| 奈玛特韦片/利托那韦片治疗COVID-19早期预后不良的危险因素及预测模型构建 |
| 投稿时间：2023-03-28 修订日期：2023-10-07 点此下载全文 |
| 引用本文：黄文辉,许燕玉,郝晓伟,林冠,欧阳山丹,王佳坤,陈锦珊.奈玛特韦片/利托那韦片治疗COVID-19早期预后不良的危险因素及预测模型构建[J].药学实践杂志,2023,41(11):700~704 |
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| 中文摘要:目的 探讨奈玛特韦片/利托那韦片（Paxlovid）对新型冠状病毒肺炎（COVID-19）患者早期预后不良的危险因素并构建预测模型，以期为提高该类患者的救治效果提供参考。方法 回顾性分析2023年1月至2023年3月于闽南地区3家军队三甲医院使用Paxlovid治疗的COVID-19住院患者92例，收集临床指标进行单因素和多因素分析，筛选出Paxlovid早期预后不良的独立危险因素，对Logistic模型方程进行转换建立联合预测因子，采用ROC曲线确定联合预测因子的曲线下面积（AUC）及最佳临界值。结果 92例患者中，早期预后不良者31例（33.70%），其中，死亡11例（35.48%），危重型17例（54.84%），重型3例（9.68%）。多因素Logistic回归分析结果显示，发病天数、淋巴细胞计数、天门冬氨酸氨基转移酶（AST）、C反应蛋白（CRP）和联合呼吸机辅助通气是使用Paxlovid早期预后不良的独立危险因素。以上述独立危险因素构建联合预测因子（Y）的计算公式，Y联合预测因子=7.875X发病天数+126.188X淋巴细胞计数+1.438XAST+XCRP+220.500X联合呼吸机辅助通气，绘制ROC曲线，联合预测因子的ROC曲线下面积最大为0.939，预测价值最优，约登指数（Youden）最大时（0.756）对应ROC曲线最佳临界值为447.920，模型的理论准确度为89.10%。结论 发病天数、淋巴细胞计数、AST、CRP和联合呼吸机辅助通气是使用Paxlovid早期预后不良的独立危险因素，用药前可通过上述各危险因素计算联合预测因子，当预测结果大于447.920时，应采取更积极的治疗措施包括联合其他抗COVID-19药物等，以提高患者的救治效果。 |
| 中文关键词:奈玛特韦/利托那韦 新冠病毒感染 预后不良 危险因素 预测模型 |
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| Risk factors of poor early prognosis in the treatment of COVID-19 with nematevir and ritonavir tablets and the establishment of prediction model |
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| Abstract:Objective To explore risk factors of poor early prognosis in the treatment of COVID-19 by nematevir and ritonavir tablets Paxlovid and establish the prediction model to provide reference for improving the effect of such patients. Methods 92 inpatients of COVID-19 treated with Paxlovid in three military tertiary hospital in southern Fujian from January 2023 to March 2023 were retrospectively analyzed. The clinical indicators of 92 inpatients were collected for univariate and multivariate analysis by single factor and multiple factors and the independent risk factors of poor early prognosis in Paxlovid were screened out. Logistic model equation was transformed to construct the combined predictors, and ROC curve was used to determine the area under the curve (AUC) and the optimal critical value of the combined predictors. Results Among 92 patients, 31 (33.70%) developed poor early prognosis, including 11 deaths (35.48%), 17 critical cases (54.84%) and 3 severe cases (9.68%). Multi-factor Logistic regression analysis showed that the disease days, lymphocyte count, aspartate aminotransferase(AST), C reactive protein(CRP) and ventilator-assisted ventilation were independent risk factors for poor early prognosis in Paxlovid. A formula for calculating the combined predictors (Y) was established as Ycombinedpredictors=7.875Xdisease days+126.188Xlymphocyte count+1.438XAST+XCRP+220.500Xventilator-assisted ventilation based on the above independent risk factors, and the ROC curve was drawn. With the maximum area under the ROC curve of the combined predictors being 0.939, the prediction value was best, and the optimal critical value of the ROC curve corresponding to the maximum Youden index (0.756) was 447.920.Theoretical accuracy of the model was 89.10%.Conclusion The disease days, lymphocyte count, AST, CRP and ventilator-assisted ventilation were independent risk factors for poor early prognosis in Paxlovid. Combined predictors could be calculated by the above risk factors before medication. The efficiency should be improved by taking more active treatment, including combining with other anti-COVID-19 drugs when the prediction result exceeds 447.920. |
| keywords:Naimatwe/Litonavir COVID-19 poor prognosis risk factor prediction model |
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