Risk factors of poor early prognosis in the treatment of COVID-19 with nematevir and ritonavir tablets and the establishment of prediction model
10.12206/j.issn.2097-2024.202303038
- VernacularTitle: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
- Author:
Wenhui HUANG
1
;
Yanyu XU
2
;
Xiaowei HAO
3
;
Guan LIN
2
;
Shandan OUYANG
3
;
Jiakun WANG
2
;
Jinshan CHEN
1
Author Information
1. Department of Pharmacy, The 909th Hospital/ Dongnan Hospital of Xiamen University, Zhangzhou 363000, China.
2. Department of Pharmacy, The 910th Hospital, Quanzhou 362000, China.
3. Department of Pharmacy, Army 73rd Group Military Hospital of PLA, Xiamen 361001, China.
- Keywords:
Naimatwe/Litonavir;
COVID-19;
poor prognosis;
risk factor;
prediction model
- From:
Journal of Pharmaceutical Practice
2023;41(11):700-704
- CountryChina
- Language:Chinese
-
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.
