Citations

Background General practitioners (GPs) have limited tools for chest pain patients to identify (non-)obstructive coronary artery disease (OCAD). This trial evaluates whether GP access to the coronary artery calcium score (CACS) improves diagnostic efficiency and cardiovascular risk management (CVRM). Methods COroNary Calcium scoring as fiRst-linE Test to dEtect and exclude coronary artery disease in GP patients with stable chest pain (CONCRETE) is a pragmatic, non-blinded implementation study that cluster-randomised 101 Dutch GP offices into CACS or standard of care (SOC). Patients aged ≥40 (men) or ≥45 (women) years, without known CAD, with possible cardiac or non-cardiac chest pain were included. The primary outcome was the proportional 2-year increase in CVRM registrations at GP office level. Patient-level secondary outcomes included cardiologist referral rate, OCAD diagnosis and CVRM enrolment. Results At GP office level, no significant difference in CVRM registration increase was seen for CACS versus SOC (46 CACS practices: +0.3%, 45 SOC practices: +0.2%, p=0.77). Per protocol analysis for patient-level outcomes included 583 patients (57.5% women, mean age 60.6±9.1 years) (CACS arm: 466; SOC arm: 117), recruited between January 2019 and October 2023. The CACS arm showed 47.1% relative reduction in cardiologist referrals compared with SOC (42.5% vs 80.3%; modelled difference 31.3% (95% CI 14.8% to 47.8%)). OCAD detection rates were not significantly different (CACS: 4.9, SOC: 7.7%, p=0.14). Patients with higher CACS had a higher probability of cardiologist referral (from 8.4% for CACS 0 to 94.2% for CACS ≥400, difference +85.7% (95% CI 79.4% to 91.9%)) and of OCAD diagnosis (0% for CACS 0 to 21.2% for CACS ≥400, OR 9.08 (95% CI 4.20 to 19.67)). Compared with SOC, more CACS patients were enrolled in CVRM (36.3% vs 17.0%, p<0.01). Conclusions In this pragmatic, primary-care implementation and proof-of-concept trial, CACS was an effective diagnostic test for stable chest pain patients with (very) low likelihood of OCAD. CACS reduced unnecessary cardiology referrals and enhanced individual preventive care, without demonstrable practice-level impact on CVRM registrations. Registration The CONCRETE study is registered under CCMO Register NL66821.042.18 and closed for enrolment.

ABSTRACT Background ACS‐NSQIP began capturing operative approach in 2022. With increased adoption of minimally invasive (MIS) techniques for malignancy, a contemporary review of benchmark outcomes for open, laparoscopic and robotic gastrectomy is warranted. Methods We performed a retrospective cohort study of adults in ACS‐NSQIP (2022–2024) undergoing partial or total gastrectomy (CPT 43631‐4 and 43620‐2) for cancer. Outcomes included operative time, length of stay (LOS), unplanned conversion‐to‐open, and 30‐day morbidity, mortality, and readmission. Multivariable logistic regression evaluated patient and operative factors associated with morbidity. Results Among 1,459 patients (median age 66, 60.4% male), 66.8% underwent partial gastrectomy and 33.2% total gastrectomy. Approaches were 61.2% open, 19.5% laparoscopic, and 19.3% robotic. Thirty‐day mortality (1.8%), major complications (18.2%), and readmissions (10.3%) did not differ by approach. Unplanned conversion‐to‐open occurred in 14.0% of MIS. Robotic had longer median operative time of +1.2 and +1.7 h than laparoscopic and open and median −1 and −2 days shorter LOS respectively ( p < 0.001). Hypoalbuminemia (OR 3.10), CKD ≥ 3 (OR 1.75), and anemia (OR 1.48) were independently associated with major complications ( p < 0.05). Conclusion Operative approach influences operative time and LOS but not short‐term morbidity and mortality. The newly available ACS‐NSQIP operative approach variable enables approach‐specific benchmarks for cancer‐related gastrectomy.

Financial toxicity is a significant but often overlooked consequence of cancer for adolescents and young adults (AYAs, 15–39 years old), who face limited savings, unstable employment, and insurance gaps that heighten financial stress. As part of a larger initiative to determine whether our cancer center can use an existing social drivers of health (SDOH) screening process to identify patients who may benefit from targeted supportive interventions, we sought to characterize financial strain, toxicity, and SDOH needs in AYAs treated in our cancer center and compare them to both younger and older cancer patients. This is a cross-sectional observational study at Mayo Clinic of patients with an oncology-related department visit between 8 September 2023–4 June 2024 (N = 81,731) who completed routine institutional electronic screenings for financial strain and SDOH. Survey items assessed financial strain, transportation barriers, and food insecurity; institutional billing data captured financial toxicity (unresolved balances, collection referrals, write-offs). AYAs (n = 5655) were more likely than non-AYAs to report medium/high financial strain, have unpaid debt, or have an unresolved balance, referral to a collection agency, or bad debt write-off, with nearly double the odds of medium/high financial strain compared to patients over 40 (OR 2.02, 95% CI 1.84–2.23, p < 0.001). Within AYAs, ages 26–32 bore the greatest burden: 24.2% in the medium/high-risk category, 9.4% with unresolved billing issues or collections, and 11.6% reporting food insecurity. These findings identify AYAs—particularly those 26–32—as a distinct high-risk group for financial toxicity and health-related social needs, underscoring the need for targeted interventions, tailored financial navigation, and policy efforts to reduce economic barriers to care. Future research should evaluate the effectiveness of these interventions in mitigating financial toxicity, addressing health-related social needs, and improving patient outcomes in this population.

Summary Background Body composition is recognized as a major determinant of health outcomes, but its multidimensional nature makes clinical adoption challenging. We sought to develop and validate a body composition index (BCI) for all-cause mortality risk assessment, integrating variables of six body composition tissues. Methods We analyzed 28509 consecutive patients undergoing myocardial perfusion imaging with routine low-dose chest CT attenuation correction (CTAC) scans acquired during myocardial perfusion imaging (MPI) at 12 centers across four countries. An artificial intelligence-based BCI was developed in a cohort of 15037 patients’ CTACs by integrating the CT-derived metrics of bone, skeletal muscle, and four adipose tissue compartments, coronary artery calcium score, and basic demographic variables (age, sex, BMI). The performance of BCI for mortality prediction was validated in an internal cohort of 6444 patients and an external cohort of 7028 patients by prognosis, calibration, net benefit, and explainability. Model-based simulation of tissue metrics modification was performed to evaluate estimated mortality risk reduction. Findings During a median of 3.5 (IQR [1.9, 5.1]) years, 4697 (16%) patients died. In the external testing cohort, the BCI demonstrated excellent discrimination for mortality (area under receiver operating characteristic curve 0.78 (95% CI [0.76, 0.79]) and Harrell’s concordance index 0.75 [0.73, 0.76]), calibration, and net benefit overall and across pre-specified subgroups stratified by patient characteristics and imaging protocols. Visceral adipose tissue attenuation was the most influential body composition measure, followed by skeletal muscle volume. Simulated improvement in body composition was associated with significant mortality risk reduction. Interpretation An index combining six body composition measures obtained opportunistically from routine chest CT provides robust mortality risk stratification. By converting complex body composition information into a single interpretable score, the BCI can facilitate clinical implementation of opportunistic CT biomarkers and guide individualized preventive strategies. Funding National Institute of Health Research in context Evidence before this study We searched PubMed and Google Scholar on July 7, 2026 for English language studies using the terms (“mortality prediction” OR “death prediction”) AND (“integrated body composition analysis” OR “body composition metrics integration”) AND (“predictive model” OR “model development”), and identified 41 publications describing predictive models incorporating body composition metrics. Recent advances in artificial intelligence (AI) have enabled increasingly granular quantification of body composition from CT, with multiple tissues and tissue-specific metrics showing independent prognostic value for all-cause mortality (ACM) prediction. However, reported associations of body composition metrics with mortality risk were highly inconsistent or even contradictory across studies. This heterogeneity likely reflected the differences in study design or the inherent complexity of body composition analysis, such as the interaction among variables derived from multiple tissues. Thus, it is difficult to interpret body composition results reliably in clinical practice. We hypothesized that integrating multiple body composition metrics could achieve comprehensive and reliable prediction of mortality across patient populations. Added value of this study In this large international, multicenter longitudinal cohort study of 28509 consecutive patients with suspected or known coronary artery disease (CAD) undergoing myocardial perfusion imaging across 12 sites in four countries, we developed and externally validated an artificial intelligence-based body composition index (BCI) for all-cause mortality prediction. The BCI integrated chest CT-derived metrics of six body composition tissue compartments – bone, skeletal muscle (SM), subcutaneous adipose tissue (SAT), intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and epicardial adipose tissue (EAT), together with demographics (age, sex, BMI) and CT-derived coronary artery calcium (CAC) score, all derived automatically from routine low-dose attenuation correction CT scans without additional imaging or laboratory tests. In an external validation cohort of 7028 patients, the BCI achieved robust discrimination for mortality prediction, substantially outperforming a baseline model using demographics and calcium score alone, and exceeded the discriminative performance of prior body composition models. Performance was consistent across subgroups defined by sex, age, body mass index, cardiometabolic risk factors, imaging modality, and acquisition protocol, supporting generalizability across clinical settings. The BCI demonstrated excellent calibration and net clinical benefit. Explainability analysis identified visceral adipose tissue attenuation and skeletal muscle volume as the dominant contributors to mortality risk, offering tissue-specific therapeutic targets that complement generic weight-based metrics. Model-based simulations suggested that improvements in these specific compartments could reduce estimated mortality risk more effectively than equivalent changes in BMI alone, pointing toward precision therapeutic targets beyond weight reduction. Our study improved over previous literatures on body composition-based predictive models in one or more of the following ways: (1) we considered six types of body composition tissues while existing studies considered only three or less tissues, thus significantly higher granularity and improved ability to capture refined tissue interactions; (2) our model was rigorously validated in external sites, showing cross-site generalizability while most previous work lacked external validation; (3) our model achieved significant prediction performance improvement over previous body composition predictive models, offering better clinical outcomes prediction and facilitating the suitability for widespread clinical adoption; (4) our study was conducted with a large multi-center cohort across multiple countries, achieving statistical power and demonstrating reliability towards patients characteristics and imaging acquisition protocols while previous studies involved small single-center cohorts; (5) our model required only CT scans and basic demographics which were widely available in clinical routine while the existing models required dedicated laboratory tests or specialized imaging modalities, enhancing the applicability in routine clinical practice. Implications of all the available evidence BCI offers an explainable and clinically deployable tool for improved prediction of mortality risk from existing chest CT scans. Its use could inform updates to existing risk models, guide precision preventive strategies, and support development of therapeutics targeting specific body composition phenotypes.

Abstract TAR DNA‐binding protein 43 (TDP‐43) inclusions are often associated with hyperphosphorylated tau, thus neurofibrillary tangles as the hallmark of Alzheimer's disease (AD) and primary age‐related tauopathy (PART). TDP‐43 in AD is associated with cognitive impairment, and while staging is known, the localization, cellular and inclusion characteristics of TDP‐43 are yet to be elucidated. We investigate relationships between TDP‐43 inclusions and the tangle maturation continuum in AD, PART, and co‐pathologies by multiplex immunostaining combined with artificial intelligence (AI)–based segmentation via object recognition, reconstruction, and quantification. We performed anti‐phosphorylated TDP‐43 immunofluorescence with phosphorylated tau labeling different stages and modifications of tangles (AT8, pS396, TauC3, MN423, GT38) in three controls, three cases with PART and TDP‐43 (PART‐TDP), five cases with high likelihood AD and TDP‐43 (AD‐TDP), and four cases of high likelihood AD with TDP‐43 and Lewy Body disease (AD‐TDP‐LBD). Confocal imaging was taken from eight regions: amygdala (amygdala‐BL and amygdala‐CM) and hippocampus (Cornu Ammonis (CA)‐1, CA2/3, CA4, dentate gyrus (DG), subiculum (SUB)), and entorhinal cortex (ERC) and quantified with AI segmentation to identify 3D spatial relations, thus the maturity of neurofibrillary tangle associated TDP‐43 (TAT) inclusions. TATs, which were either identified by pTDP‐43 and AT8 or pTDP‐43 and pS396 double positivity, were also investigated by Thioflavin S (ThioS) histochemistry. We found pS396 labeled mature TATs predominated in PART and AD in every region. Basolateral and centromedial amygdala displayed overall greatest number of pre‐TATs and mature TATs. Mature TATs were homogenously distributed among hippocampal subfields whereas CA4 and DG had the greatest mature TAT composition. ERC revealed closer numbers of pre‐TATs and mature TATs yet mature TATs predominated all groups. Unbiased AI‐based object identification, reconstruction, and TAT maturation analysis pipeline in conjunction with TDP‐43, tau, and ThioS multiplex immunostaining demonstrated unique aggregation and maturation patterns, highlighting region‐specific dynamics in the neurodegenerative processes of PART and AD.

This study found that inhibiting TrkB kinase activity decreases the extent of neuromuscular transmission failure during repetitive stimulation at low frequency while increasing failure with high-frequency stimulation. The frequency-dependent effect of 1NMPP1 treatment suggests that the role of TrkB signaling in maintaining neuromuscular transmission during repetitive stimulation may differ between motor unit types (slow-twitch, fatigue-resistant vs. fast-twitch, fatigable) and likely reflect effects at the presynaptic terminal without major effects on the muscle itself.

Background: Despite guideline support for plain radiography (XR) in low-risk pediatric blunt trauma, CT remains the predominant imaging modality for cervical spine evaluation, increasing radiation exposure. We evaluated contemporary XR utilization and its diagnostic performance in children meeting consensus criteria for XR-first imaging. Study Design: We performed a prospective, multicenter observational study of 19,995 children enrolled in the Western Pediatric Cervical Spine Study across 72 U.S. trauma centers (2022–2025). Children appropriate for XR screening (Glasgow Coma Scale score >13, asymptomatic, non-obtunded) were identified using consensus criteria. XR utilization, sensitivity, and negative predictive value (NPV) were assessed, and multivariable logistic regression identified predictors of XR use. Results: XR was performed in 39% of patients overall and varied significantly by trauma center type (pediatric 48% vs adult 14% vs mixed 15%; p<0.001), whereas CT was used in 60%. Among XR-appropriate children (n=12,650), an estimated 7,705 CT examinations could potentially have been replaced with XR. In the overall cohort, XR sensitivity for any cervical spine injury was 30.3% (95% CI 26.2–34.6%) with an NPV of 95.2% (95% CI 94.7–95.7%). In XR-appropriate children, only two clinically significant cervical spine injuries were missed, yielding a sensitivity of 75.0% (95% CI 34.9–96.8%) and an NPV of 99.9% (95% CI 99.9%–100.0%). Conclusions: Plain radiography is substantially underutilized in children meeting consensus criteria for XR-first imaging. In appropriately selected patients, XR demonstrated an NPV of 99.9% for clinically significant cervical spine injury, supporting broader implementation of XR-first imaging strategies to reduce CT utilization and pediatric radiation exposure.

Abstract Cellular senescence has been implicated in the pathophysiology of radiotherapy-associated bone loss. Based on our previous work, clearance of senescent cells using genetic and pharmacological tools alleviates the anomalies associated with radiation-associated bone deterioration. The pro-inflammatory senescence associated secretome referred to as senescence associated secretory phenotype (SASP), is a hallmark of cellular senescence. The modulation of SASP by senomorphic drugs, potentially can suppress the pro-inflammatory secretome of senescent cells, irrespective of the underlying senescence mechanism. In this study we tested a senomorphic drug, ruxolitinib, a Janus kinase inhibitor (JAKi), during acute and chronic radiotherapy related effects on the bone. Our clinical data indicate an early increase in several pro-inflammatory SASP proteins following radiotherapy of spinal metastasis in prostate cancer patients. Longitudinal assessment of SASP-related genes confirmed this acute elevation in several SASP markers in systemic circulation following irradiation of male mouse femurs. In studies done in male mice, following three preclinical radiotherapy regimens of 30Gy (5 x 6Gy), 60Gy (5 x 12Gy) and a single dose of 24Gy, suppression of SASP by JAKi was efficacious in suppressing radiation-induced bone damage. In comparison and as shown before, the senolytic combination of D+Q was also able to alleviate radiation-associated bone loss. Early and intermittent suppression of SASP using JAK inhibitors in male mice alleviated chronic bone deterioration, diminished telomere dysfunction, lowered senescence and SASP marker expression and reduced bone-marrow adiposity. Overall, our study shows that early targeting of SASP proteins could be a potential therapeutic to prevent radiotherapy-related chronic bone loss and risk of fractures.

ABSTRACT Prolonged operative time is associated with increased surgical complications, resource utilization, and cost. While factors such as surgeon experience and patient habitus are well recognized, the impact of anatomical anomalies and variations remains poorly quantified. This systematic review evaluates the influence of abdominal structural anomalies and anatomical variations on operative time. Following PRISMA 2020 guidelines, a search of PubMed (2000–2025) identified 82 eligible studies. Operative‐time impact was assessed using added operative time relative to reference benchmarks. The unit of analysis was the procedure‐level observation. Observations were stratified by procedure category and surgical complexity and summarized using median added operative time and range. Among procedure‐level observations with available benchmarks, 13 of 14 (92.9%) structural anomalies, 48 of 54 (88.9%) situs inversus cases, and 10 of 11 (90.9%) other anatomical variants demonstrated increased operative time relative to baseline. Structural anomalies were associated with larger median increases, particularly in colorectal procedures, whereas anatomical variations demonstrated a more heterogeneous effect across procedural systems. Higher‐complexity procedures, including pancreatic operations, showed greater absolute increases in operative time. Preoperative identification of anatomical differences was associated with attenuation of operative delays. Structural anomalies are frequently associated with increased operative duration, whereas anatomical variations demonstrate a more variable and context‐dependent effect. The magnitude of operative time impact is influenced by procedural complexity and preoperative planning. Incorporating anatomical variability into surgical planning may reduce avoidable operative delays and improve operative efficiency.

Abstract Standard of care RPT may result in dose-limiting side effects of the salivary glands include sialadenitis and xerostomia that are inconsistent with outcomes from external beam for equivalent ADs. This work develops a parametrizable ‘Macro-to-Micro’ (M2μ) model that demonstrates the consideration of small-scale dosimetry in comparison to conventional methods that typically assume uniform voxel or organ-level uptake. Anatomical features of the salivary gland are represented by annular structures (a centralized branching network of ducts, including excretory, lobar, interlobular) and small-scale voxels (intralobular ducts and acinar cells) with dimensions set to reproduce ex-vivo murine histopathology measurements and scaled up in size for extrapolation to humans. Simulations were performed by scoring and recording S-value histograms to the target ductal and acinar cells, for two beta emitters (177Lu, 131I) and one alpha emitter (225Ac). Four idealized activity distributions were created to assign activity to surface and volumes of the annuli, and GEANT4 v11 was used for radiation transport calculations. Comparisons against whole gland uniform spherical self-dose S-value calculations were conducted to validate the radiation transport and to highlight differences between M2μ and conventional dosimetry approaches. Analyses for both models showed greater S-value variation in comparison to the homogeneously distributed activity S-value calculation. The most notable result was that the calculated S-values differed between different branches, depending on the geometric size of the annuli. For the surrounding acinar cells, S-values from ductal cells decreased as a function of distance from the branching structures. High variability of S-values, depending on ductal cell dimensions as well as within the acinar cell distribution of the salivary gland highlights the potential clinical utility of small-scale approaches to RPT salivary gland dosimetry, contingent on clinical translation and validation. To this end, future work should further refine the model and incorporate small-scale activity distributions from pre-clinical and translational studies.