Journal of neurosurgical anesthesiology
-
J Neurosurg Anesthesiol · Oct 2018
ReviewAnesthesia for Same Day Discharge After Craniotomy: Review of a Single Center Experience.
Same day discharge or outpatient surgery for intracranial procedures has become possible with the advent of image-guided minimally invasive approaches to surgery and availability of short-acting anesthetic agents. In addition, patient satisfaction and the benefits of avoiding hospital stay have resulted in the evolution of neurosurgical day surgery. We reviewed our experience and the available literature to determine the perioperative factors involved which have promoted and will improve this concept in the future. ⋯ Patient perceptions and satisfaction surveys have helped in better understanding and delivery of care and successful outcomes. There are major differences in health care across the globe along with socioeconomic, medicolegal, and ethical disparities, which must be considered before widespread application of this approach. Nevertheless, collaborative effort by surgeons, anesthesiologists, and nurses can help in same day discharge of patients after cranial neurosurgery.
-
J Neurosurg Anesthesiol · Oct 2018
Safety Outcomes Following Spine and Cranial Neurosurgery: Evidence From the National Surgical Quality Improvement Program.
The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) was used to establish predictors for 30-day postoperative complications following spine and cranial neurosurgery. ⋯ After controlling for demographic characteristics, preoperative comorbidities, and perioperative factors, cranial surgery had higher risk for mortality compared with spine surgery despite lower risk for other complications. These findings highlight a discrepancy in the risk for postoperative complications following neurosurgical procedures that requires emphasis within quality improvement initiatives.
-
J Neurosurg Anesthesiol · Oct 2018
Hemodynamic Instability and Cardiovascular Events After Traumatic Brain Injury Predict Outcome After Artifact Removal With Deep Belief Network Analysis.
Hemodynamic instability and cardiovascular events heavily affect the prognosis of traumatic brain injury. Physiological signals are monitored to detect these events. However, the signals are often riddled with faulty readings, which jeopardize the reliability of the clinical parameters obtained from the signals. A machine-learning model for the elimination of artifactual events shows promising results for improving signal quality. However, the actual impact of the improvements on the performance of the clinical parameters after the elimination of the artifacts is not well studied. ⋯ The prevalence of false incidents due to signal artifacts can be significantly reduced using machine-learning. Some clinical events, such as hypotension and alterations in CPP, gain particularly high predictive capacity for patient outcomes after artifacts are eliminated from physiological signals.