Xu Cheng-Bin, Su Shan-Shan, Yu Jia, Lei Xiong, Lin Peng-Cheng, Wu Qing, Zhou Ying, Li Yu-Ping
The Key Laboratory of Interventional Pulmonology of Zhejiang Province, Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, South Baixiang, Ouhai District, Wenzhou, Zhejiang Province, 325015, People's Republic of China.
The Center of Laboratory and Diagnosis, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, 325015, People's Republic of China.
BMC Pulm Med. 2024 Jan 27;24(1):57. doi: 10.1186/s12890-023-02813-w.
Currently, there remains insufficient focus on non-severe community-acquired pneumonia (CAP) patients who are at risk of clinical deterioration, and there is also a dearth of research on the related risk factors. Early recognition of hospitalized patients at risk of clinical deterioration will be beneficial for their clinical management.
A retrospective study was conducted in The First Affiliated Hospital of Wenzhou Medical University, China, spanning from January 1, 2018 to April 30, 2022, and involving a total of 1,632 non-severe CAP patients. Based on whether their condition worsened within 72 h of admission, patients were divided into a clinical deterioration group and a non-clinical deterioration group. Additionally, all patients were randomly assigned to a training set containing 75% of patients and a validation set containing 25% of patients. In the training set, risk factors for clinical deterioration in patients with non-severe CAP were identified by using LASSO regression analysis and multivariate logistic regression analysis. A nomogram was developed based on identified risk factors. The effectiveness of the nomogram in both the training and validation sets was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
Age, body mass index (BMI), body temperature, cardiovascular comorbidity, respiratory rate, LDH level, lymphocyte count and D-dimer level were identified as risk factors associated with the clinical deterioration of non-severe CAP within 72 h of admission. The area under curve (AUC) value of the nomogram was 0.78 (95% CI: 0.74-0.82) in the training set and 0.75 (95% CI: 0.67-0.83) in the validation set. Furthermore, the calibration curves for both the training and validation sets indicated that the predicted probability of clinical deterioration aligned with the actual probability. Additionally, DCA revealed clinical utility for the nomogram at a specific threshold probability.
The study successfully identified the risk factors linked to the clinical deterioration of non-severe CAP and constructed a nomogram for predicting the probability of deterioration. The nomogram demonstrated favorable predictive performance and has the potential to aid in the early identification and management of non-severe CAP patients at elevated risk of deterioration.
目前，对于有临床恶化风险的非重症社区获得性肺炎（CAP）患者的关注仍不足，且相关危险因素的研究也较为匮乏。早期识别有临床恶化风险的住院患者将有利于其临床管理。
在中国温州医科大学附属第一医院进行了一项回顾性研究，时间跨度为2018年1月1日至2022年4月30日，共纳入1632例非重症CAP患者。根据患者入院72小时内病情是否恶化，将其分为临床恶化组和非临床恶化组。此外，所有患者被随机分配到一个包含75%患者的训练集和一个包含25%患者的验证集。在训练集中，通过LASSO回归分析和多因素逻辑回归分析确定非重症CAP患者临床恶化的危险因素。基于确定的危险因素绘制列线图。使用受试者工作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）评估列线图在训练集和验证集中的有效性。
年龄、体重指数（BMI）、体温、心血管合并症、呼吸频率、乳酸脱氢酶（LDH）水平、淋巴细胞计数和D-二聚体水平被确定为与非重症CAP入院72小时内临床恶化相关的危险因素。列线图在训练集中的曲线下面积（AUC）值为0.78（95%CI：0.74-0.82），在验证集中为0.75（95%CI：0.67-0.83）。此外，训练集和验证集的校准曲线均表明临床恶化的预测概率与实际概率相符。此外，DCA显示在特定阈值概率下列线图具有临床实用性。
该研究成功识别了与非重症CAP临床恶化相关的危险因素，并构建了用于预测恶化概率的列线图。该列线图显示出良好的预测性能，有可能有助于早期识别和管理有较高恶化风险的非重症CAP患者。
