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Minimally Invasive Thumb-sized Pterional Craniotomy for Surgical Clip Ligation of Unruptured Anterior Circulation Aneurysms
Published on: August 11, 2015
Predicting inpatient complications from cerebral aneurysm clipping: the Nationwide Inpatient Sample 2005-2009
Kimon Bekelis1, Symeon Missios, Todd A MacKenzie
1Appledore Neurosurgery Group, Portsmouth Hospital, Portsmouth;
Insights
A new predictive model estimates individual patient risks for complications after cerebral aneurysm clipping surgery. This tool aids neurosurgeons in making informed decisions for better patient outcomes.
Area of Science:
- Neurosurgery
- Vascular Surgery
- Medical Informatics
Background:
- Accurate risk assessment is vital for patient management in cerebrovascular neurosurgery.
- Cerebral aneurysm clipping (CAC) carries significant risks of morbidity and mortality.
- Individualized risk prediction is essential for optimizing surgical decision-making.
Purpose of the Study:
- To develop a predictive model for postoperative complications in patients undergoing cerebral aneurysm clipping (CAC).
- To identify preoperative patient characteristics associated with adverse outcomes.
- To provide an adjunct tool for clinical decision support in neurosurgery.
Main Methods:
- Retrospective cohort study utilizing the Nationwide Inpatient Sample (NIS) database (2005-2009).
- Analysis of 7651 patients who underwent CAC, categorized by ruptured versus unruptured aneurysms.
- Development and validation of a predictive model based on preoperative patient data, assessed using the area under the receiver operating characteristic curve.
Main Results:
- Patients with ruptured aneurysms faced substantially higher risks for death (11.5% vs. 0.7%), unfavorable discharge (52.8% vs. 15.3%), and hydrocephalus (39.2% vs. 1.5%) compared to those with unruptured aneurysms.
- Multivariate analysis identified key independent risk factors for various postoperative complications.
- The developed predictive model demonstrated good discrimination accuracy.
Conclusions:
- A validated model can provide individualized risk estimates for postoperative complications following CAC.
- This predictive tool can assist cerebrovascular neurosurgeons in preoperative decision-making.
- The model enhances personalized risk assessment for patients undergoing aneurysm clipping.
Object:
Precise delineation of individualized risks of morbidity and mortality is crucial in decision making in cerebrovascular neurosurgery. The authors attempted to create a predictive model of complications in patients undergoing cerebral aneurysm clipping (CAC).
Methods:
The authors performed a retrospective cohort study of patients who had undergone CAC in the period from 2005 to 2009 and were registered in the Nationwide Inpatient Sample (NIS) database. A model for outcome prediction based on preoperative individual patient characteristics was developed.
Results:
Of the 7651 patients in the NIS who underwent CAC, 3682 (48.1%) had presented with unruptured aneurysms and 3969 (51.9%) with subarachnoid hemorrhage. The respective inpatient postoperative risks for death, unfavorable discharge, stroke, treated hydrocephalus, cardiac complications, deep vein thrombosis, pulmonary embolism, and acute renal failure were 0.7%, 15.3%, 5.3%, 1.5%, 1.3%, 0.6%, 2.0%, and 0.1% for those with unruptured aneurysms and 11.5%, 52.8%, 5.5%, 39.2%, 1.7%, 2.8%, 2.7%, and 0.8% for those with ruptured aneurysms. Multivariate analysis identified risk factors independently associated with the above outcomes. A validated model for outcome prediction based on individual patient characteristics was developed. The accuracy of the model was estimated using the area under the receiver operating characteristic curve, and it was found to have good discrimination.
Conclusions:
The featured model can provide individualized estimates of the risks of postoperative complications based on preoperative conditions and can potentially be used as an adjunct in decision making in cerebrovascular neurosurgery.
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