ArticleMedicine2019
A nomogram to predict cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients: A retrospective cohort study.
Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Clinical prediction rules for cognitive outcomes post-stroke: an updated systematic review and meta-analysis.EClinicalMedicine · 2025Article
- A nomogram for predicting mild cognitive impairment in older adults with hypertension.BMC neurology · 2023Article
- European Stroke Organisation and European Academy of Neurology joint guidelines on post-stroke cognitive impairment.European stroke journal · 2021Article
- Prognostic rules for predicting cognitive syndromes following stroke: A systematic review.European stroke journal · 2021Review
- Decision-making impairments under ambiguous and risky situations in patients with prefrontal tumor: A neuropsychological study.Brain and behavior · 2021Article
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Authors and funding
4 authors at 1 institution in 1 country.
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Abstract
To establish a nomogram model to predict early cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients.A retrospective cohort study was held between January 2016 and October 2018. One hundred twenty seven out of 170 consecutive patients with supratentorial spontaneous intracranial hematoma were enrolled in this study. They were divided into development (n = 92) and validation (n = 35) dataset according to their admission time. Mini-mental State Examination (MMSE) was conducted between the third and the sixth month after the onset of stroke. MMSE ≤ 24 was considered as cognitive impairment. Univariate and multivariate logistic regression was used to screen for independent risk factors which correlate with cognitive impairment on the development dataset. A nomogram was built based on Akaike Information Criterion (AIC). Receiver operating characteristic (ROC) curve and calibration curve on development and validation dataset was drawn with each area under the curves (AUC) calculated. The decision curve analysis was also conducted with the development dataset.The bleeding volume, Glasgow Coma Scale (GCS), and intraventricular hemorrhage (IVH) are the most significant risk factors which may cause cognitive impairment both in the univariate and multivariate analysis. The finial model performed good discrimination ability on both development and validation dataset with AUC 0.911 and 0.919. Most patients would benefit from the model according to the decision curve analysis.A nomogram, constructed based on bleeding volume, GCS, and IVH can provide a feasible tool to evaluate cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients.
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