Citations

Background: Glucagon-like peptide-1 receptor agonists (GLP-1) are approved for type 2 diabetes treatment. Given the link between diabetes-associated metabolic inflammation and increased carpal tunnel syndrome (CTS) risk, the aim of this study was to investigate development of CTS in diabetic patients who both were and were not taking GLP-1 therapy using a large claims database. Methods: A retrospective cohort study used a national claims database to identify diabetic patients. Those prescribed GLP-1 therapy were matched to controls by age, sex, comorbidity index, tobacco use, and obesity. Multivariable logistic regression evaluated the 2-year CTS incidence, controlling for various health conditions and socioeconomic factors. Secondary analysis also evaluated the rate of carpal tunnel release (CTR) after being diagnosed with CTS. Results: Glucagon-like peptide-1 therapy significantly reduced 2-year CTS diagnosis risk (odds ratio [OR] 0.49; 95% confidence interval [CI] 0.46-0.52; P < .001). Independent risk factors for increased CTS incidence included chronic obstructive pulmonary disease, osteoarthritis, coronary artery disease, depression, hypothyroidism, and rheumatoid arthritis (RA). Of patients who developed CTS, GLP-1 therapy was associated with increased odds of undergoing CTR (OR 1.23; 95% CI: 1.08-1.41; P = .002). Conclusions: Glucagon-like peptide-1 therapy is associated with decreased CTS risk in diabetic patients—potentially due to improved metabolic health—and increased odds of undergoing CTR once diagnosed. Further research is needed to clarify GLP-1 therapy’s role in reducing nervous system and musculoskeletal disease burden.

Introduction and Objective: Kidney stone growth and new stone formation are common clinical trial endpoints and are associated with future symptomatic events. To date, a manual review of CT scans has been required to assess stone growth and new stone formation, which is laborious. We validated the performance of a software algorithm that automatically identified, registered, and measured stones over longitudinal CT studies. Methods: We validated the performance of a pretrained machine learning algorithm to classify stone outcomes on longitudinal CT scan images at baseline and at the end of the 2-year follow-up period for 62 participants aged >18 years in the Prevention of Urinary Stones with Hydration (PUSH) randomized controlled trial. Stones were defined as an area of voxels with a minimum linear dimension of 2 mm that was higher in density than the mean plus 4 standard deviations of all nonnegative HU values within the kidney. The four outcomes assessed were: (1) growth of at least one existing stone by ≥2 mm, (2) formation of at least one new ≥2 mm stone, (3) no stone growth or new stone formation, and (4) loss of at least one stone. The accuracy of the algorithm was determined by comparing its outcomes to the gold standard of independent review of the CT images by at least two expert clinicians. Results: The algorithm correctly classified outcomes for 61 paired scans (98.4%). One pair that the algorithm incorrectly classified as stone growth was a new renal artery calcification on end-of-study CT. Conclusions: An automated image analysis method validated for the prospective PUSH trial was highly accurate for determining clinical outcomes of new stone formation, stone growth, stable stone size, and stone loss on longitudinal CT images. This method has the potential to improve the accuracy and efficiency of clinical care and endpoint determination for future clinical trials.

Background and Aims: Prognosticating outcomes such as hospitalizations in outpatients with cirrhosis is challenging, especially with changing etiologies and demographics. This study aims to determine the impact of multi-omic strategies on outcome prediction. Approach and Results: NACSELD3 enrolls outpatients with cirrhosis with controlled/eradicated etiologies from 10 centers and follows them systematically. At baseline, clinical/demographic and cirrhosis details were recorded and saliva and serum samples were collected for microbiome and metabolome analysis, respectively. Multi-omic bioinformatic studies to determine the interaction of microbiota and metabolites with the clinical prediction of 6-month hospitalizations were performed. Five hundred sixty-five patients (60.2 y, 68% men, 35% alcohol, 33% metabolic dysfunction-associated steatohepatitis, 21%, eradicated HCV with MELD 3.0 12) were enrolled. One hundred sixty-three (29%) required 6-month hospitalizations; most (75%) were liver-related. Those hospitalized had worse cirrhosis severity and comorbidity indices but similar demographics and oral health variables. Salivary microbiome alpha-diversity was lower (1.96±0.48 vs. 2.09±0.45, p =0.018) with greater pathobionts ( Streptococcus , Treponema, Enterococcaceae) and lower commensal genhospitalized/noera ( Veillonella, Prevotella, Haemophilus , Lachnospiraceae spp) at baseline. Serum metabolomics showed significant separation at baseline between hospitalized/non-hospitalized patients using supervised analyses with microbial-origin (phenyllactate, secondary bile acids, indoles), choline moieties, and polyamine/GABA (3-ureidopropionate/spermidine) metabolites being most prominent. Area under the curve using random forest for clinical, microbial, and metabolomic variables was higher than that of these individually. Latent factor analysis showed clinical variables (MELD 3.0, hemoglobin, and albumin) with the greatest impact, followed by salivary microbiota and then serum microbiome for hospitalization prediction. Conclusions: In a multicenter North American outpatient cirrhosis cohort with controlled etiologies, serum metabolomics and salivary microbiome add to clinical variables to prognosticate 6-month hospitalization.

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 Suppression of insulin-like growth factor-1 (IGF-1) signaling extends mammalian lifespan and protects against a range of age-related diseases. Surprisingly though, we found that reduced IGF-1 signaling fails to extend the lifespan of mitochondrial mutator mice. Accordingly, most of the longevity pathways that are normally initiated by IGF-1 suppression were either blocked or blunted in the mutator mice. These observations suggest that the pro-longevity effects of IGF-1 suppression critically depend on the integrity of the mitochondrial genome and that mitochondrial mutations may impose a hard limit on mammalian lifespan. Together, these findings deepen our understanding of the interactions between the hallmarks of aging and underscore the need for interventions that preserve the integrity of the mitochondrial genome.

Background Given the low haemorrhagic risk of intracranial low-grade dural arteriovenous fistulas (dAVFs), the benefits of routine intervention remain controversial. This study compares patient outcomes treated with stereotactic radiosurgery (SRS) versus conservative management. Method Multicentre retrospective analysis of the Consortium for Dural Arteriovenous Fistula Outcomes Research and the International Radiosurgery Research Foundation data. Inclusion criteria were (1) intracranial low-grade dAVF diagnosed by catheter-based angiography, (2) no prior dAVF-related haemorrhage and (3) management with upfront SRS (intervention group) or conservative management (observation group). The primary outcome was symptomatic improvement. Secondary outcomes included dAVF obliteration, up-conversion, haemorrhage, improvement and favourable modified Rankin Scale (mRS) at follow-up. Results 304 patients with a mean age of 56 years (SD 13.5) and a follow-up of 46.7 months (SD 45.5) were included. 135 (44.4%) were managed conservatively and 169 (55.6%) had upfront SRS. Compared with the observation group, symptomatic and mRS Score improvement (≥1-point decrease in baseline score) was more likely in the intervention group (95.1% vs 58.5%; OR=13.75 (5.61–33.69) and 37.0% vs 24.0%; OR=1.85 (1.09–3.15), respectively). These findings remained significant after multiple imputation and propensity score matching. Remaining outcomes were similar between groups. The all-cause mortality rate was 5.4% (n=16), unrelated to the dAVF or treatment. Five (3.0%) SRS-related complications were reported and resolved during the follow-up period. Conclusions SRS was associated with increased symptomatic and mRS Score improvement for low-grade dAVFs compared with conservative management. SRS had a low complication risk and did not appear to alter dAVF obliteration or haemorrhage. Future prospective trials on SRS as a first-line intervention for symptomatic low-grade dAVFs should be considered.

Objective: To establish comprehensive recommendations on the management of perihilar cholangiocarcinoma (pCCA) and to identify areas in need of future investigation. Summary Background Data: The lack of consensus in management of pCCA across institutions worldwide impairs optimal patient care and best-achievable oncological outcome. A holistic and critical assessment of the body of evidence and collaborative guidance are required. Methods: The Consensus4pCCA conference developed unbiased consensus using the Zurich-Danish model. An impartial and multidisciplinary jury adopted comprehensive recommendations grounded on the work of eight expert panels answering predefined clinical questions and considering the best-quality evidence through a systematic review. The development of recommendations complied with GRADE and SIGN50 methodologies. Results: Seventy-one international experts considered 570 studies. Ten jury members concluded 71 recommendations covering definition and diagnosis, preoperative assessment and optimization, surgical resection, liver transplantation, and outcome reporting for pCCA patients. The consensus underscored that making patients amenable to high-quality curative resection and reducing its associated morbidity must be of highest priority. As such, multidisciplinary expertise and centralized care at all stages of disease management are critical to ensure both safety and oncological adequacy. To overcome the evidence-gap for rare diseases like pCCA, the jury urged large-scale registries to address open questions across the disease continuum and highlighted priorities for future investigation. Conclusion: The Consensus4pCCA represents an unprecedented commitment to collectively harmonize global treatment strategies for pCCA. This collective effort bridges the gap between expert opinions and clinical evidence and holds great promise to improve patient outcomes in the future.