Citations

Donation after circulatory death (DCD) has become a key avenue for expanding the organ donor pool. Many DCD protocols include premortem intravenous heparin to reduce microthrombus formation and preserve graft viability. This presents the plausible risk of premortem bleeding from an intervention that offers no direct therapeutic benefit to the donor. Ethical concerns and moral distress can arise when potential donors have a catastrophic intracranial hemorrhage with ongoing physiological concern for bleeding risk that is not survivable, but do not currently meet brain death criteria. While prior analyses describe premortem interventions in DCD in conceptual or protocol-driven terms, this case report considers the ethical concerns inherent in premortem heparin administration and illustrates how multidisciplinary teams can operationalize ethical safeguards, including transparent communication, attention to surrogate understanding, and separation of end-of-life decisions from donation-related interventions, to mitigate concerns and minimize moral distress. These issues are directly relevant to palliative care clinicians, who frequently support families during end-of-life crises and when there is consideration for organ donation. Through a multidisciplinary and ethically guided approach, this case illustrates how collaborative decision-making and transparent communication can uphold both donor dignity and transplant integrity.

ABSTRACT Objective To evaluate long‐term failure rates and complications after retropubic and transobturator midurethral sling procedures for primary stress urinary incontinence (SUI). Design Retrospective cohort study. Setting Academic medical centre. Population A previously described cohort of patients ( n = 1881) who underwent midurethral sling procedures (2002–2012) and a covariate‐matched cohort of patients with retropubic ( n = 570) or transobturator ( n = 317) slings. Methods Health record review with follow‐up extended by 9 years (through December 31, 2022). Main Outcome Measures Treatment failure (reoperation for recurrent SUI) and procedure‐associated complications. Results The duration of assessment was extended by 6.9 years for the retropubic group and by 6.4 years for the transobturator group. The median (IQR) follow‐up was 11.1 (5.1–14.5) years (retropubic, 11.4 [5.9–14.6]; transobturator, 9.6 [2.6–13.7]). Higher risk of reoperation was observed with transobturator (8.8%) than retropubic (4.4%) slings (unadjusted hazard ratio [HR], 2.29 [95% CI, 1.49–3.54]; p < 0.001; covariate‐matched analysis HR, 1.91 [95% CI, 1.15–3.17]; p = 0.01). The increased risk of reoperation with a transobturator sling was higher when the procedure was combined with prolapse repair (unadjusted HR, 6.34 [95% CI, 3.09–13.02]; p < 0.001; covariate‐matched analysis HR, 3.96 [95% CI, 1.35–11.58]; p = 0.01). Higher rates of reoperation for urinary retention were observed for the retropubic group than for the transobturator group (covariate‐matched analysis HR, 8.39 [95% CI, 1.11–63.22]; p = 0.04). Conclusion In this long‐term follow‐up study, midurethral slings had a low failure rate. Women with SUI undergoing transobturator sling placement plus prolapse repair had a greater risk of reoperation. However, women with retropubic slings had a greater risk of urinary retention requiring intervention.

Abstract Objective Current clinical risk models were developed for longer-term breast cancer risk stratification and therefore have limited utility for predicting short-term (1-year) breast cancer risk. This study evaluates the performance of a mammogram-based artificial intelligence (MB-AI) risk model for predicting breast cancer diagnosis within 1 year in high-risk women. Methods This retrospective case-control study included 340 women who underwent supplemental MRI screening within 1 year following a negative mammogram, of whom 101 (29.7%) developed breast cancer and 239 (70.3%) remained cancer-free during the same interval. Artificial-intelligence–assigned absolute 1-year risk scores, Tyrer–Cuzick (TC) lifetime and 10-year scores, and Gail lifetime and 5-year scores were analyzed. Model discrimination was evaluated using receiver operating characteristic (ROC) curves. Sensitivity, specificity, and predictive values were estimated at optimal cutoffs. Subgroup analyses examined model performance across genetic, menopausal, reproductive, and tumor-based strata. Results The MB-AI model demonstrated the highest overall discriminative ability (area under the curve [AUC] = 0.812), with strong performance in extremely dense breasts (AUC = 0.976). By comparison, TC lifetime (AUC = 0.625) and Gail lifetime (AUC = 0.668) models showed modest discrimination, while TC 10-year and Gail 5-year models did not discriminate (AUCs ≤0.49). Subgroup analyses showed consistent performance across clinical and pathological categories. The MB-AI model also showed an AUC comparable to that of previously developed AI models. Conclusions A mammogram-based AI model demonstrated improved performance compared with traditional clinical risk models for predicting breast cancer diagnosis within 1 year in women undergoing supplemental screening. These findings support that AI-based approaches may reflect both short-term risk and early imaging features of occult disease and suggest further investigation of AI as a complement to existing risk stratification strategies.

ABSTRACT Objective This study aimed to evaluate relationships between delayed gastric emptying and appetite suppression during treatment with liraglutide, a glucagon‐like peptide‐1 receptor agonist (GLP‐1RA). Methods We conducted a secondary data analysis from a 16‐week randomized, placebo‐controlled liraglutide trial in patients with obesity. We examined correlations between solid food gastric emptying and measurements of satiation and energy intake in the entire cohorts at baseline and end of treatment and separately in placebo‐ and liraglutide‐treated patients who completed the trial. We also compared appetitive measures among liraglutide‐treated participants who displayed either normal, persistently delayed, or transiently delayed emptying during treatment. Results In the entire cohorts at baseline and completion, gastric emptying correlated significantly with energy intake and, at baseline, with one parameter of satiation. Gastric emptying accounted for only 4%–6% of the variance in these appetitive measures. No such correlations were found in the placebo‐ or liraglutide‐treated groups alone. There were no differences in appetitive measures among the subgroups that displayed different gastric emptying patterns during liraglutide treatment. Conclusions Delayed gastric emptying appears to play little direct role in appetite suppression induced by liraglutide. Further research should explore whether delayed emptying or other gastrointestinal effects of other GLP‐1RAs affect appetite directly or indirectly. Trial Registration: ClinicalTrials.gov identifier: NCT02647944

Patients with plasma cell leukemia (PCL) are generally excluded from pivotal T-cell redirecting bispecific antibody (BsAb) trials. We evaluated real-world outcomes in a multicenter retrospective study of 122 patients with primary or secondary PCL across 15 academic centers, categorized as 'active' (≥5% circulating plasma cells within 30 days of BsAb initiation) or 'historical'. In a heavily pretreated population, patients received teclistamab (37%), elranatamab (11%), talquetamab as a line of therapy (Tal LOT, 42%), or talquetamab as bridging therapy to CAR-T (Tal Bridge, 11%). Cytokine release syndrome (CRS) was grade 1-2 in 56% and grade 3-4 in 4%, whereas neurotoxicity was grade 1-2 in 16% and grade 3-4 in 5%. Among 110 evaluable patients, the overall response rate (ORR) was 55%, including 61% with Tal LOT, 58% with Tal Bridge, 46% with elranatamab, and 33% with teclistamab. With a median follow-up of 8.3 months, talquetamab demonstrated superior survival. Tal LOT showed a median progression-free survival (mPFS) of 5.5 months and a median overall survival (mOS) of 11.5 months, and both were unreached in the Tal Bridge cohort. In contrast, teclistamab and elranatamab showed a mPFS of 1.2 and 1.6 months and mOS of 8.1 and 3.6 months, respectively (P=0.007, P=0.023). In active PCL, Tal LOT achieved mPFS/mOS of 6.9/12.2 months versus 0.7/1.4 months with teclistamab and 1.0/3.1 months with elranatamab, respectively (P&lt;0.001, P=0.002). Multivariable analysis associated active PCL with worse survival and Tal LOT with improved outcomes. BsAbs were safe in PCL, with talquetamab showing superior outcomes compared with BCMA-directed BsAbs.

PURPOSE Incorporation of structured data elements within the electronic health record generates real-time data for many potential uses. However, this requires a change in documentation practices, which may increase documentation effort. The best strategies to support structured documentation interventions have not been thoroughly investigated. Herein, we report the results of extending a data capture tool across multiple disease sites and practice locations. METHODS A note-based data capture tool was developed to collect five data elements using minimum common oncology data elements language. Soft-stop close visit validation (CVV), offloading of data entry tasks to allied health staff, group education, individualized e-mails, and one-on-one assistance were used to support utilization. Baseline and follow-up surveys were collected. For each provider, we compared data capture in the 6 months before and after their CVV go-live. RESULTS Forty-five providers participated (31 physicians, 14 nurse pracationers and physician assistants [NPPAs]), resulting in 23,274 encounters pre-CVV go-live and 23,146 post-CVV go-live visits. Median percentage of all data elements captured increased from 69.5% to 82.6% across all providers. The effect of CVV was immediate and sustained. When surveyed, most respondents agreed with the value propositions of understanding practice population, outcomes, selecting trials to open, and identifying patients for trial enrollment. Most respondents (15/20, 75%) felt the soft stop was a helpful reminder. CONCLUSION Structured data can be successfully collected in provider notes with >80% data capture. Personalized assistance incorporating the structured data elements into users' preexisting templates and soft-stop CVV, along with monitoring the results of implementation and personalized follow-up, was used to support the structured data capture intervention.