Department of Intensive Care Unit, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, China.
Am J Trop Med Hyg. 2024 Sep 17;111(5):1027-1033. doi: 10.4269/ajtmh.23-0661. Print 2024 Nov 6.
High mortality rates are commonly found in critically ill patients with tuberculosis (TB), which is due partially to limitations in the existing prognostic evaluation methods. Therefore, we aimed to find more effective prognostic evaluation tools to reduce the mortality rate. Data from critically ill patients with TB admitted to the intensive care unit of The Second Hospital of Nanjing, Nanjing, China, between January 2020 and December 2022 were analyzed retrospectively. A total of 115 patients were enrolled and divided into a survival group (n = 62) and a death group (n = 53) according to 30-day survival. Univariate and least absolute shrinkage and selection operator (LASSO) regression analyses were used to investigate the risk factors for 30-day death in critically ill patients with TB. A prediction model for risk of 30-day mortality was developed for critically ill patients with TB in the intensive care unit. The LASSO regression model showed that the prognostic nutritional index (PNI) and Acute Physiology and Chronic Health Status (APACHE II) scores on the third day after admission to the intensive care unit were independent risk factors for 30-day mortality in critically ill patients with TB (P <0.05). The area under the curve value and that PA3 represents the combination of the PNI and APACHE II score on the third day, which was 0.952 (95% CI: 0.913-0.991, P <0.001), was significantly higher than that of the PNI or the APACHE II score on the third day. The new model is as follows: PA3 = APACHE II score (on the third day) × 0.421 - PNI × 0.204. The PNI combined with the APACHE II score on the third day could well predict the 30-day mortality risk of critically ill patients with TB.
高死亡率在患有结核病（TB）的重症患者中很常见，这部分是由于现有预后评估方法的局限性。因此，我们旨在寻找更有效的预后评估工具，以降低死亡率。回顾性分析了 2020 年 1 月至 2022 年 12 月期间在中国南京第二医院重症监护病房住院的重症 TB 患者的数据。共纳入 115 例患者，根据 30 天生存率分为存活组（n=62）和死亡组（n=53）。采用单因素和最小绝对收缩和选择算子（LASSO）回归分析探讨了重症 TB 患者 30 天死亡的危险因素。为重症监护病房的重症 TB 患者建立了 30 天死亡率风险预测模型。LASSO 回归模型显示，入住重症监护病房第 3 天的预后营养指数（PNI）和急性生理学和慢性健康状况评分（APACHE II）是重症 TB 患者 30 天死亡的独立危险因素（P<0.05）。曲线下面积值和 PA3 代表第 3 天 PNI 和 APACHE II 评分的组合，为 0.952（95%CI：0.913-0.991，P<0.001），明显高于第 3 天的 PNI 或 APACHE II 评分。新模型如下：PA3=APACHE II 评分（第 3 天）×0.421-PNI×0.204。第 3 天 PNI 与 APACHE II 评分相结合可很好地预测重症 TB 患者 30 天死亡率风险。
