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Prognostic Impact of Adjuvant Immunotherapy in Patients with High-Risk Upper Tract Urothelial Cancer: Results from the ROBUUST 2.0 Collaborative Group
No full textBackground/Objective: The impact of adjuvant immunotherapy (IO) on the prognosis of patients with upper tract urothelial carcinoma (UTUC) remains unclear. This study examines the association of adjuvant IO with oncologic outcomes in patients with high-risk UTUC.
Methods: This retrospective study reviewed patients with high-risk UTUC treated with adjuvant IO using the ROBotic surgery for Upper tract Urothelial cancer STudy (ROBUUST) database. Propensity-score-matched analysis (nearest-neighbor algorithm, caliper 0.1) was conducted to compare patients receiving adjuvant IO versus those who did not, with matching based on pathologic T and N category and receipt of neoadjuvant chemotherapy. Associations between adjuvant IO and urothelial recurrence-free survival (URFS), non-urothelial recurrence-free survival (NRFS), and overall survival (OS) were estimated using a Cox proportional hazards model.
Results: Seventy-five patients received adjuvant IO following nephroureterectomy (median four cycles, including eleven (14.7%) nivolumab, thirty-one (41.3%) pembrolizumab, four (5.3%) atezolizumab, and twenty-nine (38.6%) other agents. These patients were matched to 68 patients without adjuvant therapy. Median follow-up times were 17 (IQR, 10-29) months and 20 (9-44) months for IO and no adjuvant therapy, respectively. Multivariable analysis revealed that adjuvant IO was not associated with URFS, NRFS, or OS. Pathologic nodal involvement (HR 7.52, p \u3c 0.001) was the only independent predictor of worse OS.
Conclusions: In this real-world retrospective data set, adjuvant IO does not have an impact on oncologic outcomes of UTUC patients following extirpative surgery
Results of Open and Endovascular Repair of Complex Aortic, Iliac, and Femoral Anastomotic Aneurysms
No full textAnastomotic aneurysms (AA) manifest as late complications of aortic-iliac-femoral reconstruction with a prosthetic graft. We studied open and endovascular repair of complex aortic iliac and femoral AA was performed for (A) Rupture, (B) Large symptomatic aneurysms, (C) Recurrent, (D) Femoral AA requiring simultaneous arterial reconstruction for critical limb ischemia in two teaching hospitals. Between 1990 and 2024, 100 aorto-femoral-iliac AA were repaired with 32 representing complex AA involving aorta (n = 6), iliac (n = 3), femoral (n = 23). Aortic and iliac anastomotic aneurysms underwent endovascular repairs in 5 patients and open repair in 4 patients with satisfactory outcomes in all. All 23 patients presenting with complex femoral anastomotic aneurysms were repaired via open technique, including five presenting with rupture with mortality in two, and one mortality among those presenting with large aneurysms. Complex femoral AA take longer to present after index operative, showed greater operative time, intra-operative blood loss but had similar mortality to patients with non-complex AAs. Most aortic and iliac AA can be repaired with endovascular and open techniques with satisfactory results, while complex femoral AA required open repair
Project #010: Influencing Outcomes through an Evidence-based Nurse-Driven Telemetry Discontinuation Protocol
Get PDFhttps://scholarlycommons.henryford.com/qualityexpo2025/1000/thumbnail.jp
Project #067: Expanded Alcohol Use Disorder Care for Patients with Advanced Liver Disease
Get PDFhttps://scholarlycommons.henryford.com/qualityexpo2025/1007/thumbnail.jp
Project #154: The Flow of Impact: CHWs Uncovering Needs, Unlocking Support
No full texthttps://scholarlycommons.henryford.com/qualityexpo2025/1030/thumbnail.jp
Fibrinogen depletion and the risk of intracerebral hemorrhage following endovascular mechanical thrombectomy
No full textBackgroundIntravenous thrombolysis (IVT) and mechanical thrombectomy (MT) are the standard of care for select stroke patients with acute large vessel occlusion (LVO). Fibrinogen levels may drop after IVT, and a significant decrease in fibrinogen is associated with an increased risk of intracranial hemorrhage (ICH). Our pilot study aimed to explore the relationship between fibrinogen levels and the development of ICH in MT-treated patients and whether bridging with IVT further increases that risk.MethodsThis is a prospective pilot study that enrolled adults presenting with a diagnosis of LVO stroke and eligible to receive MT with or without IVT between April 2020 and May 2023. Fibrinogen levels were drawn before treatment with IVT or MT and immediately following MT.ResultsForty-one patients were enrolled. Median age was 68 years [interquartile range 56-79], 58.5% were females and 56.1% were black. Nineteen patients (46.3%) were treated with MT + IVT, and 22 (53.6%) were treated with MT-only. There was no difference in baseline characteristics between the two groups. Baseline fibrinogen levels were similar between MT + IVT and MT-only groups [391 vs. 352 mg/dL, p = 0.4]. Post MT, the MT + IVT group had lower fibrinogen levels compared to the MT-only group [224 vs. 303 mg/dL, p \u3c 0.001]. Similarly, there was a significant change between baseline and follow-up levels in the MT + IVT vs. MT-only group [106 vs. 39.5 mg/dL, p = 0.001]. Eight patients (19.5%) developed ICH; 5 (26.3%) in the MT + IVT group and 3 (13.6%) in the MT-only group. No significant differences were seen in baseline, follow-up, or change in fibrinogen levels between patients who developed ICH and those who did not. However, when stratified by treatment group, postintervention fibrinogen levels were significantly lower in patients who developed an ICH in the MT + IVT group compared to those without ICH in the MT group (200 vs. 301 mg/dL, p = 0.006). There was also a negative correlation between the change in fibrinogen levels and the rate of first-pass recanalization (Spearman CC -0.33, p = 0.03).ConclusionThis pilot study\u27s preliminary data showed an association between fibrinogen depletion and hemorrhagic transformation in MT-treated patients. Since intracerebral hemorrhage is the most dire side effect in stroke treatment, fibrinogen monitoring in patients undergoing MT after IVT may help identify patients with an increased risk of ICH. Larger, prospective, and multicenter studies are needed to confirm these findings and if fibrinogen repletion should be considered for dysfibrinogenemia
Triage of Patient Messages Sent to the Eye Clinic via the Electronic Medical Record: A Comparative Study on AI and Human Triage Performance
No full textBackground/Objectives: Assess the ability of ChatGPT-4 (GPT-4) to effectively triage patient messages sent to the general eye clinic at our institution. Methods: Patient messages sent to the general eye clinic via MyChart were de-identified and then triaged by an ophthalmologist-in-training (MD) as well as GPT-4 with two main objectives. Both MD and GPT-4 were asked to direct patients to either general or specialty eye clinics, urgently or nonurgently, depending on the severity of the condition.
Main Outcomes: GPT-4s ability to accurately direct patient messages to (1) a general or specialty eye clinic and (2) determine the time frame within which the patient needed to be seen (triage acuity). Accuracy was determined by comparing percent agreement with recommendations given by GPT-4 with those given by MD.
Results: The study included 139 messages. Percent agreement between the ophthalmologist-in-training and GPT-4 was 64.7% for general/specialty clinic recommendation and 60.4% for triage acuity. Cohen\u27s kappa was 0.33 and 0.67 for specialty clinic and triage urgency, respectively. GPT-4 recommended a triage acuity equal to or sooner than ophthalmologist-in-training for 93.5% of cases and recommended a less urgent triage acuity in 6.5% of cases.
Conclusions: Our study indicates an AI system, such as GPT-4, should complement rather than replace physician judgment in triaging ophthalmic complaints. These systems may assist providers and reduce the workload of ophthalmologists and ophthalmic technicians as GPT-4 becomes more adept at triaging ophthalmic issues. Additionally, the integration of AI into ophthalmic triage could have therapeutic implications by ensuring timely and appropriate care, potentially improving patient outcomes by reducing delays in treatment. Combining GPT-4 with human expertise can improve service delivery speeds and patient outcomes while safeguarding against potential AI pitfalls
Coronary Artery Calcification Identified on Lung Cancer Screening CT Scans: A Scoping Review
No full textBACKGROUND: Coronary artery calcification (CAC) can be a significant incidental finding on low-dose CT scans performed for lung cancer screening (LCS). CAC presence and grade hold important diagnostic and preventive value, particularly in patients without previously recognized coronary artery disease.
RESEARCH QUESTION: What is the prevalence of CAC as an incidental finding on LCS CT scans across prior studies?
STUDY DESIGN AND METHODS: A literature review was conducted using the PubMed database to identify studies investigating CAC identified on LCS CT scans. The review included articles published in English from January 2012 through March 2024. The search query used 3 main keywords: CAC, LCS, and incidental finding.
RESULTS: The initial search resulted in 256 abstracts screened for eligibility, resulting in 32 articles included in the final review. CAC presence across included studies varied from 14.8% to 98%. CAC most commonly was reported as mild in grade, among 46.9% of studies. Most studies were conducted among predominantly White male participants. Finally, only 6 articles provided information on downstream interventions for patients with newly detected CAC.
INTERPRETATION: CAC, a predictive risk factor for cardiovascular events and mortality, is a frequently detected incidental finding on LCS CT scans, with substantial variation in presence across studies. Identification of CAC on LCS CT scans could inform clinical decisions to reduce patients\u27 overall cardiovascular risk. These findings underscore the significance of standardizing the documentation and management of CAC in LCS. Finally, future studies should include greater race diversity
Enhancing CT image segmentation accuracy through ensemble loss function optimization
No full textBACKGROUND: In CT-based medical image segmentation, the choice of loss function profoundly impacts the training efficacy of deep neural networks. Traditional loss functions like cross entropy (CE), Dice, Boundary, and TopK each have unique strengths and limitations, often introducing biases when used individually.
PURPOSE: This study aims to enhance segmentation accuracy by optimizing ensemble loss functions, thereby addressing the biases and limitations of single loss functions and their linear combinations.
METHODS: We implemented a comprehensive evaluation of loss function combinations by integrating CE, Dice, Boundary, and TopK loss functions through both loss-level linear combination and model-level ensemble methods. Our approach utilized two state-of-the-art 3D segmentation architectures, Attention U-Net (AttUNet) and SwinUNETR, to test the impact of these methods. The study was conducted on two large CT dataset cohorts: an institutional dataset containing pelvic organ segmentations, and a public dataset consisting of multiple organ segmentations. All the models were trained from scratch with different loss settings, and performance was evaluated using Dice similarity coefficient (DSC), Hausdorff distance (HD), and average surface distance (ASD). In the ensemble approach, both static averaging and learnable dynamic weighting strategies were employed to combine the outputs of models trained with different loss functions.
RESULTS: Extensive experiments revealed the following: (1) the linear combination of loss functions achieved results comparable to those of single loss-driven methods; (2) compared to the best non-ensemble methods, ensemble-based approaches resulted in a 2%-7% increase in DSC scores, along with notable reductions in HD (e.g., a 19.1% reduction for rectum segmentation using SwinUNETR) and ASD (e.g., a 49.0% reduction for prostate segmentation using AttUNet); (3) the learnable ensemble approach with optimized weights produced finer details in predicted masks, as confirmed by qualitative analyses; and (4) the learnable ensemble consistently outperforms the static ensemble across most metrics (DSC, HD, ASD) for both AttUNet and SwinUNETR architectures.
CONCLUSIONS: Our findings support the efficacy of using ensemble models with optimized weights to improve segmentation accuracy, highlighting the potential for broader applications in automated medical image analysis
