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揭示2型糖尿病患者发生新冠后综合征的风险因素。

Unveiling risk factors for post-COVID-19 syndrome development in people with type 2 diabetes.

作者信息

Matviichuk Anton, Yerokhovych Viktoriia, Zemskov Sergii, Ilkiv Yeva, Gurianov Vitalii, Shaienko Zlatoslava, Falalyeyeva Tetyana, Sulaieva Oksana, Kobyliak Nazarii

机构信息

Department of Endocrinology, Bogomolets National Medical University, Kyiv, Ukraine.

Department of Endocrinology with Pediatric Infectious Diseases, Poltava State Medical University, Poltava, Ukraine.

出版信息

Front Endocrinol (Lausanne). 2024 Dec 11;15:1459171. doi: 10.3389/fendo.2024.1459171. eCollection 2024.

Abstract

INTRODUCTION

Post-COVID-19 syndrome (PCS) is a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-associated chronic condition characterized by long-term violations of physical and mental health. People with type 2 diabetes (T2D) are at high risk for severe COVID-19 and PCS.

AIM

The current study aimed to define the predictors of PCS development in people with T2D for further planning of preventive measures and improving patient outcomes.

MATERIALS AND METHODS

The data were collected through the national survey targeting persons with T2D concerning the history of COVID-19 course and signs and symptoms that developed during or after COVID-19 and continued for more than 12 weeks and were not explained by an alternative diagnosis. In total, 469 patients from different regions of Ukraine were enrolled in the study. Among them, 227 patients reported PCS development (main group), while 242 patients did not claim PCS symptoms (comparison group). Stepwise multivariate logistic regression and probabilistic neural network (PNN) models were used to select independent risk factors.

RESULTS

Based on the survey data, 8 independent factors associated with the risk of PCS development in T2D patients were selected: newly diagnosed T2D (OR 4.86; 95% CI 2.55-9.28; p<0.001), female sex (OR 1.29; 95% CI 0.86-1.94; p=0.220), COVID-19 severity (OR 1.35 95% CI 1.05-1.70; p=0.018), myocardial infarction (OR 2.42 95% CI 1.26-4.64; p=0.002) and stroke (OR 3.68 95% CI 1.70-7.96; p=0.001) in anamnesis, HbA1c above 9.2% (OR 2.17 95% CI 1.37-3.43; p=0.001), and the use of insulin analogs (OR 2.28 95% CI 1.31-3.94; p=0.003) vs human insulin (OR 0.67 95% CI 0.39-1.15; p=0.146). Although obesity aggravated COVID-19 severity, it did not impact PCS development. In ROC analysis, the 8-factor multilayer perceptron (MLP) model exhibited better performance (AUC 0.808; 95% CІ 0.770-0.843), allowing the prediction of the risk of PCS development with a sensitivity of 71.4%, specificity of 76%, PPV of 73.6% and NPV of 73.9%.

CONCLUSIONS

Patients who were newly diagnosed with T2D, had HbA1c above 9.2%, had previous cardiovascular or cerebrovascular events, and had severe COVID-19 associated with mechanical lung ventilation were at high risk for PCS.

摘要

引言

新冠后综合征(PCS)是一种与严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染相关的慢性疾病,其特征是长期存在身心健康问题。2型糖尿病(T2D)患者患重症新冠和PCS的风险较高。

目的

本研究旨在确定T2D患者发生PCS的预测因素,以便进一步规划预防措施并改善患者预后。

材料与方法

通过针对T2D患者的全国性调查收集数据,内容涉及新冠病程、新冠期间或之后出现且持续超过12周且无法用其他诊断解释的体征和症状。乌克兰不同地区的469名患者参与了本研究。其中,227名患者报告发生了PCS(主要组),而另外242名患者未出现PCS症状(对照组)。采用逐步多因素逻辑回归和概率神经网络(PNN)模型来选择独立危险因素。

结果

根据调查数据,确定了与T2D患者发生PCS风险相关的8个独立因素:新诊断的T2D(比值比4.86;95%置信区间2.55 - 9.28;p<0.001)、女性(比值比1.29;95%置信区间0.86 - 1.94;p = 0.220)、新冠严重程度(比值比1.35,95%置信区间1.05 - 1.70;p = 0.018)、既往有心肌梗死(比值比2.42,95%置信区间1.26 - 4.64;p = 0.002)和中风(比值比3.68,95%置信区间1.70 - 7.96;p = 0.001)、糖化血红蛋白高于9.2%(比值比2.17,95%置信区间1.37 - 3.43;p = 0.001)以及使用胰岛素类似物(比值比2.28,95%置信区间1.31 - 3.94;p = 0.003)与使用人胰岛素(比值比0.67,95%置信区间0.39 - 1.15;p = 0.146)相比。尽管肥胖会加重新冠严重程度,但对PCS的发生没有影响。在ROC分析中,8因素多层感知器(MLP)模型表现更佳(曲线下面积0.808;95%置信区间0.770 - 0.843),预测PCS发生风险的敏感度为71.4%,特异度为76%,阳性预测值为73.6%,阴性预测值为73.9%。

结论

新诊断为T2D、糖化血红蛋白高于9.2%、既往有心血管或脑血管事件且患有与机械通气相关的重症新冠的患者发生PCS的风险较高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57ed/11668646/3698c47d6325/fendo-15-1459171-g001.jpg

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