To explore the risk factors of pulmonary infection in patients with acute intracerebral hemorrhage based on nomogram prediction model
10.3760/cma.j.cn115455-20220518-00458
- VernacularTitle:基于列线图预测模型探讨急性脑出血患者并发肺部感染的危险因素
- Author:
Wenbing ZHANG
1
;
Jiawei XU
;
Hong WEI
Author Information
1. 安徽医科大学附属六安医院急诊医学科急诊内科，六安 237005
- Keywords:
Nomogram;
Cerebral hemorrhage;
Pulmonary infection;
Risk factors
- From:
Chinese Journal of Postgraduates of Medicine
2023;46(9):774-779
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the risk factors of pulmonary infection in patients with acute intracerebral hemorrhage based on nomogram prediction model.Methods:The clinical data of 235 patients with acute intracerebral hemorrhage admitted to Lu′an Hospital of Anhui Medical University from June 2018 to December 2021 were retrospectively analyzed. According to whether the patients were complicated with pulmonary infection, they were divided into pulmonary infection group (55 cases) and non-pulmonary infection group (180 cases). The best cut-off value of each factor was obtained through the receiver operating characteristic (ROC) curve analysis of all patients. Multivariate Cox regression analysis was used to analyze the independent risk factors of pulmonary infection in patients with acute intracerebral hemorrhage. The R software "rms" package was constructed to predict pulmonary infection in patients with acute intracerebral hemorrhage. For high-risk nomogram model, calibration curves were used for internal validation of the nomogram model, and decision curves were used to assess the predictive power of the nomogram model.Results:Patients in the pulmonary infection group were with higher age, proportion of smoking, proportion of brain ventricle bleeding, bleeding volume, length of stay, Glasgow coma scale (GCS) score, white blood cell count (WBC) and interleukin-6 (IL-6) than in the non-pulmonary infection group: (78.65 ± 5.33) years old vs. (65.41 ± 4.55) years old, 67.27% (37/55) vs. 48.89% (88/180), 49.09% (27/55) vs. 7.22% (13/180), (26.47 ± 1.41) ml vs. (18.24 ± 0.47) ml, (15.65 ± 2.49) d vs. (10.16 ± 1.64) d, (13.74 ± 1.48) points vs. (7.81 ± 1.09) points, (16.50 ± 2.40) × 10 9/L vs. (9.10 ± 2.35) × 10 9/L, (82.50 ± 21.80) ng/L vs. (57.90 ± 11.50) ng/L, with statistically significant differences ( P<0.05); the AUCs of age, bleeding volume, hospital stay, GCS score, WBC, and IL-6 were 0.743, 0.886, 0.771, 0.800, 0.829 and 0.557, respectively; the best cut-off values were 69 years old, 20 ml, 12 d, and 10 scores, 13 × 10 9/L, 66 ng/L, respectively; age (≥69 years old), smoking (yes), bleeding site (brain ventricle), bleeding volume (≥20 ml), hospital stay (≥12 d) and GCS score (<10 points) were independent risk factors for pulmonary infection in patients with acute intracerebral hemorrhage ( P<0.05); the decision curve results showed that when the risk threshold was greater than 0.15, the clinical net benefit provided by this predictive model was higher than that by a single independent risk factor, and in predicting the high risk of pulmonary infection in patients with acute intracerebral hemorrhage this predictive model could provide a significant additional net clinical benefit. Conclusions:This study constructed a nomogram model for predicting the risk of pulmonary infection in patients with acute intracerebral hemorrhage based on age, smoking history, bleeding site, bleeding volume, hospital stay and GCS score. It could provide important strategic guidance for prevention and control of this disease.
