ArticleTherapeutics and clinical risk management2021
A Prognostic Model Incorporating Red Cell Distribution Width to Platelet Ratio for Patients with Traumatic Brain Injury.
Article in Therapeutics and clinical risk management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Meta-analysis of Predicting Disorders of Consciousness After Traumatic Brain Injury by Machine Learning Models.Alpha psychiatry · 2024Pooled it
- Associations Between Routine Blood-Derived Inflammatory Markers and 14-Day Readmission After Total Hip Arthroplasty: An Exploratory Study.Orthopaedic surgery · 2026Article
- Investigation of the Expression, Localization, and Acidosis-Associated Conformational Changes in Connexin 43 in Traumatic Brain Injury with the Development of a Neural Network Model for Assessing Systemic Inflammation.International journal of molecular sciences · 2025Article
- Article
- Development and validation of a nomogram for predicting mortality in patients with acute severe traumatic brain injury: A retrospective analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- Prediction of Mortality in Geriatric Traumatic Brain Injury Patients Using Machine Learning Algorithms.Brain sciences · 2023Article
- A Novel Blood Inflammatory Indicator for Predicting Deterioration Risk of Mild Traumatic Brain Injury.Frontiers in aging neuroscience · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs an inflammation-based marker, red cell distribution width to platelet ratio (RPR) has been verified to be associated with disease severity and outcome in many clinical settings. We designed this study to evaluate the prognostic value of RPR in patients with traumatic brain injury (TBI).
methodsA total of 420 patients admitted with TBI were included in this study. Laboratory and clinical data were collected from an electronic medical record system. Univariate and multivariate logistic regression analyses were sequentially performed to discover risk factors of in-hospital mortality. Receiver operating characteristic (ROC) curves were drawn to confirm the predictive value of different markers including RPR in training set and testing set.
resultsNon-survivors had higher level of RPR than survivors (P<0.001). Logistic regression analysis showed that RPR was significantly associated with mortality even after adjusting for confounding factors (P<0.001). The area under the ROC curve (AUC) value of Glasgow Coma Scale (GCS) for predicting mortality was 0.761 and 0775 in training set and testing set, respectively. And the constructed predictive model incorporating RPR had the highest AUC value of 0.858 and 0.884 in training set and testing set.
conclusionRPR is significantly associated with mortality in TBI patients. Utilizing RPR to construct a predictive model is valuable to evaluate prognosis of TBI patients.
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