise large populations that often experience health disparities, with those from marginalized gender, racial, ethnic and low-socioeconomic communities commonly experiencing compounded health inequities. Including these populations in precision medicine research is critical for scientific benefits to accrue to them. We assessed representation of blind and deaf people in the All of Us Research Program (AoURP) 2018-2023 cohort of participants who provided electronic health records and compared it with the Centers for Disease Control and Prevention 2018 national estimates by key demographic characteristics and intersections thereof. Blind and deaf AoURP participants are considerably underrepresented in the cohort, especially among working-age adults (younger than age 65 years), as well as Asian and multi-racial participants. Analyses show compounded underrepresentation at the intersection of multiple marginalization (that is, racial or ethnic minoritized group, female sex, low education and low income), most substantively for working-age blind participants identifying as Black or African American female with education levels lower than high school (representing one-fifth of their national prevalence). Underrepresentation raises concerns about the generalizability of findings in studies that use these data and limited benefits for the already underserved blind and deaf populations.