Risk factors for mortality in patients with spontaneous cerebellar hemorrhage based on Mimics software analysis.
10.3760/cma.j.cn121430-20240717-00611
- Author:
Jiacheng WU
1
;
Zhenning LIU
Author Information
1. Department of Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning, China. Corresponding author: Liu Zhenning, Email: liuzn999@hotmail.com.
- Publication Type:Journal Article
- MeSH:
Humans;
Male;
Female;
Risk Factors;
Retrospective Studies;
Middle Aged;
Aged;
Software;
Adult;
Cerebral Hemorrhage/diagnosis*;
Logistic Models
- From:
Chinese Critical Care Medicine
2024;36(12):1279-1284
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To investigate the independent risk factors for short-term mortality in patients with spontaneous cerebellar hemorrhage (SCH) based on Mimics software of medical image control system.
METHODS:The clinical data of SCH patients treated at Shengjing Hospital of China Medical University from January, 2010 to December, 2021 was retrospectively analyzed and compared, including gender, age, underlyin g diseases, Glasgow coma scale (GCS) and blood pressure at admission, laboratory indicators, imaging data, and short-term (3 weeks after onset) survival status. The imaging examination parameters were accurately calculated using Mimics software, including hematoma volume, longest diameter, and maximum cross-sectional area of cerebellar hemorrhage. Multivariate Logistic regression analysis was used to evaluate the independent risk factors for short-term death in SCH patients. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of the four significant factors on short-term mortality in SCH patients.
RESULTS:A total of 202 patients with SCH were included, of which 42 patients (20.8%) died within 3 weeks of onset and 160 patients (79.2%) survived. Univariate analysis showed that, compared with the survival group, the death group had significantly higher blood glucose, hematoma volume, hematoma longest diameter, hematoma maximum cross-sectional area, the ratio of hematoma maximum cross-section area and the corresponding posterior cranial fossa area, while GCS score was significantly lower, the distance from hematoma edge to the cerebral aqueduct center, and the distance from hematoma edge to the edge of brainstem were significantly shorter, the differences were statistically significant. Multivariate Logistic regression analysis showed that GCS score at admission [odds ratio (OR) = 0.875, 95% confidence interval (95%CI) was 0.767-0.998], hematoma volume (OR = 1.068, 95%CI was 1.022-1.115), the longest diameter of hematoma (OR = 1.086, 95%CI was 1.049-1.124), and the ratio of hematoma maximum cross-section area and the corresponding posterior cranial fossa area (OR = 1.119, 95%CI was 1.060-1.181) were independent risk factors for short-term mortality in SCH patients (all P < 0.05). ROC curve analysis showed that the area under the ROC curve (AUC) for predicting short-term death of patients with SCH were 0.738, 0.839, 0.728 and 0.727, respectively. When the GCS score was 12 at admission, the sensitivity was 85.0% and the specificity was 57.1%. When the hematoma volume was 8.40 mL, the sensitivity was 95.2% and the specificity was 65.0%. When the longest diameter of the hematoma was 47.10 mm, the sensitivity was 57.1% and the specificity was 80.6%. When the ratio of hematoma maximum cross-section area and the corresponding posterior cranial fossa area was 0.11, the sensitivity was 88.1% and the specificity was 48.7%.
CONCLUSIONS:GCS score < 12 on admission, hematoma volume > 8.40 mL, hematoma longest diameter > 47.10 mm, the ratio of hematoma maximum cross-section area and the corresponding posterior cranial fossa area > 0.11 suggest a higher risk of short-term mortality in SCH patients.
