Outcomes of Aortobifemoral Bypass Based on Configuration of the Proximal Anastomosis.

BACKGROUND: Aortobifemoral bypass (ABF) remains an important treatment modality in the revascularization of aortoiliac occlusive disease. Despite ABF being performed for decades, questions remain regarding the preferred technique for the proximal anastomosis, specifically whether an end-to-end (EE) or an end-to-side (ES) configuration is superior. The goal of this study was to compare the outcomes of ABF based on proximal configuration. METHODS: We queried the Vascular Quality Initiative registry for ABF procedures performed between 2009 and 2020. Univariate and multivariate logistic regression analyses were used to compare perioperative and 1-year outcomes between EE and ES configurations. RESULTS: Of the 6,782 patients (median [interquartile range] age, 60.0 [54-66 years]) who underwent ABF, 3,524 (52%) had an EE proximal anastomosis and 3,258 (48%) had an ES proximal anastomosis. Postoperatively, the ES cohort had a higher frequency of extubation in the operating room (80.3% vs. 77.4%; P < 0.01), lower change in renal function (8.8% vs. 11.5%; P < 0.01), and lower use of vasopressors (15.6% vs. 19.1%; P < 0.01), but higher rates of unanticipated return to the operating room (10.2% vs. 8.7%; P = 0.037) compared with the EE configuration. At 1-year follow-up, the ES cohort had a significantly lower primary graft patency rate (87.5% vs. 90.2%; P < 0.01) and higher rates of graft revision (4.8% vs. 3.1%; P < 0.01) and claudication symptoms (11.6% vs. 9.9%; P < 0.01). The ES configuration was significantly associated with a higher rate of 1-year major limb amputations in univariate (1.6% vs. 0.9%; P < 0.01) and multivariate (odds ratio, 1.95, confidence interval, 1.18-3.23, P=<0.01) analyses. CONCLUSIONS: While the ES cohort seemed to have less physiologic insult immediately postoperatively, the EE configuration appeared to have improved 1-year outcomes. To our knowledge, this study is one of the largest population-based studies comparing the outcomes of the proximal anastomotic configurations. Longer-term follow-up is needed to determine which configuration is optimal.

Continuous Glucose Monitoring Use in Clinical Trials for On-Market Diabetes Drugs.

To the best of our knowledge, there are no published data on the historical and recent use of CGM in clinical trials of pharmacological agents used in the treatment of diabetes. We analyzed 2,032 clinical trials of 40 antihyperglycemic therapies currently on the market with a study start date between 1 January 2000 and 31 December 2019. According to ClinicalTrials.gov, 119 (5.9%) of these trials used CGM. CGM usage in clinical trials has increased over time, rising from <5% before 2005 to 12.5% in 2019. However, it is still low given its inclusion in the American Diabetes Association's latest guidelines and known limitations of A1C for assessing ongoing diabetes care.

Evaluating capabilities of large language models: Performance of GPT-4 on surgical knowledge assessments.

BACKGROUND: Artificial intelligence has the potential to dramatically alter health care by enhancing how we diagnose and treat disease. One promising artificial intelligence model is ChatGPT, a general-purpose large language model trained by OpenAI. ChatGPT has shown human-level performance on several professional and academic benchmarks. We sought to evaluate its performance on surgical knowledge questions and assess the stability of this performance on repeat queries. METHODS: We evaluated the performance of ChatGPT-4 on questions from the Surgical Council on Resident Education question bank and a second commonly used surgical knowledge assessment, referred to as Data-B. Questions were entered in 2 formats: open-ended and multiple-choice. ChatGPT outputs were assessed for accuracy and insights by surgeon evaluators. We categorized reasons for model errors and the stability of performance on repeat queries. RESULTS: A total of 167 Surgical Council on Resident Education and 112 Data-B questions were presented to the ChatGPT interface. ChatGPT correctly answered 71.3% and 67.9% of multiple choice and 47.9% and 66.1% of open-ended questions for Surgical Council on Resident Education and Data-B, respectively. For both open-ended and multiple-choice questions, approximately two-thirds of ChatGPT responses contained nonobvious insights. Common reasons for incorrect responses included inaccurate information in a complex question (n = 16, 36.4%), inaccurate information in a fact-based question (n = 11, 25.0%), and accurate information with circumstantial discrepancy (n = 6, 13.6%). Upon repeat query, the answer selected by ChatGPT varied for 36.4% of questions answered incorrectly on the first query; the response accuracy changed for 6/16 (37.5%) questions. CONCLUSION: Consistent with findings in other academic and professional domains, we demonstrate near or above human-level performance of ChatGPT on surgical knowledge questions from 2 widely used question banks. ChatGPT performed better on multiple-choice than open-ended questions, prompting questions regarding its potential for clinical application. Unique to this study, we demonstrate inconsistency in ChatGPT responses on repeat queries. This finding warrants future consideration including efforts at training large language models to provide the safe and consistent responses required for clinical application. Despite near or above human-level performance on question banks and given these observations, it is unclear whether large language models such as ChatGPT are able to safely assist clinicians in providing care.

Diffuse dermal angiomatosis of the thigh as the presenting sign of critical limb ischemia.

Diffuse dermal angiomatosis (DDA) is a rare, benign disease that can serve as the precursor to critical limb ischemia. Pruritic, erythematous plaques form from a proliferation of endothelial cells in response to dermal hypoxia. We present the case of a 63-year-old female patient with DDA of the left medial thigh, followed by ischemia of her distal extremities. Revascularization of her left leg resulted in resolution of the DDA and healing of her ulcers. DDA can be an important clue to identify significant peripheral vascular disease.

Evaluating Capabilities of Large Language Models: Performance of GPT4 on Surgical Knowledge Assessments.

Background: Artificial intelligence (AI) has the potential to dramatically alter healthcare by enhancing how we diagnosis and treat disease. One promising AI model is ChatGPT, a large general-purpose language model trained by OpenAI. The chat interface has shown robust, human-level performance on several professional and academic benchmarks. We sought to probe its performance and stability over time on surgical case questions. Methods: We evaluated the performance of ChatGPT-4 on two surgical knowledge assessments: the Surgical Council on Resident Education (SCORE) and a second commonly used knowledge assessment, referred to as Data-B. Questions were entered in two formats: open-ended and multiple choice. ChatGPT output were assessed for accuracy and insights by surgeon evaluators. We categorized reasons for model errors and the stability of performance on repeat encounters. Results: A total of 167 SCORE and 112 Data-B questions were presented to the ChatGPT interface. ChatGPT correctly answered 71% and 68% of multiple-choice SCORE and Data-B questions, respectively. For both open-ended and multiple-choice questions, approximately two-thirds of ChatGPT responses contained non-obvious insights. Common reasons for inaccurate responses included: inaccurate information in a complex question (n=16, 36.4%); inaccurate information in fact-based question (n=11, 25.0%); and accurate information with circumstantial discrepancy (n=6, 13.6%). Upon repeat query, the answer selected by ChatGPT varied for 36.4% of inaccurate questions; the response accuracy changed for 6/16 questions. Conclusion: Consistent with prior findings, we demonstrate robust near or above human-level performance of ChatGPT within the surgical domain. Unique to this study, we demonstrate a substantial inconsistency in ChatGPT responses with repeat query. This finding warrants future consideration and presents an opportunity to further train these models to provide safe and consistent responses. Without mental and/or conceptual models, it is unclear whether language models such as ChatGPT would be able to safely assist clinicians in providing care.

Internal iliac artery aneurysm in a patient with proximal occlusion at its origin.

We present the case of an 87-year-old man with a ruptured right internal iliac artery aneurysm with hemoperitoneum. The right internal iliac artery aneurysm appeared to fill from the retrograde profunda femoris artery in the setting of a previously repaired abdominal aortic aneurysm with aorta-bi-iliac bypass with ligation of the bilateral internal iliac arteries. Abdominal computed tomography revealed an aneurysm of the right internal iliac artery measuring 8.9 cm, with filling through the collateral vessels. Open repair was performed, leading to complete exclusion of the aneurysm with no perioperative complications.