Coagulation and inflammatory markers independently predict in-hospital mortality in aspiration pneumonia patients undergoing bronchoalveolar lavage.

IF 1.6 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
American journal of translational research Pub Date : 2025-06-15 eCollection Date: 2025-01-01 DOI:10.62347/BAQD6951
Tao Ren, Weimin Jiang
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引用次数: 0

Abstract

Objectives: To evaluate the prognostic value of serum coagulation and inflammatory markers for in-hospital mortality in patients with aspiration pneumonia (AP) undergoing bronchoalveolar lavage, and to develop a predictive model.

Methods: This retrospective study included 220 AP patients admitted to XianJu People's Hospital between January 2022 and October 2024. Data on demographics, coagulation parameters, inflammatory markers, and in-hospital outcomes were collected. Multivariate logistic regression was used to identify independent predictors of mortality, and a nomogram was constructed based on significant variables.

Results: Among the 220 patients, 42 (19.1%) died during hospitalization. Multivariate logistic regression identified age (OR = 1.057, P = 0.006), fibrinogen (FIB; OR = 1.456, P = 0.002), D-dimer (OR = 2.414, P < 0.001), leukocyte count (OR = 1.128, P = 0.027), and procalcitonin (PCT; OR = 9.240, P < 0.001) as independent predictors of in-hospital mortality. The nomogram model incorporating these variables demonstrated good discriminative ability with an area under the curve of 0.835. Calibration plots and decision curve analysis further confirmed the model's accuracy and clinical utility.

Conclusion: Age, FIB, D-dimer, leukocyte count, and PCT are independent predictors of in-hospital mortality in AP patients undergoing bronchoalveolar lavage. The nomogram based on these markers shows strong predictive performance and may facilitate individualized risk assessment and clinical decision-making.

凝血和炎症标志物独立预测吸入性肺炎患者接受支气管肺泡灌洗的住院死亡率。
目的:评价血清凝血和炎症标志物对吸入性肺炎(AP)行支气管肺泡灌洗术患者住院死亡率的预测价值,并建立预测模型。方法:对2022年1月至2024年10月在仙居人民医院住院的220例AP患者进行回顾性研究。收集了人口统计学、凝血参数、炎症标志物和住院结果的数据。采用多元逻辑回归确定死亡率的独立预测因子,并根据显著变量构建nomogram。结果:220例患者中,42例(19.1%)在住院期间死亡。多因素logistic回归确定年龄(OR = 1.057, P = 0.006)、纤维蛋白原(FIB;OR = 1.456, P = 0.002)、d -二聚体(OR = 2.414, P < 0.001)、白细胞计数(OR = 1.128, P = 0.027)、降钙素原(PCT;OR = 9.240, P < 0.001)作为院内死亡率的独立预测因子。纳入这些变量的nomogram模型具有较好的判别能力,曲线下面积为0.835。校正图和决策曲线分析进一步证实了模型的准确性和临床实用性。结论:年龄、FIB、d -二聚体、白细胞计数和PCT是行支气管肺泡灌洗术的AP患者住院死亡率的独立预测因子。基于这些标记的nomogram (nomogram)显示出较强的预测性能,并可能促进个体化风险评估和临床决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
American journal of translational research
American journal of translational research ONCOLOGY-MEDICINE, RESEARCH & EXPERIMENTAL
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