Scientific Reports (Feb 2023)

A nomogram predictive model for long-term survival in spontaneous intracerebral hemorrhage patients without cerebral herniation at admission

  • Fuxin Lin,
  • Qiu He,
  • Lingyun Zhuo,
  • Mingpei Zhao,
  • Gengzhao Ye,
  • Zhuyu Gao,
  • Wei Huang,
  • Lveming Cai,
  • Fangyu Wang,
  • Huangcheng Shangguan,
  • Wenhua Fang,
  • Yuanxiang Lin,
  • Dengliang Wang,
  • Dezhi Kang

DOI
https://doi.org/10.1038/s41598-022-26176-0
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 11

Abstract

Read online

Abstract Stratification of spontaneous intracerebral hemorrhage (sICH) patients without cerebral herniation at admission, to determine the subgroups may be suffered from poor outcomes or benefit from surgery, is important for following treatment decision. The aim of this study was to establish and verify a de novo nomogram predictive model for long-term survival in sICH patients without cerebral herniation at admission. This study recruited sICH patients from our prospectively maintained ICH patient database (RIS-MIS-ICH, ClinicalTrials.gov Identifier: NCT03862729) between January 2015 and October 2019. All eligible patients were randomly classified into a training cohort and a validation cohort according to the ratio of 7:3. The baseline variables and long-term survival outcomes were collected. And the long-term survival information of all the enrolled sICH patients, including the occurrence of death and overall survival. Follow-up time was defined as the time from the onset to death of the patient or the last clinical visit. The nomogram predictive model was established based on the independent risk factors at admission for long-term survival after hemorrhage. The concordance index (C-index) and ROC curve were used to evaluate the accuracy of the predictive model. Discrimination and calibration were used to validate the nomogram in both the training cohort and the validation cohort. A total of 692 eligible sICH patients were enrolled. During the average follow-up time of 41.77 ± 0.85 months, a total of 178 (25.7%) patients died. The Cox Proportional Hazard Models showed that age (HR 1.055, 95% CI 1.038–1.071, P < 0.001), Glasgow Coma Scale (GCS) at admission (HR 2.496, 95% CI 2.014–3.093, P < 0.001) and hydrocephalus caused by intraventricular hemorrhage (IVH) (HR 1.955, 95% CI 1.362–2.806, P < 0.001) were independent risk factors. The C index of the admission model was 0.76 and 0.78 in the training cohort and validation cohort, respectively. In the ROC analysis, the AUC was 0.80 (95% CI 0.75–0.85) in the training cohort and was 0.80 (95% CI 0.72–0.88) in the validation cohort. SICH patients with admission nomogram scores greater than 87.75 were at high risk of short survival time. For sICH patients without cerebral herniation at admission, our de novo nomogram model based on age, GCS and hydrocephalus on CT may be useful to stratify the long-term survival outcomes and provide suggestions for treatment decision-making.