Department of Paediatric, Fuyang Cancer Hospital, Fuyang, Anhui, China.
Department of Cardiology, Hefei Second People's Hospital Affiliated to Bengbu Medical College, Hefei, Anhui, China.
Medicine (Baltimore). 2024 Jan 5;103(1):e36840. doi: 10.1097/MD.0000000000036840.
To investigate the influencing factors of in-hospital acute heart failure (AHF) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and to construct and validate a risk prediction nomogram model. Three Hundred Thirty patients with AECOPD admitted to our hospital from June 2020 to June 2023 were retrospectively analyzed as a training set for the construction of the model. Three Hundred Twenty-five AECOPD patients admitted to the Second People's Hospital of Hefei from 2006 to June 2023 were also collected as the validation set for the validation of the model. A nomogram model was constructed to predict the risk of nosocomial AHF in patients with AECOPD, and C-index and receiver operating characteristic curve were drawn to assess the predictive predictive efficacy of the model. Model fit was evaluated by Hosmer-Lemeshow test, calibration curve was drawn to evaluate the calibration of the model; decision curve was drawn to analyze the net benefit rate of this nomogram model. Multivariate logistic regression analysis indicated that body mass index, mmRC grade, neutrophils, lymphocytes, hemoglobin, creatinine, PO2, PCO2, and Homocysteine were independent risk factors for in-hospital AHF in patients with AECOPD. To construct a nomogram model for risk prediction of in-hospital AHF in patients with AECOPD. The C-index of the training set was 0.949 (95% CI: 0.91-0.961); the C-index of the validation set was 0.936 (95% CI: 0.911-0.961) suggesting good model discrimination. The receiver operating characteristic curve calculated area under curve for the training set was 0.949 (95% CI: 0.928-0.97); area under curve for the validation set was 0.936 (95% CI: 0.91-0.961) suggesting good model accuracy. The results of Hosmer-Lemeshoe goodness-of-fit test and calibration curve analysis showed that the calibration curve of this nomogram model was close to the ideal curve. The clinical decision curve also showed good clinical net benefit of the nomogram model. Body mass index, mmRC grade, neutrophils, lymphocytes, hemoglobin, creatinine, PO2, PCO2, and Homocysteine are risk factors for in-hospital AHF in AECOPD patients, and nomogram models constructed based on the above factors have some predictive value for in-hospital AHF in AECOPD patients. It is also vital for nursing staff to strengthen nursing care.
目的 探讨慢性阻塞性肺疾病急性加重（AECOPD）患者住院期间发生急性心力衰竭（AHF）的影响因素，并构建和验证风险预测列线图模型。
方法 回顾性分析 2020 年 6 月至 2023 年 6 月我院收治的 330 例 AECOPD 患者作为训练集，构建模型。收集 2006 年至 2023 年 6 月合肥市第二人民医院收治的 325 例 AECOPD 患者作为验证集，验证模型。建立预测 AECOPD 患者住院期间发生 AHF 风险的列线图模型，并通过 C 指数和受试者工作特征曲线评估模型的预测效果。通过 Hosmer-Lemeshow 检验评估模型拟合优度，绘制校准曲线评估模型的校准度；绘制决策曲线分析该列线图模型的净获益率。采用多因素 logistic 回归分析确定 AECOPD 患者住院期间发生 AHF 的独立危险因素，并构建预测模型。
结果 多因素 logistic 回归分析结果显示，体质量指数、改良呼吸困难量表（mmRC）分级、中性粒细胞、淋巴细胞、血红蛋白、肌酐、氧分压（PO2）、二氧化碳分压（PCO2）、同型半胱氨酸是 AECOPD 患者住院期间发生 AHF 的独立危险因素。构建预测 AECOPD 患者住院期间发生 AHF 的列线图模型。训练集的 C 指数为 0.949（95%CI：0.910.961），验证集的 C 指数为 0.936（95%CI：0.9110.961），提示模型具有良好的区分度。训练集受试者工作特征曲线下面积为 0.949（95%CI：0.9280.97），验证集受试者工作特征曲线下面积为 0.936（95%CI：0.910.961），提示模型具有良好的准确性。Hosmer-Lemeshow 拟合优度检验和校准曲线分析结果表明，该列线图模型的校准曲线与理想曲线较为接近。临床决策曲线分析也显示，该列线图模型具有较好的临床净获益。体质量指数、mmRC 分级、中性粒细胞、淋巴细胞、血红蛋白、肌酐、PO2、PCO2、同型半胱氨酸是 AECOPD 患者住院期间发生 AHF 的危险因素，基于上述因素构建的列线图模型对 AECOPD 患者住院期间发生 AHF 具有一定的预测价值，护理人员应加强护理。
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