ArticleCurrent neurovascular research2022
Prediction of Symptoms on Admission with Early Neurological Deterioration in Single Small Subcortical Infarct.
Article in Current neurovascular research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- PI-MMNet: a cross-modal neural network for predicting neurological deterioration in pontine infarction.Frontiers in neuroscience · 2025Article
- Lesion Indexes Predict Early Neurologic Deterioration in Lenticulostriate Single Small Subcortical Infarction.AJNR. American journal of neuroradiology · 2024Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly neurological deterioration (END) often occurs during hospitalization in single small subcortical infarct (SSSI). While, symptoms on admission were rarely reported about its performance on predicting the risk of END.
objectivesThe objective of this study is to explore the relationship between symptoms on admission and END in SSSI.
methodsPatients with SSSI in the lenticulostriate artery (LSA) territory presenting within 72 hours of stroke onset were screened prospectively. Clinical characteristics, including symptoms on admission, laboratory tests and imaging findings, were collected. Based on the body regions involved including spherical face (SF), upper limb (UL) or lower limb (LL), symptoms on admission were classified into single spherical face (sSF) and any involvement of limbs (AL). END was defined as ≥2 points increase in total National Institutes of Health Stroke Scale (NIHSS) score or ≥ 1 point increase in motor score within 72 hours after admission. Multivariate logistic regression was used to analyze factors associated with END.
resultsOut of 5,832 ischemic stroke patients in the database, 394 patients were finally enrolled in analysis. 65 patients (16.5%) developed END. Multivariable logistic regression revealed that symptoms with LL (OR 2.337, 95% CI 1.041-5.246), UL (OR 2.936, 95% CI 1.349-6.390) were both associated with END, while the involvement of SF (OR 0.447, 95% CI 0.249-0.804) showed the opposite result. Further analysis found that symptoms with AL (OR 3.958, 95% CI 1.355-11.565) showed a higher risk of END compared to sSF after adjustment.
conclusionOur results discovered that symptoms with AL carried a higher risk of END than those involving sSF in SSSI.
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