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ImportanceHospital ratings including the US News & World Report’s Best Hospitals rankings and the Centers for Medicare & Medicaid Services’ (CMS’) Overall Hospital Quality Star Rating (Overall Star Rating) measure different outcomes and are weakly correlated. Therefore, methods for defining and measuring reliable excellence, defined as consistently great performance across all quality measures, are needed.ObjectiveTo assess a measure of reliable excellence using the 45 quality measures reported in the Overall Star Ratings.Design, Setting, and ParticipantsThis cross-sectional study used hospital-level data from the 2023 and 2024 CMS Overall Star Ratings at all US hospitals with a 2023 and 2024 CMS Overall Star Rating.ExposuresThe exposure was the CMS Overall Star Rating summary score, a continuous variable calculated from the weighted z scores of 45 quality measures used in the Overall Star Rating. A total of 100 000 simulations were run in which all US hospitals’ CMS Overall Star Rating summary scores were calculated through summation of z scores from randomly generated measure weights, as opposed to the existing weights used in the Overall Star Rating method.Main Outcomes and MeasuresReliable excellence, defined as achieving a 90th percentile (or better) CMS Overall Star Rating summary score on at least 50 000 of 100 000 simulations. The percentage of hospitals achieving reliable excellence was calculated both overall and stratified by CMS Ovearll Star Ratings.ResultsThere were 2700 hospitals in the analysis, with 335 5-star hospitals (12.4%), 727 4-star hospitals (26.9%), 799 3-star hospitals (29.6%), 572 2-star hospitals (21.2%), and 267 1-star hospitals (9.9%) in the 2024 CMS Overall Star Rating. A total of 244 of 2700 hospitals (9.0%) met the study definition of reliable excellence, whereas 1287 of 2700 hospitals (47.7%) achieved excellence in at least 1 simulation.Conclusions and RelevanceThis cross-sectional study of 2700 US hospitals found that only 244 hospitals (9.0%), including less than two-thirds of the CMS 5-star rated hospitals, were reliably excellent across 100 000 CMS Overall Star Rating scoring simulations using random measure weightings. These findings lend credence to the ubiquity of inconsistent greatness in health care quality and illuminate the need for methods to distinguish hospitals that provide reliably excellent care.

Importance Tumor-infiltrating lymphocytes (TILs) are a provocative biomarker in melanoma, influencing diagnosis, prognosis, and immunotherapy outcomes; however, traditional pathologist-read TIL assessment on hematoxylin and eosin–stained slides is prone to interobserver variability, leading to inconsistent clinical decisions. Therefore, development of newer TIL scoring approaches that produce more reliable and consistent readouts is important. Objective To evaluate the analytical and clinical validity of a machine learning algorithm for TIL quantification in melanoma compared with traditional pathologist-read methods. Design, Setting, and Participants This multioperator, global, multi-institutional prognostic study compared TIL scoring reproducibility between traditional pathologist-read methods and an artificial intelligence (AI)-driven approach. The study was conducted using retrospective cohorts of patients with melanoma between January 2022 and June 2023 across 45 institutions, with tissue evaluated by participants from academic, clinical, and research institutions. Participants were selected to ensure diverse expertise and professional backgrounds. Main Outcomes and Measures Intraclass correlation coefficient (ICC) values were calculated for the manual and AI-assisted arms using log-transformed data. Kendall W values were calculated for Clark scores (brisk = 3, nonbrisk = 2, and sparse = 1). Reliabilities of ICC and W values were classified as moderate (0.40-0.60), good (0.61-0.80), or excellent (>0.80). AI TIL measurements were dichotomized using the 16.6 and median cutoffs. Univariable and multivariable Cox regression analyses assessed the prognostic value of TIL scores adjusted for clinicopathologic variables. Results There were 111 patients with melanoma in the independent testing cohort (median [range] age at diagnosis, 61.0 [25.0-87.0] years; 56 [50.5%] male) who contributed melanoma whole tissue sections. A total of 98 participants evaluated TILs on 60 hematoxylin and eosin–stained melanoma tissue sections. All 40 participants in the manual arm were pathologists, while the AI-assisted arm included 11 pathologists and 47 nonpathologists (scientists). The AI algorithm demonstrated superior reproducibility, with ICCs higher than 0.90 for all machine learning TIL variables, significantly outperforming manual assessments (ICC, 0.61 for AI-derived stromal TILs vs Kendall W , 0.44 for manual Clark TIL scoring). AI-based TIL scores showed prognostic associations with patient outcomes (n = 111) using the median cutoff approach with a hazard ratio (HR) of 0.45 (95% CI, 0.26-0.80; P = .005), and using the cutoff of 16.6, with an HR of 0.56 (95% CI, 0.32-0.98; P = .04). Conclusions and Relevance In this prognostic study of TIL quantification in melanoma, the AI algorithm demonstrated superior reproducibility and prognostic associations compared with traditional methods. Although the retrospective nature of the cohorts limits demonstration of clinical utility, the publicly available dataset and open-source AI tool offer a foundation for future validation and integration into melanoma management.

ABSTRACTThe current study includes 910 patients with systemic mastocytosis (SM) seen at the Mayo Clinic from 1968 to 2024. The primary objective was to examine the prognostic contribution of the International Consensus Classification (ICC), in the context of the Mayo Alliance Prognostic System (MAPS) for SM. World Health Organization classification (WHO‐HAEM5) subcategories included (i) indolent/smoldering SM (ISM/SSM; N = 518), (ii) SM associated with another hematological neoplasm (SM‐AHN; N = 273), with the latter including both myeloid and lymphoid neoplasms, (iii) aggressive SM (ASM; N = 106), and (iv) WHO‐defined mast cell leukemia (MCL; N = 13), which included mast cells with both “mature” and “immature” morphology. The ICC‐defined subcategories were mostly similar with the exception that SM‐AHN was replaced by SM associated with another myeloid neoplasm (SM‐AMN; N = 235) and WHO‐defined MCL was replaced by ICC‐defined MCL (N = 8), which included only those with immature MC morphology. Overall survival (OS) was similar between WHO‐defined MCL (median 1.8 years) vs. SM‐AHN (median 2.3 years; p = 0.3) but significantly different between ICC‐defined MCL (median 0.08 years) vs. SM‐AMN (median 2.0 years; p < 0.01). Significant difference in OS was also apparent between ICC‐defined SM‐AMN and SM associated with lymphoid neoplasm (SM‐ALN; median 8.1 years; HR 3.4; p < 0.01). Multivariable analysis confirmed the inter‐independent prognostic contributions of both ICC‐defined morphologic subcategories and MAPS risk variables, including age > 60 years, anemia, alkaline phosphatase > ULN, and platelet count < 150 × 109/L (p < 0.03 in all instances); the same was not true for WHO‐HAEM5‐defined SM subcategories. The addition of mutational information into the multivariable model resulted in ousting anemia and inclusion of ASXL1 (p < 0.01), SRSF2 (p = 0.01), and NRAS (p = 0.01) mutations as additional risk factors. Classification of SM by ICC is prognostically more accurate, compared to WHO‐HAEM5, and strengthens the prognostic contribution of morphology to current clinical and molecular risk models.

This study evaluated the effectiveness of using a traditional computed tomography (CT) simulation scan in the Leksell Gamma Knife® Icon™ workflow for stereotactic radiosurgery. We compared two workflows, one involving a traditional CT simulation co-registered with the magnetic resonance imaging (MRI) and cone-beam CT (CBCT) (MRI-CT-CBCT) and another without the CT scan, co-registering the MRI directly with CBCT (MRI-CBCT). The cohort included 50 frame-based (54 targets) and 55 frameless (124 targets) patients treated between August 2020 and December 2022. Target coverage was assessed by the percentage of each target covered by the prescription isodose line. The mean coverage differences for the frame-based and frameless cohorts were −1.20% ± 1.43% and −1.06% ± 1.51%, respectively, with 95% confidence intervals of −1.59, −0.81 and −1.32, −0.79. The MRI-CBCT workflow was deemed noninferior to the MRI-CT-CBCT workflow. Our data indicate that both workflows yield similar results, suggesting that a traditional CT simulation scan is unnecessary.

Study Design: A national prospective cervical spine surgery registry was developed to archive radiographic studies, patient-reported outcome measures (PROMs), and surgical implant data to assess long-term safety. Objective: To describe the design, development, funding, and implementation of a cervical spine data registry for 1000 patients with myelopathy and radiculopathy. Summary of Background Data: While surgery for cervical radiculopathy and myelopathy is safe and effective, there is significant practice variation among spine surgeons. While randomized clinical trials (RCTs) can provide high-quality comparative effectiveness data, RCTs lack the ability to evaluate the safety and effectiveness of various surgical procedures and implants among heterogenous real-world patient populations. The CSRS Registry was designed to collect patient demographics, outcomes, radiographic imaging, surgical approach, and implant data for the purpose of conducting high-quality research. Methods: Patients with cervical myelopathy or radiculopathy were enrolled in the CSRS National Registry. De-identified patient data, validated PROMs, radiographic data, and implant data were collected from multiple clinical sites across the United States. Results: One thousand patients [mean age, 58 y; 456 (46%) women] were enrolled, with 31% follow-up at 1 year. Five hundred ninety-two patients were diagnosed with radiculopathy, 252 with myelopathy, and 156 with radiculopathy and myelopathy. Patients had significant improvements in their PROMs after surgery. At 1 year, the mean NDI score improved from 37.2 to 20.9 ( P <0.001). The mean self-reported P-mJOA score at baseline was 14.2 and improved to 15.2 by 1 year ( P <0.001). Baseline CSDI score was 23.6 and improved with a 1-year decrease to an average score of 13.6 ( P <0.001). There was significant improvement in PROMIS-10 Physical Health score from 41.0 to 45.9 (n=311; P <0.001) at 1-year follow-up. Conclusions: The CSRS Registry has successfully collected clinical outcomes data that is being leveraged for comparative effectiveness research and evaluations of the long-term safety and effectiveness of spinal implants.

The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.

The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.

Background/Objectives: Spinoplastic surgery is an emerging multidisciplinary field developed to address and reduce the complication of pseudoarthrosis following complex spinal reconstructions. While the number of spinal fusion procedures continues to rise every year, fusion failure rates remain as high as 40%. Although pseudoarthrosis may not always manifest clinically, it remains a leading cause of persistent pain and need for subsequent revision surgeries. The multidisciplinary collaboration between spine and plastic surgeons in spinoplastic surgery has therefore emerged as a proactive strategy aimed at preventing complications, particularly in patients identified as high-risk for pseudoarthrosis. As the patient population expands and spinoplastic surgery continues to evolve, refining patient selection criteria becomes essential for achieving optimal surgical outcomes. This review aims to provide a comprehensive overview of recent advancements in spinoplastic surgery, highlighting current indications, surgical techniques, recent case reports, and strategies for identifying suitable candidates. Methods: We performed a narrative review of English language literature through April 2025. Spinoplastic case reports and case series published within the last 20 years were included in the review. Results: Indications for use of a spinoplastic approach clustered into prior fusion failure, extensive oncologic resection, severe spinal deformity, procedures requiring extensive spinal involvement, and/or patients at risk for impaired bone healing. Succesful radiographic union and improvement of symptoms were widely reported across all 9 case reports/series. Conclusions: Although evidence is presently limited, spinoplastic surgery appears to achieve high bone graft fusion rates with acceptable morbidity and functional improvement in a carefully selected group of high-risk spinal reconstruction patients. Still, larger prospective studies are warranted to refine patient selection and validate functional benefit.