Harshitha Reddy, Sunil Kumar, Sourya Acharya, Suprit Malali, Kaumudi Ayaluri, Venkat Reddy, Saket Toshniwal, Sanchit Chabra, Meraj Khan, Johar Iqbal, Mohammad S Akhter, Hina Rashid
{"title":"Neutrophil-Lymphocyte-Platelet Ratio as a Prognostic Marker in Rural ICU Patients: a Two-Year Cross-Sectional Study.","authors":"Harshitha Reddy, Sunil Kumar, Sourya Acharya, Suprit Malali, Kaumudi Ayaluri, Venkat Reddy, Saket Toshniwal, Sanchit Chabra, Meraj Khan, Johar Iqbal, Mohammad S Akhter, Hina Rashid","doi":"10.7754/Clin.Lab.2025.250902","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Early risk identification can improve treatment outcomes for sepsis patients, leading to timely intervention and better quality of life. An identification of certain parameters in such patients is necessary to determine the risk in such patients. The present study evaluated the predictive efficiency of various critical care assessment scores (CAS), including SOFA, qSOFA, APACHE IV, and biomarkers such as NLR and NLPR, for in-hospital mortality, the need for mechanical ventilation (MV), and hospital length of stay (LOS), as a risk for sepsis patients.</p><p><strong>Methods: </strong>A total of 300 patients were included in the study; however, 70 mortalities were recorded. A significant difference was observed in the hematological and biochemical parameters between the survivors and non-survivors (p < 0.001). Associations between CAS, biomarkers, and clinical outcomes were assessed by binary logistic regression, while receiver operating characteristic (ROC) curve analysis was used to determine optimal cutoffs for mortality and MV prediction.</p><p><strong>Results: </strong>SOFA was the best predictor of mortality (OR: 2.98, p < 0.001) and MV requirement (OR: 2.90, p < 0.001), with a cutoff of ≥ 9 having 94% sensitivity and 86% specificity for mortality. APACHE IV with a cutoff > 71, AUC: 0.840, and NLPR with a cutoff > 3.1, AUC: 0.716, also significantly predicted mortality. PaO2/FiO2 had a negative correlation with both mortality (OR: 0.022, p < 0.001) and MV need (OR: 0.004, p < 0.001). An inverse prediction of LOS with SOFA scores was seen (β = -0.191, p = 0.003), whereas higher PaO2/FiO2 ratios indicated prolonged hospitalization (β = 0.193, p = 0.011).</p><p><strong>Conclusions: </strong>When predicting sepsis-related mortality and MV requirement, SOFA is a better option than other CAS and biomarkers. In setups with limited resources, NLPR is a helpful substitute. Important information about mortality risk and length of hospital stay is provided by PaO2/FiO2. However, to confirm these results in various contexts, more investigation is necessary.</p>","PeriodicalId":10384,"journal":{"name":"Clinical laboratory","volume":"72 10","pages":"2126-2135"},"PeriodicalIF":0.7000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical laboratory","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.7754/Clin.Lab.2025.250902","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Early risk identification can improve treatment outcomes for sepsis patients, leading to timely intervention and better quality of life. An identification of certain parameters in such patients is necessary to determine the risk in such patients. The present study evaluated the predictive efficiency of various critical care assessment scores (CAS), including SOFA, qSOFA, APACHE IV, and biomarkers such as NLR and NLPR, for in-hospital mortality, the need for mechanical ventilation (MV), and hospital length of stay (LOS), as a risk for sepsis patients.
Methods: A total of 300 patients were included in the study; however, 70 mortalities were recorded. A significant difference was observed in the hematological and biochemical parameters between the survivors and non-survivors (p < 0.001). Associations between CAS, biomarkers, and clinical outcomes were assessed by binary logistic regression, while receiver operating characteristic (ROC) curve analysis was used to determine optimal cutoffs for mortality and MV prediction.
Results: SOFA was the best predictor of mortality (OR: 2.98, p < 0.001) and MV requirement (OR: 2.90, p < 0.001), with a cutoff of ≥ 9 having 94% sensitivity and 86% specificity for mortality. APACHE IV with a cutoff > 71, AUC: 0.840, and NLPR with a cutoff > 3.1, AUC: 0.716, also significantly predicted mortality. PaO2/FiO2 had a negative correlation with both mortality (OR: 0.022, p < 0.001) and MV need (OR: 0.004, p < 0.001). An inverse prediction of LOS with SOFA scores was seen (β = -0.191, p = 0.003), whereas higher PaO2/FiO2 ratios indicated prolonged hospitalization (β = 0.193, p = 0.011).
Conclusions: When predicting sepsis-related mortality and MV requirement, SOFA is a better option than other CAS and biomarkers. In setups with limited resources, NLPR is a helpful substitute. Important information about mortality risk and length of hospital stay is provided by PaO2/FiO2. However, to confirm these results in various contexts, more investigation is necessary.
期刊介绍:
Clinical Laboratory is an international fully peer-reviewed journal covering all aspects of laboratory medicine and transfusion medicine. In addition to transfusion medicine topics Clinical Laboratory represents submissions concerning tissue transplantation and hematopoietic, cellular and gene therapies. The journal publishes original articles, review articles, posters, short reports, case studies and letters to the editor dealing with 1) the scientific background, implementation and diagnostic significance of laboratory methods employed in hospitals, blood banks and physicians'' offices and with 2) scientific, administrative and clinical aspects of transfusion medicine and 3) in addition to transfusion medicine topics Clinical Laboratory represents submissions concerning tissue transplantation and hematopoietic, cellular and gene therapies.