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Background Right ventricular (RV) maladaptation to elevated pulmonary afterload is the primary determinant of outcomes in pulmonary artery (PA) hypertension; however, the pathobiological mechanisms underlying RV decompensation remain poorly understood. Methods We performed global untargeted metabolomics on plasma from 55 patients who underwent gold‐standard RV‐PA coupling measurements using multibeat pressure volume loop assessment in a single‐center cohort and from 1027 patients with coupling surrogate measurements in a larger multicenter cohort, the PVDOMICS (Pulmonary Vascular Disease Phenomics) study. Age and sex‐adjusted linear regression was performed to identify associations between metabolites and coupling metrics. Additionally, we performed a metabolic flux analysis using gene expression data from RV tissue in an independent cohort of 32 patients. Partial least squares–discriminant analysis was used to identify metabolites and reactions characteristic of the decompensated RV. Results RV‐PA coupling was negatively associated with tricarboxylic acid (TCA) cycle intermediate levels. Specifically, plasma α‐ketoglutarate and fumarate were significantly associated with all coupling metrics in both cohorts. Metabolic flux analysis indicated that decompensated RVs exhibited aberrant TCA cycle activity, including reduced acetyl coenzyme A entry and increased lactate elimination, suggesting a shift from the TCA cycle toward glycolysis at the RV tissue level. Conclusions We identify an association between circulating TCA cycle intermediate levels and RV‐PA uncoupling in 2 independent cohorts, and dysregulated TCA cycle metabolism in decompensated PA hypertension RVs, suggesting that aberrant TCA cycle metabolism could represent a hallmark of RV maladaptation in PA hypertension. Further study of this pathway is warranted to develop novel biomarkers of RV function or RV‐targeted therapies.

ABSTRACT Pneumonia may be caused by a diverse group of microorganisms; however, a microbiologic diagnosis is not universally made. Molecular tests such as the BIOFIRE FILMARRAY Pneumonia Panel (BF-PP) offer the possibility of rapid identification of potential pneumonia pathogens. This retrospective analysis was conducted as a sub-study of a recently published randomized controlled trial. Specimens from patients with suspected pneumonia were tested by the BF-PP, with results compared to cultures. The overall BF-PP positivity rate was 44.8% (252/563), and was higher [64.6% (164/254)] in specimens from patients ultimately diagnosed with pneumonia. Discrepancies between the BF-PP and cultures were most common for Streptococcus pneumoniae , Haemophilus influenzae , Moraxella catarrhalis, and Streptococcus agalactiae . Positive percent agreement (PPA) and negative percent agreement (NPA) between the BF-PP and culture were 91.4% (CI 86.3%–94.9%) and 83.6% (CI 79.5%–87.2%), respectively. For most bacteria, a correlation between high genomic abundance (genomic copies/mL) reported from the BF-PP and culture growth abundance was found. In specimens from patients ultimately diagnosed with pneumonia, clinical consistency—assessed based on whether BF-PP results aligned with associated culture results—was 79.9% and was highest for bronchoalveolar lavage fluid specimens. The BF-PP has reliable analytical performance and offers the potential advantage over conventional cultures of providing higher detection rates and more rapid results. Interestingly, despite the use of this advanced molecular diagnostic tool, one-third of pneumonia cases remained without a microbiologic etiology. IMPORTANCE This study evaluates the BIOFIRE FILMARRAY Pneumonia Panel by comparing its performance to conventional cultures in a real-world patient population (including patients ultimately diagnosed as not having pneumonia) using different types of specimens. Findings show a higher detection rate of microorganisms with the panel compared to cultures, suggesting that this test could aid in tailoring treatments for pneumonia. However, challenges remain and require further study, including distinguishing true pathogens from colonizing microorganisms and determinig why one-third of patients diagnosed with pneumonia still lacked a microbiologic etiology.

Currently, approximately 90,000 patients are on the kidney transplant waitlist in the United States, including 10,000 individuals awaiting re-transplantation due to prior graft failure. Allograft rejection remains a leading cause of kidney transplant failure. While the current gold standard for diagnosing rejection is tissue biopsy, it is invasive and impractical for routine or longitudinal graft surveillance. This review summarizes the current landscape of non-invasive biomarkers for detecting and predicting kidney transplant rejection, with a focus on both historical context and recent advancements. In particular, we highlight the roles of donor-derived cell-free DNA (dd-cfDNA) and gene expression profiling (GEP) in identifying acute rejection. We also discuss emerging biomarkers such as torque teno virus (TTV), which has shown potential as an indirect indicator of immunosuppression levels and rejection risk. Importantly, this review excludes biomarker studies that rely on tissue biopsy, emphasizing non-invasive approaches to rejection monitoring.

Abstract As the prevalence of hip arthroscopy increases, management of capsular defects as well as capsulotomy closure has increasingly been recognized for their impact on recurrent symptoms in the young athletic hip. Several recent studies have shown that capsular closure at the time of primary hip arthroscopy improves both short‐ and long‐term patient‐reported outcomes, revision rates, and conversion to arthroplasty. Specifically, capsular insufficiency is a source of recurrent pain and microinstability. In this context, far medial labral tears pose a challenge for suture fixation, given the historic need of extending the interportal capsulotomy to obtain adequate trajectory for suture anchors and subsequent passage. Given the suboptimal stability consequences of extending the capsulotomy medially, here we present a novel approach for suture fixation of the medial labrum. This technique provides an effective method for suture fixation of the medial labrum, without necessitating extension of the interportal capsulotomy. Technique Video video See video under supplementary data.

Abstract Arthrofibrosis of the knee is a difficult‐to‐manage complication after meniscoligamentous knee injuries, traumatic injuries with articular extension, and surgeries to treat these conditions. Treatment protocols for the management of postoperative arthrofibrosis exhaust nonoperative therapies before proceeding to the operating room for lysis of adhesions (LOA). Although LOA restores range of motion in most cases, a recurrence of arthrofibrosis is possible when postoperative therapy protocols are not strictly followed. Limited treatment options exist in the setting of recalcitrant arthrofibrosis. Revision arthroscopic LOA may be performed in this scenario. This revision procedure places neurovascular anatomy in the posterior compartment at risk. Performing a posterior capsule release in the arthroscopic management of recalcitrant arthrofibrosis is challenging but important to optimize recovery of range of motion. This Technical Note and accompanying video present a stepwise approach to LOA that demonstrates a safe method for performing an arthroscopic posterior capsule release in these challenging cases. Technique Video video See video under supplementary data.

Abstract INTRODUCTION Clinicians’ views on the clinical readiness of Alzheimer's disease (AD) blood biomarkers (BBMs) are not well understood. METHODS The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment Biofluid‐Based Biomarkers Professional Interest Area conducted a survey to elicit clinician opinions on AD BBM implementation, including contexts of use, assay selection, reporting, and result interpretation. RESULTS Clinician respondents ( n = 212) practiced in Europe (56%), North America (24%), the Caribbean and Central/South America (11%), and other continents (9%). Most respondents were medical doctors (80%) practicing in secondary or tertiary care (88%). For 56%, cerebrospinal fluid AD biomarkers or amyloid positron emission tomography were accessible, but 48% agreed and 52% disagreed with the implementation of AD BBMs in any clinical context. Respondents emphasized the need for data from diverse populations and educational resources to support test interpretation. DISCUSSION Surveyed clinicians generally agreed with published appropriate use recommendations but were divided on AD BBM readiness for clinical use. Highlights A survey of clinicians was conducted regarding clinical readiness of Alzheimer's disease (AD) blood biomarkers (BBMs). Views were split on AD BBM clinical readiness: 48% agreed, 52% disagreed. Most responders supported AD BBM use for treatment decisions. Most responders opposed AD BBM testing in asymptomatic individuals. Test performance data and educational materials to aid interpretation were of high importance.

Purpose Automating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. Manual QA is tedious, time-consuming, and prone to subjective experiences. Automatic segmentation reduces physician workload and improves consistency. However, an effective QA process for these automatic contours remains an unmet need in clinical practice. Materials and Methods The patient data used in this study was derived from the AAPM Thoracic Auto-Segmentation Challenge dataset, including left and right lungs, heart, esophagus, and spinal cord. Two groups of organ-at-risk (OAR) were generated. A ResNet-152 network was used as a feature extractor, and a one-class support vector machine (OC-SVM) was employed to classify contours as ‘high’ or ‘low’ quality. To evaluate the generalizability, we generated low-quality contours using translation and resizing techniques and assessed correlations between detection limits and metrics such as volume, Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD). Results The proposed OC-SVM model outperformed binary classifiers n metrics such as balanced accuracy and area under the receiver operating characteristic curve (AUC) . It demonstrated superior performance in detecting various types of contour errors while maintaining high interpretability. Strong correlations were observed between detection limits and contour metrics. Conclusion Our proposed model integrates an attention mechanism with a one-class classification framework to automate QA for OAR delineations. This approach effectively detects diverse types of contour errors with high accuracy, significantly reducing the burden on physicians during radiotherapy planning.