PDF(Pubmed)
Abstract：
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.
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.
摘要：
■确定社区获得性肺炎（CAP）患者的诊断和预后仍然具有挑战性。我们旨在确定溶血磷脂酰胆碱酰基转移酶（LPCAT）在CAP中的作用，并评估该蛋白作为疾病严重程度和死亡率的生物标志物的有效性。
■前瞻性多中心研究在住院患者中进行。共纳入299例CAP患者（包括97例重度CAP患者[SCAP]）和20例健康对照（HC）。使用定量酶联免疫吸附测试试剂盒检测血浆中的LPCAT水平。我们开发了基于深度学习的二元分类（SCAP或非严重CAP[NSCAP]）模型来处理LPCAT水平和其他实验室测试结果。
■SCAP患者的LPCAT水平和死亡结局明显高于其他患者。LPCAT对SCAP的预测价值最高。LPCAT能够预测CAP患者的30天死亡率，将LPCAT值与PSI评分或CURB-65相结合,可进一步提高死亡率预测的准确性.
■发现SCAP患者中LPCAT的入院水平显着升高，并强烈预测了SCAP患者，但与病因无关。将LPCAT值与CURB-65或PSI相结合，显着改善了30天死亡率预测。
■NCT03093220于3月28日注册，2017.
■前瞻性多中心研究在住院患者中进行。共纳入299例CAP患者（包括97例重度CAP患者[SCAP]）和20例健康对照（HC）。使用定量酶联免疫吸附测试试剂盒检测血浆中的LPCAT水平。我们开发了基于深度学习的二元分类（SCAP或非严重CAP[NSCAP]）模型来处理LPCAT水平和其他实验室测试结果。
■SCAP患者的LPCAT水平和死亡结局明显高于其他患者。LPCAT对SCAP的预测价值最高。LPCAT能够预测CAP患者的30天死亡率，将LPCAT值与PSI评分或CURB-65相结合,可进一步提高死亡率预测的准确性.
■发现SCAP患者中LPCAT的入院水平显着升高，并强烈预测了SCAP患者，但与病因无关。将LPCAT值与CURB-65或PSI相结合，显着改善了30天死亡率预测。
■NCT03093220于3月28日注册，2017.
