ArticlePloS one2026
Neutrophil-to-lymphocyte and neutrophil-to-platelet ratios for predicting 28-day mortality in sepsis: A retrospective cohort study.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to evaluate the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and neutrophil-to-platelet ratio (NPR), alone and in combination with procalcitonin (PCT), for predicting 28‑day mortality in patients with sepsis.
methodsIn this single‑center retrospective cohort study, 395 adult sepsis patients admitted to the emergency department between 2020 and 2025 were included. NLR and NPR were calculated from the first complete blood count obtained within 24 hours of initial emergency department presentation. Univariable Cox regression was used for preliminary screening. The C-index was used to compare the discriminative ability of traditional inflammatory markers (PCT, CRP, and WBC) to select a reference biomarker. Multivariable Cox regression and restricted cubic spline (RCS) analysis were performed to evaluate the linear and non-linear associations of NLR and NPR with mortality. To assess whether adding NLR or NPR provided incremental prognostic value to PCT, multivariable Cox models with interaction terms (PCT × NLR and PCT × NPR) were constructed. LASSO regression was applied for variable selection, and VIF was used to assess multicollinearity.
resultsThe overall 28‑day mortality was 38.2%. Neither NLR nor NPR outperformed PCT in predicting 28-day mortality, and none of the three biomarkers showed significant independent associations with mortality after adjusting for confounders (PCT: adjusted HR per IQR = 1.02, 95% CI: 0.94-1.11, p = 0.605; NLR: HR = 1.01, 95% CI: 1.00-1.02, p = 0.235; NPR: HR = 1.00, 95% CI: 1.00-1.01, p = 0.378). Restricted cubic spline (RCS) curves confirmed no non-linear associations or threshold effects for NLR and NPR. Multivariable Cox regression with interaction terms showed that adding NLR or NPR to PCT did not provide additional prognostic value beyond PCT alone (PCT × NLR: HR = 1.00, 95% CI: 0.97-1.03, p = 0.854; PCT × NPR: HR = 0.97, 95% CI: 0.92-1.01, p = 0.121).
conclusionNeither NLR nor NPR alone, nor their combination with PCT, improved 28-day mortality prediction in this elderly sepsis cohort, suggesting that a single early measurement may be insufficient for sepsis prognostication. Future studies should explore serial measurements and integrate multiple pathophysiological dimensions. The low cost and wide availability of NLR and NPR still support their potential role within a multi-parameter panel, particularly in resource-limited settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.