Citations

Objective We aimed to use machine learning (ML) models to investigate the impact of clinical, social and behavioural factors on 1-year progression from pre-diabetes to type 2 diabetes mellitus (DM). Design A retrospective cohort study. Setting A large health system including eight sites in southeast Michigan. Participants Adults with haemoglobin A1c (HbA1c) between 5.7% and 6.4% for two consecutive years between 1 January 2008 and 31 December 2023, and no prior history of type 2 DM or metformin use. Primary outcome measure New-onset type 2 DM (HbA1c ≥6.5%) in 1 year. Results Among 11 809 individuals, 815 (6.9%) progressed to type 2 DM within 1 year. CatBoost demonstrated the best performance (average area under the curve 0.78). Prior-year HbA1c was the most influential covariate (SHapley Additive exPlanations 1.02). Traditional metabolic factors (high-density lipoprotein, body mass index (BMI), white blood cell, age, gender, triglycerides) also contributed. Lastly, while inclusion of social and behavioural determinants of health (SBDH) did not significantly improve the overall model performance, depression emerged as the prominent SBDH covariate. Depression was a stronger predictor of diabetes progression in individuals with higher baseline BMI and lower baseline HbA1c. Conclusions Inclusion of social and behavioural covariates provided no incremental value for prediction of diabetes progression from pre-diabetes. However, machine learning revealed that depression may play a role in progression to type 2 DM.

Abstract Background Failure to rescue (FTR) is a key driver of postoperative mortality and reflects a hospital’s ability to recognize, escalate, and treat complications. Although FTR varies substantially between hospitals, the hospital characteristics that underpin this variation are inconsistently described. The aim of this study was to synthesize evidence on hospital-level factors associated with FTR after postoperative complications across surgical populations and health systems. Methods A systematic review of observational studies evaluating associations between hospital-level characteristics and FTR in surgical patients was undertaken. MEDLINE, EMBASE, and Scopus were systematically searched on 17 July 2024 and updated to 31 December 2025. Hospital factors were classified into structural, staffing, and system domains. Where three or more non-overlapping studies reported adjusted estimates in comparable formats, random-effects meta-analyses were performed; otherwise, findings were summarized narratively. Methodological quality of included studies was assessed using the ROBINS-I tool (version 2). Results A total of 111 studies encompassing over 137 million patients and 301 hospital factors were included. Meta-analyses demonstrated lower FTR rates in larger hospitals (odds ratio 0.85, 95% confidence interval 0.74 to 0.97), hospitals with greater intensive care unit capacity (odds ratio 0.80, 0.71 to 0.90), and teaching hospitals (odds ratio 0.88, 0.83 to 0.93). Better nursing resources were consistently associated with lower FTR, including patient-to-nurse ratios (odds ratio 1.07, 1.03 to 1.10), higher nurse education (odds ratio 0.95, 0.91 to 0.99), and more favourable work environments (odds ratio 0.93, 0.90 to 0.95). Safety-net hospital status was associated with higher FTR (odds ratio 1.22, 1.03 to 1.45). Substantial heterogeneity was observed across most analyses. Conclusion Hospital-level structural, staffing, and system characteristics are associated with variation in FTR. Postoperative mortality is closely linked to institutional capacity to detect and manage complications, underscoring the importance of adequate resourcing and system organization to improve surgical outcomes.

Context.— One objective of the College of American Pathologists/American College of Medical Genetics Cytogenetics Committee is to ensure the accurate detection and clinical interpretation of abnormalities observed by fluorescence in situ hybridization (FISH) analysis when evaluating hematologic neoplasms. Objective.— To report a 20-year performance summary (2005–2024) of FISH challenges focusing on hematologic neoplasms. Design.— A retrospective review was performed from 2005 through 2024 to identify FISH challenges specifically addressing hematologic neoplasms. The overall performance of participants was evaluated to identify potential recurring errors of clinical relevance. Results.— A total of 124 hematologic neoplasm FISH challenges from 2005 to 2024 were provided to participating laboratories, including 45 paper challenges (results and/or images were provided for interpretation purposes), 43 liquid challenges (bone marrow aspirate or peripheral blood), and 36 formalin-fixed paraffin-embedded (FFPE) tissue challenges. Of the 124 challenges, 120 (97%) exceeded the required 80% consensus for grading purposes. Of the 4 failed challenges (3%), 2 (1 liquid, 1 paper) involved the interpretation of atypical FISH signal patterns; 1 (paper) involved the interpretation of FISH signal patterns correlating involvement by myeloid versus lymphoid interphase nuclei; and 1 (liquid) likely involved a specimen processing or handling error that resulted in discordant participant responses. All 36 FFPE tissue challenges exceeded the 80% consensus for grading purposes. Conclusions.— This 20-year retrospective review demonstrates that clinical cytogenomic laboratories have been and continue to be highly proficient in the detection and interpretation of FISH abnormalities associated with hematologic neoplasms.

Abstract Frontotemporal dementia (FTD) is characterized by selective neuronal vulnerability, yet the features that predispose specific neuron types to degeneration remain unclear. We performed single-nucleus RNA sequencing of frontoinsular cortex, a region affected early in behavioral variant FTD, across individuals with C9orf72 -associated and sporadic FTD-MND spectrum disease. By enriching for large projection neurons, we resolved molecular subtypes of layer 5 extratelencephalic neurons, including von Economo neurons, and identified selective depletion of specific layer 2/3 and layer 5 neuron subtypes, convergent across genotypes. Despite selective neuronal loss, disease-associated transcriptional changes were convergent across excitatory neuron populations, suggesting that they reflect upstream pathophysiology or shared responses to local neurodegeneration. By relating neighborhood-level depletion in disease to gene expression in controls, we found that baseline cellular respiration and ATP synthesis predict neuronal vulnerability in disease. These findings define molecular correlates of selective neuronal vulnerability in FTD and provide a framework linking cell type and state to neurodegeneration.

ABSTRACT Approximately 30% of patients with acute graft-versus-host disease (GVHD) develop steroid-refractory disease and have very poor outcomes. Ruxolitinib has become the standard of care for steroid-refractory acute GVHD, but it is unclear which patients derive benefit. The MAGIC Composite Score (MCS), an algorithm that combines clinical symptoms and biomarkers, has been validated to predict outcomes at the start of primary GVHD treatment. Here, we evaluated its performance at the initiation of second-line treatment in 278 patients. MCS stratified patients into three risk groups (MCS1-3), with the majority (88%) classified as intermediate or high risk. Increasing MCS score was associated with progressively higher 1-year non-relapse mortality (NRM) rates (16%, 41%, and 73%; p<0.001), lower 1-year survival (77%, 56%, and 24%; p<0.001), and lower complete response (CR) rates at day 28 (47%, 38%, and 20%, respectively; p<0.01). The area under the receiver operating characteristic curve (AUROC) for 1-year NRM was significantly higher with MCS compared to clinical symptoms alone (0.70 vs. 0.63; p=0.023). Among patients treated with ruxolitinib, higher MCS similarly predicted higher NRM and lower survival and CR rates. Patients classified as MCS2/3 had poor outcomes despite ruxolitinib, underscoring the need for novel therapies in this patient population. In conclusion the MCS is an accurate predictor of outcomes for patients who require second-line treatment and may be of use as an eligibility criterion for future clinical trials in this high-risk population. Key Points MAGIC Composite Scores that integrate clinical symptoms and biomarker scores predict outcomes of second-line therapy for acute GVHD more accurately than clinical symptoms alone. MCS identifies patients with high NRM despite treatment with ruxolitinib.

Most patients with chest pain do not have acute myocardial infarction (AMI), yet post-AMI rule-out disposition remains variable. Detectable but sub-99th percentile high-sensitivity cardiac troponin I (hs-cTnI) provides additional prognostic information. We evaluated the economic value of hs-cTnI-guided hospitalizations among non-AMI patients. We analyzed 1481 non-AMI chest pain visits with detectable baseline hs-cTnI across 29 U.S. emergency departments (2014–2016) in the prospective HIGH-US trial using the Atellica IM TnIH assay(Siemens Healthcare Diagnostics, Tarrytown, NY, US). We compared observed standard-of-care admissions with modeled pathways incorporating hs-cTnI thresholds and risk scores, assessing admission rates, costs, and diagnostic accuracy for 30-day death/MI. Overall, 1.0% (n = 15/1481) experienced 30-day death/MI. Standard-of-care admitted 59% of patients with 93% sensitivity and 41% specificity. The modeled pathway using hs-cTnI ≥ 5 ng/L plus non-low risk scores was associated with reduced projected admission of 41%, higher specificity of 60%, and the same 93% sensitivity. Estimated per-patient diagnostic costs were lower under Scenario 1 (noninvasive diagnostic testing only; $1025 vs. $1139) and under Scenario 2 (including inpatient/invasive procedures; $2672 vs. $3536). In subgroups, higher hs-cTnI thresholds conferred further economic benefit without compromising sensitivity. Incorporating sub-99th percentile hs-cTnI thresholds alongside risk scores may support more efficient resource use while maintaining safety, although findings require prospective validation.

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Importance In vivo biomarkers for detecting neuropathologies from repetitive head impacts (RHI), including chronic traumatic encephalopathy (CTE), are needed. Objective To evaluate the utility of plasma phosphorylated tau 217 (p-tau217), assess its performance as a beta-amyloid (Aβ) biomarker in participants with RHI exposure at risk for CTE, and explore concordance with CTE neuropathology in a postmortem subsample. Design, Setting, and Participants This longitudinal, multicenter, case-control study used data from the Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of CTE (DIAGNOSE CTE) Research Project, collected from September 2016 to October 2023. Participants were former American football players (case participants) and asymptomatic men unexposed to RHI (control participants). A subsample had available neuropathologic data. Exposures RHI, traumatic encephalopathy syndrome (TES) diagnoses, and levels of CTE certainty. Main Outcomes and Measures Plasma p-tau217 (classified as positive [≥0.63 pg/mL], intermediate [0.40-0.62 pg/mL], and negative [&amp;lt;0.40 pg/mL]), Aβ–positron emission tomography (PET; 18 F-florbetapir; with Aβ-positive defined as a standardized uptake value ratio [SUVR] ≥1.10), and tau-PET ( 18 F-flortaucipir). TES diagnoses were assigned by multidisciplinary consensus conference. Analyses of postmortem brains controlled for age, race, and APOE ε4 status. Results Among 231 participants (mean [SD] age, 57.75 [8.25] years), 177 were former football players (117 professional and 60 college) and 54 were unexposed participants. Former football players had higher baseline mean (SD) p-tau217 concentrations than unexposed participants (0.35 [0.26] pg/mL vs 0.27 [0.14] pg/mL; P = .008), although this was driven by a higher proportion of Aβ-PET–positive participants among former players. Plasma p-tau217 increased over time across the sample (B = 0.207 [95% CI, 0.117-0.298]; P &amp;lt; .001), with no significant time × exposure group interactions. Among football players, p-tau217 showed no time × group interactions with TES diagnosis, TES-CTE certainty, or RHI metrics. Higher p-tau217 concentration correlated with higher global Aβ-PET SUVR (B = 0.058 [95% CI, 0.053-3.501; P = .01), with a few discordant cases (5 participants were p-tau217–negative and Aβ-PET–positive; 7 participants were p-tau217–positive and Aβ-PET–negative). P-tau217 had similar areas under the curve for projecting Aβ-PET positivity as cerebrospinal fluid (CSF) p-tau181/Aβ42 and CSF Aβ40/42 measures (p-tau217: AUC, 0.88 [95% CI, 0.80-0.96]; CSF p-tau181/Aβ42: AUC, 0.89 [95% CI, 0.79-1.00]; CSF Aβ40/42: AUC, 0.85 [95% CI, 0.72-0.98]). Among 9 brain donors, 6 had CTE (stages II-IV; none with Alzheimer disease). Seven had negative or intermediate p-tau217, concordant with Aβ-PET. Two p-tau217 outliers with stage III CTE had normal concentrations upon additional testing. Conclusions and Relevance The findings of this study suggest that plasma p-tau217 concentration is unlikely to be useful for the detection of CTE, but it does show utility for ruling out Aβ pathology in participants at risk for CTE.

Abstract Frontotemporal lobar degeneration (FTLD) and Alzheimer’s disease (AD) differ in their clinical features and genetic etiologies but share progressive cognitive decline. Emerging evidence implicates lipid dysregulation in neurodegeneration, but its extent across FTLD subtypes and how it compares to AD are unclear. Here, we performed integrated lipidomic and proteomic analyses of matched frontal (disease-vulnerable) and occipital (relatively spared) post-mortem cortices from individuals with genetic and sporadic FTLD-TDP, FTLD-tau (Pick’s disease, PiD), AD, and controls. FTLD and AD exhibited convergent lipid alterations, including reduced levels of cardiolipins and phosphatidylethanolamines, alongside increased gangliosides, diacylglycerols, cholesterol esters, acylcarnitines, and coenzyme Q, with generally greater changes in FTLD frontal cortex. FTLD displayed additional alterations, including reductions in bis(monoacylglycerol)phosphate, ceramides, phosphatidylserines, phosphatidylinositols, and sulfatides. These lipid changes were accompanied by proteomic alterations involving lysosomal proteins, phospholipases, phospholipid remodeling enzymes, and fatty acid oxidation pathways. Although lipidomic and proteomic signatures were broadly shared across FTLD subtypes, GRN associated FTLD-TDP and PiD showed the most extensive alterations. Triglycerides were selectively reduced in PiD in association with decreased DGAT1 expression, whereas cholesterol esters were elevated across all subtypes except C9orf72 associated FTLD-TDP. These findings identify shared disruptions in lipid homeostasis and lysosomal lipid metabolism across FTLD and AD, highlighting convergent metabolic pathways underlying neurodegeneration.

Aims: The primary aim of this study was to determine whether CYP2D6 phenotypes are associated with atomoxetine treatment outcomes in children and adolescents with attention-deficit hyperactivity disorder. Patients and Methods: Patients 21 years and younger with a known CYP2D6 genotype and a prescription for atomoxetine were included in this electronic health record review. The primary outcome was defined as discontinuation of atomoxetine due to a lack of efficacy or due to toxicity. CYP2D6 activity scores were adjusted to account for phenoconversion if patients were concomitantly taking a CYP2D6 inhibitor medication. Results: Of 108 patients that met inclusion criteria, including 13 poor, 30 intermediate, 61 normal, and 4 ultra-rapid CYP2D6 metabolizers after adjusting for phenoconversion. Normal/ultrarapid metabolizers were significantly more likely to discontinue atomoxetine due to lack of efficacy (subdistribution hazard ratio [sHR] = 1.9, p = 0.04), while poor/intermediate metabolizers were significantly more likely to stop due to toxicity (sHR 0.4, p = 0.03). A significant nonlinear effect of adjusted activity score on likelihood of discontinuation due to lack of efficacy ( p < 0.001) or toxicity ( p < 0.001) was identified, where higher CYP2D6 activity scores were associated with more discontinuation due to lack of efficacy and lower activity scores were associated with more discontinuation due to toxicity. When CYP2D6 genotype was available prior to prescribing atomoxetine in intermediate/poor metabolizers, lower median initial doses were observed (0.5 mg/kg/day) compared to those who underwent CYP2D6 genotyping after the initial atomoxetine prescription (0.8 mg/kg/day). Conclusion: Patients with normal or increased CYP2D6 phenotypes may be more likely to discontinue atomoxetine due to a lack of efficacy, while those with reduced function CYP2D6 phenotypes may be more likely to discontinue atomoxetine due to toxicity.