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Published on: September 22, 2012
Development and validation of the hypertensive intracerebral hemorrhage prognosis models
Wu Ding1, Zhiwei Gu2, Dagang Song2
1Department of Oncological Surgery, Shaoxing Second Hospital.
Insights
A new model accurately predicts 3-month outcomes for patients with hypertensive intracerebral hemorrhage using admission data. This tool aids early clinical decision-making for better patient prognosis.
Area of Science:
- Neurology
- Clinical Medicine
- Biostatistics
Background:
- Hypertensive intracerebral hemorrhage (HICH) poses significant mortality and morbidity risks.
- Accurate prediction of patient outcomes is crucial for effective clinical management.
Purpose of the Study:
- To develop and validate a prognostic model for predicting 3-month outcomes in HICH patients.
- The model utilizes readily available admission characteristics for early prediction.
Main Methods:
- Retrospective analysis of 325 HICH patients admitted between 2012 and 2016.
- Logistic regression models were employed to identify independent predictors of 3-month outcomes.
- Model performance was assessed using discrimination (ROC curves) and calibration, with internal and external validation.
Main Results:
- Key predictors identified include age, Glasgow Coma Scale score, pupillary light reflex, hypoxemia, hemorrhage volume, blood glucose, and D-dimer levels.
- The comprehensive prognostic model demonstrated strong predictive performance, with the area under the ROC curve reaching 0.913.
- Internal and external validation confirmed the model's reliability and applicability without over-optimism.
Conclusions:
- The developed prognosis model offers an early, simple, and accurate method for predicting HICH patient outcomes.
- This tool can significantly contribute to guiding clinical treatment strategies and improving patient prognosis.
Abstract:
To develop and validate the prognosis model of hypertensive intracerebral hemorrhage based on admission characteristics, which would be applied to predict the 3-month outcome.For developing the prognosis models, we studied data from 325 patients with retrospectively consecutive hypertensive intracerebral hemorrhage admitted between 2012 and 2016. The predictive value of admission characteristics was tested in logistic regression models, presenting 3-month outcome as the primary outcome. The performance of the models was tested by discrimination and calibration. After development, internal and external validations were used to test the function.The multivariate analysis of logistic regression indicated that age, Glasgow coma scale score, pupillary light reflex, hypoxemia, intracerebral hemorrhage volume, blood glucose, and D-dimer level were independent factors of the hypertensive intracerebral hemorrhage prognosis model. The prognosis model based on those admission risk factors worked well. The receiver operating characteristic curve was used to analyze the discriminant ability of model A, model A + B, and model A + B + C. Specifically, the area under the receiver operating characteristic curve increased from 0.816 (model A; 95% CI, 0.760-0.872) to 0.913 (model A + B + C; 95% CI, 0.881-0.946), and the models were not overoptimistic and were applicably confirmed by internal and external validations respectively.This prognosis model could be used to predict the prognosis of patients with hypertensive intracerebral hemorrhage early, simply and accurately, contributing to the clinical treatment eventually.
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