Wong, Jenise C

Sharing research code in an open access version-controlled repository offers significant benefits for both science as a whole and for individual researchers. In this article, we focus on this practice, which is fully aligned with the NIH’s Gold Standard Science (GSS) program as well as FAIR (findable, accessible, interoperable, reusable) and TRUST (transparency, responsibility, user focus, sustainability, technology) principles. Gold Standard Science supports open science by emphasizing transparency, reproducibility, and the use of best practices that enable others to verify and extend research. Pairing a research article’s cited data snapshot with a versioned, environment-specific code release, deposited in a companion code repository, ensures that, upon submission to a medical journal, readers and reviewers can directly verify results. An executable and updatable companion code repository complements, rather than replaces, established research data repositories. When code underlying medical research results is made openly available, then other scientists can inspect, run, and validate analyses. These activities enhance reproducibility, which is a core aim of GSS. Shared code also facilitates collaborative innovation by allowing researchers to extend the utility of the code to new datasets and applications. For researchers, code sharing can increase visibility, credibility, and citation impact. Demonstrating transparency through shared executable and updatable code builds trust with journal readers, peer reviewers, funders, and peers. Shared code in an open access repository signals adherence to high standards of scientific integrity and attracts opportunities for collaboration. A researcher who shares code receives recognition as a leader in reproducible, trustworthy research consistent with NIH’s GSS principles.

AbstractBackgroundDiabetes is a risk factor for poor COVID‐19 outcomes, but pediatric patients with type 1 diabetes are poorly represented in current studies.MethodsT1D Exchange coordinated a US type 1 diabetes COVID‐19 registry. Forty‐six diabetes centers submitted pediatric cases for patients with laboratory confirmed COVID‐19. Associations between clinical factors and hospitalization were tested with Fisher's Exact Test. Logistic regression was used to calculate odds ratios for hospitalization.ResultsData from 266 patients with previously established type 1 diabetes aged <19 years with COVID‐19 were reported. Diabetic ketoacidosis (DKA) was the most common adverse outcome (n = 44, 72% of hospitalized patients). There were four hospitalizations for severe hypoglycemia, three hospitalizations requiring respiratory support (one of whom was intubated and mechanically ventilated), one case of multisystem inflammatory syndrome in children, and 10 patients who were hospitalized for reasons unrelated to COVID‐19 or diabetes. Hospitalized patients (n = 61) were more likely than nonhospitalized patients (n = 205) to have minority race/ethnicity (67% vs 39%, P < 0.001), public insurance (64% vs 41%, P < 0.001), higher A1c (11% [97 mmol/mol] vs 8.2% [66 mmol/mol], P < 0.001), and lower insulin pump and lower continuous glucose monitoring use (26% vs 54%, P < 0.001; 39% vs 75%, P < 0.001). Age and gender were not associated with risk of hospitalization. Higher A1c was significantly associated with hospitalization, with an odds ratio of 1.56 (1.34‐1.84) after adjusting for age, gender, insurance, and race/ethnicity.ConclusionsHigher A1c remained the only predictor for hospitalization with COVID‐19. Diabetic ketoacidosis is the primary concern among this group.