Intraoperative blink reflex monitoring during skull base surgery: a single-institution method.

Objective: Cranial nerve (CN) preservation remains a challenge for skull base neurosurgeons, and neurophysiological intraoperative monitoring presents many methods for CN identification and mapping. The blink reflex, which is the electrophysiological representation of the corneal reflex, can be used to test both trigeminal and facial nerve function. The objective of this study was to present a method for obtaining a reliable blink reflex response and maintaining it during the course of a procedure.

Current state of intraoperative neuromonitoring of the facial nerve during skull base surgery: A systematic review.

Intraoperative neuromonitoring of the facial nerve (cranial nerve VII) is critical during skull base surgery due to the nerve's proximity to surgical pathologies and the significant morbidity associated with a facial nerve injury. Objective: This systematic review aims to summarize and describe the numerous intraoperative neuromonitoring techniques available to the skull base surgeon for identification, preservation, and prognostication of facial nerve function during skull base surgery. A systematic review was performed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) checklist.

Intraoperative brain tumor classification via laser-induced fluorescence spectroscopy and machine learning.

Objective: To optimize neurosurgical tumor resection, tissue types and borders must be appropriately identified. Authors of this study established the use of a nondestructive laser-based endogenous fluorescence spectroscopy device, "TumorID," to almost immediately classify a specimen as glioma, meningioma, pituitary adenoma, or nonneoplastic tissue in the operating room, utilizing a machine learning algorithm.

Methods: TumorID requires only 0.

Keyhole Mini-Craniotomy Middle Fossa Approach for Tegmen Repair: A Case Series and Technical Instruction.

 Tegmen defects associated with cerebrospinal fluid (CSF) leaks are a rare pathology that can result in severe complications if left untreated. There is no universal optimal surgical algorithm for repair, although the most common techniques are the middle fossa craniotomy (traditionally 25 cm in area), the transmastoid approach, or both. Here, we describe successful use of a keyhole mini-craniotomy, only 6 cm in area, without mastoidectomy or days of lumbar drainage.

Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?

Objective: The Endoscopic Third Ventriculostomy Success Score (ETVSS) is a useful decision-making heuristic when considering the probability of surgical success, defined traditionally as no repeat cerebrospinal fluid diversion surgery needed within 6 months. Nonetheless, the performance of the logistic regression (LR) model in the original 2009 study was modest, with an area under the receiver operating characteristic curve (AUROC) of 0.68.

A Nationwide Analysis of Aneurysmal Subarachnoid Hemorrhage Mortality, Complications, and Health Economics in the USA.

Aneurysmal subarachnoid hemorrhage (aSAH) is a devastating neurological condition. Endovascular coiling or surgical clipping have equivocal success rates, but relatively little is known regarding the health economics and complications of these procedures at the population level. We aimed to analyze the complication profiles and healthcare resource utilization (HRCU) associated with the treatment of aSAH in the USA.

Treatment Patterns and Health Care Resource Utilization of Iatrogenic Spinal Cerebrospinal Fluid Leaks in the United States.

Study Design: Retrospective cohort study.

Objective: We aimed to characterize the treatment patterns and the associated costs in patients with cerebrospinal fluid (CSF) leak after spine procedures in the United States.

Background: CSF leak is a common complication after spinal procedures.

Machine Learning to Predict Successful Opioid Dose Reduction or Stabilization After Spinal Cord Stimulation.

Background: Spinal cord stimulation (SCS) effectively reduces opioid usage in some patients, but preoperatively, there is no objective measure to predict who will most benefit.

Objective: To predict successful reduction or stabilization of opioid usage after SCS using machine learning models we developed and to assess if deep learning provides a significant benefit over logistic regression (LR).

Methods: We used the IBM MarketScan national databases to identify patients undergoing SCS from 2010 to 2015.

Deep Learning to Predict Traumatic Brain Injury Outcomes in the Low-Resource Setting.

Objective: Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these settings, accurate patient prognostication is both difficult and essential for high-quality patient care. With the ultimate goal of enhancing TBI triage in LMICs, we aim to develop the first deep learning model to predict outcomes after TBI and compare its performance with that of less complex algorithms.

Machine Learning for Predicting In-Hospital Mortality After Traumatic Brain Injury in Both High-Income and Low- and Middle-Income Countries.

Background: Machine learning (ML) holds promise as a tool to guide clinical decision making by predicting in-hospital mortality for patients with traumatic brain injury (TBI). Previous models such as the international mission for prognosis and clinical trials in TBI (IMPACT) and the corticosteroid randomization after significant head injury (CRASH) prognosis calculators can potentially be improved with expanded clinical features and newer ML approaches.

Objective: To develop ML models to predict in-hospital mortality for both the high-income country (HIC) and the low- and middle-income country (LMIC) settings.

Palliative Care Consultations in Patients with Severe Traumatic Brain Injury: Who Receives Palliative Care Consultations and What Does that Mean for Utilization?

Background: Palliative care has the potential to improve goal-concordant care in severe traumatic brain injury (sTBI). Our primary objective was to illuminate the demographic profiles of patients with sTBI who receive palliative care encounters (PCEs), with an emphasis on the role of race. Secondary objectives were to analyze PCE usage over time and compare health care resource utilization between patients with or without PCEs.

Mobile Health Application for Patients Undergoing Breast Cancer Surgery: Feasibility Study.

Purpose: Contemporary breast cancer surgery often requires hospital stays of 1 day or less, presenting challenges to delivery of high-quality care. Without sufficient time for proper education and guidance, patients may delay seeking care, experience anxiety, or seek unnecessary care, leading to poorer outcomes and increased costs. To address this, we evaluated the feasibility of a planning-, outcomes-, and analytics-based mobile health application called Manage My Surgery (MMS) for patients undergoing elective breast cancer surgery.

Corticosteroid Randomization after Significant Head Injury and International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury Models Compared with a Machine Learning-Based Predictive Model from Tanzania.

Hospitals in low- and middle-income countries (LMICs) could benefit from decision support technologies to reduce time to triage, diagnosis, and surgery for patients with traumatic brain injury (TBI). Corticosteroid Randomization after Significant Head Injury (CRASH) and International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury (IMPACT) are robust examples of TBI prognostic models, although they have yet to be validated in Sub-Saharan Africa (SSA). Moreover, machine learning and improved data quality in LMICs provide an opportunity to develop context-specific, and potentially more accurate, prognostic models.

A high-resolution interactive atlas of the human brainstem using magnetic resonance imaging.

Conventional atlases of the human brainstem are limited by the inflexible, sparsely-sampled, two-dimensional nature of histology, or the low spatial resolution of conventional magnetic resonance imaging (MRI). Postmortem high-resolution MRI circumvents the challenges associated with both modalities. A single human brainstem specimen extending from the rostral diencephalon through the caudal medulla was prepared for imaging after the brain was removed from a 65-year-old male within 24 h of death.

Complementary and alternative medicine in children with diffuse intrinsic pontine glioma-A SIOPE DIPG Network and Registry study.

Introduction: Diffuse intrinsic pontine glioma (DIPG) is a rare and aggressive childhood brainstem malignancy with a 2-year survival rate of <10%. This international survey study aims to evaluate the use of complementary and alternative medicine (CAM) in this patient population.

Methods: Parents and physicians of patients with DIPG were asked to participate in a retrospective online survey regarding CAM use during time of illness.

Outcomes and Health Care Resource Utilization of Adult Bacterial Meningitis in the United States.

Objective: To examine the longitudinal health care resource utilization, in-hospital mortality, and incidence of downstream complications of bacterial meningitis in the United States.

Methods: Using IBM MarketScan, we retrieved data on adult patients with a diagnosis of bacterial meningitis admitted to a US hospital between 2008 and 2015. Patients were stratified into groups (1) with/without prior head trauma/neurosurgical complications, (2) nosocomial/community acquisition, and (3) Gram-negative/positive bacteria.

Surgical intervention and patient factors associated with poor outcomes in patients with traumatic brain injury at a tertiary care hospital in Uganda.

Objective: The purpose of this study was to investigate whether neurosurgical intervention for traumatic brain injury (TBI) is associated with reduced risks of death and clinical deterioration in a low-income country with a relatively high neurosurgical capacity. The authors further aimed to assess whether the association between surgical intervention and acute poor outcomes differs according to TBI severity and various patient factors.

Methods: Using TBI registry data collected from a national referral hospital in Uganda between July 2016 and April 2020, the authors performed Cox regression analyses of poor outcomes in admitted patients who did and did not undergo surgery for TBI, with surgery as a time-varying treatment variable.

Inpatient mortality and healthcare resource utilization of nontraumatic intracerebral hemorrhage complications in the US.

Objective: Nontraumatic, primary intracerebral hemorrhage (ICH) accounts for 2 million strokes worldwide annually and has a 1-year survival rate of 50%. Recent studies examining functional outcomes from ICH evacuation have been performed, but limited work has been done quantifying the incidence of subsequent complications and their healthcare economic impact. The purpose of this study was to quantify the incidence and healthcare resource utilization (HCRU) for major complications that can arise from ICH.

A Smartphone App With a Digital Care Pathway for Patients Undergoing Spine Surgery: Development and Feasibility Study.

Background: There is a great unmet clinical need to provide patients undergoing spinal surgery and their caregivers with ongoing, high-quality care before and after surgery in an efficiency-focused health care environment.

Objective: The objective of this study is to design, develop, and evaluate the acceptability and feasibility of a novel planning-, outcomes-, and analytics-based smartphone app called ManageMySurgery (MMS) in patients undergoing elective spine surgery (MMS-Spine).

Methods: The development process of the MMS app was conducted over 2 sequential stages: (1) an evidence-based intervention design with refinement from surgeon and patient feedback and (2) feasibility testing in a clinical pilot study.

Health care resource utilization and treatment of leptomeningeal carcinomatosis in the United States.

Background: The economic burden of cancer in the United States is substantial, and better understanding it is essential in informing health care policy and innovation. Leptomeningeal carcinomatosis (LC) represents a late complication of primary cancer spreading to the leptomeninges.

Methods: The IBM MarketScan Research databases were queried for adults diagnosed with LC from 2001 to 2015, secondary to 4 primary cancers (breast, lung, gastrointestinal, and melanoma).

Paediatric bacterial meningitis in the USA: outcomes and healthcare resource utilization of nosocomial versus community-acquired infection.

Paediatric bacterial meningitis remains a costly disease, both financially and clinically.. Previous epidemiological and cost studies of bacterial meningitis (BM) have largely focused on adult populations or single pathogens.

Predicting the Individual Treatment Effect of Neurosurgery for Patients with Traumatic Brain Injury in the Low-Resource Setting: A Machine Learning Approach in Uganda.

Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these low-resource settings, effective triage of patients with TBI-including the decision of whether or not to perform neurosurgery-is critical in optimizing patient outcomes and healthcare resource utilization. Machine learning may allow for effective predictions of patient outcomes both with and without surgery.

Impact of Spinal Cord Stimulation on Opioid Dose Reduction: A Nationwide Analysis.

Background: Opioid misuse in the USA is an epidemic. Utilization of neuromodulation for refractory chronic pain may reduce opioid-related morbidity and mortality, and associated economic costs.

Objective: To assess the impact of spinal cord stimulation (SCS) on opioid dose reduction.

Painful diabetic peripheral neuropathy: Health care costs and complications from 2010 to 2015.

Objective: To quantify health care resource utilization and risk of complications in painful diabetic peripheral neuropathy (pDPN).

Methods: Adult patients diagnosed with diabetes mellitus or diabetic peripheral neuropathy (DPN) were identified in MarketScan from January 2010 to December 2015. Subgroups (pDPN and nonpainful DPN) were based on the use of pain medications 6 months before a new indexed diagnosis and 1 year thereafter.

The longitudinal health economic impact of viral encephalitis in the United States.

Previous studies of viral encephalitis have focused on acute costs, estimating incidence at 7.3 per 100 000 and total US annual charges at $2 billion in 2010. We aim to quantify the most updated longitudinal health economic impact of viral encephalitis in the USA from 2008 to 2015.