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Background Competition for urgent and emergent operating-room access is a significant challenge in many hospitals. Evidence-based benchmarks for early intervention are well established for emergencies like acute appendicitis or hip fracture. In contrast, laparoscopic cholecystectomy for acute cholecystitis or symptomatic cholelithiasis is often delayed. The purpose of this study was to evaluate the clinical and economic impact of delays in laparoscopic cholecystectomy across the US. Methods The Nationwide Readmissions Database was queried for patients aged ≥18 years admitted between 2021 and 2022 undergoing urgent or emergent laparoscopic cholecystectomy. Patients were stratified based on operative timing (<3 vs ≥ 3 days). The primary outcome was 30-day readmission. Secondary outcomes included VTE, SSI, and total cost. Propensity score matching (1:1) was performed using 46 covariates. Linear regression assessed the cost associated with each additional hospital day prior to surgery, with a subgroup analysis of safety-net hospitals. Results Among 136,893 patients, 24,496 (17.9%) experienced delayed laparoscopic cholecystectomy. After matching (n = 48,992), delays were associated with increased odds of readmission (9.5%; OR 1.22 [1.15-1.29], P < 0.001) and VTE (1.5%; OR 1.51 [1.30-1.77], P < 0.001). SSI (0.2%) was not significantly different. The mean total cost was $25,957 ± $21,609 for delayed patients vs $20,784 ± $20,027 for early surgery. Linear regression revealed an incremental cost of $1,695 per additional hospital day prior to surgery, rising to $2071 per day in safety-net hospitals ( P < 0.001). Discussion Delays in laparoscopic cholecystectomy have significant clinical and economic impacts, underscoring the urgent need for national benchmarks to standardize operative timing and reduce disparities for patients in safety-net hospitals.

ABSTRACT Purpose This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Objectives: Women with a history of breast cancer are at increased risk of developing subsequent breast cancer, including ipsilateral recurrence and contralateral new primary breast cancer. This study evaluated the discriminatory performance of a mammogram-based artificial intelligence (AI) risk model for predicting subsequent breast cancer within one year after a negative screening mammogram. Methods: This enriched retrospective case–control study included women with a prior history of breast cancer who underwent screening digital breast tomosynthesis between January 2018 and December 2023 at three affiliated academic breast imaging centers. Digital breast tomosynthesis examinations classified as BI-RADS 1 or 2 were retrospectively analyzed using the ProFound AI® Risk model version 1.0 to estimate 1-year breast cancer risk. Patients were classified according to whether they developed subsequent breast cancer within one year of the index screening examination. Model discrimination was evaluated using receiver operating characteristic analysis. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated at an exploratory cutoff selected by maximizing the Youden index. Results: The study included 96 women (mean age, 65.3 ± 8.7 years), of whom 32 developed subsequent breast cancer within one year, and 64 did not. The mean AI risk score was significantly higher in the subsequent breast cancer group than in the control group (1.18 ± 0.59 vs. 0.49 ± 0.41; p < 0.001). The AI model demonstrated an AUC of 0.824 (95% CI: 0.728–0.921). At an exploratory cutoff of 0.39, sensitivity was 81.3%, specificity was 76.6%, PPV was 63.4%, and NPV was 89.1%. In separate exploratory analyses, the AUC was 0.790 (95% CI: 0.641–0.939) for ipsilateral recurrence and 0.860 (95% CI: 0.752–0.974) for contralateral new primary breast cancer. AI risk scores were not significantly correlated with tumor size or age at subsequent breast cancer diagnosis. Conclusions: In this enriched retrospective case–control study, higher mammogram-based AI risk scores were associated with subsequent breast cancer within one year after a negative screening examination. The model demonstrated discriminatory performance for both ipsilateral recurrence and contralateral new primary breast cancer; however, these analyses were exploratory. Because the cohort was enriched for subsequent breast cancer events, the reported predictive values are specific to the study sample and should not be extrapolated to routine surveillance populations. Larger prospective cohorts are needed to validate discrimination, calibration, and clinical utility.

ABSTRACT Studies in humans and murine models have pointed towards a possible link between metabolic syndrome, which shows insulin resistance and metabolic dysregulation, and Alzheimer’s disease (AD) pathology marked by amyloid-beta (Aβ) accumulation at the BBB and hypometabolism in the brain. Yet, the underlying biological mechanisms by which metabolic syndrome affects these pathological changes in AD brain remain unknown. We hypothesized that insulin resistance is responsible for alterations in blood-brain barrier (BBB) transport of Aβ peptides and glucose. This hypothesis was tested by employing radiolabeled tracers ( 125 I-Aβ40, 125 I-Aβ42, and 18 F-FDG) in high-fat diet (HFD)-fed mouse models that manifest metabolic syndrome. Further, we assessed alterations in the expression of various molecular mediators within the brain microcapillaries harvested from both low-fat diet (LFD)-fed and HFD-fed mice. As expected, our studies show that HFD- fed mice developed peripheral insulin resistance and obesity. In addition, HFD-fed mice demonstrated an increase in the influx rate of Aβ peptides and a reduction in 18 F-FDG (a glucose surrogate) influx rate at the BBB compared to LFD-fed mice. These transport changes are associated with increase in the BBB endothelial expression of RAGE (receptor to traffic Aβ from plasma-to-brain) and a reduction of GLUT1 (glucose transporter) expression in HFD-fed mice compared to LFD-fed mice. Moreover, disruption in insulin signaling, as indicated by reduced pAKT and pERK expression, was observed in HFD-fed mice. Inhibiting AKT or ERK phosphorylation with specific inhibitors resulted in similar changes in Aβ and glucose uptake in polarized BBB endothelial cell monolayers in vitro. These results indicate that HFD induced metabolic syndrome may lead to BBB dysfunction, characterized by increased plasma-to-brain Aβ trafficking and diminished glucose transport at the BBB, thereby aggravating the expression of AD pathological hallmarks.

Myeloproliferative neoplasm (MPN) patients are at risk of splanchnic vein thromboses (SVT). Prior studies have failed to demonstrate a benefit of hydroxyurea therapy in preventing recurrent thrombosis after SVT, but are limited by small sample sizes and inability to account for starting, stopping, or switching of cytoreductive therapies. To better assess the impact of cytoreductive therapy on thrombosis recurrence, we performed a retrospective cohort study of MPN-SVT patients from the international GASTRO-MPN Consortium, treating cytoreductive therapy as a time-dependent covariate. We identified 757 patients, of which 43% were treated with cytoreductive therapy. During a median follow-up of 7.4 years, 256 patients (34%) had thrombosis recurrence; 145 (19%) had SVT extension/recurrence/TIPS thrombosis, 138 (18%) an thrombosis recurrence outside the splanchnic bed (74% were venous). Additionally, 262 patients (35%) experienced clinically relevant bleeding and 170 (22%) died. After adjusting for age, sex, prior thrombosis, timing of MPN diagnosis relative to SVT, anticoagulation initiation within 30 days of SVT diagnosis, MPN type, JAK2 status, other cancers and cirrhosis, cytoreductive therapy was associated with a decreased risk of recurrent thrombosis (HR 0.67 95%CI 0.50-0.89, p=0.01). This was driven by a lower risk of SVT extension/recurrence (HR 0.62 95%CI 0.42-0.90, p=0.01) but not by extra-splanchnic thrombosis recurrence (HR 0.97 95%CI 0.72-1.30, p=0.82). In a subgroup of patients without erythrocytosis/thrombocytosis at initial SVT (n=275), cytoreductive therapy was associated with a HR 0.65 (95%CI 0.40-1.07, p=0.09) for recurrent thrombosis. These data support the use of cytoreductive therapy in MPN-SVT patients to prevent recurrent thrombosis, particularly SVT extension/recurrence.

Abstract Objective Surgery is an effective, yet underutilized treatment for children with drug‐resistant epilepsy. Although predictors of surgical outcomes are well described, the decision to recommend surgery varies by institution. We aim to evaluate the rates of not recommending surgery, identify associated patient characteristics, and quantify variability across centers. Methods We queried the Pediatric Epilepsy Research Consortium Surgery database, a prospective multicenter cohort of children (0–18 years) undergoing initial evaluation for epilepsy surgery. Patients with documented surgical decisions were included. Demographic, clinical, and presurgical evaluation variables were compared by surgical recommendation status. Logistic regression identified factors associated with not recommending surgery. Mixed‐effects models quantified between‐center variability. Results Among 2480 patients across 29 centers, 532 (21%) were not recommended epilepsy surgery (median center rate 17%, interquartile range [IQR] 10%–28%). After accounting for patient characteristics associated with surgical candidacy, substantial variation in decision‐making remained across centers, with a median twofold difference in the odds of not recommending surgery between otherwise similar patients evaluated at different institutions (Median Odds Ratio = 2.25; Intraclass Correlation Coefficient = .18). The clinical characteristics most strongly associated with not recommending surgery included monthly or less frequent seizures (odds ratio [OR] 2.17, 95% confidence interval [CI] 1.75–2.69), non‐structural etiology (OR 2.02, 95% CI 1.56–2.61), and taking ≤2 anti‐seizure medications (ASMs) (OR 1.67, 95% CI 1.34–2.08, all p 's < .01). These characteristics showed minimal clustering across centers (ICCs < .05). Significance One in five children evaluated for epilepsy surgery are not recommended to pursue surgical treatment. Although clinical factors influence decision‐making, they do not explain the substantial variation in recommendations across pediatric epilepsy centers. Similar children evaluated at different institutions had significant differences in the odds of not being recommended surgery, suggesting that institutional decision‐making contributes importantly to surgical candidacy.