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

识别影响因素并构建血液透析患者长期新冠肺炎的预测模型

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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.

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