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Updated: May 2, 2026
Endoscopic Endonasal Trans-sphenoidal Approach: Minimally Invasive Surgery for Pituitary Adenomas
Published on: January 17, 2018
Predictive model for meningitis after pituitary tumor resection by endoscopic nasal trans-sphenoidal sinus approach
Peiyun Zhou1, Jianan Shi1, Zongke Long1
1School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Background:
Meningitis is a significant complication following nasal trans-sphenoidal surgery for pituitary tumor resection. Meningitis increases hospital stays and costs, posing a burden to both patients and healthcare systems. This study aimed to develop a perioperative predictive model for meningitis based on key factors, such as the operation duration, tumor diameter, and intraoperative cerebrospinal fluid (CSF) leakage.
Methods:
A retrospective analysis was conducted on patients undergoing pituitary tumor resection via the nasal trans-sphenoidal approach. Predictive factors for meningitis, including operation duration, tumor diameter, and intraoperative CSF leakage, were analyzed. The model's predictive efficacy was evaluated using the collected data.
Results:
Meningitis occurred in 8.7% of cases (35/401). Intraoperative CSF leakage, observed in 24.2% of cases, significantly increased the risk of infection. The tumor diameter was also linked to higher infection rates. The constructed model demonstrated good predictive performance, allowing for early risk identification.
Conclusions:
This study developed a predictive model for Meningitis after pituitary tumor resection using the operation duration, tumor diameter, and CSF leakage. The model provides healthcare professionals with an effective tool to assess infection risk and implement timely intervention strategies to improve patient outcomes.
Insights
A new model predicts meningitis risk after pituitary tumor surgery. Key factors include operation duration, tumor size, and cerebrospinal fluid (CSF) leakage, enabling early intervention and improved patient outcomes.
Area of Science:
- Neurosurgery
- Oncology
- Infectious Disease Epidemiology
Background:
- Meningitis is a serious complication after trans-sphenoidal pituitary tumor surgery.
- This infection leads to prolonged hospital stays and increased healthcare costs.
- Developing a predictive model is crucial for managing this risk.
Purpose of the Study:
- To develop and validate a perioperative predictive model for meningitis.
- Identify key risk factors associated with meningitis post-surgery.
- Enhance early risk assessment and patient management strategies.
Main Methods:
- Retrospective analysis of patients undergoing trans-sphenoidal pituitary tumor resection.
- Evaluation of operation duration, tumor diameter, and intraoperative cerebrospinal fluid (CSF) leakage as predictive factors.
- Assessment of the model's predictive performance.
Main Results:
- Meningitis incidence was 8.7% (35/401 patients).
- Intraoperative CSF leakage (24.2% of cases) and larger tumor diameter significantly increased meningitis risk.
- The developed model showed effective predictive capabilities for early risk identification.
Conclusions:
- A predictive model for meningitis following pituitary tumor resection was successfully developed.
- The model incorporates operation duration, tumor diameter, and CSF leakage.
- This tool aids healthcare professionals in assessing infection risk and optimizing patient care.
