Ece Unal Cetin, Ozge Kurtkulagi, Fatih Kamis, Murat Das, Esen Simsek, Adil Ugur Cetin, Yavuz Beyazit
{"title":"Advancing ICU mortality prediction in community-acquired pneumonia: Combining fibrinogen-to-albumin ratio, CT severity score, PSI, and CURB-65.","authors":"Ece Unal Cetin, Ozge Kurtkulagi, Fatih Kamis, Murat Das, Esen Simsek, Adil Ugur Cetin, Yavuz Beyazit","doi":"10.17305/bb.2025.12127","DOIUrl":null,"url":null,"abstract":"<p><p>Community-acquired pneumonia (CAP) is a leading cause of ICU admissions, with significant morbidity and mortality. Traditional risk stratification tools, such as CURB-65, the pneumonia severity index (PSI), and computed tomography severity scores (CT-SS) are widely used for prognosis but could be improved by incorporating novel biomarkers. This retrospective study evaluated the fibrinogen-to-albumin ratio (FAR) as an additional predictor of 30-day mortality in ICU patients with CAP. A total of 158 CAP patients admitted to a tertiary care ICU were included. Baseline data encompassed demographic, clinical, laboratory, and radiological parameters, including FAR, CURB-65, PSI, and CT-SS. Logistic regression and receiver operating characteristic curve (ROC) analyses were conducted to assess mortality predictors. The 30-day mortality rate was 70.88% (112/158). Higher FAR, PSI, CURB-65, CT-SS, and lactate levels were independently associated with increased mortality (P < 0.05). FAR demonstrated strong discriminatory power (area under the receiver operating characteristic [AUROC]: 0.704) and significantly improved the predictive accuracy of established models. Adding FAR to PSI increased the AUROC from 0.705 to 0.791 (P = 0.009), while combining FAR, CT-SS, and PSI yielded the highest predictive accuracy (AUROC: 0.844, P = 0.032). These findings suggest that FAR, which reflects both inflammation and nutritional status, complements traditional risk assessment tools by providing a dynamic perspective. Integrating FAR into existing models enhances the identification of high-risk patients, enabling timely interventions and more efficient resource allocation in the ICU.</p>","PeriodicalId":72398,"journal":{"name":"Biomolecules & biomedicine","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomolecules & biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17305/bb.2025.12127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Community-acquired pneumonia (CAP) is a leading cause of ICU admissions, with significant morbidity and mortality. Traditional risk stratification tools, such as CURB-65, the pneumonia severity index (PSI), and computed tomography severity scores (CT-SS) are widely used for prognosis but could be improved by incorporating novel biomarkers. This retrospective study evaluated the fibrinogen-to-albumin ratio (FAR) as an additional predictor of 30-day mortality in ICU patients with CAP. A total of 158 CAP patients admitted to a tertiary care ICU were included. Baseline data encompassed demographic, clinical, laboratory, and radiological parameters, including FAR, CURB-65, PSI, and CT-SS. Logistic regression and receiver operating characteristic curve (ROC) analyses were conducted to assess mortality predictors. The 30-day mortality rate was 70.88% (112/158). Higher FAR, PSI, CURB-65, CT-SS, and lactate levels were independently associated with increased mortality (P < 0.05). FAR demonstrated strong discriminatory power (area under the receiver operating characteristic [AUROC]: 0.704) and significantly improved the predictive accuracy of established models. Adding FAR to PSI increased the AUROC from 0.705 to 0.791 (P = 0.009), while combining FAR, CT-SS, and PSI yielded the highest predictive accuracy (AUROC: 0.844, P = 0.032). These findings suggest that FAR, which reflects both inflammation and nutritional status, complements traditional risk assessment tools by providing a dynamic perspective. Integrating FAR into existing models enhances the identification of high-risk patients, enabling timely interventions and more efficient resource allocation in the ICU.