Citations

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

Abstract Introduction Revascularization to prevent limb loss is not feasible or represents a very high risk in a significant proportion of patients with chronic limb-threatening ischaemia (CLTI). No standard definition currently exists to define this population of patients. The aim of this study was to develop a consensus-based, multidomain definition to improve clinical assessment and reporting of studies in people with ‘no option’ (NO) or ‘poor option’ (PO) CLTI. Methods A modified Delphi process was conducted with 164 specialists from 30 countries. Two iterative survey rounds were used to reach consensus, defined as ≥70% agreement with a score of ≥7 on a nine-point scale. Results Some 164 international vascular specialists participated in the study, averaging 19 years of experience. A multidomain framework including arterial disease anatomy, biology, risk, function, and context (ABRFC) achieved 83% consensus. A ‘desert foot’ was defined as the absence of distal arterial revascularization targets on advanced non-invasive imaging, invasive digital subtraction angiography, and at least one failed endovascular revascularization attempt (81.6% agreement). Inadequate autogenous bypass conduit was defined as the lack of usable autologous vein across all four limbs (85% agreement). Patients were classified as NO for revascularization if they present with ‘desert foot’, prohibitive medical risk, a non-functional limb, or in those patients who refused arterial revascularization. PO revascularization patients combined factors such as severe infection, lack of autologous vein, or treatment non-compliance (72.1% agreement). Conclusion This consensus study established a structured, expert-validated definition of no option or poor option for revascularisation of patients with CLTI. The multidomain ABRFC framework provides a foundation for standardized clinical assessment, trial design, and future guideline development.

PURPOSE Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The higher incidence and earlier onset of HCC in sub-Saharan Africa suggest a potential role for a genetic predisposition. This study evaluated the association of TERT -rs2242652-(A), a variant linked to lower HCC risk, with HCC in populations from Ghana, Nigeria, and Cameroon, compared with a population from the United States. METHODS The study included 537 patients with HCC: United States (n = 348), Ghana (n = 79), Nigeria (n = 43), and Cameroon (n = 67). The control group had 2,872 cancer-free individuals: United States (n = 2,399), Ghana (n = 323), Nigeria (n = 85), and Cameroon (n = 65). Whole-exome sequencing was conducted using germline DNA, and data for TERT -rs2242652 were analyzed. Odds ratios (ORs) and 95% CIs were calculated using unconditional logistic regression. Chi-square tests assessed protective allele frequencies. RESULTS In the US cohort, TERT -rs2242652 was significantly associated with lower HCC risk (OR, 0.75 [95% CI, 0.58 to 0.96]; P = .02), with an allele frequency of 18.8% (15.4% in HCC cases v 19.3% in controls). In the combined sub-Saharan African population, no significant association was observed, but there was a trend toward decreased HCC risk (OR, 0.80 [95% CI, 0.53 to 1.22]; P = .29), with an allele frequency of 12.2% (10.6% in HCC cases v 12.9% in controls). Separate analyses of Ghanaian, Nigerian, and Cameroonian populations showed similar nonsignificant trends. The protective allele frequency in the combined African populations was significantly lower than in the US cohort ( P < .0001). CONCLUSION In sub-Saharan African populations, there was a lower frequency of the HCC protective allele TERT -rs2242652 compared with European Americans. These findings underscore the importance of multiethnic genetic studies in understanding population differences in HCC risk and developing prevention strategies.

ABSTRACT In cartilage tissue engineering, there is a growing interest in dynamic hydrogels that promote spheroid fusion and cartilaginous matrix deposition, while maintaining sufficient stability for long‐term construct maturation. In this study, Diels‐Alder click chemistry is employed as a dynamic‐covalent crosslinking method to create hydrogels composed of hyaluronic acid, gelatin, and PEG. By adjusting the pH during crosslinking, the tuneability of hydrogel stiffness and stability at pH values around the physiological pH of native cartilage is demonstrated. This pH modulation does not compromise hydrogel functionality, as encapsulated equine articular cartilage progenitor cell spheroids remain viable and functional for a culture period of 28 days. The hydrogel environment supports the deposition of cartilaginous extracellular matrix components, including collagens and sulphated glycosaminoglycans. Enhanced chondrogenesis and deposition of collagen type II are observed at higher spheroid concentrations, corresponding to inter‐spheroid distances of 100–150 µm following hydrogel swelling, compared to lower concentrations at a distance of >500 µm. To further improve construct robustness, the hydrogel constructs can be reinforced on day 1 with a melt electrowritten scaffold, increasing the compressive modulus 100‐fold by day 28 compared to non‐reinforced constructs, highlighting the potential of this system for engineering cartilage implants.

Abstract Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally, with particularly high burdens among people living with HIV (PLWH) in low‐resource settings like Nigeria. Effective early detection remains a major challenge due to limited access to imaging‐based surveillance and the low sensitivity of current biomarkers such as alpha‐fetoprotein (AFP). We conducted an epigenome‐wide association study (EWAS) of circulating cell‐free DNA (ccfDNA) methylation in a Nigerian cohort of HIV‐positive individuals ( n = 245), spanning HCC, cirrhosis (FibroScan ≥12.3 kPa), fibrosis (FibroScan ≥7.6 and <12.3 kPa), and HCC‐free without fibrosis (FibroScan <7.6 kPa) groups. Using random forest modeling, we developed and evaluated a ccfDNA methylation classifier (ccfDNAmRF) for HCC risk prediction. We identified 73 CpG sites significantly associated with HCC (false discovery rate <0.01). The ccfDNAmRF model demonstrated strong discriminatory power, achieving 100% sensitivity and 80%–91% specificity for distinguishing HCC from cirrhosis, fibrosis, and HCC‐free groups (area under the curve [AUC]: 92%–97%). Combining ccfDNA methylation risk scores with AFP further improved classification accuracy (AUC up to 98.5%). Notably, ccfDNA methylation patterns displayed clear dose–response relationships across the disease spectrum, supporting their utility for early‐stage detection and risk stratification. Our findings highlight the promise of ccfDNA methylation biomarkers as a non‐invasive, blood‐based screening tool for improving early identification of HCC cases among PLWH.

Abstract Background Malignant peripheral nerve sheath tumors (MPNSTs) are rare, aggressive sarcomas, with 40% associated with neurofibromatosis type 1 (NF1). Surgical excision is the main treatment for localized disease; however, local recurrence (LR) remains high. Radiotherapy (RTx) is increasingly used to enhance local control in STS, but its use remains controversial due to the potential for increased major wound complications and an increased risk of secondary malignancies in NF1 patients. This study investigated the use and impact of RTx on local control in MPNSTs, particularly in the NF1 setting. Methods Surgically treated primary MPNSTs from 1988 to 2019 in the MONACO multicenter cohort were included. Differences in demographics, treatment, and RTx use between NF1 and non-NF1 cases were examined. Factors influencing RTx administration and LR were assessed via multivariable analyses. Results Among 499 patients (33.1% NF1), 143 (28.7%) experienced LRs. Radiotherapy was administered to 56.3% of patients (57.0% in the NF1 group), with 27.3% receiving neoadjuvant and 72.7% adjuvant RTx. RTx was administered significantly more often to high-grade and extremity tumors. While RTx did not affect overall survival, it reduced LR risk in sporadic cases (hazard ratio [HR] 0.530; 95% confidence interval [CI], 0.354–0.793) but not in the NF1 subgroup (HR 1.00; 95% CI, 0.545–1.85). In NF1 patients, a microscopically positive margin (R1) was the only risk factor for LR development (HR 2.1; 95% CI, 1.19–3.79). Conclusions RTx is frequently used in the treatment of MPNSTs, regardless of NF1 status. While it may affect the LR rate in sporadic cases, its impact on NF1 patients is less clear.

Background: Cardiogenic shock (CS) is a life-threatening complication of ST-elevation myocardial infarction (STEMI) and remains the leading cause of in-hospital mortality, with rates ranging from 5 to 10% despite advances in reperfusion strategies. Early identification and timely intervention are critical for improving outcomes. This study investigates the utility of machine learning (ML) models for predicting the risk of CS during the early phases of care—prehospital, emergency department (ED), and cardiology-on-call—with a focus on accurate triage and prioritization for urgent angiography. Results: In the prehospital phase, the Extra Trees classifier demonstrated the highest overall performance. It achieved an accuracy (ACC) of 0.9062, precision of 0.9078, recall of 0.9062, F1-score of 0.9061, and Matthews correlation coefficient (MCC) of 0.8140, indicating both high predictive power and strong generalization. In the ED phase, the support vector machine model outperformed others with an ACC of 78.12%. During the cardiology-on-call phase, Random Forest showed the best performance with an ACC of 81.25% and consistent values across other metrics. Quadratic discriminant analysis showed consistent and generalizable performance across all early care stages. Key predictive features included the Killip class, ECG rhythm, creatinine, potassium, and markers of renal dysfunction—parameters readily available in routine emergency settings. The greatest clinical utility was observed in prehospital and ED phases, where ML models could support the early identification of critically ill patients and could prioritize coronary catheterization, especially important for centers with limited capacity for angiography. Conclusions: Machine learning-based predictive models offer a valuable tool for early risk stratification in STEMI patients at risk for cardiogenic shock. These findings support the implementation of ML-driven tools in early STEMI care pathways, potentially improving survival through faster and more accurate decision-making, especially in time-sensitive clinical environments.

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: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persists after revascularization due to reperfusion injury and evolving instability. However, risk prediction in later phases—after revascularization—is less explored, despite its importance in guiding intensive care decisions. This study evaluates machine learning (ML) models for dynamic risk assessment in interventional cardiology and cardiac intensive care unit (CICU) phases, where timely detection of deterioration can guide treatment escalation. Methods: We retrospectively analyzed clinical and procedural data from 158 patients diagnosed with STEMI complicated by cardiogenic shock, treated between 2019 and 2022 at the Cardiology Department of the University Emergency Hospital of Bucharest, Romania. Machine learning models—Random Forest (RF), and Quadratic Discriminant Analysis (QDA)—were developed and tested specifically for the interventional cardiology and CICU phases. Model performance was evaluated using area under the receiver operating characteristic curve (ROC-AUC), accuracy (ACC), sensitivity, specificity, and F1-score. Results: In the interventional phase, RF and QDA achieved the highest accuracy, both reaching 87.50%. In the CICU, RF and QDA demonstrate the best performance, reaching ACCs of 0.843. QDA maintained consistent performance across phases. Relevant predictors included reperfusion strategy, TIMI flow before percutaneous coronary intervention (PCI), Killip class, creatinine, and Creatine Kinase Index (CKI)—all parameters routinely assessed in STEMI patients. These models effectively identified patients at risk for post-reperfusion complications and hemodynamic decline, supporting decisions regarding extended monitoring and ICU-level care. Conclusions: Predictive models implemented in advanced STEMI phases can contribute to dynamic, phase-specific risk reassessment and optimize CICU resource allocation. These findings support the integration of ML-based tools into post-PCI workflows, enabling earlier detection of clinical decline and more efficient deployment of intensive care resources. When combined with earlier-stage models, the inclusion of interventional and CICU phases forms a dynamic, end-to-end risk assessment framework. With further refinement, this system could be implemented as a mobile application to support clinical decisions throughout the STEMI care continuum.

ABSTRACT Background The relationship between height differences related to graft anatomy and physiological pressure indices in coronary bypass grafts has not been studied. We sought to study the impact of hydrostatic pressure on fractional flow reserve (FFR) in saphenous vein grafts (SVGs). Methods Included were 66 symptomatic patients (76 SVGs) with prior coronary artery bypass grafting who underwent coronary computed tomography angiography (CCTA) preceding invasive coronary angiography with FFR interrogation of ≥ 1 SVGs. The graft course and height excursion were reconstructed based on CCTA images. The impact of hydrostatic pressure on FFR (corrected FFR) was calculated by adding or subtracting 0.077 mmHg to the distal coronary pressure for every millimeter height difference in a supine position between the SVG ostium and the pressure wire tip position. Results The height difference (mm) between the SVG ostium and pressure wire tip position was largest for single SVGs to the circumflex artery (Cx; −55.1 ± 17.0), followed by sequential SVGs to the Cx (−51.8 ± 17.3) and the right coronary artery (RCA; −36.7 ± 21.6). The correlation between height difference and uncorrected FFR was −0.59 ( p < 0.001). Corrected FFR was lower as compared to uncorrected FFR in the overall cohort (0.86 ± 0.17 vs. 0.88 ± 0.18), in single SVGs to Cx (0.85 ± 0.17 vs. 0.90 ± 0.18), and in sequential SVGs to Cx (0.92 ± 0.14 vs. 0.96 ± 0.15) and RCA (0.82 ± 0.17 vs. 0.85 ± 0.21) ( p < 0.001 for all). Conclusions Hydrostatic pressure related to height differences along the course anatomy of SVGs can impact FFR measurements, with corrected FFR being significantly lower in SVGs to the Cx and sequential SVGs to the RCA.