ArticleEndocrinology, diabetes & metabolism2022
Real-world risk factors of confirmed or probable COVID-19 in Americans with diabetes: A prospective, community-based study (iNPHORM).
Article in Endocrinology, diabetes & metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04219514 (Investigating Novel Predictions of Hypoglycemia Occurrence in Real-world Models), which is not on this map. Cited by 3 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Investigating Novel Predictions of Hypoglycemia Occurrence in Real-world Models
Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Diabetes as a predictor of COVID-19 preventive behaviors.Frontiers in psychology · 2025Article
- Comorbidities increase COVID-19 hospitalization in young people with type 1 diabetes.Pediatric diabetes · 2022Article
- Real-world risk factors of confirmed or probable COVID-19 in Americans with diabetes: A prospective, community-based study (iNPHORM).Endocrinology, diabetes & metabolism · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAmericans with diabetes are clinically vulnerable to worse COVID-19 outcomes; thus, insight into how to prevent infection is imperative. Using longitudinal, prospective data from the real-world iNPHORM study, we identify the intrinsic and extrinsic risk factors of confirmed or probable COVID-19 in people with type 1 or 2 diabetes.
methodsThe iNPHORM study recruited 1206 Americans (18-90 years) with insulin- and/or secretagogue-treated type 1 or 2 diabetes from a probability-based internet panel. Online questionnaires (screener, baseline and 12 monthly follow-ups) assessed COVID-19 incidence and various plausible intrinsic and extrinsic factors. Multivariable Cox regression was used to model the rate of COVID-19 (confirmed or probable). Risk factors were selected using a repeated backwards-selection 'voting' procedure.
resultsA sub-sample of 817 iNPHORM participants (type 1 diabetes: 16.9%; age: 52.1 [SD: 14.2] years; female: 50.2%) was analysed between May 2020 and March 2021. During this period, 13.7% reported confirmed or probable COVID-19. Age, body mass index, number of chronic comorbidities, most recent A1C, past severe hypoglycaemia, and employment status were selected in our final model. Body mass index ≥30 kg/m
conclusionsThis is the first US-based epidemiologic investigation to characterize community-based COVID-19 susceptibility in diabetes. Our results reveal specific and promising avenues to prevent COVID-19 in this at-risk population. CLINICALTRIALS: gov Identifier: NCT04219514.
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