Incorporating platelet-to-white blood cell ratio into survival prediction models for intracerebral hemorrhage: a nomogram approach

 What the fuck are the interventions needed when this long-term survival is not assured?  THAT IS THE RESEARCH NEEDED, NOT THIS!

Incorporating platelet-to-white blood cell ratio into survival prediction models for intracerebral hemorrhage: a nomogram approach

Jiake Xu^1,2†Xing Wang^1,2†Wei Chen^1,2Meng Tian^1,2Chao You^1,2*

• ¹Department of Neurosurgery, Neurosurgery Research Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan, China
• ²West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China

Background: Predicting long-term survival in intensive care unit patients with intracerebral hemorrhage (ICH) is crucial. This study aimed to develop a platelet-to-white blood cell ratio (PWR) incorporated nomogram for long-term survival prediction.

Methods: A retrospective analysis was conducted on 1,728 ICH patients in the MIMIC-IV 2.2 database. The independent prognostic value of PWR for 1-year mortality was assessed. A nomogram was developed using LASSO and Cox regression to predict 1-year survival, incorporating PWR and other factors. The performance of the nomogram was evaluated through calibration curves, area under the curve, Delong test, net reclassification index, integrated discrimination improvement, and decision curve analysis.

Results: The nomogram, which included age, weight, Glasgow Coma Scale (GCS) score, mechanical ventilation, glucose, red blood cell (RBC) count, blood urea nitrogen (BUN), and PWR, showed good predictive performance for 1-year survival. The C-index was 0.736 (95% CI = 0.716–0.756) for the training set and 0.766 (95% CI = 0.735–0.797) for the testing set. Higher age and ventilation increased mortality risk, while higher weight, GCS score, RBC count, and PWR decreased risk. The nomogram outperformed conventional scores.

Conclusions: A nomogram incorporating PWR as a prognostic factor accurately predicts long-term survival in ICH patients. However, validation in large-scale multicenter studies and further exploration of biomarkers are needed.

Introduction

Intracerebral hemorrhage (ICH) accounts for about 15% of all strokes and imposes a significant global burden in terms of disability-adjusted life years, often leading to various levels of functional impairment (1). Unlike ischemic strokes, there are currently no effective clinical treatments to prevent neuronal damage or promote neural repair for ICH (2, 3). Therefore, it is essential to fully understand the severity of ICH prognosis early on and identify risk factors that lead to poor outcomes in ICH patients to prepare for prevention and treatment.

Evaluating disease severity through scoring systems is beneficial for assessing patient prognosis and adjusting treatment plans. Many ICH scoring systems have been developed to date, primarily combining basic patient information with parameters obtained from computed tomography (CT) and neurological examinations (4, 5). It is widely accepted that the pathophysiological process of ICH consists of two stages: primary injury and more complex secondary injury. Inflammation is closely related to the progression of secondary injury and directly affects treatment outcomes (6). Current research suggests that inflammation induced by ICH manifests as changes in peripheral blood immune cells (7), with many inflammation markers related to disease progression, such as platelets, white blood cell (WBC) count, and neutrophils, easily obtainable through routine laboratory tests. Moreover, ratios of certain variables, such as the neutrophil-to-lymphocyte ratio (NLR), provide more stable predictive performance compared to single variables and have found widespread application in clinical settings (8).

The platelet-to-white blood cell ratio (PWR), a newly discovered inflammatory biomarker similar to NLR, has shown excellent predictive performance in ischemic stroke patients, although its role as an independent prognostic factor in ICH patients remains to be confirmed (9–11). Given its unique characteristics, PWR reflects both inflammation and coagulation processes, which are key factors in the pathophysiology of ICH. Unlike other indicators such as NLR, PWR provides a more comprehensive view by combining information on platelet function and immune response, making it a robust indicator of patient status. Additionally, PWR is easily obtainable through routine laboratory tests, making it a practical and accessible marker for clinical use. Incorporating these readily available laboratory markers into scoring systems may help create more convenient and accurate prediction models (12). Additionally, while many scoring systems have been developed, most only predict in-hospital or one-month mortality rates, with few studies focusing on longer-term outcomes such as 1-year prognoses (5).

In this study, we first examined the role of the PWR in predicting ICH mortality. To more accurately assess the prognosis of ICH patients, we developed a prediction model incorporating PWR using the lasso method and multivariate regression analyses and constructed corresponding nomograms for predicting 3-month, 6-month, and 1-year survival. By validating the nomograms, we evaluated the accuracy and reliability of this model in predicting ICH survival. This study aims to provide clinicians with a more effective tool for assessing the prognosis of hemorrhagic stroke patients, thereby enabling the development of more appropriate treatment plans.

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