Incidence, Risk, and Clinical Course of New-Onset Diabetes in Long COVID: Protocol for a Systematic Review and Meta-Analysis of Cohort Studies

• Type of Material: Article
• Authors: Ananya Talanki, Emory University; Neha Bajaj, Emory University; Twinkle Trehan, Emory University; Sathish Thirunavukkarasu, Emory University
• Language: English
• Date: 2024
• Publisher: JMIR
• Publication Version: Final Published Version
• Copyright Statement: ©Ananya Sri Talanki, Neha Bajaj, Twinkle Trehan, Sathish Thirunavukkarasu. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 04.06.2024.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): https://doi.org/10.2196%2F54853
• Title of Journal or Parent Work: JMIR Research Protocols
• Volume: 13
• Start Page: e54853
• Grant/Funding Information: This research was funded by the 2023 Emory Global Health Initiative (EGHI) Field Scholars Award Program, Emory University, Atlanta, United States. The article processing charge for this publication was covered by Emory’s Open Access Publication Fund. The funder had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the paper.
• Keywords: SARS-CoV-2; type 2 diabetes; cohort studies; long COVID; postacute sequela; incidence; new-onset diabetes; meta-analysis; type 1 diabetes; COVID-19; systematic review
• Research Categories: Statistics; Biology, Virology; Health Sciences, Public Health

Abstract

Background COVID-19, an infectious disease pandemic, affected millions of people globally, resulting in high morbidity and mortality. Causing further concern, significant proportions of COVID-19 survivors endure the lingering health effects of SARS-CoV-2, the pathogen that causes COVID-19. One of the diseases manifesting as a postacute sequela of COVID-19 (also known as “long COVID”) is new-onset diabetes. Objective The aim of this study is to examine the incidence of new-onset diabetes in patients with long COVID and assess the excess risk compared with individuals who tested negative for COVID-19. The study also aims to estimate the population-attributable fraction for COVID-19 as a risk factor for new-onset diabetes in long COVID and investigate the clinical course of new-onset diabetes cases. Methods This is a protocol for a systematic review and meta-analysis. PubMed, MEDLINE, Embase, Scopus, and Web of Science databases will be systematically searched to identify articles published between December 2019 and July 2024. A comprehensive search strategy for each database will be developed using a combination of Medical Subject Headings terms, subject headings, and text words to identify eligible studies. Cohort studies and randomized controlled trials (only control arms) involving patients with COVID-19 of any age, with follow-up data on new-onset diabetes in long COVID, will be considered for inclusion. Controls will comprise individuals who tested negative for COVID-19, with or without other respiratory tract infections. Three independent reviewers (AST, NB, and TT) will perform article selection, data extraction, and quality assessment of the studies. A fourth reviewer (ST) will review the identified studies for final inclusion in the analysis. The random-effects DerSimonian-Laird models will be used to estimate the pooled incidence proportion (%), incidence rate of diabetes (per 1000 person-years), and risk ratio (with 95% CIs) for diabetes incidence. Results A total of 1972 articles were identified through the initial search conducted in August 2023. After excluding duplicates, conducting title and abstract screening, and completing full-text reviews, 41 articles were found to be eligible for inclusion. The search will be updated in July 2024. Currently, data extraction is underway, and the meta-analysis is expected to be completed in August 2024. Publication of the study findings is anticipated by the end of 2024. Conclusions The study findings should provide valuable insights to inform both clinical practice and public health policies regarding the effective management of new-onset diabetes in patients with long COVID.