A Predictive Model of Unfavorable Outcomes After Benign Intracranial Tumor Resection

World Neurosurgery
Kimon BekelisSymeon Missios

Abstract

Benchmarking of outcomes and individualized risk prediction are central in patient-oriented shared decision making. We attempted to create a predictive model of complications in patients undergoing benign intracranial tumor resection. We performed a retrospective cohort study involving patients who underwent craniotomies for benign intracranial tumor resection during the period 2005-2011 and were registered in the National (Nationwide) Inpatient Sample database. A model for outcome prediction based on individual patient characteristics was developed. There were 19,894 patients who underwent benign tumor resection. The respective inpatient postoperative incidences were 1.3% for death, 22.7% for unfavorable discharge, 4.2% for treated hydrocephalus, 1.1% for cardiac complications, 0.9% for respiratory complications, 0.5% for wound infection, 0.5% for deep venous thrombosis, 2.3% for pulmonary embolus, and 1.5% for acute renal failure. Multivariable analysis identified risk factors independently associated with the above-mentioned outcomes. A model for outcome prediction based on patient and hospital characteristics was developed and subsequently validated in a bootstrap sample. The models demonstrated good discrimination with are...Continue Reading

References

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Jul 11, 2001·Mayo Clinic Proceedings·F B MeyerB P O'Neill
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Citations

Jul 6, 2015·World Neurosurgery·L Madison Michael, Paul Klimo
May 26, 2015·World Neurosurgery·Randy L Jensen
Aug 4, 2016·World Neurosurgery·Kimon BekelisNathan Simmons
Dec 23, 2016·World Neurosurgery·Kimon BekelisTodd A MacKenzie
Jul 4, 2017·Neurosurgical Review·Sayied Abdol Mohieb HosaineyTorstein R Meling

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