社区获得性肺炎
医学
内科学
生物标志物
肺炎
前瞻性队列研究
肺炎严重指数
病因学
溶血磷脂酰胆碱
胃肠病学
生物
磷脂
遗传学
膜
磷脂酰胆碱
生物化学
作者
Li Chen,Junfeng Xue,Lili Zhao,Yukun He,Siqing Fu,Xinqian Ma,Wenyi Yu,Yanfen Tang,Yongjun Wang,Zhancheng Gao
标识
DOI:10.3389/fimmu.2023.1295353
摘要
Identifying the diagnosis as well as prognosis for patients presented with community-acquired pneumonia (CAP) remains challenging. We aimed to identify the role of lysophosphatidylcholine acyl-transferase (LPCAT) for CAP along with assessing this protein's effectiveness as a biomarker for severity of disease and mortality.Prospective multicenter research study was carried out among hospitalized patients. A total of 299 CAP patients (including 97 severe CAP patients [SCAP]) and 20 healthy controls (HC) were included. A quantitative enzyme-linked immunosorbent test kit was employed for detecting the LPCAT level in plasma. We developed a deep-learning-based binary classification (SCAP or non-severe CAP [NSCAP]) model to process LPCAT levels and other laboratory test results.The level of LPCAT in patients with SCAP and death outcome was significantly higher than that in other patients. LPCAT showed the highest predictive value for SCAP. LPCAT was able to predict 30-day mortality among CAP patients, combining LPCAT values with PSI scores or CURB-65 further enhance mortality prediction accuracy.The on admission level of LPCAT found significantly raised among SCAP patients and strongly predicted SCAP patients but with no correlation to etiology. Combining the LPCAT value with CURB-65 or PSI improved the 30-day mortality forecast significantly.NCT03093220 Registered on March 28th, 2017.
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