The Statistical Fragility of Lumbar Disc Arthroplasty vs Lumbar Fusion: A Systematic Review of Randomized Controlled Trials.

Study DesignSystematic Review of Randomized Controlled Trials.ObjectivesTo assess the statistical fragility of randomized controlled trials (RCTs) comparing lumbar fusion and lumbar disc arthroplasty (LDA).MethodsFollowing PRISMA guidelines, PubMed, Embase, and Medline databases were searched for RCTs on lumbar fusion and LDA published between January 1, 2000 and August 1, 2023.

Associations Between Patients' Primary Spoken Language and Perioperative Outcomes After Hip Fracture.

Introduction: Recently, the role of a patient's primary spoken language (PSL) has emerged as a potential contributor to perioperative outcomes. This study aimed to identify the association between a patient's PSL and hip fracture perioperative outcomes, including hospital length of stay (LOS), in-hospital mortality, nonhome discharge, 30-day emergency department visits, 90-day readmissions, and 90-day complications.

Methods: An institutional review board-approved retrospective cohort study was performed using institutional data.

Socioeconomic and Demographic Variables Are Lacking in Meniscectomy Randomized Controlled Trials: A Systematic Review.

Purpose: To evaluate the inclusion of sociodemographic factors in randomized controlled trials (RCTs) on meniscectomy outcomes, with the goal of understanding the extent to which RCTs on meniscectomy consider sociodemographic variables.

Methods: PubMed, Embase, and MEDLINE were queried from January 1, 2014, to October 10, 2024, for meniscectomy RCTs in high-impact journals. Each RCT was assessed for inclusion of the following background and sociodemographic variables: age, sex, body mass index (BMI), race/ethnicity, education level, insurance, smoking/tobacco use, socioeconomic status, marital status, alcohol use, proficiency in country's official language, employment status, and residence status.

Can generative artificial intelligence provide accurate medical advice?: a case of ChatGPT versus Congress of Neurological Surgeons management of acute cervical spine and spinal cord injuries clinical guidelines.

Study Design: An experimental study.

Purpose: To explore the concordance of ChatGPT responses with established national guidelines for the management of cervical spine and spinal cord injuries.

Overview Of Literature: ChatGPT-4.

Reducing postoperative morbidity by diminishing chest tube drainage utilizing tranexamic acid following vertebral body tethering for adolescent idiopathic scoliosis.

Purpose: Vertebral body tethering (VBT) is a non-fusion surgical option for adolescent idiopathic scoliosis (AIS) that requires a postoperative (PO) chest tube. This study evaluates whether 48 h of PO TXA reduces chest tube (CT) drainage and retention compared to 24 h of TXA following VBT for AIS.

Methods: Consecutively treated patients with a diagnosis of AIS who underwent VBT were assessed.

Racial Disparities in Utilization and Outcomes of Cervical Disc Arthroplasty.

Study Design: Retrospective study.

Objective: We examined racial disparities in (1) cervical disc arthroplasty (CDA) versus anterior cervical discectomy and fusion (ACDF) utilization and (2) CDA in-hospital outcomes.

Summary Of Background Data: ACDF and CDA are established treatments for cervical disc disease.

Associations Between Patients' Primary Language and Outcomes and Patient Engagement Process Metrics for Total Joint Arthroplasty.

Introduction: Previous research has indicated language-based disparities in outcomes after total hip and knee arthroplasty. In this study, we examined the relationship between primary spoken language and outcomes and patient engagement process metrics in a multihospital academic health system.

Methods: This retrospective cohort study included patients who underwent elective primary total hip or knee arthroplasty in 2018 to 2022.

Can Large Language Models (LLMs) Predict the Appropriate Treatment of Acute Hip Fractures in Older Adults? Comparing Appropriate Use Criteria With Recommendations From ChatGPT.

Background: Acute hip fractures are a public health problem affecting primarily older adults. Chat Generative Pretrained Transformer may be useful in providing appropriate clinical recommendations for beneficial treatment.

Objective: To evaluate the accuracy of Chat Generative Pretrained Transformer (ChatGPT)-4.

Differences in Perioperative Metrics by Race and Ethnicity and Insurance After Pelvic Fracture: A Nationwide Study.

Background: Disparities in orthopedic trauma care have been reported for racial-ethnic minority and socially disadvantaged patients. We examined differences in perioperative metrics by patient race and ethnicity and insurance after pelvic fracture in a national sample in the United States.

Materials And Methods: The 2016-2019 National Inpatient Sample was queried for White, Black, and Hispanic patients 18 to 64 years old with private, Medicaid, or self-pay insurance who underwent non-elective pelvic fracture surgery.

Performance of a Large Language Model in the Generation of Clinical Guidelines for Antibiotic Prophylaxis in Spine Surgery.

Objective: Large language models, such as chat generative pre-trained transformer (ChatGPT), have great potential for streamlining medical processes and assisting physicians in clinical decision-making. This study aimed to assess the potential of ChatGPT's 2 models (GPT-3.5 and GPT-4.

ChatGPT versus NASS clinical guidelines for degenerative spondylolisthesis: a comparative analysis.

Background Context: Clinical guidelines, developed in concordance with the literature, are often used to guide surgeons' clinical decision making. Recent advancements of large language models and artificial intelligence (AI) in the medical field come with exciting potential. OpenAI's generative AI model, known as ChatGPT, can quickly synthesize information and generate responses grounded in medical literature, which may prove to be a useful tool in clinical decision-making for spine care.

Performance of ChatGPT on NASS Clinical Guidelines for the Diagnosis and Treatment of Low Back Pain: A Comparison Study.

Study Design: Comparative analysis.

Objective: To evaluate Chat Generative Pre-trained Transformer (ChatGPT's) ability to predict appropriate clinical recommendations based on the most recent clinical guidelines for the diagnosis and treatment of low back pain.

Background: Low back pain is a very common and often debilitating condition that affects many people globally.

ChatGPT and its Role in the Decision-Making for the Diagnosis and Treatment of Lumbar Spinal Stenosis: A Comparative Analysis and Narrative Review.

Study Design: Comparative Analysis and Narrative Review.

Objective: To assess and compare ChatGPT's responses to the clinical questions and recommendations proposed by The 2011 North American Spine Society (NASS) Clinical Guideline for the Diagnosis and Treatment of Degenerative Lumbar Spinal Stenosis (LSS). We explore the advantages and disadvantages of ChatGPT's responses through an updated literature review on spinal stenosis.