Department of Pulmonary and Critical Care Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Department of Pulmonary and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, China.
Clin Respir J. 2024 Aug;18(8):e70001. doi: 10.1111/crj.70001.
Low body weight in patients with COPD is associated with a poor prognosis and more comorbidities. However, the impact of increased body weight in patients with COPD remains controversial. The aim of this study was to explore the clinical features of overweight patients with AECOPD.
In this multicenter cross-sectional study, a total of 647 AECOPD patients were recruited. Finally, 269 normal weight and 162 overweight patients were included. Baseline characteristics and clinical and laboratory data were collected. The least absolute shrinkage and selection operator (LASSO) regression was performed to determine potential features, which were substituted into binary logistic regression to reveal overweight-associated clinical features. The nomogram and its associated curves were established to visualize and verify the logistic regression model.
Six potential overweight-associated variables were selected by LASSO regression. Subsequently, a binary logistic regression model identified that the rates of type 2 diabetes (T2DM) and hypertension and levels of lymphocytes (LYM)%, and alanine aminotransferase (ALT) were independent variables of overweight in AECOPD patients. The C-index and AUC of the ROC curve of the nomogram were 0.671 and 0.666, respectively. The DCA curve revealed that the nomogram had more clinical benefits if the threshold was at a range of 0.22~0.78.
Collectively, we revealed that T2DM and hypertension were more common, and LYM% and ALT were higher in AECOPD patients with overweight than those with normal weight. The result suggests that AECOPD patients with overweight are at risk for additional comorbidities, potentially leading to worse outcomes.
COPD 患者体重偏低与预后不良和更多合并症相关。然而，COPD 患者体重增加的影响仍存在争议。本研究旨在探讨 AECOPD 超重患者的临床特征。
本多中心横断面研究共纳入 647 例 AECOPD 患者，最终纳入 269 例体重正常和 162 例超重患者。收集基线特征、临床和实验室数据。采用最小绝对收缩和选择算子（LASSO）回归确定潜在特征，将其代入二项逻辑回归揭示与超重相关的临床特征。建立列线图及其相关曲线，以可视化和验证逻辑回归模型。
LASSO 回归选择了 6 个潜在的超重相关变量。随后，二元逻辑回归模型确定 2 型糖尿病（T2DM）和高血压的发生率以及淋巴细胞（LYM）%和丙氨酸氨基转移酶（ALT）水平是 AECOPD 患者超重的独立变量。列线图的 C 指数和 AUC 分别为 0.671 和 0.666。ROC 曲线的 DCA 曲线显示，如果阈值在 0.22~0.78 范围内，列线图具有更多的临床获益。
总的来说，我们发现与体重正常的 AECOPD 患者相比，超重患者的 T2DM 和高血压更为常见，LYM%和 ALT 水平更高。这表明 AECOPD 超重患者存在发生额外合并症的风险，可能导致预后更差。
