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In the U.S., diagnostic errors are common across various healthcare settings due to factors like complex procedures and multiple healthcare providers, often exacerbated by inadequate initial evaluations. This study explores the role of Large Language Models (LLMs), specifically OpenAI’s ChatGPT-4 and Google Gemini, in improving emergency decision-making in plastic and reconstructive surgery by evaluating their effectiveness both with and without physical examination data. Thirty medical vignettes covering emergency conditions such as fractures and nerve injuries were used to assess the diagnostic and management responses of the models. These responses were evaluated by medical professionals against established clinical guidelines, using statistical analyses including the Wilcoxon rank-sum test. Results showed that ChatGPT-4 consistently outperformed Gemini in both diagnosis and management, irrespective of the presence of physical examination data, though no significant differences were noted within each model’s performance across different data scenarios. Conclusively, while ChatGPT-4 demonstrates superior accuracy and management capabilities, the addition of physical examination data, though enhancing response detail, did not significantly surpass traditional medical resources. This underscores the utility of AI in supporting clinical decision-making, particularly in scenarios with limited data, suggesting its role as a complement to, rather than a replacement for, comprehensive clinical evaluation and expertise.

AbstractObjectiveCartilaginous tumors of the larynx are rare, representing less than 1% of all laryngeal tumors. Chondromas are benign mesenchymal tumors characterized by a slow‐paced growth, primarily originated in the cricoid cartilage, followed by the thyroid, arytenoid, and epiglottic cartilages. This scoping review aims to understand the extent of evidence on the epidemiology, clinical characteristics, morbidity, and recurrence of the laryngeal chondroma (LC).Data sourcesMEDLINE (Ovid), Embase (Elsevier), Web of Science (Clarivate), Cochrane Central Register of Controlled Trials and Systematic Reviews, Lilacs, Scopus, and Google Scholar databases.Review methodsThe scoping review was conducted from 1816 to 2023, for observational studies describing LC. Titles and abstracts were screened for relevance, followed by an evaluation of the full text for eligibility. The data were collected from the qualifying articles, and a narrative summary of the outcomes was prepared.ResultsOne hundred and nineteen studies met the inclusion criteria. Ninety‐four case reports, 22 case series, and 3 cohorts. Two hundred and four participants with a diagnosis of LC were described. Male:female ratio was 2.8:1. The most common localization was the cricoid (113; 47.08%), followed by the thyroid (45; 18.75%), and the arytenoid cartilage (27; 11.25%). Dyspnea (78.85%) and hoarseness (74.28%) were the most reported symptoms. The recurrence rate was 11.25%, and complications were uncommon following the resection.ConclusionThis scoping review found a low‐frequency rate over all the cartilaginous laryngeal tumors. Most patients were treated with resection, with a low rate of malignancy conversion. This population has low attributable mortality, morbidity, and recurrence according to the current literature.

1105 Background: Approximately 2-5% of breast cancers harbor HER2 mutations, often occurring in hormone receptor-positive (HR+) disease. There are currently no approved treatment options for patients (pts) with HER2-mutated metastatic breast cancer (HER2-mut MBC). Tucatinib (TUC) is a tyrosine kinase inhibitor highly selective for HER2 and is approved for previously treated HER2+ MBC with or without brain metastases in combination with trastuzumab (Tras) and capecitabine. Here, we report the efficacy and safety results of TUC combined with Tras in pts with previously treated HER2-mut MBC. Methods: SGNTUC-019 (NCT04579380) is an open-label phase 2 basket study evaluating efficacy, safety, and tolerability of TUC and Tras in pts with metastatic HER2-altered solid tumors. Pts in the HER2-mut MBC cohort must have HER2 mutations determined locally by tissue- or blood-based next-generation sequencing, not be HER2+ per local testing, been previously treated with ≥1 systemic therapy in the locally advanced, unresectable, or metastatic setting, and if HR+, have received a CDK4/6 inhibitor. Pts were treated in 21-day cycles with TUC (300 mg orally twice a day) and Tras (8 mg/kg IV followed by 6 mg/kg every 3 wks). Pts with HR+ disease also received fulvestrant (F; 500 mg IM once every 4 wks starting from cycle 1 day 1, and cycle 1 day 15). Disease status was determined based on RECIST v1.1 with assessments performed every 6 wks for 24 wks and every 12 wks thereafter. The primary endpoint is cORR per investigator assessment. Secondary endpoints include OS, DCR, DOR, PFS, and safety. Results: As of Nov 1, 2023, 31 pts were enrolled in the HER2-mut MBC cohort. The median duration of follow-up for OS was 15.0 months. Twenty-seven (87%) pts had HR+ disease and 18 (58%) had lobular histology. The pts received a median of 4 prior lines of systemic therapy in any setting. cORR was 41.9% (90% CI, 26.9-58.2) with 13 responses including 2 complete responses. Median DOR was 12.6 months (90% CI, 4.7, not estimable), DCR was 80.6% (n=25; 90% CI, 65.3-91.2), median PFS was 9.5 months (90% CI, 5.4-13.8), and median OS was 20.1 months (90% CI, 15.9 to not estimable). The most common treatment-emergent adverse events (TEAEs) reported were diarrhea (64.5%) and nausea (35.5%). The most common grade ≥3 TEAEs reported were diarrhea (13%), alanine aminotransferase increase (10%), and hypertension (10%). Two (6.5%) pts discontinued TUC due to TEAEs, but these pts continued Tras. No deaths were due to TEAEs. Additional biomarker analyses will be included in the presentation. Conclusions: The investigational combination of TUC and Tras, plus F in pts with HR+ disease, was well tolerated and had clinical activity in pts with previously treated HER2-mut MBC. The results support further evaluation of the combination of TUC and Tras as a potential treatment option for this pt population. Clinical trial information: NCT04579380 .

Revisional metabolic and bariatric surgery (RMBS) presents unique challenges in addressing weight loss failure or complications arising from initial bariatric procedures. This review aims to explore the complexities and solutions associated with revisional bariatric procedures comprehensively, offering insights into the evolving terrain of metabolic and bariatric surgery. A literature review is conducted to identify pertinent studies and expert opinions regarding RMBS. Methodological approaches, patient selection criteria, surgical techniques, preoperative assessments, and postoperative management strategies are synthesized to provide a comprehensive overview of current practices and advancements in the field, including institutional protocols. This review synthesizes key findings regarding the challenges encountered in RMBS, including the underlying causes of primary procedure failure, anatomical complexities, technical considerations, and assessments of surgical outcomes. Additionally, patient outcomes, complication rates, and long-term success are presented, along with institutional approaches to patient assessment and procedure selection. This review provides valuable insights for clinicians grappling with the complexities of RMBS. A comprehensive understanding of patient selection, surgical techniques, preoperative management, and postoperative care is crucial for enhancing outcomes and ensuring patient satisfaction in the field of metabolic bariatric surgery.

AbstractINTRODUCTIONWhile Latin America (LatAm) is facing an increasing burden of dementia due to the rapid aging of the population, it remains underrepresented in dementia research, diagnostics, and care.METHODSIn 2023, the Alzheimer's Association hosted its eighth satellite symposium in Mexico, highlighting emerging dementia research, priorities, and challenges within LatAm.RESULTSSignificant initiatives in the region, including intracountry support, showcased their efforts in fostering national and international collaborations; genetic studies unveiled the unique genetic admixture in LatAm; researchers conducting emerging clinical trials discussed ongoing culturally specific interventions; and the urgent need to harmonize practices and studies, improve diagnosis and care, and use affordable biomarkers in the region was highlighted.DISCUSSIONThe myriad of topics discussed at the 2023 AAIC satellite symposium highlighted the growing research efforts in LatAm, providing valuable insights into dementia biology, genetics, epidemiology, treatment, and care.

Abstract Primary thyroid lymphoma is a rare thyroid cancer, comprising ˂5% of thyroid neoplasms. Most cases are diffuse large B-cell lymphoma (DLBCL). Coexistence with papillary thyroid cancer (PTC) is extremely rare. This study presents a case of a 55-year-old woman with DLBCL and micropapillary thyroid cancer who underwent lobectomy, chemotherapy, and radiotherapy. Additionally, we performed a systematic review of 10 cases, including the reported case. The risk of bias in case reports varied. DLBCL diagnoses were mainly made after surgery, with total thyroidectomy being the most common surgical procedure. Chemotherapy was administered in most cases, and radiotherapy was used in some cases. Long-term outcomes indicated a low recurrence rate. While some debate the role of surgery in thyroid lymphoma, this study suggests that surgery should be considered in selected cases. Further research is needed to determine optimal treatment strategies for DLBCL with PTC.

Since their release, the medical community has been actively exploring large language models’ (LLMs) capabilities, which show promise in providing accurate medical knowledge. One potential application is as a patient resource. This study analyzes and compares the ability of the currently available LLMs, ChatGPT-3.5, GPT-4, and Gemini, to provide postoperative care recommendations to plastic surgery patients. We presented each model with 32 questions addressing common patient concerns after surgical cosmetic procedures and evaluated the medical accuracy, readability, understandability, and actionability of the models’ responses. The three LLMs provided equally accurate information, with GPT-3.5 averaging the highest on the Likert scale (LS) (4.18 ± 0.93) (p = 0.849), while Gemini provided significantly more readable (p = 0.001) and understandable responses (p = 0.014; p = 0.001). There was no difference in the actionability of the models’ responses (p = 0.830). Although LLMs have shown their potential as adjunctive tools in postoperative patient care, further refinement and research are imperative to enable their evolution into comprehensive standalone resources.

PURPOSE Patients with Waldenström macroglobulinemia (WM) have disparate outcomes. Newer therapies have emerged since the development of International Prognostic Scoring System, and MYD88 L265P mutation is now frequently assessed at diagnosis, warranting reexamination of the prognostic parameters. PATIENTS AND METHODS We reviewed records of 889 treatment-naïve patients with active WM, consecutively seen between January 01, 1996, and December 31, 2017, to identify clinical predictors of overall survival (OS) in univariate analyses. Patients with complete data for the parameters significant on the univariate analyses (n = 341) were included in a multivariable analysis to derive a prognostic model, subsequently validated in a multi-institutional cohort. RESULTS In the derivation cohort (n = 341), age (hazard ratio [HR], 1.9 [95% CI, 1.2 to 2.1]; P = .0009), serum lactate dehydrogenase (LDH) above upper limit of normal (HR, 2.3 [95% CI, 1.3 to 4.5]; P = .007), and serum albumin <3.5 g/dL (HR, 1.5 [95% CI, 0.99 to 2.3]; P = .056) were independently prognostic. By assigning a score of 1 point each to albumin <3.5 g/dL (HR, 1.5) and age 66-75 years (HR 1.4) and 2 points for age >75 years (HR, 2.6) or elevated LDH (HR, 2.3), four groups with distinct outcomes were observed on the basis of the composite scores. Five-year OS was 93% for the low-risk (score 0), 82% for low-intermediate risk (score 1), 69% for intermediate-risk (score 2), and 55% for the high-risk (score ≥3; P < .0001) groups. In the validation cohort (N = 335), the model maintained its prognostic value, with a 5-year OS of 93%, 90%, 75%, and 57% for the four groups, respectively ( P < .0001). CONCLUSION Modified Staging System for WM (MSS-WM), utilizing age, albumin, and LDH is a simple, clinically useful, and externally validated prognostic model that reliably risk-stratifies patients with symptomatic WM into four groups with distinct prognosis.

Background: Large language models (LLMs) represent a recent advancement in artificial intelligence with medical applications across various healthcare domains. The objective of this review is to highlight how LLMs can be utilized by clinicians and surgeons in their everyday practice. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Six databases were searched to identify relevant articles. Eligibility criteria emphasized articles focused primarily on clinical and surgical applications of LLMs. Results: The literature search yielded 333 results, with 34 meeting eligibility criteria. All articles were from 2023. There were 14 original research articles, four letters, one interview, and 15 review articles. These articles covered a wide variety of medical specialties, including various surgical subspecialties. Conclusions: LLMs have the potential to enhance healthcare delivery. In clinical settings, LLMs can assist in diagnosis, treatment guidance, patient triage, physician knowledge augmentation, and administrative tasks. In surgical settings, LLMs can assist surgeons with documentation, surgical planning, and intraoperative guidance. However, addressing their limitations and concerns, particularly those related to accuracy and biases, is crucial. LLMs should be viewed as tools to complement, not replace, the expertise of healthcare professionals.