Evidence mapPaperPMID 39015182Full record

ArticleFrontiers in endocrinology2024

A moderately higher time-in-range threshold improves the prognosis of type 2 diabetes patients complicated with COVID-19.

Riping Cong, Jianbo Zhang, Lujia Xu, Yujian Zhang, Hao Wang, Jing Wang, Wei Wang, Yingli Diao, Haijiao Liu, Jing Zhang and 1 more

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Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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11 authors.

Riping Cong *Department of General Practice, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Jianbo Zhang *Department of General Practice, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Lujia Xu *Department of General Practice, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Yujian ZhangDepartment of General Practice, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Hao WangDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Jing WangDepartment of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Wei WangDepartment of General Practice, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Yingli DiaoDepartment of General Practice, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Haijiao LiuDepartment of Internal Medicine, Jinan Hospital, Jinan, Shandong, China.
Jing ZhangDepartment of Endocrinology, Lanling County Traditional Chinese Medicine Hospital, Linyi, Shandong, China.
Kuanxiao TangDepartment of General Practice, Qilu Hospital of Shandong University, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: After fully lifting coronavirus disease 2019 (COVID-19) pandemic control measures in mainland China in 12/2022, the incidence of COVID-19 has increased markedly, making it difficult to meet the general time-in-range (TIR) requirement. We investigated a more clinically practical TIR threshold and examined its association with the prognosis of COVID-19 patients with type 2 diabetes(T2D). Research design and methods: 63 T2D patients complicated with COVID-19 were evaluated. Patients were divided into favorable outcome group and adverse outcome group according to whether achieving composite endpoint (a >20-day length of stay, intensive care unit admission, mechanical ventilation use, or death). TIR, the time-below-range (TBR) and the time-above-range (TAR) were calculated from intermittently scanned continuous glucose monitoring. Logistic regression analysis and other statistical methods were used to analyze the correlation between glucose variability and prognosis to establish the appropriate reference range of TIR. Results: TIR with thresholds of 80 to 190 mg/dL was significantly associated with favorable outcomes. An increase of 1% in TIR is connected with a reduction of 3.70% in the risk of adverse outcomes. The Youden index was highest when the TIR was 54.73%, and the sensitivity and specificity were 58.30% and 77.80%, respectively. After accounting for confounding variables, our analysis revealed that threshold target ranges (TARs) ranging from 200 mg/dL to 230 mg/dL significantly augmented the likelihood of adverse outcomes. Conclusion: The TIR threshold of 80 to 190 mg/dL has a comparatively high predictive value of the prognosis of COVID-19. TIR >54.73% was associated with a decreased risk of adverse outcomes. These findings provide clinically critical insights into possible avenues to improve outcomes for COVID-19 patients with T2D.

Indexed as

COVID-19Diabetes Mellitus, Type 2AgedBlood GlucoseChinaFemaleHumansMaleMiddle AgedPrognosisReference ValuesRetrospective StudiesSARS-CoV-2Time FactorsBlood Glucosecontinuous glucose monitoringCOVID-19glucose variabilitytime-in-rangetype 2 diabetes

Identifiers

PMID39015182
PMCPMC11250251

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.