Journal of the American College of Surgeons最新文献

Background: Cancer patients in rural areas often encounter significant barriers to accessing cancer care. This study evaluated whether Medicare-aged patients can safely undergo lung and colon cancer surgery at their local rural hospital, limiting travel burden.

Study design: The SEER-Medicare files were used to identify patients with stage I-III colon and lung cancers. Patients residing in ZIP codes outside a metropolitan statistical area (MSA) were defined as rural; facilities were categorized similarly. Rural patients undergoing elective colon or lung cancer surgery at rural vs urban facilities were compared. Unadjusted and risk-adjusted complication and mortality rates were compared using multivariate logistic regression. Driving distances between patients' residences and surgery facilities were calculated based on ZIP codes.

Results: A total of 10,383 rural colon cancer patients and 6,006 rural lung cancer patients were identified. There were no clinically significant differences between rural and urban treatment in either colon or lung cohorts in terms of demographics or cancer stage; their comorbidity risks were similar. Mortality and complication rates were comparable across urban and rural facilities. Travel distance was significantly greater for patients treated at urban facilities compared with rural for both colon (49 vs 16 miles, p<0.001) and lung (61 vs 35 miles, p<0.001) patients.

Conclusions: Rural patients can achieve comparable short term surgical outcomes for lung and colon cancer when treated at local rural facilities, decreasing the travel burden of treatment at higher volume urban facilities.

Background: Despite the widespread adoption of minimally invasive surgery in the U.S., disparities in its use persist. One unexplored contributor is geographic access to robotic surgical systems. This study evaluates the geospatial association between: (i) social vulnerability index (SVI) and open surgery rates, (ii) availability of robotic systems and open surgery, and (iii) open surgery rates in demographically similar areas with differing robotic access.

Study design: Data from six sources were linked at the ZIP Code Tract Area (ZCTA) level to identify hospitals and extract procedure modality, presence of robotic systems, and area characteristics. Regression analysis assessed the association between SVI and open surgery rates. Open rates were then compared between hospitals with and without robotic systems. Propensity score matching was used to compare open rates across matched ZCTAs by robotic access and SVI levels.

Results: Higher social vulnerability was associated with increased open surgery rates (estimate = 0.20; p < 0.01), with rates ranging from 18.3% in low-vulnerability areas to 32.7% in high-vulnerability areas. Among 3,446 eligible ZCTAs, 57% had at least one robotic system. ZCTAs without robotic systems had higher open surgery rates (42.9 vs. 19.4 per 100 procedures; relative rate = 2.21; p < 0.01). This association remained significant after matching (relative rate = 1.66; p < 0.01), for the low-mid- and high-SVI strata, and three of the five procedures examined.

Conclusion: When correcting for geographic variation, the availability of robotic surgery was associated with a decrease in open surgery rates.

Objective: 1) Analyze National Institutes of Health grant disbursement to female otolaryngologists, 2) compare funding patterns to those of ophthalmology and neurosurgery, and 3) provide strategies to increase female surgeon-scientists.

Methods: The principal investigators of K, R, and U grants in each specialty were collected from the National Institutes of Health Research Portfolio Online Reporting Tools Expenditures and Results for 2000-2021. To factor in the number of females versus males, the number of female or male grant holders was divided by the respective number of female or male physicians in each field for proportional analysis. Conversion rates of K to R or U grants were calculated.

Results: Otolaryngology had a 1.46 times higher rate of female K grant holders (p=0.02), and a trend of 1.27 times higher rate of female R and U grant holders than male grant holders (p=0.13). Neurosurgery had 2.23 times greater rate of female K grant holders (p<0.01), and 2.62 times greater rate of female R and U grant holders than otolaryngology (p<0.01). Ophthalmology trended to have a 0.25 times higher rate of female K grant holders (p=0.24), but a 0.19 times lower rate of R and U grant holders than otolaryngology (p=0.12). Female otolaryngology grant holders tended to convert at a 24.4% lower rate than males (p=0.13).

Conclusion: Female otolaryngology surgeon-scientists' success in obtaining funding reflects successful prior initiatives and holds promise for increased female representation in leadership. However, there are fewer female otolaryngology grant holders compared to neurosurgery, illuminating the need for continued efforts.

Background: Artificial intelligence (AI)-enabled clinical decision support systems (CDSS) demonstrate performance comparable or superior to human experts in certain tasks. However, their integration into surgical practice faces a significant implementation gap, alongside ethical, privacy, and legal concerns. Clear governance frameworks are needed to guide their responsible adoption in surgery, to prevent inconsistent application, care quality variation, and exacerbation of algorithmic bias. Herein, we establish a systematic, evidence-based, and consensus-driven framework to guide the ethical, effective, and sustainable adoption of AI-enabled CDSS in surgery.

Methods: A systematic literature review was conducted of PubMed, Cochrane Library, Medline, and Embase databases until 2024 to identify key governance themes. The themes informed the generation of candidate items, which were then refined through a multi-round expert panel consensus process utilizing a modified Delphi approach to produce the final framework.

Results: Thematic analysis of 80 full-text articles meeting inclusion criteria identified four overarching themes for AI governance: (1) Technical Prerequisites and Model Design, (2) Clinical Implementation and Human Factors, (3) Ethics, Safety, and Trustworthiness, and (4) Bias, Fairness, and Equity. Panel consensus evaluation resulted in the development of a 19-item framework.

Conclusions: The consensus-driven framework presented herein provides foundational guidance essential for navigating the complexities of implementing AI-enabled CDSS safely and ethically in surgery. Addressing the considerations outlined across these four core themes can facilitate the responsible adoption of AI, accelerating the transition towards an advanced, data-driven surgical practice while mitigating potential risks.

Background: Pancreatic neuroendocrine tumors (PNETs) are associated with multiple endocrine neoplasia type 1 (MEN1) and von Hippel-Lindau syndrome (VHL) yet data regarding surgical outcomes in these patients is lacking. This study compared outcomes after pancreatectomy across a large cohort of sporadic, MEN1-, and VHL-PNET patients.

Study design: Retrospective analysis of pancreatectomies for PNETs performed at five institutions in the United States between 2000-2023 as part of the PAncreatic Neuroendocrine Disease Alliance (PANDA). All adult patients with MEN1- and VHL-associated PNETs were included. Adult sporadic PNET patients with overall survival and tumor grade data were included.

Results: Of 1,527 patients, 73 had MEN1, 26 had VHL, and 1,428 had sporadic PNETs. Majority were male (54%) with median age of 59 years (IQR 50-68). Median follow-up was 53 months. MEN1 and VHL patients were significantly younger and had more pancreatic head and multifocal disease compared to sporadic patients. MEN1 patients had more functional tumors (19.2% vs 10.9% sporadic vs 3.8% VHL, p=0.045). Formal resection was most common while enucleation occurred in 9.4%, 6.8%, and 3.8% of sporadic, MEN1-, and VHL-PNETs respectively. Tumors were predominantly Grade 1/2 (97%) but larger in MEN1 (2.8cm vs 2.3cm sporadic vs 2.5cm VHL, p=0.03). R2 resection occurred in 2.6% of sporadic, 9.6% of MEN1-, and 3.8% of VHL-PNETs. Rates of lymphadenectomy (86-92%), positive lymph nodes (24-31%), and Clavien-Dindo grade ≥3 complications were similar across groups. Progression-free survival (PFS) and overall survival (OS) among groups were not significantly different.

Conclusion: Despite significant differences in age, tumor size, R status, and surgical approach, outcomes including postoperative complications, PFS and OS after surgery are similar between sporadic, MEN1-, and VHL-associated PNET patients at 5-year follow-up.

Background: Mild Autonomous Cortisol Secretion(MACS) is present in approximately 20-50% of adrenal incidentalomas. These patients do not exhibit the clinical manifestations of overt Cushing's syndrome, and differentiation from Nonfunctional Adrenal Incidentalomas(NFAI) is typically made following a low-dose dexamethasone suppression test. The objective of this study was to develop predictive models to distinguish MACS from NFAI using clinical and radiological parameters.

Study design: This retrospective study included patients evaluated in an Adrenal Incidentaloma Clinic between February 2022 and August 2024 who were diagnosed with either NFAI or MACS. Demographic characteristics, medical and medication history, and radiological features were collected. Patients were randomly divided into training and test cohorts in a 3:1 ratio. Predictive models for MACS were developed using LASSO regression and random forest (RF) algorithms.

Results: A total of 397 patients were included, with 297 allocated to the training set and the remaining 100 to the test set. The mean age was 62.3 years, and 55% (n = 220) of participants were female. MACS was present in 34% (n = 136) of the study population. The most influential predictive factors of MACS were Body Mass Index(BMI), Posterior Adiposity Index, and the number of antihypertensive medications. The LASSO and RF models achieved discrimination with area under the curve(AUC) values of 0.686 and 0.736. At Youden Index thresholds balancing sensitivity and selectivity, LASSO model had 58.8% sensitivity, 75.8% specificity, and 70% accuracy while the RF model had 64.7% sensitivity, 75.8% specificity, and 72% accuracy.

Conclusion: Predictive models incorporating clinical and radiological characteristics offer a promising approach for distinguishing MACS from NFAI in patients with adrenal incidentalomas.