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A Low Mortality Rat Model to Assess Delayed Cerebral Vasospasm After Experimental Subarachnoid Hemorrhage
Published on: January 17, 2013
Development and validation of an early predictive nomogram for delayed cerebral ischemia after aneurysmal
Long Zhao1,2,3, Tao Chen2,4, Hao-Ji Yan5
1Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
Background:
Previous studies have shown that platelet is involved in the occurrence and progression of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH), but the relationship between platelet and DCI is not completely clear. Here, we aimed to screen the early platelet parameters associated with DCI after aSAH and develop an early predictive nomogram for DCI after aSAH.
Methods:
The study was carried out in the neurosurgery department of Affiliated Hospital of North Sichuan Medical College. A total of 285 consecutive aSAH patients admitted within 24 hours after onset were analyzed retrospectively. Univariate and multivariate analyses were used to identify risk factors for DCI. A predictive nomogram was developed and validated with R software.
Results:
Sixty-six (23.16%) of the 285 patients with aSAH exhibited DCI during hospitalization. The DCI group and the non-DCI group showed statistically significant differences in red blood cell count (RBC), platelet count (PLT), mean platelet volume (MPV), modified Fisher grade and platelet distribution width (PDW). Multivariable logistic regression analysis showed that modified Fisher grade [odds ratio (OR) =1.354; 95% confidence interval (CI): 1.034-1.773; P=0.028] and mean MPV [OR =1.825; 95% CI: 1.429-2.331; P<0.001] were independent risk factors for DCI. Modified Fisher grade, RBC, PLT, MPV, and PDW were used to develop a predictive nomogram for DCI. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.799 (95% CI: 0.737-0.861) in the training set and 0.783 (95% CI: 0.616-0.949) in the validation set. The calibration curve showed that the predicted probability concurred with the actual probability. Decision curve analysis indicated that this nomogram had good clinical application value and could be used for clinical decision making.
Conclusions:
Our study found that MPV was an early predictor of DCI after aSAH. The nomogram incorporating early MPV had greater value in predicting DCI after aSAH.
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