Statins are prescribed to lower LDL cholesterol. Clinical guidelines recommend 30-50% reduction within 3 months, yet many patients do not achieve this. We investigated predictors of LDL-c reduction, treatment adherence, and adverse clinical outcomes in a sample of UK Biobank participants.

We analysed 76,000 UK Biobank participants prescribed atorvastatin or simvastatin in primary care: 41,000 had LDL-c measurements before statin initiation (median = 16 days prior, IQR = 28) and within a year of starting treatment (median = 89 days, IQR = 125). Adherence was defined as the "proportion of days covered" (PDC). We estimated associations between PDC within 1 year of statin initiation, genetic factors, post-treatment LDL-c reduction, and clinical adverse outcomes. For 13,000 patients with ≥ 3 LDL-c measures, we used inverse probability of treatment weighting methods to estimate the effect of sustained adherence intervention on LDL-c reduction longitudinally.

LDL-c reduction following statin initiation was predicted by time until the 1st measurement (up to 26% greater reduction if returned ≤ 3 months vs > 3 months), PDC (up to 38% reduction when PDC > 95% [high] vs. 15% when PDC < 50% [low]), and the pharmacogenetic variant SLCO1B1*5 (lowest reduction in CC-allele: 37% versus TT-allele: 39.5%). Longitudinal causal modelling showed that the most recent PDC measure exerted the largest influence on overall LDL-c reduction, followed by the initial PDC. Genetic predictors of reduced PDC included liability to schizophrenia (Coef_{top 20%} - 1.94, 95%CI - 2.69 to - 1.19), while genetic liability to cardiovascular diseases increased PDC (Coef_{top 20%}1.30, 95%CI 0.55 to 2.05). High PDC was associated with increased risk of incident iron deficiency anaemia (HR 1.30, 95%CI 1.09-1.54) and cataract (HR 1.20, 95%CI 1.07-1.34), and decreased risk of incident coronary heart disease (HR 0.78, 95%CI 0.73-0.84).

We identify substantial variability in the time to first on-treatment LDL-c measurements and also in adherence to statin medication, highlighting a gap between NHS guidelines, LDL-c monitoring, and statin adherence. We show its subsequent impact on long-term health, demonstrating the potential effect of targeted interventions to improve adherence. We identify important predictors of reduced statin effectiveness, including pharmacogenetic variants, polygenic scores, but most of all, adherence. Tailored statin therapy strategies with patient education on statin indication and adherence could optimize treatment efficacy, safety, and long-term clinical outcomes.

Cardiovascular disease, the world's leading cause of death, could be significantly reduced through sodium reduction strategies; however, the implementation of such strategies has had limited impact in Australia and globally. Switching to potassium-enriched salt is a highly promising intervention, but uptake by the food industry and consumers remains limited. This study investigated the barriers and enablers for scaling up potassium-enriched salt use in Australia.

A qualitative, theory-informed study design was used to conduct 24 semi-structured interviews with representatives from civil society, government, and industry. Interviewees discussed scaling up potassium-enriched salt in relation to their interests, ideas, existing policies and guidelines, and perceived challenges and opportunities within the Australian context. Data were analysed using thematic analysis.

Minimal knowledge and awareness of potassium-enriched salt among all stakeholder groups was the most prominent finding. The key perceived barriers were low consumer demand for potassium-enriched salt products and little incentive for industry to invest in supply. Further, government stakeholders expressed hesitancy to implement policies due to perceived health risks such as hyperkalaemia. Interviewees identified increased awareness, support for industry research and development, and leveraging current policies and initiatives (such as the Australian Health Star Rating system) as potential enablers.

Improving stakeholder understanding of the benefit of switching to potassium-enriched salt in Australia may require a coordinated advocacy strategy that disseminates the evidence and addresses misconceptions. Efforts to drive increased supply and demand could be advanced using a multi-sectoral approach that focuses on supporting industry uptake, encouraging consumer demand, and informing policy implementation.

Single stent-assisted coiling (sSAC) is used to treat saccular unruptured intracranial aneurysms (sUIAs), but factors influencing delayed complete occlusion (CO) remain incompletely understood. We retrospectively analyzed 260 patients with sUIAs treated with sSAC. Immediate CO was assessed angiographically post-procedure, and delayed CO was defined as progression to CO during follow-up in initially incompletely occluded aneurysms. Clinical and morphological variables were evaluated using univariate and multivariate logistic regression to identify factors. Immediate CO was achieved in 38.1% of patients. An aspect ratio ≥ 1.1 was positively associated with immediate CO (adjusted OR, 2.01; 95% CI, 1.09-3.71; P = 0.02), while hyperlipidemia was negatively associated (adjusted OR, 0.47; 95% CI, 0.26-0.88; P = 0.02). Among 161 patients without immediate CO, 81.4% achieved delayed CO during a median follow-up of 491 days. Aneurysms with a wide neck (> 4 mm or dome-to-neck ratio < 1.5) or a size ratio (maximum aneurysm size / parent artery diameter) ≥ 2.3 were less likely to achieve delayed CO (adjusted ORs, 0.35 [95% CI, 0.13-0.94] and 0.34 [95% CI, 0.12-0.93], respectively; both P = 0.04). Clinical outcomes were favorable overall, with 98.8% of patients achieving a 90-day modified Rankin Scale score of 0-2 with a low complication rate of 5.8%. While most sUIAs without immediate CO progress to occlusion over time, specific morphological and clinical factors may influence this outcome. Identifying these predictors can support patient selection, procedural decision-making, and follow-up planning to optimize long-term results after sSAC for sUIAs.

Surgical aortic valve replacement (SAVR) is the treatment of choice for young patients with severe aortic stenosis (AS). Left ventricular (LV) reverse remodeling (RR) after surgery is expected to occur, even though its definition is largely heterogenous and ill-defined. However, LV RR not always occurs following afterload relief, and such may impact the prognosis. Single-centre prospective study including patients referred for SAVR due to severe symptomatic AS, with no previous history of ischemic cardiomyopathy. Both pre- and post-operative transthoracic echocardiographic (TTE) and cardiac magnetic resonance (CMR) study (at the 3rd to 6th month after SAVR) were performed. LV RR was defined when in presence of at least one of the imaging criteria: >15% decrease in end-diastolic volume (CMR); >15% decrease in LV indexed mass (CMR); >10% decrease in geometric remodeling (LV mass/EDV ratio) by CMR; >10% increase in LV ejection fraction (CMR); >50% increase on global longitudinal strain (TTE). We assess the prognostic value of RR definitions for the outcome after SAVR using Cox regression and Kaplan-Meier analysis. The primary endpoint was defined as all-cause mortality, heart failure (HF) hospitalization or worsening HF. We enrolled 140 patients - mean age 71 ± 9 years-old, 49% male, predominantly high-gradient-normal flow AS submitted to SAVR. At a mean follow-up of 34 ± 12 months, 16% patients met the primary endpoint, with an overall mortality rate of 6%. Twelve patients (9%) were admitted for HF and 7 (5%) had at least one episode of worsening HF. 118 patients had complete pre and post-surgery imaging study (mean follow-up: 36 ± 10 months): 103 patients (87%) met at least one RR parameter. Post-operative RR was not independently associated with the primary endpoint. LV mass regression was the sole predictor of the outcome. LV RR after SAVR is highly prevalent in a cohort of patients with classical severe symptomatic AS. However, only LV mass regression independently predicts the clinical outcome after surgery. LV structural remodeling, rather than functional improvement after surgery, may better define the prognosis after pressure overload relief.

A precise evaluation of the positional distribution of hemorrhoidal piles has not been distinctly conducted. We hypothesized that the distribution of hemorrhoidal piles follows a predictable anatomical pattern influenced by disease duration and recurrence.

Our retrospective study analyzed the demographic data, surgical records, operative photographs, previous treatments, and associated colorectal symptoms of patients who underwent invasive procedures for advanced hemorrhoidal disease (2020-2024).

Of the 171 patients (123 male; 71.9%; median age 41 ± 12.04 years, range 18-88), 35 had prior interventions (recurrent cases). The largest pile was most commonly in the left lateral quadrant (40.14%), followed by right posterior (31.97%), right anterior (23.47%), and atypical locations (4.42%). Left lateral predominance was significantly higher in primary cases than in recurrent cases (p = 0.031). Most patients had more than one pile (87.7%). Symptom duration positively correlated with pile number (Spearman's rho = 0.229, p = 0.013), but not with hemoroid grade (p = 0.977). No significant differences in pile distribution were observed in patients with defecation disorders, labor history, or concomitant anal fissure (p > 0.05). Of the 48 patients with anal fissure had significantly shorter symptom duration compared to those without fissure (p = 0.011).

The classical three-quadrant distribution is confirmed, with the left lateral pile being predominant in primary cases. The association between prolonged symptom duration and increased pile number offers novel insights, highlighting left lateral predominance in primary cases and its reduction in recurrence, enhancing clinical understanding and management.

This study aimed to evaluate the association between neutrophil percentage-to-albumin ratio (NPAR) and both all-cause and cardiovascular disease (CVD) mortality in patients with chronic kidney disease (CKD). Data from 7854 CKD patients aged ≥ 20 years were analyzed using the National Health and Nutrition Examination Survey (NHANES) data from 2001 to 2018. Weighted Cox proportional hazards models, subgroup analyses, smoothed curve fitting, and Kaplan-Meier survival curves were employed to examine the association between NPAR and mortality risk. Additionally, Receiver operating characteristic (ROC) curves were used to compare NPAR's predictive performance against traditional inflammatory markers. During a median follow-up of 79 months, there were 2795 all-cause deaths and 1019 CVD deaths. A U-shaped association was identified between NPAR and all-cause mortality, with an inflection point at NPAR = 12. Below this threshold, higher NPAR was associated with lower mortality risk (HR: 0.94, 95% CI 0.90-0.99); above it, increased NPAR corresponded to higher risk (HR: 1.14, 95% CI 1.12-1.16). Additionally, NPAR exhibited a positive association with CVD mortality (HR: 1.08, 95% CI 1.04-1.12). Compared to the lowest quartile, the highest NPAR quartile demonstrated significantly increased risks of all-cause mortality (HR: 2.24, 95% CI 1.88-2.66) and CVD mortality (HR: 1.91, 95% CI 1.42-2.58). ROC curve analysis demonstrated NPAR's superior predictive capability compared to traditional inflammatory markers. NPAR exhibits significant associations with mortality outcomes in patients with CKD and surpasses traditional inflammatory markers in predicting mortality risk, highlighting its potential clinical value as a simple and cost-effective prognostic indicator.

This study aimed to develop a nomogram for accurately predicting in-hospital mortality in patients with infective endocarditis (IE). We conducted a retrospective analysis of clinical, echocardiographic, and laboratory data from IE patients admitted between January 2010 and September 2024. 252 IE patients from the Second Hospital of Lanzhou University were included in the training cohort, while 65 IE patients from the First Hospital of Lanzhou University were enrolled for external validation. The least absolute shrinkage and selection operator (LASSO) regression method was used to identify factors associated with in-hospital mortality. A nomogram was constructed using multivariate logistic regression. Model performance was assessed using receiver operating characteristic (ROC) curve and calibration curve. Clinical utility was evaluated through decision curve analysis (DCA) and clinical impact curve (CIC). The nomogram included five independent risk factors: embolic events, vegetation size ≥ 10 mm, moderate or higher pulmonary hypertension, hydropericardium, and surgery. The area under the curve (AUC) of the nomogram in the training cohort was 0.850 (95% CI: 0.794-0.906), and external validation cohort was 0.819 (95% CI: 0.693-0.946). The calibration plot demonstrated excellent prediction consistency. Both DCA and CIC confirmed the clinical utility of the nomogram. We developed and validated a nomogram for predicting in-hospital mortality in patients with IE. The model demonstrated excellent performance and provided a useful tool to assist clinicians in decision-making and patient management.

Mannitol is widely used for treating brain edema caused by various diseases, but it has been reported to cause acute kidney injury. However, the prognosis for patients with non-traumatic intracerebral hemorrhage who also have acute kidney injury and continue to receive mannitol has not yet been documented. This study presents a retrospective cohort analysis utilizing the MIMIC-IV (medical information mart for intensive care-IV) database. The study population comprised adult patients diagnosed with non-traumatic intracerebral hemorrhage (ICH) and concurrent acute kidney injury (AKI). Mannitol administration during the intensive care unit (ICU) stay was considered the exposure variable. The primary endpoint for analysis was 28-day all-cause mortality. To account for potential confounding factors, multivariable analytical methods were employed. The 28-day mortality rate within the total cohort was 25%. In the mannitol group, the 28-day mortality rate was 50.4% (58/115), compared to 21.9% (203/927) in the control group. Mannitol use was associated with a significantly higher 28-day all-cause mortality in both the multivariable analysis (HR 2.42; 95% CI 1.80-3.25; p < 0.001) and the univariable analysis (HR 2.31; 95% CI 1.67-3.19; p < 0.001). Other variables independently associated with mortality included higher heart rate, mean arterial pressure, respiratory rate, platelet count, sodium, chloride, lactate, urea nitrogen, creatinine, SAPSII, SOFA, GCS, and Charlson Index. The in-hospital mortality rate was 47.8% (55 out of 115) in the mannitol treatment group and 16.2% (150 out of 927) in the non-treatment group. Mannitol use was associated with higher 28-day all-cause mortality in patients with non-traumatic ICH and AKI. However, given the methodological limitations and incomplete confounder adjustment of this study, this finding should be interpreted with caution. Further research is needed to confirm this relationship and explore the underlying mechanisms.

Though wearable cuffless blood pressure (BP) measurement technology has attracted significant attention from both academia and industry, the ability of existing methods and devices to track dynamic BP changes and provide reliable BP readings remains low, especially in ambulatory environments. This study develops and validates an algorithm for 24-h ambulatory cuffless BP confidence intervals (CIs) estimation with conformal guaranteed coverage of the true BP values using wearable electrocardiogram (ECG) and photoplethysmogram (PPG) on subjects in the ambulatory setting. First, a quantile loss-based Gradient Boosting Regression Tree (GBRT) model was trained to obtain ambulatory BP estimates along with model uncertainty. The model uncertainty was then calibrated using conformal prediction to obtain CIs with guaranteed reference values coverage. Ambulatory physiological data from 483 participants from the Aurora-BP study dataset were used for model validation. For ambulatory measurements during the daytime phase, the mean absolute difference (MAD) of the systolic BP (SBP) and diastolic BP (DBP) estimated by the proposed model was 14.32 mmHg and 9.53 mmHg, respectively. For ambulatory measurements during the nighttime phase, the MAD of SBP and DBP estimated by the proposed model were 14.22 mmHg and 10.13 mmHg, respectively. Providing CIs with guaranteed reference BP coverage for 24-h ambulatory BP estimation can enhance the trust of patients and physicians in wearable devices, thereby facilitating the prevention, screening, and management of hypertension.

Peripheral arterial disease (PAD) affects approximately 236.62 million individuals globally, exposing them to significantly increased risks of major limb events such as death and amputation. Concurrently, the number of diagnostic prediction models for PAD patients is steadily rising; however, these studies exhibit varying results, and their quality and applicability in clinical practice and future research remain unclear. To systematically assess the methodological quality of studies on PAD diagnostic prediction models. PubMed, Embase, Web of Science and Cochrane Database of Systematic Reviews were searched to identify studies which aiming to develop or validate a diagnostic prediction model of PAD. The retrieval time limit is from the establishment of the database to June 1, 2025. Two researchers independently screened and extracted data from eligible studies and evaluated the risk of bias using the Prediction Model Risk of Bias Assessment Tool (PROBAST). A total of 24 studies on PAD diagnostic prediction models were included, most of which exhibited high risk of bias, predominantly in the domains of study population and statistical analysis. The meta-analyzed Area Under the Receiver Operating Characteristic Curve (AUC) was 0.79 [0.74, 0.84], indicating favorable model performance. The reported number of predictor variables ranged from 2 to 20, with common predictors including age, gender, hypertension, diabetes, smoking, and BMI. This study demonstrates that PAD diagnostic prediction models exhibit good predictive performance, albeit accompanied by a high risk of bias and substantial heterogeneity across studies. Future research on modeling should emphasize comprehensive methodological enhancements in model design, construction, evaluation, and validation, with full disclosure of crucial model information. It should also utilize network computing for presenting model outcomes and conduct large-scale, multi-center external validation of existing models to promote their clinical application.Trial registration: This study protocol has been registered with PROSPERO (registration number: CRD42024557144).