MethodsX

Distal radius fractures (DRFs) can delay return to activities of daily living and social participation because of postoperative pain, temporary joint immobilization, and limited wrist and forearm range of motion. The Ghost System developed at Saitama Prefectural University, Japan, combines visual action observation with tendon vibration stimulation and has shown potential as an adjunct to conventional rehabilitation. This Study Protocol describes a modified Ghost system intended to improve clinical implementation by replacing the head-mounted virtual reality display with iPad-based action observation and by using a wristband-type vibrator. This single-center, single-arm, open-label feasibility trial will enroll 10 adults after palmar locking plate fixation for DRF. The intervention will be delivered twice weekly during outpatient rehabilitation follow-up sessions from the early postoperative period (postoperative days 2-10 after enrollment) through the approved early postoperative rehabilitation period (generally up to postoperative week 8), in parallel with standard rehabilitation practices. Primary feasibility and preliminary clinical outcomes include device fit and acceptability, pain assessed using a 100-mm Visual Analog Scale, and wrist/forearm range of motion. Secondary implementation and safety outcomes include Disabilities of the Arm, Shoulder and Hand (DASH), Patient-Rated Wrist Evaluation (PRWE), Hand20 Questionnaire (HANDS-20), EuroQol 5 Dimensions 5 Levels (EQ-5D-5L), body ownership and hand-illusion questionnaires, setup time, setup errors, adherence, adverse events, and device incidents. We hypothesize that the modified Ghost system will be feasible and acceptable for early postoperative outpatient rehabilitation and will be delivered without serious device-related adverse events. Clinical outcomes will be summarized descriptively to inform a future controlled study rather than to establish efficacy.

Minimally invasive endovascular procedures offer reduced surgical trauma, shorter recovery times, and improved outcomes, but rely on 2D fluoroscopic X-ray imaging, which provides limited depth perception and exposes patients and clinicians to ionizing radiation. Here we present an augmented reality (AR) system that fuses intravascular ultrasound (IVUS) and electromagnetic (EM) position tracking with preoperative computed tomography (CT) to produce an anatomically accurate, deformation-corrected navigational reference. A robotic device performs ECG-gated pullback of the IVUS probe, capturing 4D aortic motion across the cardiac cycle. We introduce a deep learning architecture for extracting vascular lumen boundaries and side-branch orifices from artifact-prone IVUS streams, and a semantically driven non-rigid CT-IVUS fusion pipeline robust to false positive landmarks. We evaluate the platform with trained surgeons in benchtop phantom studies and in-vivo ovine models, and demonstrate its application to fenestrated endovascular aneurysm repair (FEVAR). Compared to fluoroscopy alone, AR guidance significantly reduces cannulation time, radiation exposure, and cognitive workload, while improving procedural efficiency and safety. Our IVUS-EM and CT aortic datasets are released open source.

Abstract Introduction: Proximal humerus fractures account for approximately 5-6% of all adult fractures and are primarily managed nonoperatively. Healing is conventionally monitored with radiographs, with radiopaque callus formation indicating healing. Visible radiographic callus appears weeks after biological union begins. Ultrasound provides a dynamic, radiation-free, and cost-effective method that can detect early callus formation before x-ray visibility. Although ultrasound has demonstrated utility for fracture healing in the clavicle and humeral shaft, its role in proximal humerus fractures remains unclear. Methods: This single-centre prospective study will be conducted in two phases. The pilot phase will measure inter-rater reliability for ultrasound detection of early callus formation at 2 and 4 weeks post-injury. Ten patients with proximal humerus fractures treated nonoperatively will undergo standardized anterior and lateral scans. Each patient will generate four saved images (short- and long-axis views), producing forty anonymized images independently reviewed by two raters. The prospective cohort phase will recruit approximately thirty additional patients. Results: Reliability will be quantified using Cohens kappa. A power calculation will be performed after pilot analysis. Results from the prospective cohort phase will help determine the association and predictive value of early ultrasound-detected bridging callus for radiographic and clinical union at three and six months. Patient reported outcome measures will be assessed using the Quick Disabilities of Arm, Shoulder and Hand (QuickDASH) questionnaire. Discussion: This study will develop and validate a standardized ultrasound protocol for assessing early fracture healing in proximal humerus fractures. By establishing both inter-rater reliability and predictive value, the findings may support ultrasound as a reproducible, radiation-free adjunct to conventional imaging and enable earlier identification of union status.

The incidence rate ratio R is the standard measure for comparing event rates in clinical trials and epidemiology. In vaccine trials, the vaccine efficacy is VE = 1 - R. When events are rare, the two arm counts are Poisson. The estimator of R is heteroskedastic: its sampling variance changes with the data. So no fixed-width interval covers correctly everywhere. The usual log-Wald interval is undefined at zero events and covers poorly at small counts. Early vaccine and drug-safety readouts fall in exactly this regime. We show that a single reparameterization collapses this bivariate problem to an effective one-parameter family with a quadratic variance function, whose variance-stabilizing transformation is 2 arcsinh(sqrt(R)). The reduction yields a closed-form confidence interval for R. Its two leading errors, a curvature bias and the variability of the estimated scale, each admit a closed-form correction with no tuning constants. In a Monte Carlo study of our seven arcsinh variants and five competitors, the +Curve+Stu variant covers within 0.002 of the nominal 0.95 for about 50 control and 5 treatment events. Its width is on par with the best competitor. It avoids the conservatism and zero-count breakdown of log-Wald and MOVER. For moderate counts, we recommend this interval; for sparser data, our Bar-Lev and Enis count-shift variant is more robust. The result is a ready-to-use, closed-form interval for the low-count regime. We illustrate it on early Covid-19 vaccine-efficacy readouts and provide reference implementations in R and Python.

BACKGROUND In line with International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) recommendations for high-sensitivity cardiac troponin assays, analytical validation and reference limit assessments are required to confirm that an assay meets performance criteria. This study evaluated the analytical performance and established the 99th percentile upper reference limit (URL) for the SPINCHIP High-Sensitivity Cardiac Troponin I (SPINCHIP hs-cTnI) point-of-care assay. METHODS Analytical performance characteristics, including the limit of blank (LoB), limit of detection (LoD), and limit of quantification (LoQ), were assessed. Additionally, 1,053 plasma samples and 1,055 whole-blood samples were used to determine the URL. Imprecision around the 99th percentile URL was evaluated as part of the analytical validation. High-sensitivity criteria were assessed by confirming measurable cTnI in [&ge;]50% of healthy individuals (n=432 plasma; n=431 whole blood) and achieving imprecision <10% at the 99th percentile (plasma, n=960; whole blood, n=480). RESULTS SPINCHIP hs-cTnI demonstrated a LoB of 0.3 ng/L; LoDs of 0.8 ng/L (plasma) and 0.9 ng/L (whole blood); and LoQs of 1.1 ng/L (plasma) and 1.4 ng/L (whole blood). The analytical measuring range was 1.1-9,000 ng/L. Imprecision at the common 99th percentile URL (14 ng/L) was 5.8%; for men (URL=16 ng/L) 5.6% and for women (URL=10 ng/L) 6.3%. Greater than 85.2% (94.0% and 76.1% in men and women, respectively) of healthy individuals showed measurable cTnI above the LoD. CONCLUSIONS The SPINCHIP hs-cTnI assay meets the IFCC high-sensitivity requirements, demonstrating <10% imprecision at the 99th percentile, reliable low-concentration precision and cTnI detection in more than half of healthy individuals.

Aims Polymer-free drug-eluting stents were developed to enhance vascular biocompatibility and safety while maintaining antirestenotic efficacy. The TRANSEVER registry evaluated 12-month clinical outcomes of the polymer-free everolimus-eluting ISAR SUMMIT stent in a large, real-world population undergoing percutaneous coronary intervention. Methods This prospective, multicentre study enrolled patients with coronary artery disease undergoing PCI with the ISAR SUMMIT stent across 33 centres in India. The primary endpoint was target-lesion failure (TLF) at 12 months, a composite of cardiac death, target vessel myocardial infarction, or clinically driven target lesion revascularisation. Secondary endpoints included the patient-oriented composite endpoint (POCE) of all-cause death, any myocardial infarction, stroke, revascularization, and definite/probable stent thrombosis. Results A total of 1,000 patients were enrolled, of whom 996 completed 12-month follow-up. The cohort presented with a high-risk profile, including an acute coronary syndrome (ACS) in 89.8% of the cases and diabetes mellitus in 44.4% of them. Procedural outcomes were excellent in terms of device success and final TIMI 3 flow (achieved in all treated lesions). At 12 months, TLF occurred in 15 patients (1.5%). Definite or probable stent thrombosis was observed in 8 patients (0.8%). POCE was observed in only 21 patients (2.1%). Conclusions In this large, contemporary real-world population with a very high proportion of patients presenting with ACS, the polymer-free everolimus-eluting ISAR SUMMIT stent demonstrated favourable 12-month clinical outcomes, with low rates of target lesion failure and stent thrombosis. These results suggest that this novel device is both safe and effective for routine clinical use.

As machine learning and artificial intelligence systems are increasingly used in healthcare, rigorous evaluation of their classification performance has become critical. The F1 and F{beta} scores are widely adopted metrics for assessing performance in imbalanced biomedical data. Recently, we introduced psF1, a unified statistical framework for inference and study design for single and comparative F1 and F{beta} scores under the assumption of independent classifiers. In practice, however, benchmarking two classifiers on the same dataset creates a correlated paired setting. Ignoring this intrinsic dependency leads to overestimation of the standard error and a substantial loss of statistical power. To address this, we develop psF1pair, an advanced framework for statistical inference and power analysis that explicitly accounts for correlations between classifier pairs. Extensive simulation studies demonstrate the performance of psF1pair, and its utility is further illustrated through application to a real-world imaging classification system. As expected, higher correlation between classifiers yields narrower confidence intervals and enhanced statistical power. A freely available R package is provided to facilitate implementation, supporting accurate evaluation and study design for predictive and classification models in biomedical research.

Importance: Heart failure readmissions remain common following hospitalization, but accurately identifying which patients will be readmitted after discharge remains challenging. Improved prediction could support targeted transitional care interventions and more efficient allocation of clinical resources. Objective: In this study we attempted to improve readmission prediction after heart failure hospitalization by using variables chosen through a modified Delphi process, and using inpatient Electronic Medical Record (EMR) data, focusing on clinical notes. Design: This prognostic study developed competing risk survival models to predict readmission after heart failure hospitalization. Variables were chosen using a modified Delphi process, and extracted from EMR notes using various natural language processing techniques or from other EMR elements where appropriate. Patients were admitted between 2011 through 2019, and at least one year of follow-up was available for all patients. Models were evaluated using C-statistics, as well as sensitivity, specificity, positive and negative predictive values. Setting: During the study period, all acute-care facilities in Calgary, Alberta used the same EMR system, from which patients were selected. Participants: Patients were 18 years or older, resided in Alberta, and were admitted to a Calgary hospital. All corresponding admissions with a most responsible diagnosis of heart failure were included (n=15,160). Main Outcomes and Measures: The main outcome of interest was readmission within 30 days, though 90- and 365-day time frames were also analyzed. Death was treated as a competing risk and analysed at those time frames as well.

Background: The optimal timing of percutaneous coronary intervention (PCI) in patients undergoing transcatheter aortic valve replacement (TAVR) remains unclear, particularly regarding its impact on renal outcomes. Methods: We conducted systematic review and meta-analysis of studies comparing staged versus concomitant PCI in patients with aortic stenosis and coronary artery disease undergoing TAVR. We searched MEDLINE, Embase, and Cochrane databases comprehensively. Using a random-effects model, we calculated odds ratios (OR) with 95% confidence intervals (CI) to assess the incidence of contrast-induced acute coronary injury (CI-AKI) across different stages. Results: The analysis included 11 studies encompassing 7,119 patients. Overall, staged PCI did not significantly differ from concomitant PCI in reducing CI-AKI (OR 1.02; 95% CI 0.53 to 1.98; p = 0.959; Figure 2A). Subgroup analysis revealed no significant differences in stage 1 (OR 1.99; 95% CI 0.38 to 10.47; p = 0.417; Figure 2B) or stage 2 CI-AKI (OR 1.01; 95% CI 0.39 to 2.64; p = 0.978; Figure 2C). However, a statistically significant difference emerged for stage 3/4 CI-AKI, favoring the staged approach (OR 0.48; 95% CI 0.24 to 0.99; p = 0.046; Figure 2D). Conclusion: While staged PCI does not consistently reduce CI-AKI in patients undergoing TAVR, it may offer potential benefits for more severe kidney injury (stages 3/4). Given the observed heterogeneity, large-scale randomized controlled trials are essential to establish the relationship between procedural timing and renal outcomes.

Background: Cardiovascular disease remains the leading cause of death in the United States, and marked geographic disparities in cardiovascular mortality persist. However, the community-level socioeconomic indicators most strongly associated with these disparities remain unclear. Community-level measures capture the social and economic conditions that influence cardiovascular health across populations and may help identify communities at greatest risk. We used the Area Health Resources File (AHRF) to identify socioeconomic measures most strongly associated with county-level cardiovascular mortality. Methods: We performed a national cross-sectional ecological analysis using the 2024-2025 Area Health Resources File (AHRF), including counties in the 50 U.S. states and the District of Columbia. The primary outcome was an AHRF-defined cardiovascular mortality composite derived from 2021-2023 National Center for Health Statistics (NCHS) mortality data. Community-level socioeconomic measures included 2023 overall, pediatric, and family childhood poverty and 2019-2023 overall, female, and White unemployment. County-level associations were evaluated using Spearman rank correlation and regional differences using the Kruskal-Wallis test. Sensitivity analyses used a partial mortality composite and Kendall {tau} correlation. Results: Among 1,982 counties, cardiovascular mortality varied significantly across U.S. Census divisions (P<0.001), with the highest population-weighted rate in the East South Central division (348.5 deaths/100,000) and the lowest in the Mountain division (233.9 deaths/100,000). Pediatric poverty demonstrated the strongest association with cardiovascular mortality ({rho}=0.612), followed by family childhood poverty ({rho}=0.603) and overall poverty ({rho}=0.524, all P<0.001). In contrast, unemployment measures were more weakly associated (overall {rho}=0.209, White {rho}=0.176, female {rho}=0.141, all P<0.001). Results were consistent in sensitivity analyses. Conclusions: County-level poverty, particularly pediatric poverty, was more strongly associated with cardiovascular mortality than unemployment across U.S. counties. These findings suggest pediatric poverty may serve as a useful community-level indicator for identifying populations at increased cardiovascular risk and prioritizing future public health interventions.

Controlled human infection models (CHIMs) are increasingly used in infectious disease research to study pathogen dynamics and evaluate interventions under controlled conditions. However, these studies are resource-intensive and involve ethical and safety constraints, making efficient study design critical. Dose-finding is a key early component in CHIMs, where the aim is to identify a challenge dose that achieves a target infection probability. Traditional rule-based designs are commonly used but can be inefficient, motivating the use of model-based adaptive approaches such as the Bayesian Continual Reassessment Method (CRM). Although CRM has been extensively studied and widely adopted in Phase I oncology trials for identifying the maximum tolerated dose of therapeutics, its application in CHIM settings remains limited, particularly when the endpoint of interest is infection. This tutorial provides step-by-step guidance for implementing a Bayesian CRM in dose-finding CHIMs, using an oropharyngeal Neisseria gonorrhoeae challenge as a motivating case study. The framework outlines key design components, including dose-grid specification, dose-response model, prior elicitation, Bayesian updating, decision rules, and stopping criteria, with particular emphasis on a clinically interpretable parameterisation. Trial operating characteristics are evaluated through simulation studies under multiple dose-response scenarios and prior-predictive analyses, and compared with a commonly used '3+3' type rule-based design. This work highlights the advantages of Bayesian model-based designs for dose-finding in CHIMs over classic rule-based designs and provides a structured, reproducible framework for implementing CRM, supporting their application in future CHIM studies.

Background: Apical sparing of left ventricular longitudinal strain (LS) is an echocardiographic clue to cardiac amyloidosis but may also occur in hypertensive heart disease (HHD). Objectives: To determine whether apical sparing in HHD is associated with regional left ventricular wall stress estimated according to Laplace's law. Methods: We retrospectively studied 1,559 patients with HHD, 47 with light-chain cardiac amyloidosis (ALCA), and 409 normotensive controls. Artificial intelligence-assisted echocardiography quantified segmental LS, wall thickness, and cavity radius at the basal, midventricular, and apical levels. Wall stress was estimated as mean blood pressure (MBP) x radius/(2 x wall thickness). Apical sparing was defined as a relative regional strain ratio (RRSR)[&ge;]1.0. Results: Apical sparing was present in 14 patients with HHD (0.9%), 13 with ALCA (27.7%), and no controls. Among HHD patients with apical sparing, RRSR decreased from 1.11{+/-}0.13 to 0.72{+/-}0.10 after antihypertensive treatment (P<0.001), accompanied by reduced wall stress and improved basal and midventricular LS, with resolution of apical sparing in all 14 patients. In the overall HHD cohort, changes in MBP and left ventricular mass index were independently associated with changes in RRSR. In an exploratory analysis of HHD patients with apical sparing, a reduction in basal wall stress was associated with a reduction in RRSR ({beta}=0.267 for {bigtriangleup}RRSRx100, 95% CI 0.023-0.511; P=0.036). In ALCA, favorable hematologic response was the only determinant of RRSR reduction. Conclusions: Apical sparing in HHD was uncommon but reversible and may represent a load-sensitive deformation pattern associated with regional wall stress, consistent with Laplace's law.

Fracture nonunion remains a major cause of morbidity, yet patient-specific factors associated with impaired healing remain incompletely characterized. Anemia has been associated with adverse orthopaedic outcomes, but its relationship with fracture nonunion is poorly understood. We examined whether pre-fracture anemia, anemia burden, and clinically relevant anemia subtypes were associated with nonunion following tibial or femoral fractures. Using commercial and Medicare fee-for-service claims from 2016 through 2023, we identified adults aged 19 years or older with a tibial or femoral fracture, continuous enrollment during the preceding year and for at least six months after fracture, and no baseline cancer. Pre-fracture anemia was evaluated as any anemia, the number of distinct anemia diagnoses, and nutritional, hemolytic, aplastic, and other anemia subgroups. Nonunion occurring six to eighteen months after fracture was assessed using incidence rates and multivariable-adjusted hazard models. Among 326,673 adults, 149,704 had pre-fracture anemia and 176,969 did not. The crude incidence of nonunion was 42% higher among individuals with anemia than among those without anemia (incidence rate ratio, 1.42; 95% confidence interval, 1.32 to 1.53) and increased with greater anemia burden. After adjustment for demographic and clinical characteristics, including prior fractures at other anatomical sites, pre-fracture anemia remained associated with nonunion following tibial and femoral fractures, with hazard ratios of 1.83 (95% confidence interval, 1.54 to 2.18) and 1.38 (95% confidence interval, 1.26 to 1.50), respectively. Associations were also observed for nutritional and other anemias, whereas estimates for hemolytic and aplastic anemias were limited by few nonunion events. Within the femur, the association was strongest for distal fractures. These findings demonstrate that pre-fracture anemia is independently associated with nonunion. The increase in risk with greater anemia burden and findings across evaluable subgroups suggest that pre-fracture anemia may help identify patients at increased risk of impaired fracture healing.

ABSTRACT Background: Metallic implants such as orthopedic screws, prostheses, and dental hardware produce beam-hardening, photon-starvation, and streak artifacts that degrade computed tomography (CT) image quality, and the metal artifact reduction (MAR) methods developed to mitigate them require objective, reproducible benchmarking. Purpose: Objective evaluation of MAR algorithms in CT is hindered by the absence of phantoms that simultaneously provide anatomically realistic backgrounds, embedded implants of known geometry, and controllable, ground-truth--referenced artifact intensity. We present a dual-filament, voxel-level three-dimensional (3D) printing method that fulfills these requirements and demonstrate its capabilities on a clinically representative cervical spine case with embedded orthopedic spinal screws. Methods: The proposed method extends the PixelPrint framework, a fused-deposition-modeling (FDM) workflow that converts clinical Digital Imaging and Communications in Medicine (DICOM) data directly into 3D-printer Geometric code (G-code) without intermediate segmentation or surface meshing, to interleaved, voxel-level deposition of two filaments: a calcium-doped polylactic acid (PLA) for soft tissue and bone, and a higher-attenuation metal-doped PLA for metallic implants. For demonstration, anonymized DICOM data of a healthy cervical spine were used to design and fabricate three matched phantoms, each with six embedded spinal screws at C4--C6: a 0% metal-infill ground-truth phantom, a 50% medium-metal-infill phantom, and an 85% high-metal-infill phantom. All phantoms were scanned on a clinical spectral CT system at 120 kVp and 1000 mAs, reconstructed at 0.67 mm slice thickness with virtual monoenergetic imaging (VMI) across 50--190 keV. Method performance was characterized by region of interest (ROI)-based Hounsfield Unit (HU) agreement with the source patient data and by the noise-independent Gumbel-distribution p-index metric. Results: The dual-filament method reproduced patient anatomy, soft-tissue contrast, and screw geometry with high fidelity. ROI HU values agreed with patient data within {+/-}25 HU for soft tissue and trabecular bone; cortical regions were underestimated owing to the current ceiling of the calcium-doped PLA used in this study. The tunable-artifact behavior was quantified as follows: the Gumbel location parameter scaled monotonically from 46.7 HU (no-metal background) to 57.1 HU (50% infill) to 90.5 HU (85% infill) for the VMI 70 keV with standard filter. High-keV VMI reconstructions substantially reduced streak and beam-hardening artifacts while preserving anatomic detail. Conclusions: The proposed dual-filament, voxel-level PixelPrint method enables the fabrication of patient-specific, multi-material CT phantoms with embedded metallic implants and controllable, ground-truth--referenced artifact intensity. Although demonstrated here in a single cervical-spine case, the workflow is anatomy- and implant-agnostic by construction and could in principle be adapted to other musculoskeletal sites (e.g., knee, hip, dental) and implant materials, providing a reproducible methodological foundation for benchmarking MAR algorithms, characterizing spectral CT performance, and validating emerging photon-counting detector systems. Keywords: 3D printing methodology; fused deposition modeling; voxel-level multi-material printing; spectral computed tomography; metal artifact reduction; phantom design; orthopedic implants; dual filament; PixelPrint.

Consumer-grade bioelectrical impedance analyzers have become widely used for body composition assessment, yet their accuracy varies considerably across devices. The Hume Pod is a popular consumer-grade analyzer marketed as being highly accurate, but independent validation is lacking. The purpose of this study was to evaluate the reliability and validity of the Hume Pod relative to both a four-compartment (4C) model and dual-energy X-ray absorptiometry (DXA). Sixty-seven adults (42 females, 25 males; age 37.2 +/- 13.5 years, body mass index: 24.6 +/- 4.9 kg/m2, body fat percentage [BF%]: 26.4 +/- 10.2%) completed duplicate Hume Pod assessments alongside DXA and 4C evaluations. Reliability was evaluated using the technical error of measurement (TEM) and intraclass correlation coefficients (ICC). Validity was assessed using equivalence testing, Lin's concordance correlation coefficient (CCC), standard error of the estimate (SEE), Bland-Altman analysis, and additional tests. The Hume Pod demonstrated strong reliability, with ICCs >/= 0.993 and TEMs of 0.8% for BF% and 0.6 kg for fat mass (FM) and fat-free mass (FFM). Relative to the 4C model, BF%, FM, and FFM estimates were statistically equivalent (all p<0.05), with strong agreement (CCC=0.95-0.98), low SEE values (3.1%, 2.3 kg, and 2.2 kg, respectively), moderate limits of agreement (+/-6.1%, +/-4.5 kg, and +/-4.5 kg), and no proportional bias. Compared with DXA, generally strong agreement was also observed. These findings indicate that the Hume Pod demonstrates strong reliability and validity compared with laboratory reference methods for body composition estimation, supporting its potential use as a consumer body composition assessment.

Hypertension is commonly defined as a binary condition despite substantial heterogeneity in diagnosis, treatment, and blood pressure (BP) control. We propose a three-axis state model integrating diagnosis status, treatment intensity, and BP control to better characterize hypertension phenotypes. The framework generates 27 possible states that can be condensed into seven clinically meaningful groups. We applied the model to 5,129,584 Japanese adults using the National Database of Health Insurance Claims and Specific Health Checkups. Hierarchical cluster analysis, sensitivity analysis excluding patients with cardiovascular diseases other than hypertension, and validation against antihypertensive medication use were performed. Overall, 64% of participants were classified as normotensive, whereas 36% belonged to hypertension-related groups, including 11% with unrecognized hypertension and 7% with diagnosed but untreated hypertension. Agreement with data-driven hierarchical cluster analysis was substantial (weighted {kappa}=0.87). The group distribution remained largely unchanged in the sensitivity analysis, supporting the robustness of the proposed classification. Hypertension diagnosis also showed high validity, with a sensitivity of 96.5%, specificity of 91.8%, and substantial agreement with antihypertensive medication use ({kappa}=0.78). This three-axis framework provides a robust and clinically interpretable approach for characterizing hypertension phenotypes, enabling systematic identification of care gaps and supporting research, clinical decision-making, and population health management.

Background: Bicuspid aortic valve anatomy increases procedural complexity during transcatheter aortic valve implantation, yet outcome-oriented anatomic risk stratification for intraprocedural events remains limited. Aims: We aimed to develop and externally validate an anatomy-driven score to predict a composite intraprocedural endpoint, assessed at exit from the procedure room, in bicuspid transcatheter aortic valve implantation. Methods: Consecutive patients with bicuspid aortic valve undergoing transcatheter aortic valve implantation were analysed in a development cohort (N=793) and a multicentre external validation cohort (N=134). Candidate preprocedural computed tomography and echocardiographic variables were prespecified by expert consensus and refined using penalized regression with bootstrap stability selection within a domain-constrained framework. A five-indicator score (0 to 10 points) was derived from routine imaging metrics spanning the ascending aorta, aortic root, valve complex, annulus-outflow tract unit, and left ventricle, and tested using multivariable logistic regression. Results: The composite intraprocedural endpoint occurred in 101/793 (12.7%) patients in the development cohort, with stepwise increases across risk strata (7.2%, 13.3%, 30.6%; p<0.001). Each 1-point increase was independently associated with higher risk (odds ratio 1.32; 95% confidence interval 1.18-1.47). A similar gradient was observed in external validation (3.1%, 10.8%, 50.0%; p=0.012; odds ratio 1.55 per point), with a C-statistic of 0.725. Higher risk categories were associated with lower early safety and higher 30-day and 1-year mortality. Conclusions: An anatomy-driven score derived from routine preprocedural imaging demonstrates graded discrimination of intraprocedural risk and may inform procedural planning in bicuspid transcatheter aortic valve implantation.

Background: Unplanned emergency readmissions remain common following hospitalisation for heart failure (HF). Residual congestion, atrial fibrillation, frailty, and other comorbidities contribute to adverse outcomes after discharge. Identifying patients at high risk of readmission or death may help target post-discharge management. Methods: We conducted a retrospective cohort study of patients hospitalised with HF in selected New South Wales hospitals who were discharged alive and not documented as receiving end-of-life care. Clinical, laboratory, medication, and text-derived variables extracted from electronic health records were used to develop predictive models and corresponding risk scores for emergency readmission and all-cause mortality within 180 days of discharge. Feature importance methods were used to identify key predictors and explain individual risk estimates. To illustrate model predictions while preserving patient privacy, we generated representative synthetic patient profiles by summarising the characteristics of groups of patients with similar predicted risk patterns and visualised the major contributors to their predicted risks using Shapley values. Results: The study included 5,202 hospitalisations among 3,933 patients. Within 180 days of discharge, 45.2% of patients experienced at least one emergency readmission and 12.4% died. The most common causes of emergency readmission were recurrent HF, followed by atrial fibrillation, chest pain, and pneumonia. Predictive performance was moderate for emergency readmission (AUC 0.70; calibration slope 1.30) and good for mortality (AUC 0.84; calibration slope 1.01). Emergency readmission risk was primarily associated with greater prior healthcare utilisation, a higher number of active medical problems, high risk of falls, older age, and impaired kidney function. Mortality risk was most strongly associated with abnormal red blood cell distribution width, elevated blood urea, older age, and lower systolic blood pressure. A lower number of discharge medications, particularly cardiovascular therapies, was associated with a higher risk of emergency readmission and a lower risk of mortality. Representative synthetic patient profiles demonstrated heterogeneity in the factors contributing to predicted risks, illustrating the value of patient-level risk visualisation. Conclusions: Predictive models identified clinically meaningful predictors of emergency readmission and mortality following HF hospitalisation. Patient-level visualisation of individual risk drivers may support more personalised post-discharge management.

Background: The clinical benefit and safety of drug-coated devices in chronic limb-threatening ischemia remain debated, particularly after recent randomized evidence questioning paclitaxel-coated technologies. We evaluated wound healing, limb outcomes, and mortality after infrainguinal endovascular therapy with uncoated, paclitaxel-coated, and sirolimus-coated devices. Methods: Consecutive patients with chronic limb-threatening ischemia undergoing successful infrainguinal endovascular therapy in a prospective single-center service evaluation were analyzed. The primary exposure was use of any drug-coated device during the index procedure. Inverse probability of treatment weighting and multivariable Cox models were used to adjust for baseline differences. Exploratory analyses compared paclitaxel-coated, sirolimus-coated, and uncoated devices. Results: Among 341 patients, 244 (71.6%) received at least one drug-coated device. After weighting, drug-coated device use was associated with more frequent wound healing, whereas major amputation, clinically driven target lesion revascularization, major adverse limb events, and death did not differ significantly between groups. In weighted multivariable models, drug-coated device use remained associated with wound healing (HR, 1.86; 95% CI, 1.14?3.02), but not with mortality or major limb events. Exploratory drug-specific analyses suggested the highest wound-healing rates among patients treated with sirolimus-coated devices, while mortality was comparable between paclitaxel-coated and uncoated devices. Conclusion: In this real-world cohort of patients with chronic limb-threatening ischemia undergoing infrainguinal endovascular therapy, drug-coated device use was not associated with increased adjusted 1-year mortality and was associated with improved wound healing. Exploratory analyses suggested favourable wound-healing outcomes with sirolimus-coated balloons, with a lower observed mortality signal that warrants confirmation in larger comparative studies.

Objective: Photobiomodulation therapy has emerged as a promising modality to facilitate scar healing and pain management in dermatology and plastic surgery. However, its role in postoperative care following spine surgeries remains understudied. This double-blinded, placebo-controlled study aimed to investigate the effects of photobiomodulation in patients with chronic lower back pain undergoing lumbar decompression, with postoperative wound healing as the primary outcome and pain reduction and functional recovery as secondary outcomes. Methods: Patients were randomized to receive either active photobiomodulation braces (N=13) or placebo braces (N=12). Follow-up assessments were performed at 2, 4, 6, 8, and 12 weeks postoperatively. Outcomes included wound healing (Stony Brook Scar Evaluation Scale), back and leg pain (Visual Analog Scale), quality of life (EuroQol 5D), and functional status (Oswestry Disability Index). Results: Compared to the placebo group, the photobiomodulation treatment group had a 4.12-fold cumulative improvement in final scar scores, with significant between-group differences at postoperative weeks 6, 8, and 12 (p = 0.0062, 0.010, 0.042). Among patients with severe preoperative disability, treatment resulted in a 1.89-fold faster improvement in back pain (p=0.025) and a 1.80-fold faster improvement in ODI scores (p=0.025); and superior treatment effect on wound healing were again observed at weeks 6, 8, and 12. Among patients with poor initial scars, treatment led to a significantly better scar outcome than placebo at week 6 and a 1.94-fold faster EQ5D improvement (p=0.052), with significant gains observed as early as two weeks after surgery. There were no adverse events associated with photobiomodulation treatment. Conclusions: Photobiomodulation significantly promoted postoperative wound healing following lumbar decompression surgery, with therapeutic benefits preserved even in patients with poor baseline scar scores and functional impairment. This indicates that the efficacy of photobiomodulation is not limited by the initial scar condition or disability, supporting its broad clinical applicability. Additionally, patients with severe preoperative disability experienced greater benefits from photobiomodulation than placebo, including faster reduction in back pain and more rapid improvement in functional capacity, highlighting its role in postoperative pain management and rehabilitation. These therapeutic effects are likely mediated by photobiomodulation-induced reduction of inflammation and enhancement of tissue repair. Together, this study suggests that photobiomodulation can be a promising adjunct therapy to facilitate postoperative recovery in patients undergoing spine surgery.