Citations

Objectives: Every year, around 300 million surgeries are conducted worldwide, with an estimated 4.2 million deaths occurring within 30 days after surgery. Adequate patient education is crucial, but often falls short due to the stress patients experience before surgery. Large language models (LLMs) can significantly enhance this process by delivering thorough information and addressing patient concerns that might otherwise go unnoticed. Material and methods: This cross-sectional study evaluated Chat Generative Pretrained Transformer-4o’s audio-based responses to frequently asked questions (FAQs) regarding six general surgical procedures. Three experienced surgeons and two senior residents formulated seven general and three procedure-specific FAQs for both preoperative and postoperative situations, covering six surgical scenarios (major: pancreatic head resection, rectal resection, total gastrectomy; minor: cholecystectomy, Lichtenstein procedure, hemithyroidectomy). In total, 120 audio responses were generated, transcribed, and assessed by 11 surgeons from 6 different German university hospitals. Results: ChatGPT-4o demonstrated strong performance, achieving an average score of 4.12/5 for accuracy, 4.46/5 for relevance, and 0.22/5 for potential harm across 120 questions. Postoperative responses surpassed preoperative ones in both accuracy and relevance, while also exhibiting lower potential for harm. Additionally, responses related to minor surgeries were minimal, but significantly more accurate compared to those for major surgeries. Conclusions: This study underscores GPT-4o’s potential to enhance patient education both before and after surgery by delivering accurate and relevant responses to FAQs about various surgical procedures. Responses regarding the postoperative course proved to be more accurate and less harmful than those addressing preoperative ones. Although a few responses carried moderate risks, the overall performance was robust, indicating GPT-4o’s value in patient education. The study suggests the development of hospital-specific applications or the integration of GPT-4o into interactive robotic systems to provide patients with reliable, immediate answers, thereby improving patient satisfaction and informed decision-making.

INTRODUCTION: To assess strategies for optimizing participation of underserved minorities in a blood-based early colorectal cancer detection test study (PREEMPT CRC; NCT04369053) at a hospital serving primarily Black individuals. METHODS: Culturally sensitive, racially congruent research staff approached individuals undergoing average-risk screening colonoscopy. Consent/study procedures were synchronized with clinical appointments. Enrolled and not-enrolled patient characteristics were compared. Recruitment was compared with other study sites. RESULTS: In total, 247 of 509 eligible individuals were enrolled; most were identified as Black (88.7%). No baseline characteristics were associated with participation. Recruitment was high compared with other sites (11th centile). DISCUSSION: Recruitment barriers for Black individuals can be overcome when easy, culturally sensitive access is facilitated.

Introduction Although the prevalence of chemotherapy-induced peripheral neuropathy (CIPN) has been reported, the proportion of patients with CIPN who report chronic moderate-to-severe neuropathy or chronic painful neuropathy remains poorly understood, despite its significant impact on patients’ quality of life and treatment outcomes. Methods A systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The primary outcome was the pooled prevalence of chronic (≥3 months) moderate-to-severe CIPN or painful CIPN among patients diagnosed with CIPN. Estimates from each study were transformed using a double-arcsine transformation and pooled in a meta-analysis using an inverse variance heterogeneity model. Subgroup analysis was conducted based on geographical region, sex, chemotherapy regimen, primary cancer type, and funding source; metaregression analysis was conducted based on study design, human development index (HDI), and publication year. Results 76 studies from 29 countries, encompassing 13 635 patients with CIPN, were included. Among patients diagnosed with CIPN, the pooled prevalence of those reporting chronic moderate-to-severe CIPN or painful CIPN was estimated at 47.76% (95% CI 37.50 to 58.08; 95% prediction interval 24.68–71.84). Substantial heterogeneity was observed across studies ( I² =97.45%; 95% CI for I 2 97.15 to 97.72). Subgroup analysis revealed that patients treated with platinum-based agents and taxanes had the highest prevalence of chronic moderate-to-severe CIPN or painful CIPN (44.47% and 55.68%, respectively), and among primary cancers, those with breast cancer, multiple myeloma, and lung cancer reported the highest prevalence of chronic moderate-to-severe CIPN or painful CIPN (61.31%, 53.55%, and 50.85%, respectively). Study design, HDI, and publication year were non-significant moderators of prevalence estimates. Based on our Grading of Recommendations, Assessment, Development, and Evaluation assessment, the certainty of evidence was considered “very low.” Sensitivity analysis restricted to studies explicitly measuring painful CIPN (40.78%; 95% CI 29.08 to 52.74) or moderate-to-severe CIPN (49.04%; 95% CI 37.16 to 60.95) yielded similar prevalence estimates. Conclusion This study provides the first comprehensive global estimate of the prevalence of chronic moderate-to-severe CIPN or painful CIPN, highlighting its significant burden on patients worldwide. The variation in prevalence across geographical regions, chemotherapy regimens, and primary cancers underscores the need for tailored management strategies and further research to address potential disparities.

Study Design. Retrospective observational study. Objective. To evaluate whether the combined American Spine Registry and Medicare (ASR/CMS) data yield substantially different findings versus ASR data alone with regard to key parameters such as risk stratification, complication rates, and readmission rates in lumbar surgery investigated through an analysis of 8755 spondylolisthesis cases. Summary of Background Data. Medicare data correlation has been effective for determining revision rates for other procedures, such as total hip replacement. Our aim is to determine whether these findings are translatable in the realm of lumbar spinal surgery investigated through an analysis of 8755 spondylolisthesis cases. Materials and Methods. The American Spine Registry (ASR) was queried for Medicare-eligible patients who underwent lumbar spinal fusion for lumbar spondylolisthesis. This cohort was analyzed based on ASR data alone in comparison to the same patients in the combined ASR/Medicare (ASR/CMS) data set. The primary outcome of interest was readmission at 30 and 90 days postoperatively. Results. There were 8755 Medicare-eligible cases with a diagnosis of spondylolisthesis within the ASR. The mean age was 72.7 years and 60.8% were female. Medical comorbidities were more frequently detected in the combined ASR/CMS data set, reflected by a higher mean Charlson Comorbidity Index score (3.49 vs. 3.27, P<0.001). Hospital readmission rates were significantly higher in the combined ASR/CMS data set at both 30 days (4.89% vs. 1.83%, P<0.001) and 90 days (7.68% vs. 2.66%, P<0.001), with notable increases in readmissions for infections and medical complications. Discharge disposition remained comparable across data sets, with most patients discharged to home or home health care. Conclusion. This study demonstrates that integrating patient-identified Medicare data with the ASR provides a more comprehensive assessment of outcomes for lumbar spinal fusion surgery as demonstrated through an analysis of 8755 spondylolisthesis cases. These findings, establish the importance of multisource data linkage to overcome the limitations of single-source registries, thereby enhancing data quality for clinical decision-making and quality improvement in spinal surgery.

A 67-year-old male with positive signals for neuroendocrine and head/neck cancer on a commercially available multicancer detection test underwent an extensive negative diagnostic workup at a local hospital. Referred to our medical center for advanced imaging and endoscopic procedures ultimately led to the diagnosis of an early-stage seminoma with eventual orchiectomy. This case highlights challenges in evaluating positive multicancer detection results, emphasizing the need for a broader understanding of how to interpret these testing results to fully evaluate complex cases, as well as the need for protocolized follow-up approaches to a positive multicancer detection test.

Abstract The common practice in meta‐analysis and clinical practice guidelines is to derive the absolute treatment effect (also called risk difference, RD) from a combination of a pooled relative risk (RR) that resulted from a meta‐analysis, and a user‐provided baseline risk (BR). However, this method does not address the uncertainty in BR. We developed a web‐based R Shiny tool to perform simple microsimulation and incorporate uncertainty in BR into the precision of RD. We empirically evaluated this approach by estimating the impact of incorporating this uncertainty when BR is derived from the control group rates in 3,128 meta‐analyses curated from the Cochrane Library (26,964 individual studies). When BR was derived from the largest study in each meta‐analysis, the median width of the CI of BR was 11.6% (interquartile range (IQR), 6.30%–18.5%). Incorporating this uncertainty in BR led to expansion of the RD CI by a median of 8 per 1,000 persons (IQR 2–24). This expansion increased in a linear fashion with BR imprecision and was more prominent in meta‐analyses with low BR. This study provides a web‐based tool to perform simple microsimulation and incorporate uncertainty in BR into the CI of RD.