Citations

Background: Patient-level value analysis (PLVA) has been applied to several orthopaedic procedures but has not yet been utilized to assess the value of total knee arthroplasty (TKA). The purpose of this study was to evaluate the 1-year episode of care for TKA with use of PLVA to identify characteristics that influence value at both the patient and surgeon level. Methods: The institutional patient-reported outcome (PRO) database was queried for all patients who underwent TKA from 2020 to 2022. Patients were excluded on the basis of an index revision procedure, a pathology other than primary osteoarthritis, unicompartmental knee arthroplasty, robotic-assisted TKA, incomplete baseline or 1-year PROs, concomitant procedures (i.e., bilateral TKA or hardware removal), complications requiring readmission or reoperation, TKA without patellar resurfacing, the use of constrained implants, incomplete cost information, or other hip or knee arthroplasty procedure during the 1-year episode of care. PROs of interest included preoperative and 1-year postoperative Knee injury and Osteoarthritis Outcome Score-Joint Replacement (KOOS-JR) scores. Episode-of-care costs were calculated using time-driven activity-based costing. The 1-year value quotient (V KOOS ) was calculated for each patient as the ratio of the 1-year change in KOOS-JR score to the total episode-of-care cost. Results: A total of 684 patients (62% female; mean age, 68 ± 8 years) met the inclusion criteria. The mean KOOS-JR score significantly increased from baseline (53 ± 11) to 1 year (79 ± 14; p < 0.001), with a mean improvement of 26 ± 16. The mean total episode-of-care cost was $9,563 ± $2,370. There was no significant correlation between episode-of-care costs and the change in KOOS-JR score (r = 0.02; p = 0.581). Surgery performed at an ambulatory surgery center (p < 0.001) and as an outpatient procedure (p = 0.036) were predictive of lower costs. Patient-specific instrumentation (p < 0.001) and a tibial stem extension (p < 0.001) were predictive of higher costs. Older age (p = 0.023) and male sex (p = 0.007) were predictive of less improvement in KOOS-JR scores from baseline to 1 year. Conclusions: Our study identified patient and surgical characteristics that drive costs and PROs in TKA. PLVA can be used to identify “bright spots” in orthopaedic procedures to optimize care delivery. Level of Evidence: Prognostic Level IV . See Instructions for Authors for a complete description of levels of evidence.

ABSTRACTBackgroundPancreatic cysts are increasingly discovered on imaging studies performed for unrelated conditions. Currently, surveillance of these lesions poses a substantial burden on patients, and health care recourses. We hypothesized that individuals with small and stable cysts have a diminutive risk of progressing to high‐grade dysplasia (HGD) or pancreatic cancer (PC) that is similar to that in the general population.MethodsThis nested PACYFIC‐study is a collaboration among 44 centers in Europe and Northern‐America, and investigates the risk of HGD and PC for different cyst sizes and growth rates in participants without baseline worrisome features (WF) or high‐risk stigmata (HRS).ResultsOf the 2369 PACYFIC participants, 975 met the inclusion criteria, with a mean age of 67 years (SD 13) and 65% being female. Of these, 438 individuals (45%) had a baseline small cyst size (< 15 mm), and 885 (91%) individuals had a slow growth rate (< 2.5 mm/year). During a median follow‐up of 45 months (IQR 27), 20 individuals (2.1%) developed HGD, or PC. Individuals with small cysts had a 1.5‐fold lower risk of developing WF or HRS (hazard ratio [HR] 0.7 [0.5–1.0], p = 0.03) than those with larger cysts but a similar risk of developing HGD or PC (p > 0.05). Slow growth was protective against the development of WF or HRS (HR 0.4 [0.2–0.6], p < 0.001) and HGD or PC (HR 0.04 [95% CI 0.02–0.12], p < 0.001). Individuals with small, stable sized cysts without baseline WF or HRS did not have a higher risk of HGD or PC than the general population (standardized incidence ratio [SIR] 1.13 [95% CI 0.01–6.30]).ConclusionCyst size < 15 mm and growth rate < 2.5 mm/year appear to be “reassuring” features associated with a negligible risk of developing WF or HRS and HGD or PC. For cysts with these characteristics—and without baseline WF or HRS—less intensive surveillance (than currently recommended) or even cessation may be appropriate.

AbstractINTRODUCTIONGiven the close interactions between the retina and the brain, retinal amyloid imaging may serve as a diagnostic and prognostic tool for Alzheimer's disease and related dementias. This retrospective study investigated multivariable associations between retinal perivascular amyloid and cognitive domains.METHODSIntegrated analysis of retinal perivascular amyloid imaging, neuropsychological assessment, and brain magnetic resonance imaging in adults with and without cognitive impairment (N = 26; mean age: 65 ± 7 years; 50% female). Correlations between perivascular amyloid plaque burden and cognitive domains were evaluated with linear regression and interactions with hippocampal volumetry were explored.RESULTSHigher perivascular and periarteriolar amyloid plaque count in the secondary small and tertiary branches were associated with poorer verbal and visual memory in this cohort (p = 0.005–0.009). Higher perivascular amyloid burden interacted with hippocampal atrophy to worsen visual memory (p = 0.033).DISCUSSIONRetinal perivascular amyloid may serve as a non‐invasive marker for cognitive impairment and may shed insight into pathological changes in the brain.Highlights In vivo retinal perivascular amyloid plaque counts are associated with poorer memory. Retinal perivascular amyloid interacted with hippocampal atrophy to worsen memory. Retinal amyloid imaging is a potential biomarker for neurodegenerative diseases.

Abstract This review explores the pivotal role of preanalytical variables in bringing liquid biopsy approaches into the clinic for brain tumors. Preanalytical variables encompass a range of critical issues, from blood sample collection and handling to the impact of tumor heterogeneity and patient-specific factors. These variables introduce challenges such as false positives, false negatives, and variability in the analysis of tumor signals, which can hinder the diagnostic and prognostic utility of liquid biopsies. Understanding the nuances of preanalytical variables is essential for the successful implementation of liquid biopsy in clinical settings. This paper delves into strategies aimed at mitigating the influence of preanalytical variables by emphasizing the importance of standardized sample collection protocols, optimized sample processing and storage, quality control measures, and the integration of multiple liquid biopsy modalities.

Abstract Objective Despite exponential growth in artificial intelligence (AI) research for laboratory medicine and pathology, a significant gap exists between model development and clinical AI implementation. This article introduces a structured framework, the Clinical AI Readiness Evaluator (CARE), to bridge this gap and support the responsible adoption of AI in clinical laboratory settings. Methods Building upon the Machine Learning Technology Readiness Levels framework, we developed CARE specifically for the clinical laboratory environment by incorporating health care–specific requirements, regulatory considerations, and workflow integration needs. This framework was iteratively refined through practical application across diverse AI use cases within laboratory medicine and pathology. Results The CARE framework provides a systematic approach to AI development and implementation through 8 component workstreams: clinical use case, data, data pipeline, code, clinical user experience, clinical technology infrastructure, clinical orchestration, and regulatory compliance. Unlike generic AI frameworks, CARE distinguishes itself by emphasizing both health care and laboratory workflow integration, regulatory requirements, ethical considerations, and comprehensive validation for clinical contexts. The framework accommodates both internally developed models and commercial AI solutions, providing clear guidance through technology readiness levels and structured review processes. Conclusions The CARE framework addresses the unique challenges of implementing AI in laboratory medicine and pathology by providing a comprehensive roadmap from initial concepts through clinical deployment and maintenance. This article, the first in a series of 4, establishes the foundational AI lifecycle framework, while subsequent articles will explore data documentation, ethical AI considerations, and governance structures. By adopting this structured approach, laboratories can responsibly harness AI’s potential to enhance diagnostic accuracy and operational efficiencies and, ultimately, improve patient care.

OBJECTIVE The principal tenet of minimally invasive neurosurgery is to limit approach-related tissue trauma, and a major assumption is that shorter incisions and smaller openings, in addition to protecting the brain, also have some perceptible benefits for the patient. This study tests the assumption of patient benefit and tries to define its significance. METHODS Procedures that fit the inclusion criteria of minimally invasive transcranial "keyhole" surgery were sought in the principal investigator’s archives. Each case was then paired with a classic procedure performed within the study time frame by the two senior authors, matched for pathology, size, location, and complexity. These pairs were then compared using a statistical tool (i.e., the Wilcoxon signed-rank test) designed for matched samples. Differences in estimated blood loss, duration of surgery, and length of hospital stay were examined. The narcotic needs during hospitalization were also examined as morphine milligram equivalent (MME). RESULTS Ninety patients were included in this study, evenly split between the minimally invasive surgery (MIS) and classic cohorts. Comparison of the 45 pairs showed no significant difference in estimated blood loss, though the operative times favored the MIS cohort significantly (mean ± SEM 310 ± 17 minutes vs 383 ± 24 minutes, p = 0.02). The length of stay was shorter for MIS, but the difference reached statistical significance only when cases with complications were excluded. The most important finding was that significantly less narcotic was needed during hospitalization in the MIS cohort (83 ± 15 MME vs 257 ± 47 MME). CONCLUSIONS The large difference in narcotic needs points to enhanced recovery from MIS techniques. While the difference in operative time did not lead to significantly shorter hospital stays, data suggest that minimally invasive technique may benefit the patient during recovery. This inspires further investigations to define the potentially positive impact on hospital and healthcare systems.