Search Results (84)

Objective: This study assessed the efficacy of the cervical pessary combined with progesterone to prevent preterm birth in pregnant women with short cervix and previous preterm birth. Methods: This post hoc analysis of the randomized, multicenter P5 trial examined the efficacy of the cervical pessary associated with vaginal progesterone versus progesterone alone for preventing recurrent preterm birth in 155 pregnant women with cervical length ≤30 mm and prior spontaneous preterm birth (sPPTB) (main subgroup), and in 85 women with cervical length ≤25 mm and sPPTB (higher-risk population). The primary outcome was spontaneous preterm birth (sPTB) before 34 weeks; secondary outcomes included sPTB rates before 37, 32, and 28 weeks, analyzed using Odds Ratio (OR) and Kaplan–Meier curves. A secondary objective was to identify predictive factors for sPTB recurrence in the cohort with prior preterm birth (n = 479), irrespective of treatment allocation. Results: Demographic profiles were balanced between groups. The addition of a cervical pessary to progesterone did not result in a significant reduction in sPTB before 34 weeks: to cervix ≤30 mm, OR 1.169 (95% CI 0.524–2.609; p = 0.703) and 1.167 (95% CI 0.466–2.921; p = 0.742) for ≤25 mm; similar null findings were observed across all gestational age thresholds. Kaplan–Meier survival curves demonstrated no significant differences between groups (p > 0.05). Secondary analysis (n = 479) identified principal predictors of sPTB recurrence, regardless of the cervical length: higher education (OR 2.37; 95% CI 0.99–5.63; p = 0.024), previous cervical conization (OR 4.78; 95% CI 1.08–21.19; p = 0.039) previous low birth weight < 2.5 kg (OR 2.43; 95% CI 1.22–4.85; p = 0.051), prior miscarriages (OR 1.36; 95% CI 1.10–1.69; p = 0.005), current twin pregnancy (OR 14.86; 95% CI 4.35–50.68; p < 0.001) and cervical funneling (OR 3.60; 95% CI 1.79–7.24; p < 0.001). Predictive models achieved an AUC of 0.719, with 87.0% sensitivity and 58.8% specificity. Conclusions: These findings do not support the routine use of cervical pessary combined with progesterone in women with dual risk factors. In this Brazilian population, specific clinical and obstetric characteristics—including higher education, cervical funneling, prior low birth weight delivery, previous conization, current twin gestation, and prior miscarriage—could identify women at increased risk for recurrent preterm birth. Full article

Background/Objectives: To develop and validate a predictive model that combines morphological features and dual-energy CT (DECT) parameters to non-invasively distinguish metastatic from benign axillary lymph nodes in patients with breast cancer (BC). Methods: In this retrospective study, 117 patients (median age, 65 years; 111 women and 6 men) who underwent DECT followed by axillary lymphadenectomy between April 2015 and July 2023, were analyzed. A total of 375 lymph nodes (180 metastatic, 195 benign) were evaluated. Two radiologists recorded morphological criteria (adipose hilum status, cortical appearance, extranodal extension, and short-axis diameter) and placed regions of interest to measure dual-energy parameters: attenuation at 40 and 70 keV, iodine concentration, water concentration and spectral slope. Normalized iodine concentration was calculated using the aorta as reference. Univariate analysis identified variables associated with metastasis. Multivariate logistic regression with cross-validation was used to construct two models: one based solely on morphological features and one integrating water concentration. Results: On univariate testing, all DECT parameters and morphological criteria differed significantly between metastatic and benign nodes (p < 0.01). In multivariate analysis, water concentration emerged as the only independent DECT predictor (odds ratio = 0.97; p = 0.002) alongside cortical abnormality, absence of adipose hilum, extranodal extension and short-axis diameter. The morphologic model achieved an area under the receiver operating characteristic curve (AUC) of 0.871. Increasing water concentration increased the AUC to 0.883 (ΔAUC = 0.012; p = 0.63, not significant), with internal cross-validation confirming stable performance. Conclusions: A model combining standard morphologic criteria with water concentration quantification on DECT accurately differentiates metastatic from benign axillary nodes in BC patients. Although iodine-based metrics remain valuable indicators of perfusion, water concentration offers additional tissue composition information. Future multicenter prospective studies with standardized imaging protocols are warranted to refine parameter thresholds and validate this approach for routine clinical use. Full article

Accurately identifying drug off-targets is essential for reducing toxicity and improving the success rate of pharmaceutical discovery pipelines. However, current deep learning approaches often struggle to fuse chemical structure, protein biology, and multi-target context. Here, we introduce HDPC-LGT (Hybrid Dual-Prompt Cross-Attention Ligand–Protein Graph Transformer), a framework designed to predict ligand binding across sixteen human translation-related proteins clinically associated with antibiotic toxicity. HDPC-LGT combines graph-based chemical reasoning with protein language model embeddings and structural priors to capture biologically meaningful ligand–protein interactions. The model was trained on 216,482 experimentally validated ligand–protein pairs from the Chemical Database of Bioactive Molecules (ChEMBL) and the Protein–Ligand Binding Database (BindingDB) and evaluated using scaffold-level, protein-level, and combined holdout strategies. HDPC-LGT achieves a macro receiver operating characteristic–area under the curve (macro ROC–AUC) of 0.996 and a micro F1-score (micro F1) of 0.989, outperforming Deep Drug–Target Affinity Model (DeepDTA), Graph-based Drug–Target Affinity Model (GraphDTA), Molecule–Protein Interaction Transformer (MolTrans), Cross-Attention Transformer for Drug–Target Interaction (CAT–DTI), and Heterogeneous Graph Transformer for Drug–Target Affinity (HGT–DTA) by 3–7%. External validation using the Papyrus universal bioactivity resource (Papyrus), the Protein Data Bank binding subset (PDBbind), and the benchmark Yamanishi dataset confirms strong generalisation to unseen chemotypes and proteins. HDPC-LGT also provides biologically interpretable outputs: cross-attention maps, Integrated Gradients (IG), and Gradient-weighted Class Activation Mapping (Grad-CAM) highlight catalytic residues in aminoacyl-tRNA synthetases (aaRSs), ribosomal tunnel regions, and pharmacophoric interaction patterns, aligning with known biochemical mechanisms. By integrating multimodal biochemical information with deep learning, HDPC-LGT offers a practical tool for off-target toxicity prediction, structure-based lead optimisation, and polypharmacology research, with potential applications in antibiotic development, safety profiling, and rational compound redesign. Full article

Background/Objectives: Comprehensive knowledge of body composition and bone status across the lifespan is critical for clinical evaluation and public health initiatives. This study aimed to develop age- and sex-specific reference curves for body composition and bone status in a physically active Greek population aged 18–80 using dual-energy X-ray absorptiometry (DXA). A secondary objective was to examine age- and sex-related trends in fat distribution, lean mass (LM), and bone status. Methods: A cross-sectional analysis was conducted on 637 participants (275 men and 362 women). Physical activity was assessed through structured interviews evaluating type, frequency, and intensity, categorized using established guidelines from organizations such as the American Heart Association and World Health Organization. Anthropometric data and DXA scans were utilized to measure parameters including fat mass (FM), LM, and BMD. Participants were stratified into age categories, and percentile curves were generated using generalized additive models for location, scale, and shape (GAMLSS). Results: Among women, body mass increased by 20.9% and body fat percentage rose by 38.3% from the youngest to the oldest age group, accompanied by a 5.7% reduction in bone mineral density (BMD) and an 11.5% decline in bone mineral content (BMC). Men exhibited a 49.1% increase in body fat percentage, with LM remaining stable across age groups. In men, BMD decreased by 1.7%, while BMC showed minimal variation. Notable sex differences were observed in fat redistribution, with android fat (AF) increasing significantly in older individuals, particularly among women, highlighting distinct age-related patterns. Conclusions: This study provides essential reference data on body composition and bone status, emphasizing the need for tailored interventions to address sex- and age-related changes, particularly in fat distribution and bone density, to support improved health outcomes in aging populations. Full article

Background and Objectives: People living with HIV (PLWH) have excess osteoporosis and fractures not fully captured by dual-energy X-ray absorptiometry (DXA). We evaluated whether trabecular bone score (TBS), calcaneal quantitative ultrasound (QUS) and bone turnover markers improve vertebral fracture risk assessment beyond areal bone mineral density (BMD) in PLWH. Methods: In this cross-sectional study, 87 antiretroviral-treated adults undergoing DXA had lumbar spine TBS and calcaneal QUS. Morphometric vertebral fractures were identified, correlates of degraded TBS were analyzed using multivariable regression, and sequential logistic models quantified the incremental contribution of TBS and CTX to discriminate for prevalent morphometric vertebral fractures. Results: Low BMD (osteopenia/osteoporosis) was present in 62% of participants, degraded TBS in 37% and morphometric vertebral fractures in 17%. Degraded versus normal TBS was associated with older age (49.1 vs. 39.7 years), longer HIV duration and lower nadir CD4+ count, as well as more frequent tenofovir disoproxil fumarate exposure (66% vs. 52%; all p ≤ 0.04). In multivariable analysis, age (per 10-year increase; adjusted odds ratio [aOR] 1.78; 95% CI 1.13–2.83) and nadir CD4+ < 200 cells/mm³ (aOR 2.29; 95% CI 1.06–4.97) independently predicted degraded TBS. In sequential cross-sectional models for prevalent morphometric vertebral fractures, the area under the curve increased from 0.71 (clinical variables) to 0.79 after adding lumbar spine T-score and to 0.85 after adding TBS; adding CTX yielded 0.87 without a statistically significant incremental gain. Conclusions: In PLWH, TBS captures bone quality deficits and improves vertebral fracture risk discrimination beyond BMD, supporting its integration alongside DXA in routine HIV care. Full article

In response to the shortage of theoretical support for negative sample selection and the imbalance between positive and negative samples in landslide susceptibility assessment (LSA), this study presents a dual optimization framework of sampling strategy and sample ratio based on the frequency ratio (FR) model and evaluates its performance in the Heishui River Basin using the random forest (RF) model. At the level of negative sample optimization, FR is used to quantify the spatial associations between landslides and environmental factors, delineate non-landslide zones as the source region for negative samples, and systematically compare the performance of five sampling strategies—random, buffer-zone, low-slope, low-density, and FR-optimized sampling. At the level of ratio adjustment, an innovative positive–negative sample ratio model based on the area ratio between susceptible and non-susceptible zones (1:1.3) is proposed, and four additional schemes (1:1, 1:2, 1:2.5, and 1:3) are designed for comparison. The results show that the FR-optimized sampling strategy provides the best discriminative performance, with AUC (area under the curve) = 0.992, Kappa = 0.964, accuracy = 0.982, and F1 score = 0.982, and achieves the highest mean metric value (0.980) and the lowest standard deviation (0.008). The 1:1.3 ratio scheme maintains the highest mean performance (0.982) and the lowest standard deviation (0.007), while yielding the optimal Kappa (0.968) and F1 score (0.982), confirming its advantages in classification balance and model stability. Spatial prediction results indicate that very high and high susceptibility zones are concentrated along both sides of the middle and lower reaches of the Heishui River Basin, occupying only 18.52% of the total area but containing 98.38% of the mapped landslide points, which strongly supports the reliability of the proposed model in identifying landslide risk hotspots. The proposed dual optimization framework not only enhances the robustness of susceptibility mapping but can also be directly applied to risk screening for territorial spatial planning and engineering development in the Heishui River Basin. Full article

Background/Objectives: New-onset atrial fibrillation (NOAF) frequently develops in patients with chronic coronary syndrome (CCS) and is associated with adverse cardiovascular outcomes. The C-reactive protein–to–albumin ratio (CAR) reflects systemic inflammation, whereas left atrial diameter (LAD) indicates structural cardiac remodeling. Their combined predictive role for NOAF in CCS remains uncertain. This study evaluated the predictive value of combined CAR and LAD for NOAF in CCS patients. Methods: We retrospectively analyzed 2431 CCS patients treated at the Third Affiliated Hospital of Sun Yat-sen University between 2012 and 2019. The primary endpoint was NOAF occurrence during follow-up. Receiver operating characteristic (ROC) analysis determined exploratory cutoff values for CAR (0.0429) and LAD (33.96 mm). Patients were categorized into four groups: Group 1 (low CAR–low LAD), Group 2 (high CAR–low LAD), Group 3 (low CAR–high LAD), and Group 4 (high CAR–high LAD). Cox proportional hazards, Kaplan-Meier, and subgroup analyses were conducted to evaluate associations with NOAF risk. Results: During a median follow-up of 4.96 years, 93 NOAF events were identified. Compared with the Group 1, patients with higher CAR and LAD showed significantly elevated NOAF risk (HR = 2.67, 95%CI 1.99–3.57, p < 0.001). The combined CAR–LAD model demonstrated superior predictive accuracy (AUC = 0.731, 95% CI = 0.654–0.765; p < 0.001) and consistent effects across most subgroups. Decision curve analysis confirmed greater net clinical benefit for the combined model. Conclusions: The integration of CAR and LAD serves as a simple, non-invasive, and effective tool for predicting NOAF in CCS patients. This dual-marker model facilitates early identification of high-risk individuals and support personalized preventive strategies in clinical practice. Full article

Background/Objectives: Cefoperazone–sulbactam is frequently prescribed to older inpatients for severe infections but has been associated with coagulation abnormalities, particularly among individuals with malnutrition or hepatic dysfunction. Early identification of at-risk patients remains challenging. To develop and validate a clinically interpretable model for predicting cefoperazone–sulbactam-related coagulation abnormalities in elderly inpatients and to provide practical tools for bedside risk estimation. Methods: We conducted a retrospective, dual-center study of 485 patients aged ≥ 60 years treated at Fuxing Hospital and Xuanwu Hospital of Capital Medical University who received cefoperazone–sulbactam for ≥72 h. Baseline clinical and demographic variables were analyzed using univariate and multivariable logistic regression to identify independent risk factors. Ten supervised machine-learning models were trained and evaluated using area under the ROC curve (AUC), accuracy, sensitivity, specificity, precision, and F1-score. SHapley Additive exPlanations (SHAP) were applied to assess model interpretability. A nomogram was constructed from the final logistic regression model, and a web-based calculator was developed for clinical use. Results: Multivariable analysis identified age ≥ 75 years, hypoproteinemia, total parenteral nutrition, insomnia, and recent oral antibiotic use as independent predictors of coagulation abnormalities. Among machine-learning models, LightGBM achieved the best overall performance by AUC and balanced classification metrics. SHAP analyses provided individualized and global explanations of feature contributions, facilitating clinical interpretation. The nomogram and web calculator enable rapid, patient-specific risk estimation. Conclusions: An interpretable machine-learning approach, complemented by a nomogram and web calculator, accurately stratifies the risk of cefoperazone–sulbactam-induced coagulation abnormalities in elderly inpatients. These tools may support personalized risk evaluation and earlier preventive interventions in routine care. The web-based calculator facilitates rapid bedside risk estimation and may help guide earlier monitoring and preventive interventions in routine care. Full article

Objective: This study aimed to investigate the relationship between computed tomography (CT)-derived Hounsfield Unit (HU) measurements and dual-energy X-ray absorptiometry (DXA) and to evaluate the feasibility of using contrast-enhanced abdominal CT as a complementary tool in the assessment of bone health in liver transplant recipients. Methods: This retrospective descriptive and analytical study included adult liver transplant recipients who underwent both contrast-enhanced abdominal CT and DXA within a three-month interval. HU measurements were obtained from sagittal and axial reformatted images at the lumbar spine (L1–L4) and femoral neck. All CT examinations were performed using a standardized venous-phase protocol. DXA-derived T-scores from the lumbar spine and femur served as the reference standard. Correlation analyses and receiver operating characteristic (ROC) curves were used to evaluate associations between HU values and BMD, as well as the diagnostic performance of HU in identifying low bone density. Results: A total of 259 recipients (mean age 55.7 ± 14.4 years; 62.9% male) were included. Based on lumbar spine DXA, 17.8% had normal BMD, 36.7% were osteopenic, and 45.5% were osteoporotic. CT-derived HU values at both the lumbar spine and femoral neck were significantly lower in patients with reduced BMD and showed a graded decline across worsening DXA categories. HU values demonstrated positive correlations with corresponding T-scores. Diagnostic performance for detecting osteoporosis was fair, with AUCs of 0.700 (sagittal), 0.698 (axial), and 0.751 (femoral). Conclusion: Contrast-enhanced abdominal CT provides useful ancillary information for opportunistic bone health assessment. CT-derived HU values offer a rapid and cost-effective complementary tool but should not replace DXA in the diagnostic evaluation of osteoporosis Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, underscoring the urgent need for reliable biomarkers and therapeutic targets. To address this need, we focused on UDP-glucose pyrophosphorylase 2 (UGP2). Although UGP2 has been implicated in tumorigenesis across multiple cancers, its precise role and clinical significance in CRC remain poorly understood. This study aimed to comprehensively characterize UGP2 in CRC through an integrated approach encompassing proteomic screening, bioinformatics analysis, and experimental validation. We identified UGP2 as a significantly downregulated tumor-suppressive factor in CRC. Specifically, UGP2 expression was significantly downregulated in CRC tissues compared with that in normal controls and exhibited strong correlations with aggressive clinicopathological features, including lymphatic invasion, perineural invasion, and colon polyp history, and patient age. It also demonstrated high diagnostic accuracy in CRC, with an area under the receiver operating characteristic curve (AUC) of 0.990. Reduced UGP2 levels were associated with poorer overall survival and disease-specific survival. Hypermethylation of the UGP2 promoter correlated with a favorable prognosis in patients with CRC. UGP2 expression positively correlated with immune cell infiltration within the tumor microenvironment. Functionally, UGP2 knockdown increased CRC cell proliferation and migration while suppressing apoptosis. Conversely, its overexpression yielded the opposite effects, confirming UGP2’s role in constraining malignant phenotypes. Collectively, these findings establish UGP2 as a key CRC tumor suppressor whose downregulation drives malignant progression and predicts adverse clinical outcomes, suggesting its potential as a dual-purpose diagnostic and prognostic biomarker. Full article

Background: Dual antiplatelet therapy (DAPT), combining aspirin with a P2Y12 receptor inhibitor (P2Y12i), remains central to the management of acute myocardial infarction (MI), especially in patients undergoing percutaneous coronary intervention (PCI). However, the pharmacodynamic response to antiplatelet therapy may vary with body composition. This study investigates the association between body mass index (BMI) and clinical outcomes in MI patients treated with PCI and DAPT. Methods: This retrospective cohort study analyzed data from 52,119 MI patients treated with coronary stenting from 2014 to 2021, sourced from the Hungarian Myocardial Infarction Registry. Patients were stratified into clopidogrel-based (n = 44,480) and potent P2Y12i-based (prasugrel or ticagrelor; n = 7639) DAPT cohorts. Clinical outcomes—including 12-month mortality and ischemic events—were assessed across BMI categories. Kaplan–Meier analysis and LASSO Cox regression identified predictors of mortality, while decision curve analysis (DCA) evaluated the net clinical benefit of potent P2Y12i across BMI strata. Results: Univariate and multivariate Cox regression analyses identified BMI and potent P2Y12i treatment as significant predictors of 365-day mortality, with higher BMI associated with lower observed rates of mortality, major adverse cardiovascular events (MACEs), and stroke. However, higher BMI was also associated with an increased risk of repeat revascularization and PCI. This study found that the protective effect of potent P2Y12i treatment was consistent across different BMI categories. Conclusions: In patients with MI undergoing PCI, elevated BMI was paradoxically associated with more favorable short-term outcomes, including reduced mortality. Potent P2Y12i therapy demonstrated a consistent benefit across BMI categories, supporting its broad application irrespective of body mass. Full article

Mathematical modeling of unitized regenerative fuel cells (URFCs) faces significant challenges in reconciling parameter conflicts between fuel cell (FC) and electrolysis cell (EC) modes. This study establishes a COMSOL-based multi-physics framework coupling water–gas–heat–electric transport for both operational states. The critical factors associated with the model were identified through a systematic sensitivity analysis of structural and operational parameters, including temperature, exchange current density, conductivity, porosity, and flow rates. FC modes exhibited strong sensitivity to exchange current density (27.8–40.5% performance variation) and conductivity of membrane (10.1–35.6%), while temperature degraded performance (−4.2% to −4.0%). Spatial analysis revealed temperature-induced membrane dehydration and accelerated gas depletion at electrodes, thus explaining the negative correlation. EC modes were dominantly governed by temperature (8.6–9.4%), exchange current density (13.0–16.4%), and conductivity (2.5–13.3%). Channel simulations revealed that elevated temperature contributed to enhanced liquid water fluidity, while high flow rates had a relatively limited effect on mitigating species concentration gradients. Parameter optimization guided by sensitivity thresholds (e.g., porosity > 0.4 in FC GDLs, conductivity > 222 S/m in EC modes) enabled dual-mode calibration. The model achieved <4% error in polarization curve validation under experimental conditions, demonstrating robust prediction of voltage–current dynamics. This work resolves key conflicts of URFC modeling through physics-informed parameterization to provide a foundation for efficient dual-mode system design. Full article

Objectives: The BRAF^V600E is the most common oncogene in thyroid cancer and is associated with the aggressiveness of papillary thyroid carcinoma (PTC). The aim of this study was to investigate the effectiveness of the arterial enhancement fraction (AEF) and dual-layer detector spectral computed tomography (DLCT) parameters for predicting the BRAF^V600E mutation in PTC. Methods: A total of 237 patients with PTC who underwent DLCT and BRAF^V600E mutation detection (mutant group: n = 187; wild group: n = 50) were retrospectively reviewed. The receiver operating characteristic curves evaluated the effectiveness of the prediction models based on the significantly different variables using logistic regression analysis. The nomogram of the prediction model with the highest AUC in the validation cohort was constructed. Results: The AUCs of the DLCT+ Hashimoto’s thyroiditis (HT) and AEF + DLCT + HT prediction models were 0.901 and 0.896, respectively, in the training cohort and 0.801 and 0.853 in the validation cohort. The calibration curve revealed the good agreement between the prediction results and the actual observations using the AEF + DLCT + HT model. The DCA demonstrated that the model can provide net benefit for all threshold probabilities. Conclusions: As an effective and visually noninvasive prediction tool, the AEF + DLCT + HT-based nomogram presented satisfactory effectiveness in preoperatively predicting the BRAF^V600E mutation in PTC. Full article

Background/Objectives: Modular dual mobility (MDM) cups are constituted by a cobalt-chromium liner inserted into a standard acetabular shell, allowing for intraoperative indication and supplementary screw fixation of the acetabular component. MDM could face mechanical and biological issues, with the associated risk of elevated blood metal ions levels and adverse local tissue reactions. Methods: This is a monocentric retrospective study on a consecutive series of 105 patients who underwent primary unilateral THA with the G7 Dual Mobility Acetabular System cup (Zimmer Biomet, Warsaw, IN, USA) from March 2019 to April 2023, and who were evaluated clinically and radiographically at a minimum two-year follow-up. All complications and revisions were recorded. Survivorship analysis with any revision surgery as endpoint was performed using Kaplan–Meier survival curves. Results: There were eighty-nine patients (follow-up rate 84.8%) who underwent clinical and radiographic follow-up. The mean follow-up was 2.5 ± 0.8 years. Revision-free survival was 98.0%. Three complications (2.8%) were recorded: one case of posterior dislocation, one periprosthetic joint infection and one post-traumatic periprosthetic femur fracture. Dislocation rate and infection rate were less than 1.0%. None of the patients were revised for adverse local tissue reactions. No cup loosening was observed. No cases of intraprosthetic dislocation, liner malseating or femoral notching were observed. Retroacetabular stress shielding was present in 43.0% of patients. Clinical scores significantly improved at the last follow-up compared with preoperative status (p < 0.0001): the final mean mHHS was 87.5 ± 5.3 and the final mean VAS was 0.5 ± 0.9. Conclusions: The Zimmer G7 modular dual mobility cup appears to be a safe and effective option and does not present specific implant-related mechanical and biological issues in primary total hip arthroplasty at a minimum two-year follow-up. Full article

Background: Mitral annular plane systolic excursion (MAPSE) is a simple and widely used M-mode echocardiographic marker of left-ventricular longitudinal function that correlates well with left ventricular ejection fraction (LVEF). Conventional chronic right ventricle (RV) pacing is associated with left ventricle (LV) dysfunction, inducing heart failure (HF) and leading to the development of pacing-induced cardiomyopathy (PiCM). The aim of this study is to ascertain the clinical usefulness of MAPSE in the assessment of LV function in patients with permanent RV pacing. Methods: We performed a cross-sectional association analysis, enrolling consecutive patients with pacemakers and chronic RV pacing burdens over 20% (Vp > 20%) from 2021 to 2024. All patients were assessed by standard transthoracic echocardiography (TTE) with LVEF and MAPSE among other parameters being assessed. We performed a correlation test using linear regression and plotted an ROC curve. Results: 409 patients (mean age = 68.7 year) were included, 225 men (55%) and 245 (59.9%) with dual-chamber pacemakers. The mean follow-up period was 18 ± 2 months, with HF incidence in the study group being 23.2%. The results showed that average, septal, and lateral MAPSE all correlate well with LVEF, but septal values seemed to provide the strongest correlation (r = 0.90, p < 0.001), and that a septal MAPSE cut off value of <10 mm (sensitivity 99.4, specificity 42.1, AUC = 0.89) was associated with impaired LVEF (<50%). Conclusions: MAPSE seems to corelate well with LVEF across the spectrum of HF in pts with chronic RV conventional pacing. Septal MAPSE shows the strongest correlation with LVEF, and a value of <10 mm is a cut-off for altered LVEF, making it a potentially useful marker of cardiac function in these pts. Full article