ArticleFrontiers in neurology2025
Individualized prediction of stroke-associated pneumonia for patients with acute ischemic stroke.
Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Development and external validation of a risk stratification model for stroke-associated pneumonia.iScience · 2026Article
- Risk estimation for stroke-associated pneumonia in acute ischemic stroke: a nomogram-based approach.Arquivos de neuro-psiquiatria · 2026Article
- Mechanistic and clinical investigation of Jiajiang Xuming decoction in multi-modal programmed cell death in stroke-associated pneumonia.Frontiers in cell and developmental biology · 2026Article
- Neutrophil-to-Lymphocyte Ratio as a Complementary Marker for Stroke-Associated Pneumonia Risk in Acute Ischemic Stroke.Stroke research and treatment · 2026Article
- Association between admission hemoglobin-to-red blood cell distribution width ratio and stroke-associated pneumonia risk in acute ischemic stroke: effect modification by diabetes status.Frontiers in endocrinology · 2026Article
- Building a SHAP interpretable prediction model for stroke-associated pneumonia [stroke-associated pneumonia (SAP)] in patients with aneurysmal subarachnoid hemorrhage (aSAH).Frontiers in neurologyArticle
- Development and validation of a machine learning model for predicting stroke-associated pneumonia in older patients with acute ischemic stroke.Frontiers in neurologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Stroke-associated pneumonia (SAP) remains a neglected area despite its high morbidity and mortality. We aimed to establish an easy-to-use model for predicting SAP. Methods: Two hundred seventy-five acute ischemic stroke (AIS) patients were enrolled, and 73 (26.55%) patients were diagnosed with SAP. Results: Three variables with the most significant associations, including age, NGT placement, and right cerebral hemisphere lesions combined with gender, were used to construct a stroke-associated pneumonia prediction scale with high accuracy (AUC = 0.93). Youden index of our SAP prediction model was 0.77. The sensitivity and specificity of our SAP prediction model were 0.89 and 0.88, respectively. Conclusion: We identified the best predictive model for SAP in AIS patients. Our study aimed to be as clinically relevant as possible, focusing on features that are routinely available. The contribution of selected variables is visually displayed through SHapley Additive exPlanations (SHAP). Our model can help to distinguish AIS patients of high-risk, provide specific management, reduce healthcare costs and prevent life-threatening complications and even death.
Indexed as
Identifiers
What Socratic 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 Socratic graph.