Delayed postoperative impedance issues in patients treated with deep brain stimulation: A single-center retrospective study.

Background: In rare circumstances, an implanted deep brain stimulation device will develop impedance issues across its contacts. Even more rare is the resultant inability to program a patient effectively, or that the patients' prior programming settings become unusable.

Objective: In this study we investigate this occurrence across the device manufacturers implanted, and whether this could be resolved.

Can Artificial Intelligence Mitigate Missed Diagnoses by Generating Differential Diagnoses for Neurosurgeons?

Background/objective: Neurosurgery emphasizes the criticality of accurate differential diagnoses, with diagnostic delays posing significant health and economic challenges. As large language models (LLMs) emerge as transformative tools in healthcare, this study seeks to elucidate their role in assisting neurosurgeons with the differential diagnosis process, especially during preliminary consultations.

Methods: This study employed 3 chat-based LLMs, ChatGPT (versions 3.

Impact of environmental pollutants on pediatric brain tumor incidence in New Jersey.

Objective: The relationship between environmental contaminants and brain tumor incidence in adults has been thoroughly explored but research into how these contaminants affect pediatric brain tumor (PBT) incidence has not been explored. Children, typically having more limited geographical movement and thus more consistent environmental contaminant exposure, might offer more reliable insights into which environmental contaminants affect the incidence of brain tumors. The present study is the first to focus on exploring whether a possible association exists between the incidence of PBTs and exposure to environmental pollutants in New Jersey (NJ).

Analysis of Concussions Reported in American Professional Football Injury Reports in the 2019 Through 2023 Regular Seasons.

Objective: The National Football League (NFL) has seen increasing scrutiny regarding its management of concussions, especially following an on-field incident involving the Miami Dolphins' quarterback Tua Tagovailoa in the 2022 season. We hope to elucidate the recent trends in the diagnosis and management of concussions during the course of 5 NFL seasons from 2019 to 2023.

Methods: We queried the NFL injury reports from the 2019 through 2023 database recording players listed with concussions.

Assessing Diversity, Equity, and Inclusion in Patient-Facing Websites in Neurosurgical Departments in the United States.

Background: Patient-facing websites serve as essential platforms for disseminating information, engaging with patients, and increasing access to neurosurgical resources and services. Diversity, Equity, and Inclusion are at the forefront of issues facing the field of neurosurgery, especially concerning race and gender disparities in regards to providers in the field.

Methods: Data were collected in regards to the race and gender of patients and providers displayed on the neurosurgery department's patient-facing website in addition to accommodations for disabilities, decreased ability to pay, and language.

Endoscopic Endonasal Transsphenoidal Surgery for the Resection of Pituitary Adenomas: A Prime Candidate for a Shortened Length of Stay Enhanced Recovery after Surgery Protocol? A Systematic Review.

Background: Enhanced Recovery After Surgery (ERAS) is a perioperative model of care aimed at optimizing postoperative rehabilitation and reducing hospital length of stay (LOS). Decreasing LOS avoids hospital-acquired complications, reduces cost of care, and improves patient satisfaction. Given the lack of ERAS protocols for endoscopic endonasal transsphenoidal surgery (EETS) resection of pituitary adenomas, a systematic review of EETS was performed to compile patient outcomes and analyze factors that may lead to increased LOS, reoperation, and readmission rates with the intention to contribute to the development of a successful ERAS protocol for EETS.

Can Publicly Available Artificial Intelligence Successfully Identify Current Procedural Terminology Codes for Common Procedures in Neurosurgery?

Objective: Coding for neurosurgical procedures is a complex process that is dynamically changing year to year, through the annual introduction and removal of codes and modifiers. The authors hoped to elucidate if publicly available artificial intelligence (AI) could offer solutions for neurosurgeons with regard to coding.

Methods: Multiple publicly available AI platforms were asked to provide Current Procedural Terminology (CPT) codes and Revenue Value Units (RVU) values for common neurosurgical procedures of the brain and spine with a given indication for the procedure.

Antimicrobial Sensitivity Pattern of Salmonella Typhi: Emergence of Resistant Strains.

Background Typhoid fever is still an important public health problem in developing countries. Increasing resistance of Salmonella Typhi to antibiotics is alarming. New extensively drug-resistant strains of Salmonella reported first time in Pakistan, resistant not only to first-line drugs and ciprofloxacin but also resistant to ceftriaxone, had spread globally, including the USA.

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures.

Spiking Neural Networks (SNNs) have recently emerged as a prominent neural computing paradigm. However, the typical shallow SNN architectures have limited capacity for expressing complex representations while training deep SNNs using input spikes has not been successful so far. Diverse methods have been proposed to get around this issue such as converting off-the-shelf trained deep Artificial Neural Networks (ANNs) to SNNs.

Rubus: A compiler for seamless and extensible parallelism.

Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU), originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently.

Weighted-incidence syndromic combination antibiograms to guide empiric treatment of critical care infections: a retrospective cohort study.

Introduction: Empiric antimicrobial selection for critical care infections must balance the need for timely adequate coverage with the resistance pressure exerted by broadspectrum agents. We estimated the potential of weighted incidence syndromic combination antibiograms (WISCAs) to improve time to adequate coverage for critical care infections. In contrast to traditional antibiograms, WISCAs display the likelihood of coverage for a specific infectious syndrome (rather than individual pathogens), and also take into account the potential for poly-microbial infections and the use of multi-drug regimens.

Effect of selective decontamination on antimicrobial resistance in intensive care units: a systematic review and meta-analysis.

Background: Many meta-analyses have shown reductions in infection rates and mortality associated with the use of selective digestive decontamination (SDD) or selective oropharyngeal decontamination (SOD) in intensive care units (ICUs). These interventions have not been widely implemented because of concerns that their use could lead to the development of antimicrobial resistance in pathogens. We aimed to assess the effect of SDD and SOD on antimicrobial resistance rates in patients in ICUs.