Affiliation:
1. Taizhou Fourth People's Hospital, Taizhou, Jiangsu, China;
2. Graduate School of Dalian Medical University, Dalian, Liaoning, China;
3. Taizhou Fourth People's Hospital, Taizhou City, Jiangsu Province, China;
4. Department of Neurosurgery, Taizhou People's Hospital, Taizhou, Jiangsu, China
Abstract
BACKGROUND AND OBJECTIVES:
Although cranioplasty (CP) is a relatively straightforward surgical procedure, it is associated with a high complication rate. The optimal timing for this surgery remains undetermined. This study aimed to identify the most suitable timing for CP to minimize postoperative complications.
METHODS:
We conducted a retrospective analysis of all CP cases performed in our department from August 2015 to March 2022. Data were gathered through case statistics and categorized based on the occurrence of complications. The collapse ratio was determined using 3-dimensional Slicer software.
RESULTS:
In our retrospective study of 266 patients, 51 experienced postoperative complications, including hydrocephalus, epidural effusion, subdural hematoma, epilepsy, and subcutaneous infection. Logistic regression analysis identified independent predictors of postcranioplasty complications, and a nomogram was developed. The predictive value of the logistic regression model, collapse ratio, and decompression craniotomy-CP operation interval for post–skull repair complications was assessed using receiver operating characteristic curve analysis. No significant differences were observed in postoperative complications and decompression craniotomy-CP intervals between the groups (P = .07, P > .05). However, significant differences were noted in postoperative collapse ratios and CP complications between the groups (P = .023, P < .05). Logistic regression revealed that the collapse ratio (odds ratio = 1.486; 95% CI: 1.001-2.008; P = .01) and CP operation time (odds ratio = 1.017; 95% CI: 1.008-1.025, P < .001) were independent risk factors for postoperative complications. Receiver operating characteristic curve analysis indicated that the collapse ratio could predict CP postoperative complications, with a cutoff value of 0.274, an area under the curve of 0.621, a sensitivity of 62.75%, and a specificity of 63.26%.
CONCLUSION:
The post–skull repair collapse ratio is a significant predictor of postoperative complications. It is advisable to base the timing of surgery on the extent of brain tissue collapse, rather than solely on the duration between cranial decompression and CP.
Funder
Shanghai Pudong New Area Health Commission
Taizhou Municipal Science and Technology Bureau
Science and Technology Plan Project of Taizhou
Publisher
Ovid Technologies (Wolters Kluwer Health)