目的 探讨影响肺炎克雷伯菌血流感染患者预后的危险因素，并构建预测模型。 方法 回顾性分析秦皇岛市第一医院2020年1月至2022年12月234例肺炎克雷伯菌血流感染患者的临床资料，将2020年1月至2022年6月收治的患者作为模型组(n＝202)，2022年7至12月收治的患者作为验证组(n＝32)，根据肺炎克雷伯菌血流感染28 d预后情况将模型组分为死亡组(n＝64)和存活组(n＝138)，采用Logistic回归对肺炎克雷伯菌血流感染死亡的危险因素进行分析，并建立死亡风险预测模型，再将模型应用于验证组，比较模型预测结果与实际情况的符合度。 结果 多因素Logistic回归分析提示，男性(OR＝2。598，95%CI 1。179~5。725，P＝0。018)、年龄≥65岁(OR＝4。420，95%CI 2。029~9。627，P<0。001)、入住重症监护病房(OR＝10。299，95%CI 4。752~22。321，P<0。001)、经验性使用喹诺酮类抗菌药物(OR＝4。288，95%CI 1。127~16。317，P＝0。033)是肺炎克雷伯菌血流感染患者28 d死亡的独立危险因素。肺炎克雷伯菌死亡风险预测模型回归方程＝－3。469+男性×0。955+年龄≥65岁×1。486+入住重症监护病房×2。332+经验性使用喹诺酮类抗菌药物×1。456，该模型预测模型组死亡的受试者工作特征曲线的曲线下面积(AUC)为0。831，敏感度和特异度分别为71。9%和80。4%；预测验证组死亡的AUC为0。881，敏感度和特异度分别为91。7%和75。0%。 结论 基于男性、年龄≥65岁、入住重症监护病房，以及经验性使用喹诺酮类抗菌药物构建的预测模型对肺炎克雷伯菌血流感染患者预后具有较好的预测价值。 Objective To explore the risk factors of mortality in patients with Klebsiella pneumoniae bloodstream infection， and to construct a predictive model。 Methods The clinical data of 234 patients with Klebsiella pneumoniae bloodstream infection admitted in the First Hospital of Qinhuangdao from January 2020 to December 2022 were retrospectively analyzed， including 202 cases admitted during January 2020 to June 2022 (model set)， and 32 cases admitted during July to December 2022 (validation set)。 There were 64 cases died (fatal group) and 138 cases survived (survival group) within 28 d after admission in model set。 Multivariate Logistic regression was used to analyze the risk factors of death in patients with Klebsiella pneumoniae bloodstream infection and a mortality prediction model was constructed。 The constructed model was applied in validation set， and the consistency between predicted mortality and real mortality was analyzed。 Results Multivariate Logistic regression analysis showed that male sex (OR=2。598， 95%CI 1。179-5。725， P=0。018)， age≥65 years (OR=4。420， 95%CI 2。029-9。627， P<0。001)， admitted to intensive care unit (ICU) (OR=10。299， 95%CI 4。752-22。321， P<0。001)， and the empirical use of quinolones antibiotics (OR=4。288， 95%CI 1。127-16。317， P=0。033) were independent risk factors for 28-day mortality in Klebsiella pneumoniae bloodstream infection patients。 The regression equation for predicting the risk of death was -3。469+ male × 0。955+ age ≥ 65 years × 1。486+ admitted to ICU × 2。332+ empirical use of quinolone antibiotics × 1。456。 The area under the ROC curve (AUC) for predicting death in the model set was 0。831， with sensitivity and specificity of 71。9% and 80。4%， respectively。 The AUC for predicting death in the validation set was 0。881， with sensitivity and specificity of 91。7% and 75。0%， respectively。 Conclusion The constructed mortality prediction model in the study has good application value for the prognosis of patients with Klebsiella pneumoniae bloodstream infection。
Risk factors of mortality inKlebsiella pneumoniae bloodstream infection and construction of a prediction model for prognosis of patients
Objective To explore the risk factors of mortality in patients with Klebsiella pneumoniae bloodstream infection, and to construct a predictive model. Methods The clinical data of 234 patients with Klebsiella pneumoniae bloodstream infection admitted in the First Hospital of Qinhuangdao from January 2020 to December 2022 were retrospectively analyzed, including 202 cases admitted during January 2020 to June 2022 (model set), and 32 cases admitted during July to December 2022 (validation set). There were 64 cases died (fatal group) and 138 cases survived (survival group) within 28 d after admission in model set. Multivariate Logistic regression was used to analyze the risk factors of death in patients with Klebsiella pneumoniae bloodstream infection and a mortality prediction model was constructed. The constructed model was applied in validation set, and the consistency between predicted mortality and real mortality was analyzed. Results Multivariate Logistic regression analysis showed that male sex (OR=2.598, 95%CI 1.179-5.725, P=0.018), age≥65 years (OR=4.420, 95%CI 2.029-9.627, P<0.001), admitted to intensive care unit (ICU) (OR=10.299, 95%CI 4.752-22.321, P<0.001), and the empirical use of quinolones antibiotics (OR=4.288, 95%CI 1.127-16.317, P=0.033) were independent risk factors for 28-day mortality in Klebsiella pneumoniae bloodstream infection patients. The regression equation for predicting the risk of death was -3.469+ male × 0.955+ age ≥ 65 years × 1.486+ admitted to ICU × 2.332+ empirical use of quinolone antibiotics × 1.456. The area under the ROC curve (AUC) for predicting death in the model set was 0.831, with sensitivity and specificity of 71.9% and 80.4%, respectively. The AUC for predicting death in the validation set was 0.881, with sensitivity and specificity of 91.7% and 75.0%, respectively. Conclusion The constructed mortality prediction model in the study has good application value for the prognosis of patients with Klebsiella pneumoniae bloodstream infection.
Klebsiella pneumoniaeBloodstream infectionRisk factorsRisk prediction model
万方数据
