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Li F, He Q, Peng H, Zhou J, Zhong C, Liang G, Li W, Xu D. The systemic inflammation indexes after admission predict in-hospital mortality in patients with extensive burns. Burns 2024; 50:980-990. [PMID: 38336497 DOI: 10.1016/j.burns.2024.01.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 02/12/2024]
Abstract
PURPOSE To explore the clinical value of various complete blood count (CBC)-derived inflammation indicators to predict in-hospital mortality in patients with extensive burns. METHODS Systemic inflammation indexes, including lymphocyte-platelet ratio (LPR), neutrophil-lymphocyte ratio (NLR), neutrophil-monocyte ratio (NMR), monocyte-lymphocyte ratio (MLR), neutrophil-to-lymphocyte * platelet (NLPR), systemic inflammation index (SII), and systemic inflammation response index (SIRI) on days 1, 3, and 7 after admission were calculated in 135 patients with extensive burns. RESULTS We included 135 patients with extensive burns, including 97 survivors and 38 non-survivors. After adjusting for confounders, only the LPR on day 1, NLPR on days 3 and 7 were significantly associated with survival (OR= 1.237, 1.097, 1.104; 95 % CI: 1.055-1.451, 1.002-1.202, 1.005-1.212; respectively) in the analysis of multivariate logistic regression. The optimum cutoff values of the LPR on day 1 and NLPR on day 3 were 6.37 and 8.06, and the area under the curves (AUC) were 0.695 and 0.794, respectively. The AUC of NLPR on day 7 had the highest value, 0.814, and the optimum cut-off value was 3.84. The efficacy of LPR on day 1, NLPR on days 3 and 7 combined with the burn prognostic score index in predicting the prognosis of patients was higher than that of the burn index alone, and the three composite inflammatory indexes combined with PBI had the highest efficacy in predicting the prognosis (AUC = 0.994). Kaplan-Meier survival analysis showed poor prognosis in patients with higher LPR on day 1 and higher NLPR on days 3 and 7 (log-rank χ2 =9.623,31.564, 20.771, respectively; P < 0.01). CONCLUSIONS LPR on day 1 and NLPR on days 3 and 7 after admission are reliable predictors of prognosis in patients with severe extensive burns. The combination of the burn prognostic score index, LPR on day 1, and NLPR on days 3 and 7 was superior to the burn indexes alone in predicting a patient's prognosis.
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Affiliation(s)
- Fuying Li
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China
| | - Quanyong He
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China
| | - Hao Peng
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China
| | - Jianda Zhou
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China
| | - Chi Zhong
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China
| | - Geao Liang
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China
| | - Wengjuan Li
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China
| | - Dan Xu
- Department of Burns and Plastic Surgery, the third Xiangya Hospital, Central South University, Changsha, China.
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Di Rosa M, Sabbatinelli J, Soraci L, Corsonello A, Bonfigli AR, Cherubini A, Sarzani R, Antonicelli R, Pelliccioni G, Galeazzi R, Marchegiani F, Iuorio S, Colombo D, Burattini M, Lattanzio F, Olivieri F. Neutrophil-to-lymphocyte ratio (NLR) predicts mortality in hospitalized geriatric patients independent of the admission diagnosis: a multicenter prospective cohort study. J Transl Med 2023; 21:835. [PMID: 37990223 PMCID: PMC10664513 DOI: 10.1186/s12967-023-04717-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 11/09/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND The Neutrophil-to-lymphocyte ratio (NLR) is a marker of poor prognosis in hospitalized older patients with different diseases, but there is still no consensus on the optimal cut-off value to identify older patients at high-risk of in-hospital mortality. Therefore, in this study we aimed at both validating NLR as a predictor of death in older hospitalized patients and assess whether the presence of specific acute diseases can modify its predictive value. METHODS This prospective cohort study included 5034 hospitalizations of older patients admitted to acute care units in the context of the ReportAge study. NLR measured at admission was considered as the exposure variable, while in-hospital mortality was the outcome of the study. ROC curves with Youden's method and restricted cubic splines were used to identify the optimal NLR cut-off of increased risk. Cox proportional hazard models, stratified analyses, and Kaplan-Meier survival curves were used to analyse the association between NLR and in-hospital mortality. RESULTS Both continuous and categorical NLR value (cut-off ≥ 7.95) predicted mortality in bivariate and multivariate prognostic models with a good predictive accuracy. The magnitude of this association was even higher in patients without sepsis, congestive heart failure, and pneumonia, and those with higher eGFR, albumin, and hemoglobin (p < 0.001). A negative multiplicative interaction was found between NLR and eGFR < 45 (p = 0.001). CONCLUSIONS NLR at admission is a readily available and cost-effective biomarker that could improve identification of geriatric patients at high risk of death during hospital stay independent of admitting diagnosis, kidney function and hemoglobin levels.
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Affiliation(s)
- Mirko Di Rosa
- Centre for Biostatistics and Applied Geriatric Clinical Epidemiology, IRCCS INRCA, Ancona, Italy
| | - Jacopo Sabbatinelli
- Department of Clinical and Molecular Sciences, Università Politecnica Delle Marche, Ancona, Italy
- Laboratory Medicine Unit, Azienda Ospedaliero Universitaria Delle Marche, Ancona, Italy
| | - Luca Soraci
- Unit of Geriatric Medicine, IRCSS INRCA, C.da Muoio Piccolo, 87100, Cosenza, Italy.
| | - Andrea Corsonello
- Centre for Biostatistics and Applied Geriatric Clinical Epidemiology, IRCCS INRCA, Ancona, Italy
- Unit of Geriatric Medicine, IRCSS INRCA, C.da Muoio Piccolo, 87100, Cosenza, Italy
- Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy
| | | | - Antonio Cherubini
- Geriatria, Accettazione Geriatrica e Centro di ricerca per l'invecchiamento, IRCCS INRCA, Ancona, Italy
| | - Riccardo Sarzani
- Department of Clinical and Molecular Sciences, Università Politecnica Delle Marche, Ancona, Italy
- Internal Medicine and Geriatrics, IRCCS INRCA, Ancona, Italy
| | | | | | - Roberta Galeazzi
- Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy
| | | | | | | | | | | | - Fabiola Olivieri
- Department of Clinical and Molecular Sciences, Università Politecnica Delle Marche, Ancona, Italy
- Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy
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