ArticleFrontiers in neurology2022
A
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- European stroke organisation guideline on stroke-associated pneumonia.European stroke journal · 2026Guideline
- Advances in stroke-associated pneumonia in the era of revascularization therapy.Chinese medical journal · 2026Review
- Association between acute-phase glycaemic metrics and stroke-associated pneumonia in patients with acute ischaemic stroke.BMJ neurology open · 2026Article
- Development and validation of radiology-clinical statistical and machine learning model for stroke-associated pneumonia after first intracerebral haemorrhage.BMC pulmonary medicine · 2024Article
- Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia.BMC neurology · 2024Article
- Euthyroid sick syndrome predicts the risk of ischemic stroke-associated pneumonia in the acute stage of ischemic stroke: a nested case-control study.Frontiers in endocrinology · 2024Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the predictors of stroke-associated pneumonia (SAP) and poor functional outcome in patients with hyperacute cerebral infarction (HCI) by combining clinical factors, laboratory tests and neuroimaging features.
methodsWe included 205 patients with HCI from November 2018 to December 2019. The diagnostic criterion for SAP was occurrence within 7 days of the onset of stroke. Poor outcome was defined as a functional outcome based on a 3-months MRS score >3. The relationship of demographic, laboratory and neuroimaging variables with SAP and poor outcome was investigated using univariate and multivariate analyses.
resultsFifty seven (27.8%) patients were diagnosed with SAP and 40 (19.5%) developed poor outcomes. A
conclusionsAfter the addition of neuroimaging features, the models exhibit good differentiation and calibration for the prediction of the occurrence of SAP and the development of poor outcomes in HCI patients. The SAP model could better predict the SAP, representing a helpful and valid tool to obtain a net benefit compared with the A
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