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(1) Background: Patients with acute ischaemic stroke (AIS) are at high risk for stroke-associated infections (SAIs). We hypothesised that increased concentrations of systemic inflammation markers predict SAIs and unfavourable outcomes; (2) Methods: In 223 patients with AIS, blood samples were taken at ≤24 h, 3 d and 7d after a stroke, to determine IL-6, IL-10, CRP and LBP. The outcome was assessed using the modified Rankin Scale at 90 d. Patients were thoroughly examined regarding the development of SAIs; (3) Results: 47 patients developed SAIs, including 15 lower respiratory tract infections (LRTIs). IL-6 and LBP at 24 h differed, between patients with and without SAIs (IL-6: p < 0.001; LBP: p = 0.042). However, these associations could not be confirmed after adjustment for age, white blood cell count, reduced consciousness and NIHSS. When considering the subgroup of LRTIs, in patients who presented early (≤12 h after stroke, n = 139), IL-6 was independently associated with LRTIs (OR: 1.073, 95% CI: 1.002−1.148). The ROC-analysis for prediction of LRTIs showed an AUC of 0.918 for the combination of IL-6 and clinical factors; (4) Conclusions: Blood biomarkers were not predictive for total SAIs. At early stages, IL-6 was independently associated with outcome-relevant LRTIs. Further studies need to clarify the use of biochemical markers to identify patients prone to SAIs.
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http://dx.doi.org/10.3390/ijms232213747 | DOI Listing |
J Inflamm Res
August 2025
Department of Neurosurgery, Clinical Medical College and Affiliated Hospital of Chengdu University, Chengdu, Sichuan, People's Republic of China.
Background And Aim: Pneumonia is a significant complication that negatively impacts outcomes in patients with intracerebral hemorrhage (ICH). Identifying reliable biomarkers for predicting such infections is crucial for timely intervention and improving patient management. This study aims to evaluate the predictive value of neutrophil-to-albumin Ratio (NAR)for pneumonia in patients undergoing surgical intervention for ICH.
View Article and Find Full Text PDFCerebrovasc Dis
July 2025
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Introduction: Stroke-associated pneumonia (SAP) is a major infectious complication after stroke and has adverse impact on clinical outcomes. This study investigates whether automatic screening the risk of SAP and giving feedback to medical staff would reduce the incidence of inhospital pneumonia and improve clinical outcomes in patients with acute ischemic stroke (AIS).
Methods: This monocentric retrospective cohort study involved eligible inpatients in neurology department of Beijing Tiantan Hospital from June 2019 to October 2023.
J Clin Neurosci
September 2025
Department of Neurosurgery, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy. Electronic address:
Introduction: Aneurysmal subarachnoid hemorrhage (aSAH) is a severe type of stroke associated with high rates of mortality and morbidity. Two major complications following aSAH are acute hydrocephalus and delayed cerebral ischemia (DCI) caused by severe vasospasm. While external ventricular drainage and lumbar drainage (LD) are typically used separately to manage hydrocephalus, the potential benefit of their combined use in reducing vasospasm risk remains underexplored.
View Article and Find Full Text PDFCirc J
June 2025
Department of Cardiovascular Surgery, Osaka University Graduate School of Medicine.
Background: Japan's heart transplantation system is characterized by an extremely long waiting period, which contributes to significant mortality on the waiting list. The current allocation system may maintain favorable post-transplant outcomes at the expense of high-risk patients, particularly those with severe heart failure or complications following left ventricular assist device (LVAD) implantation. To explore an optimal allocation system for Japan, we investigated risk factors for waiting list mortality.
View Article and Find Full Text PDFComput Biol Med
September 2025
Department of Nursing Quality Management, The Affiliated Hospital of Guizhou Medical University, China. Electronic address:
Objective: The heterogeneity of machine learning (ML) models predicting the risk of stroke-associated pneumonia (SAP) is considerable. This study aims to conduct a meta-analysis and comparison of published ML models that predict SAP risk.
Methods: A systematic search was conducted across eight databases, covering the period from their inception to August 16, 2024.