Citations

Context.— Decedent Affairs Offices and Programs can serve as an avenue to assist medical centers in facilitating efficient and comprehensive decedent management, despite a paucity of literature on their roles, establishment, and efficacy. Objective.— To characterize the motivations and rationales for establishing Decedent Affairs Offices. Design.— A survey was administered to 11 established Decedent Affairs Offices/Programs, identified through the College of American Pathologists Autopsy Committee and a Medical Autopsy Listserv. The questions comprehensively cover establishment, operations, and outcomes data available by institution. Results.— Survey respondents reported the rationale for starting their programs and the benefits such offices can have. Conclusions.— Decedent Affairs Offices and Programs provide a useful option to medical centers to navigate the increasingly complex task of comprehensive decedent management. The present survey helps to delineate the similarities and differences between these programs at 11 institutions, to aid nascent programs in their establishment and growth over time.

Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.

Abstract Objective This study was undertaken to evaluate the response to second treatments for infantile epileptic spasms syndrome (IESS). Methods Infants aged 2–24 months with IESS were prospectively enrolled in the National Infantile Spasms Cohort study at 21 pediatric epilepsy centers in the United States from 2012 to 2018. We analyzed data from infants who initially received standard treatment (hormonal therapy [adrenocorticotropic hormone, high‐dose prednisolone] or vigabatrin), had continued or recurring epileptic spasms, and received a second treatment. We excluded those with tuberous sclerosis. Treatment groups included hormonal therapy followed by vigabatrin (reference), hormonal‐to‐hormonal, hormonal‐to‐nonstandard, vigabatrin‐to‐hormonal, and vigabatrin‐to‐nonstandard. Nonstandard treatments included other antiseizure medications and dietary therapy. Treatment groups were tested for differences in 3‐month clinical remission using a binary logistic regression to estimate odds ratios (ORs). Results There were 153 infants with IESS who received second treatments. The highest rates of 3‐month remission were among infants in the hormonal‐to‐vigabatrin (22/65, 34%) and vigabatrin‐to‐hormonal (9/26, 35%) groups, followed by vigabatrin‐to‐nonstandard (3/10, 30%), hormonal‐to‐hormonal (4/22, 18%), and hormonal‐to‐nonstandard (1/30, 3.3%). Compared to the hormonal‐to‐vigabatrin group (reference), fewer infants had remission in the hormonal‐to‐nonstandard group (OR = .07, 95% confidence interval [CI] = .01–.53), and there was a trend toward fewer infants in the hormonal‐to‐hormonal group (OR = .43, 95% CI = .13–1.4, p = .17). Following initial hormonal treatment, the number needed to treat was three infants for one additional infant to have remission when treated with vigabatrin compared to nonstandard therapy as the second treatment. Significance This updated analysis with an expanded sample size provided power for additional subgroup analysis. Overall response rates were low, and at best only one third had remission after second treatment. Results support a clinical strategy of switching mechanism of action when selecting a second medication for epileptic spasms (i.e., use vigabatrin after hormonal therapy, or hormonal therapy after vigabatrin). Our findings also support the use of standard over nonstandard therapies.

ImportanceThere exists substantial heterogeneity in outcomes within T stages for patients with cutaneous squamous cell carcinoma (cSCC).ObjectiveTo determine whether a customized generative pretrained transformer model, trained on a comprehensive dataset with more than 1 trillion parameters and equipped with relevant focused context and retrieval augmented generation (RAG), could excel in aggregating and interpreting vast quantities of data to develop a novel class-based risk stratification system that outperforms the current standards.Design, Setting, and ParticipantsTo build the RAG knowledge base, a systematic review of the literature was conducted that addressed risk factors for poor outcomes in cSCC. Using the RAG-enabled generative pretrained transformer (GPT) model, we developed a novel class-based risk stratification system that assigned point values for risk factors, culminating in a GPT-based prognostication system called the artificial intelligence–derived risk score (AIRIS). The system’s performance was validated on a combined prospective and retrospective cohort of 2379 primary cSCC tumors (1996-2023) with at least 36 months of follow-up, against Brigham and Women’s Hospital (BWH) and American Joint Committee on Cancer Staging Manual, eighth edition (AJCC8) systems in stratifying risk for locoregional recurrence (LR), nodal metastasis (NM), distant metastasis (DM), and disease-specific death (DSD).Main Outcomes and MeasuresPerformance metrics evaluated included distinctiveness, homogeneity, and monotonicity, as defined by the AJCC8, as well as sensitivity, specificity, positive predictive value, negative predictive value, accuracy, the area under the receiver operating characteristic curve, and concordance.ResultsThe median age at diagnosis was 73 (IQR, 64-81) years, with 38.5% female patients and 61.5% male patients. The AIRIS prognostication system demonstrated superior sensitivity across all outcomes (LR, 49.1%; NM, 73.7%; DM, 82.5%; and DSD, 72.2%) and the highest area under the receiver operating characteristic curve values (LR, 0.69; NM, 0.81; DM, 0.85; and DSD, 0.80), indicating significantly enhanced discriminative capability compared with the BWH and AJCC8 systems. While all systems were comparably distinctive, the AIRIS prognostication system consistently demonstrated the lowest proportion of tumors exhibiting poor outcomes in low-risk categories, suggesting its improved homogeneity and monotonicity.Conclusions and RelevanceThe results of this diagnostic study suggest that the AIRIS system outperforms the existing BWH and AJCC8 prognostication systems, potentially providing a more effective tool for predicting poor outcomes in cSCC. This study illustrates the potential of large language models in refining prognostic tools, offering implications for treating patients with cancer.

Background: Amid mounting pressure to reduce health care spending, strategies for identifying and eliminating unwarranted variation in costs have garnered significant attention. Previous studies have characterized intersurgeon variation in costs for common orthopaedic procedures, but such variation remains unexplored in the context of hip arthroscopic surgery. Purpose: To (1) characterize variation in the cost of hip arthroscopic surgery between surgeons using time-driven activity-based costing (TDABC) and (2) identify patient characteristics, intraoperative findings, and operative procedures underlying such intersurgeon variation in costs. Study Design: Cohort study; Level of evidence, 3. Methods: Employing TDABC, the authors determined the intraoperative cost of 890 outpatient hip arthroscopic surgery cases performed by 5 surgeons at 4 surgery centers from 2015 to 2022. All costs were calculated in United States dollars. Costs were normalized to protect the confidentiality of internal hospital cost data. Surgeon-specific mean costs were calculated with and without adjustment for patient characteristics, surgical personnel, operative factors, and surgery center. Finally, to elucidate the sources of surgeon-driven cost variation, the authors estimated the proportion of variation attributable to different cost subcategories, including labor, implant/allograft, and other supply costs. Results: The intraoperative cost per patient ranged from 38.2 to 212.8 normalized cost units (mean, 100.0 ± 26.5), with a 1.6-fold variation in the mean cost between the highest and lowest cost surgeons. Operating surgeon alone explained 53.4% of the observed variation in costs. Controlling for case-specific features significantly improved the explanatory power to 91.8% ( P < .001), but the adjusted variation in costs between surgeons remained essentially unchanged (decreased by <3%). Each of the 5 surgeons generated costs that deviated significantly from those predicted based on case-specific factors, with mean surgeon deviations ranging from −5.0% to 21.8% ( P < .001 for all). Drivers of cost variation differed substantially between surgeons but generally stemmed from labor or other supply costs rather than implant/allograft costs. Conclusion: The cost of outpatient hip arthroscopic surgery varied widely between surgeons; the cause of this deviation was multifactorial and surgeon specific. While within-surgeon cost variation was effectively explained by patient and operative characteristics, most between-surgeon variability remained unexplained by observable factors. These insights may support individual surgeons in cost reduction efforts and, more importantly, may enable the alignment of reimbursement rates with costs.

Osteoarthritis (OA) is a major global health problem with no disease-modifying therapies. Interleukin-1 (IL-1) is a critical cytokine associated with the pathophysiology of OA and can be inhibited by IL-1 receptor antagonist (IL-1Ra). Here, we tested the delivery of a gene therapeutic encoding the human IL-1Ra to the knee in a phase 1, open-label clinical trial that enrolled nine patients with radiographic knee OA. The IL-1Ra gene was delivered by a self-complementary (sc)–recombinant adeno-associated virus (rAAV) serotype 2.5 (sc-rAAV2.5IL-1Ra) by intra-articular injection into an index knee at one of three doses: low [1 × 10 11 viral genomes (vg)], mid (1 × 10 12 vg), or high (1 × 10 13 vg). The primary outcome was safety. There were no serious adverse events (AEs) related to sc-rAAV2.5IL-1Ra. Two AEs occurred that were possibly related to the vector. Both were effusions with increased pain and resolved with conservative treatment. sc-rAAV2.5IL-1Ra did not cause changes in vital signs, physical findings, or clinical laboratory measures. Less than 1% of the injected dose of sc-rAAV2.5IL-1Ra vg was detected in circulation after 1 day and was cleared within a week. Titers of neutralizing antibodies to AAV2.5 rose in serum and synovial fluid. In all cases, IL-1Ra concentration increased in the synovial fluid, and IL-1Ra concentrations remained elevated after 1 year. Baseline pain and function scores improved during the study. Therefore, we found that intra-articular gene therapy with sc-rAAV2.5IL-1Ra was safe. The sustained increase in local IL-1Ra in human knee joints supports the further clinical examination of this therapy to provide therapeutic benefit in OA.

BACKGROUND: Small, randomized trials of patients with cervical artery dissection showed conflicting results regarding optimal stroke prevention strategies. We aimed to compare outcomes in patients with cervical artery dissection treated with antiplatelets versus anticoagulation. METHODS: This is a multicenter observational retrospective international study (16 countries, 63 sites) that included patients with cervical artery dissection without major trauma. The exposure was antithrombotic treatment type (anticoagulation versus antiplatelets), and outcomes were subsequent ischemic stroke and major hemorrhage (intracranial or extracranial hemorrhage). We used adjusted Cox regression with inverse probability of treatment weighting to determine associations between anticoagulation and study outcomes within 30 and 180 days. The main analysis used an as-treated crossover approach and only included outcomes occurring with the above treatments. RESULTS: The study included 3636 patients (402 [11.1%] received exclusively anticoagulation and 2453 [67.5%] received exclusively antiplatelets). By day 180, there were 162 new ischemic strokes (4.4%) and 28 major hemorrhages (0.8%); 87.0% of ischemic strokes occurred by day 30. In adjusted Cox regression with inverse probability of treatment weighting, compared with antiplatelet therapy, anticoagulation was associated with a nonsignificantly lower risk of subsequent ischemic stroke by day 30 (adjusted hazard ratio [HR], 0.71 [95% CI, 0.45–1.12]; P =0.145) and by day 180 (adjusted HR, 0.80 [95% CI, 0.28–2.24]; P =0.670). Anticoagulation therapy was not associated with a higher risk of major hemorrhage by day 30 (adjusted HR, 1.39 [95% CI, 0.35–5.45]; P =0.637) but was by day 180 (adjusted HR, 5.56 [95% CI, 1.53–20.13]; P =0.009). In interaction analyses, patients with occlusive dissection had significantly lower ischemic stroke risk with anticoagulation (adjusted HR, 0.40 [95% CI, 0.18–0.88]; P interaction =0.009). CONCLUSIONS: Our study does not rule out the benefit of anticoagulation in reducing ischemic stroke risk, particularly in patients with occlusive dissection. If anticoagulation is chosen, it seems reasonable to switch to antiplatelet therapy before 180 days to lower the risk of major bleeding. Large prospective studies are needed to validate our findings.

Abstract TDP-43 pathology is a defining feature of Limbic-Predominant Age-Related TDP-43 Encephalopathy neuropathologic change (LATE-NC) and is frequently comorbid with Alzheimer’s disease neuropathologic change (ADNC). However, the molecular consequences of co-occurring LATE-NC and ADNC pathology (TDP-43, β-amyloid, and tau protein pathologies) remain unclear. Here, we conducted a comparative biochemical, molecular, and proteomic analysis of hippocampal tissue from 90 individuals spanning control, LATE-NC, ADNC, and ADNC+LATE-NC groups to assess the impact of cryptic exon (CE) inclusion, phosphorylated TDP-43 pathology (pTDP-43), and AD-related pathologies (β-amyloid, and tau) on the proteome. ADNC+LATE-NC cases exhibited the highest burden of CE inclusion as quantified by measuring the levels of known TDP-43 regulated CEs within eight transcripts: STMN2, UNC13A, ELAVL3, KALRN, ARHGAP32, CAMK2B, PFKP, and SYT7 . While CE levels correlated with pTDP-43 pathology, they were more strongly correlated with each other, suggesting that the molecular signature of CE inclusion may serve as a more sensitive measure of TDP-43 dysfunction than pTDP-43 pathology alone. Unbiased classification based on the relative abundance of these eight CEs stratified individual cases into low, intermediate, and high CE burden subtypes, largely independent of β-amyloid and tau pathology. Proteome-wide correlation analysis revealed a bias toward reduced protein levels from genes harboring TDP-43-regulated CEs in cases with high cumulative CE burden. Notably, proteins significantly decreased under high CE burden included canonical STMN2, ELAVL3, and KALRN, as well as kinesin proteins that are genetically associated with amyotrophic lateral sclerosis. Co-expression network analysis identified both shared and distinct biological processes across CE subtypes and pathways associated with pTDP-43, tau, β-amyloid pathologies, and CE accumulation in the hippocampus. Protein modules associated with TDP-43 loss of function were prioritized by integrating proteomic data from TDP-43–depleted human neurons with the hippocampal co-expression network. Specifically, we observed decreased endosomal vesicle, microtubule-binding, and synaptic modules, alongside an increase in RNA-binding modules. These results provide new insights into the proteomic impact of CE burden across the spectrum of LATE and AD pathological severity, highlighting the molecular consequences of TDP-43 dysfunction in neurodegenerative disease