Identifying influencing factors and constructing a prediction model for long COVID-19 in hemodialysis patients.

IF 1.8 4区 医学 Q3 UROLOGY & NEPHROLOGY
Ding Chen, Xinlun Li, Chang Xiao, Wangyan Xiao, Linjing Lou, Zhuo Gao
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引用次数: 0

Abstract

Purpose: This study aimed to identify the potential influencing factors and construct a prediction model for long COVID in hemodialysis patients.

Methods: We retrospectively reviewed 115 patients undergoing hemodialysis in a tertiary hospital between December 2022 and January 2023. Both univariate and multivariate logistic regression models were applied to identify potential influencing factors, and the prediction model was constructed using an ROC curve.

Results: Of the 115 included patients, 60 experienced long COVID, with a prevalence of 52.2%. The univariate analysis found that a three-dose COVID-19 vaccination was associated with a reduced risk of long COVID (OR: 0.10; 95%CI: 0.01-0.86; P = 0.036). However, severe COVID (OR: 9.49; 95%CI: 1.14-78.90; P = 0.037), undergoing CT examination (OR: 3.01; 95%CI: 1.34-6.78; P = 0.008), and abnormal neutrophil (OR: 5.95; 95%CI: 1.26-28.19; P = 0.025), and platelet (OR: 2.39; 95%CI: 1.11-5.13; P = 0.025) counts were associated with a higher risk of long COVID. After adjusting for potential confounding factors, undergoing CT examination (OR: 2.60; 95%CI: 1.02-6.64; P = 0.046) and having abnormal neutrophil (OR: 8.16; 95%CI: 1.57-42.38; P = 0.013) and monocyte (OR: 17.77; 95%CI: 1.30-242.29; P = 0.031) counts were associated with a higher risk of long COVID. The prediction model constructed based on these factors showed a relatively better predictive value (AUC: 0.738; 95%CI: 0.648-0.828; P < 0.001).

Conclusions: The risk of long COVID-19 in hemodialysis patients was significantly related to undergoing CT examination and having abnormal neutrophil and monocyte counts, and the prediction model constructed using these factors showed a moderate predictive value.

确定血液透析患者长 COVID-19 的影响因素并构建预测模型。
目的:本研究旨在确定血液透析患者长COVID的潜在影响因素并构建预测模型:我们回顾性研究了 2022 年 12 月至 2023 年 1 月期间在一家三级医院接受血液透析的 115 例患者。应用单变量和多变量逻辑回归模型确定潜在的影响因素,并利用 ROC 曲线构建预测模型:结果:在纳入的 115 名患者中,有 60 人经历了长时间的 COVID,患病率为 52.2%。单变量分析发现,接种三剂 COVID-19 疫苗与长 COVID 风险降低相关(OR:0.10;95%CI:0.01-0.86;P = 0.036)。然而,重度 COVID(OR:9.49;95%CI:1.14-78.90;P = 0.037)、接受 CT 检查(OR:3.01;95%CI:1.34-6.78;P = 0.008)和中性粒细胞异常(OR:5.95;95%CI:1.26-28.19;P = 0.025)和血小板(OR:2.39;95%CI:1.11-5.13;P = 0.025)计数与较高的长COVID风险相关。调整潜在混杂因素后,接受 CT 检查(OR:2.60;95%CI:1.02-6.64;P = 0.046)和中性粒细胞(OR:8.16;95%CI:1.57-42.38;P = 0.013)和单核细胞(OR:17.77;95%CI:1.30-242.29;P = 0.031)计数异常与长 COVID 风险较高相关。根据这些因素构建的预测模型显示出相对较好的预测价值(AUC:0.738;95%CI:0.648-0.828;P 结论:血液透析患者发生长COVID-19的风险与接受CT检查以及中性粒细胞和单核细胞计数异常显著相关,利用这些因素构建的预测模型显示出中等预测价值。
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来源期刊
International Urology and Nephrology
International Urology and Nephrology 医学-泌尿学与肾脏学
CiteScore
3.40
自引率
5.00%
发文量
329
审稿时长
1.7 months
期刊介绍: International Urology and Nephrology publishes original papers on a broad range of topics in urology, nephrology and andrology. The journal integrates papers originating from clinical practice.
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