College of Arts and Sciences, Emory University, Atlanta, GA, United States.
Rollins School of Public Health, Emory University, Atlanta, GA, United States.
JMIR Res Protoc. 2024 Jun 4;13:e54853. doi: 10.2196/54853.
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.
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.
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.
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.
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.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54853.
COVID-19 是一种传染病大流行，影响了全球数百万人，导致高发病率和死亡率。更令人担忧的是，相当一部分 COVID-19 幸存者仍在遭受 SARS-CoV-2（导致 COVID-19 的病原体）的挥之不去的健康影响。COVID-19 的后遗症之一是新发糖尿病（也称为“长 COVID”）。
本研究旨在检查长 COVID 患者新发糖尿病的发病率，并评估与 COVID-19 检测阴性个体相比的超额风险。该研究还旨在估计 COVID-19 作为长 COVID 新发糖尿病的危险因素的人群归因分数，并调查新发糖尿病病例的临床过程。
这是一项系统评价和荟萃分析的方案。将系统检索 PubMed、MEDLINE、Embase、Scopus 和 Web of Science 数据库，以确定 2019 年 12 月至 2024 年 7 月期间发表的文章。将为每个数据库制定全面的搜索策略，使用医学主题词、主题词和文本词的组合来确定合格的研究。将纳入涉及任何年龄 COVID-19 患者的队列研究和随机对照试验（仅对照臂），并随访长 COVID 中的新发糖尿病数据。对照组将包括 COVID-19 检测阴性的个体，无论是否有其他呼吸道感染。三名独立的审稿人（AST、NB 和 TT）将进行文章选择、数据提取和研究质量评估。第四名审稿人（ST）将审查已确定的研究，以最终纳入分析。将使用随机效应 DerSimonian-Laird 模型估计新发糖尿病的总发病率（%）、糖尿病发病率（每 1000 人年）和糖尿病发病率的风险比（95%CI）。
通过 2023 年 8 月进行的初步搜索共确定了 1972 篇文章。排除重复项后，进行标题和摘要筛选，并完成全文审查，共发现 41 篇文章符合纳入标准。搜索将于 2024 年 7 月更新。目前正在进行数据提取，预计 2024 年 8 月完成荟萃分析。预计 2024 年底公布研究结果。
研究结果应该为有效管理长 COVID 患者的新发糖尿病提供有价值的信息，以指导临床实践和公共卫生政策。
国际注册报告标识符（IRRID）：DERR1-10.2196/54853。
