Evidence map›Paper›PMID 41816734›Full record

ArticleTurkish journal of medical sciences2026

Inflammation as a harbinger of death: a retrospective cohort study of preoperative biomarker risk stratification in orthopedic trauma.

Serkan Aydin, Burhan Kurtuluş

Abstract readMulticenter Study
In one paragraph

Article in Turkish journal of medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Serkan AydinDepartment of Orthopedics and Traumatology, Ministry of Health Etlik City Hospital, Ankara, Turkiye.ORCID https://orcid.org/0000-0002-3620-7041
Burhan KurtuluşDepartment of Orthopedics and Traumatology, Ankara Dışkapı Yıldırım Beyazıt Education and Research Hospital, Ankara, Turkiye.ORCID https://orcid.org/0000-0001-8816-5819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/aim: This study aimed to evaluate the prognostic significance of preoperative inflammatory markers including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), C-reactive protein (CRP), and procalcitonin in predicting 30-day and 1-year mortality in patients undergoing femur fracture surgery. Materials and methods: This retrospective, multicenter cohort study included patients who underwent surgical treatment for femur fractures between January 2018 and December 2024. Patients were stratified into survivor and nonsurvivor groups based on 30-day and 1-year outcomes. Demographic characteristics, comorbidities, laboratory parameters, and inflammatory indices were recorded and analyzed. Linear and multivariate logistic regression analyses were performed to identify independent predictors of mortality. Receiver operating characteristic (ROC) curve analysis was used to assess the predictive performance of the inflammatory markers. Results: A total of 430 patients were included, 310 (72.1%) of whom survived while 120 (27.9%) died during the 1-year follow-up. The 30-day mortality rate was 15% (n = 65) and the 1-year mortality rate was 38% (n = 163). Nonsurvivors were significantly older (81.3 ± 9.6 vs. 75.2 ± 10.1 years, p < 0.001) and had higher rates of diabetes mellitus (45% vs. 30%, p = 0.003), hypertension (80% vs. 40%, p < 0.001), and chronic kidney disease (55% vs. 16%, p < 0.001). Laboratory analysis showed elevated white blood cell count, red cell distribution width, neutrophils, CRP, procalcitonin, NLR, PLR, and MLR, while albumin was lower in nonsurvivors (all p < 0.05). Multivariate analysis identified age, chronic kidney disease, low albumin, elevated creatinine, CRP, the MLR, and hospital stay as independent mortality predictors. The MLR showed the strongest association (OR = 4.12 for 30-day mortality; OR = 3.85 for 1-year). ROC analysis revealed CRP (AUC = 0.811 and 0.783) and the MLR (AUC = 0.765 and 0.751) as the most accurate predictors, followed by the NLR and hospital stay. Conclusion: Preoperative inflammatory markers, particularly the MLR and CRP, were strongly associated with short- and long-term mortality in femur fracture surgery. Their integration into preoperative assessment may enhance risk stratification and guide clinical decision-making.

Indexed as

Femoral FracturesInflammationAgedAged, 80 and overBiomarkersC-Reactive ProteinFemaleHumansMaleNeutrophilsProcalcitoninPrognosisRetrospective StudiesRisk AssessmentBiomarkersC-Reactive ProteinProcalcitoninFemur fractureinflammatory markersmortalityprognosisrisk stratificationsurgery

Identifiers

PMID41816734
PMCPMC12974289

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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.