ArticleActa neurochirurgica2022
External validation of prognostic models predicting outcome after chronic subdural hematoma.
Article in Acta neurochirurgica, 2022. 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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5 citing papers in PubMed, 8 citations in OpenAlex.
- Classification of recurrence status after surgical treatment of chronic subdural hemorrhage - A machine learning approach.PloS one · 2026Article
- Impact of surgical timing on chronic subdural hematoma outcomes: novel insights from a multicenter study.Neurosurgical review · 2025Article
- Prediction model for poor short-term prognosis in patients with chronic subdural hematoma after burr hole drainage: a retrospective cohort study.Neurosurgical review · 2024Article
- Synthetic minority over-sampling technique-enhanced machine learning models for predicting recurrence of postoperative chronic subdural hematoma.Frontiers in neurology · 2024Article
- A Linear Regression Equation for Predicting the Residual Volume of Chronic Subdural Hematoma 1 Week After Surgery.Neuropsychiatric disease and treatment · 2023Article
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Authors and funding
16 authors at 6 institutions in 1 country.
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Abstract
backgroundSeveral prognostic models for outcomes after chronic subdural hematoma (CSDH) treatment have been published in recent years. However, these models are not sufficiently validated for use in daily clinical practice. We aimed to assess the performance of existing prediction models for outcomes in patients diagnosed with CSDH.
methodsWe systematically searched relevant literature databases up to February 2021 to identify prognostic models for outcome prediction in patients diagnosed with CSDH. For the external validation of prognostic models, we used a retrospective database, containing data of 2384 patients from three Dutch regions. Prognostic models were included if they predicted either mortality, hematoma recurrence, functional outcome, or quality of life. Models were excluded when predictors were absent in our database or available for < 150 patients in our database. We assessed calibration, and discrimination (quantified by the concordance index C) of the included prognostic models in our retrospective database.
resultsWe identified 1680 original publications of which 1656 were excluded based on title or abstract, mostly because they did not concern CSDH or did not define a prognostic model. Out of 18 identified models, three could be externally validated in our retrospective database: a model for 30-day mortality in 1656 patients, a model for 2 months, and another for 3-month hematoma recurrence both in 1733 patients. The models overestimated the proportion of patients with these outcomes by 11% (15% predicted vs. 4% observed), 1% (10% vs. 9%), and 2% (11% vs. 9%), respectively. Their discriminative ability was poor to modest (C of 0.70 [0.63-0.77]; 0.46 [0.35-0.56]; 0.59 [0.51-0.66], respectively).
conclusionsNone of the examined models showed good predictive performance for outcomes after CSDH treatment in our dataset. This study confirms the difficulty in predicting outcomes after CSDH and emphasizes the heterogeneity of CSDH patients. The importance of developing high-quality models by using unified predictors and relevant outcome measures and appropriate modeling strategies is warranted.
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