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Importance Nontraumatic subarachnoid hemorrhage (SAH) represents the third most common stroke type with unique etiologies, risk factors, diagnostics, and treatments. Nevertheless, epidemiological studies often cluster SAH with other stroke types leaving its distinct burden estimates obscure. Objective To estimate the worldwide burden of SAH. Design, Setting, and Participants Based on the repeated cross-sectional Global Burden of Disease (GBD) 2021 study, the global burden of SAH in 1990 to 2021 was estimated. Moreover, the SAH burden was compared with other diseases, and its associations with 14 individual risk factors were investigated with available data in the GBD 2021 study. The GBD study included the burden estimates of nontraumatic SAH among all ages in 204 countries and territories between 1990 and 2021. Exposures SAH and 14 modifiable risk factors. Main Outcomes and Measures Absolute numbers and age-standardized rates with 95% uncertainty intervals (UIs) of SAH incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) as well as risk factor–specific population attributable fractions (PAFs). Results In 2021, the global age-standardized SAH incidence was 8.3 (95% UI, 7.3-9.5), prevalence was 92.2 (95% UI, 84.1-100.6), mortality was 4.2 (95% UI, 3.7-4.8), and DALY rate was 125.2 (95% UI, 110.5-142.6) per 100 000 people. The highest burden estimates were found in Latin America, the Caribbean, Oceania, and high-income Asia Pacific. Although the absolute number of SAH cases increased, especially in regions with a low sociodemographic index, all age-standardized burden rates decreased between 1990 and 2021: the incidence by 28.8% (95% UI, 25.7%-31.6%), prevalence by 16.1% (95% UI, 14.8%-17.7%), mortality by 56.1% (95% UI, 40.7%-64.3%), and DALY rate by 54.6% (95% UI, 42.8%-61.9%). Of 300 diseases, SAH ranked as the 36th most common cause of death and 59th most common cause of DALY in the world. Of all worldwide SAH-related DALYs, 71.6% (95% UI, 63.8%-78.6%) were associated with the 14 modeled risk factors of which high systolic blood pressure (population attributable fraction [PAF] = 51.6%; 95% UI, 38.0%-62.6%) and smoking (PAF = 14.4%; 95% UI, 12.4%-16.5%) had the highest attribution. Conclusions and Relevance Although the global age-standardized burden rates of SAH more than halved over the last 3 decades, SAH remained one of the most common cardiovascular and neurological causes of death and disabilities in the world, with increasing absolute case numbers. These findings suggest evidence for the potential health benefits of proactive public health planning and resource allocation toward the prevention of SAH.

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.

ABSTRACTBackgroundRenal medullary carcinoma (RMC) is an aggressive tumor associated with sickle cell trait. Despite treatment advances for other rare renal tumors, RMC survival remains poor. We aimed to describe the contemporary management and survival of children and adults with RMC.ProcedureIn this multicenter retrospective cohort study, Pediatric Surgical Oncology Research Collaborative sites searched their databases for patients diagnosed with RMC (2000–2022). Descriptive statistics were calculated and survival analyses performed using Kaplan–Meier and Cox regression.ResultsThirty‐four patients with RMC were identified. Median age was 19 years (IQR: 15–28; range: 7–52). Most were male (24/34; 71%), Black (27/32; 84%), had sickle cell trait or disease (30/33; 91%), presented with metastatic disease (27/34; 79%), and were symptomatic at presentation (32/34; 94%). Median overall survival (OS) was 24 months from diagnosis (16 months for children, 28 months for adults, p = 0.6). Receipt of platinum‐based chemotherapy (23/34; 68%) was associated with significantly higher OS than other regimens (35 vs. 5 months, p < 0.001). Nephrectomy (24/34; 71%) was associated with significantly improved OS compared with non‐operative management (34 vs. 7 months, p = 0.001). Immunotherapy, targeted therapy, or radiation therapy were not associated with significant differences in OS, nor were age, sex, race, sickle cell status, SMARCB1/INI‐1, stage, nephrectomy approach, retroperitoneal lymph node dissection, gross residual disease, margins, or tumor size.ConclusionsRMC survival remains poor despite newer therapies. Nephrectomy and platinum‐based chemotherapy should be considered in locally advanced and metastatic disease. Coordinated international cooperative group studies are needed to meaningfully improve RMC survival.

Artificial intelligence (AI) has emerged as a transformative force in orthopedic surgery. Potentially encompassing pre-, intra-, and postoperative processes, it can process complex medical imaging, provide real-time surgical guidance, and analyze large datasets for outcome prediction and optimization. AI has shown improvements in surgical precision, efficiency, and patient outcomes across orthopedic subspecialties, and large language models and agentic AI systems are expanding AI utility beyond surgical applications into areas such as clinical documentation, patient education, and autonomous decision support. The successful implementation of AI in orthopedic surgery requires careful attention to validation, regulatory compliance, and healthcare system integration. As these technologies continue to advance, maintaining the balance between innovation and patient safety remains crucial, with the ultimate goal of achieving more personalized, efficient, and equitable healthcare delivery while preserving the essential role of human clinical judgment. This review examines the current landscape and future trajectory of AI applications in orthopedic surgery, highlighting both technological advances and their clinical impact. Studies have suggested that AI-assisted procedures achieve higher accuracy and better functional outcomes compared to conventional methods, while reducing operative times and complications. However, these technologies are designed to augment rather than replace clinical expertise, serving as sophisticated tools to enhance surgeons’ capabilities and improve patient care.

Background: Hidradenitis suppurativa (HS) is a chronic, recurrent inflammatory condition and is associated with significant psychosocial impacts on patient quality of life. Objective: This study aimed to characterize the utilization of patient-reported outcomes (PROs) in HS clinical trials and their concordance with trial primary endpoints. Methods: A systematic review of clinical trials was performed using the publicly available U.S. National Library of Medicine (ClinicalTrials.gov) in June 2023 utilizing the search terms hidradenitis, hidradenitis suppurativa, and suppurativa hidradenitis. Study title, start year, trial status, intervention, design, location, and primary and secondary outcomes were collected. To assess for concordance of patient and provider-reported outcomes, we identified published placebo-controlled trials that included Dermatology Life Quality Index (DLQI) and/or a numeric rating scale (NRS) for pain, the 2 most utilized PROs. Results: One hundred sixty-four HS clinical trials were identified, of which 115 were interventional studies. A total of 65.2% ( n = 107) of HS trials included at least one PRO. Pain NRS (42.7%, n = 70) and DLQI (42.1%, n = 69) were the most frequently used PRO instruments. The use of PROs in clinical trials increased over time, with 50% of trials between 2020 and 2023 utilizing PROs. Of 11 published HS trials, 82% ( n = 9) trials showed concordance of provider-assessed and PROs in at least one treatment arm. Limitations: Significance and standard deviations of PROs were rarely reported, preventing the calculation of significance and is a limitation of this review. Conclusion: While lesion counts provide single snapshots of disease, PROs can capture perceptions of lesions not actively present. PROs are frequently concordant with both achievement and nonachievement of primary endpoints in clinical trials.

Background Heart failure self‐care can contribute to a high daily workload and treatment burden. The goal of this cohort study was to assess the characteristics and outcomes associated with burden of treatment (BoT). Methods Surveys comprising validated instruments to measure BoT and other constructs were mailed to patients with heart failure in Southeastern Minnesota. Participants were divided into tertiles by BoT scores. Associations of clinical variables with BoT were examined using multinomial logistic regression. Associations of BoT with mortality and hospitalizations were examined using Cox proportional hazard regression and Andersen–Gill models, respectively. Results A total of 609 participants (mean age 76.3 years, 60.3% men, 55.2% urban, 64.3% preserved ejection fraction) completed surveys. Higher BoT was associated with worse health status, more depressive symptoms, lower resilience, less social support, lower medication adherence, and worse health literacy. Mean±SD follow‐up was 14.4 (4.1) months. Estimated 1‐year mortality (8.3% [95% CI, 4.3%–12.1%], 11.0% [95% CI, 6.5%–15.2%], 16.0% [95% CI, 10.8%–21.0%]) and 1‐year mean cumulative hospitalizations (0.57 [95% CI, 0.45–0.72], 0.83 [95% CI, 0.66–1.05], 1.15 [95% CI, 0.93–1.42]) increased across patients reporting low, medium, and high BoT, respectively. Adjustment for health status eliminated any significant association of BoT with risks of death and hospitalization (adjusted hazard ratio [HR], 1.10 [95% CI, 0.58–2.07] and 1.09 [95% CI, 0.74–1.61], respectively, highest versus lowest BoT tertile). Conclusions BoT in heart failure varies by clinical and psychosocial factors. Higher BoT identifies patients at increased risk of adverse health outcomes due to their worse health status. These findings can serve as a foundation for interventions to minimize workload and improve quality of life.

Acute right ventricular failure (ARVF) is commonly seen in the intensive care unit and constitutes a significant clinical challenge, with associated high in-hospital mortality. Recently, the treatment of ARVF has significantly changed, with the progressive implementation of mechanical circulatory support devices that now represent important tools for clinicians in treating this condition. However, despite recent advancements, the optimal approach for ARVF remains elusive, and precise treatment algorithms and comprehensive management protocols are still lacking. In the present review, we explore the pathophysiology of ARVF, highlighting the different mechanisms that may lead to this clinical entity and emphasizing the left and right heart’s complex interplay. We analyze the different therapeutic options that are now available for short- and long-term management of ARVF, with a particular focus on the advantages and disadvantages of the mechanical circulatory support devices actually used. Furthermore, we propose future directions in the field and a possible flowchart for the treatment of this condition.

Abstract RATIONALE: Airway-to-lung ratio (AirLR), calculated as the mean of airway lumen diameters at standard anatomic locations divided by the cube-root of total lung volume, is associated with COPD risk regardless of smoking status, and we have previously shown an association between total-pulmonary-vascular-volume-to-lung-size relationship with AirLR. [PMCID: PMC11284327] Using dual energy computed tomography (DECT), we recently developed a deep learning-based algorithm for pulmonary arterial segmentation to compute pulmonary-arterial-to-lung ratio (ArtLR) which correlated significantly with AirLR and markers COPD. Here we automate image processing in a larger cohort to estimate ArtLR, introduce an alternative ArtLR standardization and correlate it to COPD-related measures of lung structure and function. METHODS: Using a SPIROMICS sub-cohort (110 participants), imaged via contrast enhanced DECT at functional residual capacity (FRC), an automatic deep learning pipeline segmented the arteries from the pulmonary vascular tree. Another pipeline automatically extracted the centerlines and calculated average arterial segment diameters. A paired non-contrast total lung capacity (TLC) scan was registered to the DECT FRC scan to transfer airway segment labels from the TLC to FRC domain. AirLR was calculated as the mean of airway lumen diameters at standard anatomic locations (trachea-to-subsegments) divided by cube root of lung volume [TLC or FRC]. A simple Long Short-Term Memory (LSTM) network was used to find corresponding anatomic arterial segments. Associations between ArtLR and %Emphysema, AirLR, pre- and post-bronchodilator FEV1/FVC, and a texture-based (AMFM) measure of %broncho-vascular bundles was assessed using linear regression to adjust for age, sex and BMI. RESULTS: In adjusted analyses, a 1-SD decrement in ArtLR-TLC was associated with 4.198 units increase in %Emphysema-910 (95%CI: 1.360-7.037; p = 0.0041), and 0.8198 units decrease in %Bronchovascular (95%CI: 0.5037-1.136; p &lt; 0.0001). A 1-SD increment in ArtLR-TLC was associated with 0.2515 SD increase in AirLR-Outer (95%CI: 0.04947SD-0.4536SD; p = 0.0152), and 0.02083 units increase in PreBronch-FEV1FVC (95%CI: 0.001814-0.03984; p = 0.0321). Sex and BMI show significant associations with ArtLR-TLC, where female is associated with 1.068 SD decrease in ArtLR, and a unit increase in BMI is associated with 0.05788 SD increase in ArtLR (both p-values &lt; 0.0001), and age was not association with ArtLR. CONCLUSIONS: An automated pipeline for pulmonary arterial tree segmentation and standardization from contrast enhanced DECT FRC scans demonstrates a significant relationship between ArtLR and AirLR as well as between ArtLR and %emphysema, and FEV1/FVC. A standardized method of arterial tree size assessment provides for expanded exploration of vascular vs airway disease etiologies.

AbstractPurposeWhile several artificial intelligence (AI)‐assisted medical imaging applications are reported in the recent orthopaedic literature, comparison of the clinical efficacy and utility of these applications is currently lacking. The aim of this systematic review is to evaluate the effectiveness and reliability of AI applications in orthopaedic imaging, focusing on their impact on diagnostic accuracy, image segmentation and operational efficiency across various imaging modalities.MethodsBased on the PRISMA guidelines, a comprehensive literature search of PubMed, Cochrane and Scopus databases was performed, using combinations of keywords and MeSH descriptors ('AI', 'ML', 'deep learning', 'orthopaedic surgery' and 'imaging') from inception to March 2024. Included were studies published between September 2018 and February 2024, which evaluated machine learning (ML) model effectiveness in improving orthopaedic imaging. Studies with insufficient data regarding the output variable used to assess the reliability of the ML model, those applying deterministic algorithms, unrelated topics, protocol studies, and other systematic reviews were excluded from the final synthesis. The Joanna Briggs Institute (JBI) Critical Appraisal tool and the Risk Of Bias In Non‐randomised Studies‐of Interventions (ROBINS‐I) tool were applied for the assessment of bias among the included studies.ResultsThe 53 included studies reported the use of 11.990.643 images from several diagnostic instruments. A total of 39 studies reported details in terms of the Dice Similarity Coefficient (DSC), while both accuracy and sensitivity were documented across 15 studies. Precision was reported by 14, specificity by nine, and the F1 score by four of the included studies. Three studies applied the area under the curve (AUC) method to evaluate ML model performance. Among the studies included in the final synthesis, Convolutional Neural Networks (CNN) emerged as the most frequently applied category of ML models, present in 17 studies (32%).ConclusionThe systematic review highlights the diverse application of AI in orthopaedic imaging, demonstrating the capability of various machine learning models in accurately segmenting and analysing orthopaedic images. The results indicate that AI models achieve high performance metrics across different imaging modalities. However, the current body of literature lacks comprehensive statistical analysis and randomized controlled trials, underscoring the need for further research to validate these findings in clinical settings.Level of evidenceSystematic Review; Level of evidence IV.

Background: When injuring the anterior cruciate ligament (ACL), simultaneous meniscal tears often occur. However, little data describe ACL reconstruction (ACLR) and the subsequent risk of revision ACLR, as well as cartilaginous and meniscal damage after primary ACLR with different treatments for injury of the lateral meniscus (LM). Purpose: To investigate (1) how different LM treatments during primary ACLR affect the odds of revision ACLR and the cartilaginous and meniscal status at revision in a long-term follow-up and (2) whether the increased risk of subsequent meniscal and cartilaginous injuries seen with meniscal resection in the short term would continue in the long term, and (3) the increased risk with subsequent meniscal injuries with meniscal repair. Study Design: Cohort study; Level of evidence, 3. Methods: Data from the Swedish National Knee Ligament Registry were used. The study compared 2 groups: patients with isolated ACLR and patients with ACLR and concomitant LM injury, further subdividing the latter into 4 treatment types: repair, resection, both, and left in situ. Patients with medial meniscal injuries were excluded. The main outcomes studied were the odds for revision ACLR and the cartilaginous and meniscal status at revision 5 and 10 years after primary surgery. Results: Data for 5 years were available for 22,208 patients and data for 10 years were available for 11,058 patients. Compared with isolated ACLR, patients with concomitant LM injury left in situ had higher odds of revision ACLR at both 5 years (odds ratio [OR], 1.49; 95% CI, 1.14-1.95; P = .004) and 10 years (OR, 1.55; 95% CI, 1.09-2.19; P = .01), while those with LM repair had higher odds at 5 years (OR, 1.73; 95% CI, 1.23-2.43; P = .002). LM repair also increased the odds of subsequent meniscal injuries at 5 years (OR, 3.52; 95% CI, 1.76-7.03; P = .0004) and 10 years (OR, 7.26; 95% CI, 1.67-31.52; P = .008). Partial meniscectomy did not show an increased risk of cartilage injury, subsequent meniscal injury, or revision ACLR at long-term follow-up compared with the control group. Conclusion: This demonstrates that over 5 and 10 years, LM repair during primary ACLR is associated with an increased risk of revision ACLR and subsequent meniscal injuries. The higher risk of revision ACLR when the LM is left in situ emphasizes the need for careful consideration of treatment methods. Conversely, partial meniscectomy did not show an associated increased risk of cartilaginous injury in the long term and is associated with a lower risk of subsequent meniscal injury and revision ACLR than other treatment options, raising questions about whether preserving the meniscus at all costs is always the best approach.