Citations

History A 30-year-old female patient with a history of infertility and no pregnancy presented to the gynecologic endometriosis clinic for follow-up 1 month after oocyte retrieval, to be evaluated for pelvic optimization before potential embryo transfer, with worsening dysmenorrhea, dyspareunia, and overall pelvic pain. Eleven years prior, the patient had undergone left ovarian cystectomy for treatment of endometrioma, as well as excision of deep infiltrative endometriosis. The oocyte retrieval procedure, where more than 30 eggs were retrieved, was complicated by ovarian hyperstimulation syndrome and intraperitoneal bleeding, which necessitated admission to the intensive care unit (ICU) for 3 days. Following discharge from the ICU, the patient experienced occasional on-and-off pressure of the urinary bladder and persistent aching pelvic pain. At the 1-month follow-up appointment, the patient’s vital signs were assessed (blood pressure, 142/94 mm Hg; pulse rate, 95 per minute; temperature, 96.8 °F [36 °C]). Routine blood investigations, including white blood cell count, were within normal limits. Physical examination showed the abdomen was soft but there was mild pelvic tenderness. The serum β–human chorionic gonadotropin test result was negative for pregnancy, and urinalysis testing showed no leukocyte esterase or nitrites. MRI of the pelvis ( Figs 1 – 3 ) was performed to evaluate the worsening pain.

Purpose To assess the ability of ChatGPT‐4, an automated Chatbot powered by artificial intelligence, to answer common patient questions concerning the Latarjet procedure for patients with anterior shoulder instability and compare this performance with Google Search Engine. Methods Using previously validated methods, a Google search was first performed using the query “Latarjet.” Subsequently, the top 10 frequently asked questions (FAQs) and associated sources were extracted. ChatGPT‐4 was then prompted to provide the top 10 FAQs and answers concerning the procedure. This process was repeated to identify additional FAQs requiring discrete‐numeric answers to allow for a comparison between ChatGPT‐4 and Google. Discrete, numeric answers were subsequently assessed for accuracy on the basis of the clinical judgment of 2 fellowship‐trained sports medicine surgeons who were blinded to search platform. Results Mean (± standard deviation) accuracy to numeric‐based answers was 2.9 ± 0.9 for ChatGPT‐4 versus 2.5 ± 1.4 for Google ( P = .65). ChatGPT‐4 derived information for answers only from academic sources, which was significantly different from Google Search Engine ( P = .003), which used only 30% academic sources and websites from individual surgeons (50%) and larger medical practices (20%). For general FAQs, 40% of FAQs were found to be identical when comparing ChatGPT‐4 and Google Search Engine. In terms of sources used to answer these questions, ChatGPT‐4 again used 100% academic resources, whereas Google Search Engine used 60% academic resources, 20% surgeon personal websites, and 20% medical practices ( P = .087). Conclusions ChatGPT‐4 demonstrated the ability to provide accurate and reliable information about the Latarjet procedure in response to patient queries, using multiple academic sources in all cases. This was in contrast to Google Search Engine, which more frequently used single‐surgeon and large medical practice websites. Despite differences in the resources accessed to perform information retrieval tasks, the clinical relevance and accuracy of information provided did not significantly differ between ChatGPT‐4 and Google Search Engine. Clinical Relevance Commercially available large language models (LLMs), such as ChatGPT‐4, can perform diverse information retrieval tasks on‐demand. An important medical information retrieval application for LLMs consists of the ability to provide comprehensive, relevant, and accurate information for various use cases such as investigation about a recently diagnosed medical condition or procedure. Understanding the performance and abilities of LLMs for use cases has important implications for deployment within health care settings.

Abstract Flexor tendon injury is a common hand trauma that requires surgical repair. The objective was to compare the repaired strength and gliding resistance with a varied number of repair strands and of square knots using a two‐strand‐overhand locking (TSOL) knot. First, isolated suture loops with different number of suture strands and number of closing knots were compared in mechanical strength and failure mode. Then, 90 flexor digitorum profundus (FDP) tendons from turkey digits were used for the tendon repair experiment. Both phases followed a similar 3 × 3 matrix comparing the knot type including TSOL+1SK (square knot), TSOL+2SK, and TSOL+3 SK and repair techniques including two‐, four‐, and six‐strand repairs techniques respectively. The repaired tendons were tested for tendon resistance against pulley (friction), maximum force, force at 2 mm displacement, stiffness, and failure mode. Increasing the number of strands and closing square knots increases the tensile strength and stiffness of flexor tendon repairs and isolated suture loops without a significant effect on tendon friction. An increase in the number of square knots have shown increased strength only in Pennington repair, which correlated with the increased number of knot unraveling, a weak knot failure model. Our data demonstrated that increasing the number of strands is effective for improving the overall strength of tendon repair. When a two‐strand repair is chosen, increasing knot number can improve repair strength. However, the number of knots appears not affecting repair strength in six‐strand repair technique.

Little is known about the expression patterns and functions of circular RNAs (circRNAs) in the heart of large mammals. In this study, we examined the expression profiles of circRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in neonatal pig hearts. Pig heart samples collected on postnatal days 1 (P1), 3 (P3), 7 (P7), and 28 (P28) were sent for total RNA sequencing. Our data revealed a total of 7,000 circRNAs in the 24 pig hearts. Pathway enrichment analysis of hallmark gene sets demonstrated that differentially expressed circRNAs were engaged in different pathways. The most significant difference was observed between P1 and the other 3 groups (P3, P7, and P28) in pathways related to cell cycle and muscle development. Out of the 10 circRNAs that were validated through real-time quantitative PCR to verify their expression, 6 exhibited significant effects on cell cycle activity in human induced pluripotent stem cell–derived cardiomyocytes following small interfering RNA–mediated knockdown. circRNA-miRNA-mRNA networks were constructed to understand the potential mechanisms of circRNAs in the heart. In conclusion, our study provided a data set for exploring the roles of circRNAs in pig hearts. In addition, we identified several circRNAs that regulate cardiomyocyte cell cycle.

LINKED CONTENTThis article is linked to Hassanein et al papers. To view these articles, visit https://doi.org/10.1111/apt.18054 and https://doi.org/10.1111/apt.18113

INTRODUCTION: Poverty traps, locations with multigenerational poverty, result from structural and economic factors that can affect health of residents within these locations. The aim of this study was to define poverty traps within the contiguous United States and their impact on outcomes from liver diseases or cancers. METHODS: A systematic census-tract level analysis was used to spatially define regions that encompassed poverty traps. Clusters of prevalent poverty and mortality from chronic liver diseases or liver cancers were identified. Temporal trends and the relationship between race and ethnicity, type of space and escape from poverty traps on disease mortality within hot spots were determined. RESULTS: The proportion of census tracts enduring multigenerational poverty within counties was strongly associated with mortality from liver disease or cancer. There was a highly significant clustering of persistent poverty and increased mortality. Hot spots of high-mortality areas correlated with factors related to income, ethnicity, and access to health care. Location or noneconomic individual factors such as race and ethnicity were important determinants of disparities within hot spots. Distinct groups of poverty traps were defined. The highly characteristic demographics and disease outcomes within each of these groups underscored the need for location-specific interventions. DISCUSSION: Poverty traps are a major and important spatially determined risk factor for mortality from liver diseases and cancers. Targeted location-specific interventions and economic development aimed at addressing the underlying causes of poverty and enhancing prosperity will be required to reduce mortality from liver diseases within poverty traps.