Neutrophil-to-lymphocyte ratio (NLR) predicts mortality in hospitalized geriatric patients independent of the admission diagnosis: a multicenter prospective cohort study.

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 5,034 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 (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..

Medienart:

Preprint

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

ResearchSquare.com - (2023) vom: 27. Nov. Zur Gesamtaufnahme - year:2023

Sprache:

Englisch

Beteiligte Personen:

Rosa, Mirko Di [VerfasserIn]
Sabbatinelli, Jacopo [VerfasserIn]
Soraci, Luca [VerfasserIn]
Corsonello, Andrea [VerfasserIn]
Bonfigli, Anna Rita [VerfasserIn]
Cherubini, Antonio [VerfasserIn]
Sarzani, Riccardo [VerfasserIn]
Antonicelli, Roberto [VerfasserIn]
Pelliccioni, Giuseppe [VerfasserIn]
Galeazzi, Roberta [VerfasserIn]
Marchegiani, Francesca [VerfasserIn]
Iuorio, Salvatore [VerfasserIn]
Colombo, Daniele [VerfasserIn]
Burattini, Maurizio [VerfasserIn]
Lattanzio, Fabrizia [VerfasserIn]
Olivieri, Fabiola [VerfasserIn]

Links:

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Themen:

570
Biology

doi:

10.21203/rs.3.rs-3390159/v1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XRA041099753