Challenges and support needs in psychological and physical health among pilots: a qualitative study.

Introduction: Physical and mental health problems among pilots affect their working state and impact flight safety. Although pilots' physical and mental health problems have become increasingly prominent, their health has not been taken seriously. This study aimed to clarify challenges and support needs related to psychological and physical health among pilots to inform development of a more scientific and comprehensive physical and mental health system for civil aviation pilots. Methods: This qualitative study recruited pilots from nine civil aviation companies. Focus group interviews via an online conference platform were conducted in August 2022. Colaizzi analysis was used to derive themes from the data and explore pilots' experiences, challenges, and support needs. Results: The main sub-themes capturing pilots' psychological and physical health challenges were: (1) imbalance between family life and work; (2) pressure from assessment and physical examination eligibility requirements; (3) pressure from worries about being infected with COVID-19; (4) nutrition deficiency during working hours; (5) changes in eating habits because of the COVID-19 pandemic; (6) sleep deprivation; (7) occupational diseases; (8) lack of support from the company in coping with stress; (9) pilots' yearly examination standards; (10) support with sports equipment; (11) respecting planned rest time; and (12) isolation periods. Discussion: The interviewed pilots experienced major psychological pressure from various sources, and their physical health condition was concerning. We offer several suggestions that could be addressed to improve pilots' physical and mental health. However, more research is needed to compare standard health measures for pilots around the world in order to improve their physical and mental health and contribute to overall aviation safety.

Implication of geriatric nutritional risk index on treatment response and long-term prognosis in patients with cardiac resynchronization therapy.

PURPOSE: Geriatric Nutritional Risk Index (GNRI) is a simple tool for assessing the nutritional status of the aging population. This study aims to explore the clinical implication of GNRI on treatment response and long-term clinical outcomes in heart failure (HF) patients receiving cardiac resynchronization therapy (CRT). METHODS: Patients who underwent CRT implantation or upgrade at our hospital were retrospectively included. The association of GNRI and its tertiles with the echocardiographic response, all-cause mortality or heart transplantation, and the first hospitalization due to HF were investigated. RESULTS: Totally, 647 patients were enrolled, with a median age of 60 [Interquartile Range (IQR): 52-67] years and mean score of GNRI at 107.9 ± 23.7. Super-response rates increased significantly among the GNRI T1, T2, and T3 groups (25.1%, 29.8% vs. 41.1%, P = 0.002). Patients with higher GNRI were more likely to have better LVEF improvement after multiple adjustments (OR = 1.13, 95% CI: 1.04-1.23, P = 0.010). Higher GNRI was independently associated with a lower risk of all-cause mortality or heart implantation (HR = 0.95, 95% CI: 0.93-0.96, P < 0.001) and HF hospitalization (HR = 0.96, 95% CI: 0.95-0.98, P < 0.001). The inclusion of GNRI enhanced the predictability of all-cause mortality based on traditional model, including sex, New York Heart Association functional class, left bundle branch block, QRS reduction, and N-terminal pro-B-type natriuretic peptide level (C statistics improved from 0.785 to 0.813, P = 0.007). CONCLUSION: Higher GNRI was associated with better treatment response and long-term prognosis in HF patients with CRT. Evaluation of nutritional status among CRT population is necessary for individualized choice of potential responders.

MYT1L deficiency impairs excitatory neuron trajectory during cortical development.

Mutations that reduce the function of MYT1L, a neuron-specific transcription factor, are associated with a syndromic neurodevelopmental disorder. Furthermore, MYT1L is routinely used as a proneural factor in fibroblast-to-neuron transdifferentiation. MYT1L has been hypothesized to play a role in the trajectory of neuronal specification and subtype specific maturation, but this hypothesis has not been directly tested, nor is it clear which neuron types are most impacted by MYT1L loss. In this study, we profiled 313,335 nuclei from the forebrains of wild-type and MYT1L-deficient mice at two developmental stages: E14 at the peak of neurogenesis and P21, when neurogenesis is complete, to examine the role of MYT1L levels in the trajectory of neuronal development. We found that MYT1L deficiency significantly disrupted the relative proportion of cortical excitatory neurons at E14 and P21. Significant changes in gene expression were largely concentrated in excitatory neurons, suggesting that transcriptional effects of MYT1L deficiency are largely due to disruption of neuronal maturation programs. Most effects on gene expression were cell autonomous and persistent through development. In addition, while MYT1L can both activate and repress gene expression, the repressive effects were most sensitive to haploinsufficiency, and thus more likely mediate MYT1L syndrome. These findings illuminate the intricate role of MYT1L in orchestrating gene expression dynamics during neuronal development, providing insights into the molecular underpinnings of MYT1L syndrome.

Pycallingcards: an integrated environment for visualizing, analyzing, and interpreting Calling Cards data.

MOTIVATION: Unraveling the transcriptional programs that control how cells divide, differentiate, and respond to their environments requires a precise understanding of transcription factors' (TFs) DNA-binding activities. Calling cards (CC) technology uses transposons to capture transient TF binding events at one instant in time and then read them out at a later time. This methodology can also be used to simultaneously measure TF binding and mRNA expression from single-cell CC and to record and integrate TF binding events across time in any cell type of interest without the need for purification. Despite these advantages, there has been a lack of dedicated bioinformatics tools for the detailed analysis of CC data. RESULTS: We introduce Pycallingcards, a comprehensive Python module specifically designed for the analysis of single-cell and bulk CC data across multiple species. Pycallingcards introduces two innovative peak callers, CCcaller and MACCs, enhancing the accuracy and speed of pinpointing TF binding sites from CC data. Pycallingcards offers a fully integrated environment for data visualization, motif finding, and comparative analysis with RNA-seq and ChIP-seq datasets. To illustrate its practical application, we have reanalyzed previously published mouse cortex and glioblastoma datasets. This analysis revealed novel cell-type-specific binding sites and potential sex-linked TF regulators, furthering our understanding of TF binding and gene expression relationships. Thus, Pycallingcards, with its user-friendly design and seamless interface with the Python data science ecosystem, stands as a critical tool for advancing the analysis of TF functions via CC data. AVAILABILITY AND IMPLEMENTATION: Pycallingcards can be accessed on the GitHub repository: https://github.com/The-Mitra-Lab/pycallingcards.

Effect of short-term cardiac function changes after cardiac resynchronization therapy on long-term prognosis in heart failure patients with and without diabetes.

Background: The relationship between short-term cardiac function changes and long-term outcomes in heart failure (HF) patients undergoing cardiac resynchronization therapy (CRT) remains uncertain, especially when stratified by diabetes status. Objectives: This study aims to assess the association between short-term cardiac function changes and outcomes such as all-cause mortality and HF hospitalization in patients undergoing CRT, stratified by diabetes status. Design: This is a cohort longitudinal retrospective study. Methods: A total of 666 HF patients, treated with CRT between March 2007 and March 2019, were included in this study. Among them, 166 patients (24.9%) were diagnosed with diabetes. Cardiac function was assessed at baseline and again at 6 months, incorporating evaluations of left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDD), left atrial diameter (LAD), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and QRS duration. The QRS duration represents the time required for a stimulus to spread through the ventricles (ventricular depolarization). The primary endpoints of the study were all-cause mortality and HF-related hospitalization. Results: During a median follow-up of 2.51 years, 172 (25.8%) patients died and 197 (29.6%) were hospitalized for HF. Changes in LVEF, LVEDD, and LAD within 6 months had similar effects on adverse outcomes in both diabetic and nondiabetic patients. However, the presence of diabetes significantly modified the association between changes in NT-proBNP and QRS duration and adverse outcomes. Short-term changes in NT-proBNP and QRS duration were positively associated with all-cause mortality and HF hospitalization in patients without diabetes. However, the relationship between short-term changes in NT-proBNP and QRS duration and adverse outcomes was non-linear in diabetic patients. Conclusion: Improvement of cardiac function after CRT implantation can reduce long-term risk of all-cause mortality and HF hospitalization in HF patients. However, the presence of diabetes may affect the association between short-term changes in NT-proBNP and QRS duration and adverse outcomes.

Genomic characterization of Streptococcus equi subspecies zooepidemicus from a 2021 outbreak in Indiana with increased sow mortality.

IMPORTANCE: This study highlights a Streptococcus equi subspecies zooepidemicus (S. zooepidemicus) strain isolated from an outbreak in Indiana, which resulted in mortality events among a swine herd in 2021. The Indiana outbreak strain was found to be genetically and phylogenetically distant to a strain isolated from the 2019 outbreaks in Ohio and Tennessee, which caused high swine mortality. We also discovered multiple unique genetic features in the Indiana outbreak strain, including distinct S. zooepidemicus genomic islands, and notable S. zooepidemicus virulence genes-many of which could serve as biomarkers for the diagnosis of this strain. These findings provide significant insights into monitoring and potentially preventing severe outbreaks caused by the Indiana outbreak strain in the future.

Joint association of sedentary behavior and vitamin D status with mortality among cancer survivors.

BACKGROUND: Sedentary behavior and vitamin D deficiency are independent risk factors for mortality in cancer survivors, but their joint association with mortality has not been investigated. METHODS: We analyzed data from 2914 cancer survivors who participated in the National Health and Nutrition Examination Survey (2007-2018) and followed up with them until December 31, 2019. Sedentary behavior was assessed by self-reported daily hours of sitting, and vitamin D status was measured by serum total 25-hydroxyvitamin D (25(OH)D) levels. RESULTS: Among 2914 cancer survivors, vitamin D deficiency was more prevalent in those with prolonged daily sitting time. During up to 13.2 years (median, 5.6 years) of follow-up, there were 676 deaths (cancer, 226; cardiovascular disease, 142; other causes, 308). The prolonged sitting time was associated with a higher risk of all-cause and noncancer mortality, and vitamin D deficiency was associated with a higher risk of all-cause and cancer mortality. Furthermore, cancer survivors with both prolonged sitting time (≥ 6 h/day) and vitamin D deficiency had a significantly higher risk of all-cause (HR, 2.05; 95% CI: 1.54-2.72), cancer (HR, 2.33; 95% CI, 1.47-3.70), and noncancer mortality (HR, 1.91; 95% CI, 1.33-2.74) than those with neither risk factor after adjustment for potential confounders. CONCLUSIONS: In a nationally representative sample of U.S. cancer survivors, the joint presence of sedentary behavior and vitamin D deficiency was significantly associated with an increased risk of all-cause and cancer-specific mortality.

Calling Cards: A Customizable Platform to Longitudinally Record Protein-DNA Interactions Over Time in Cells and Tissues.

Calling Cards is a platform technology to record a cumulative history of transient protein-DNA interactions in the genome of genetically targeted cell types. The record of these interactions is recovered by next-generation sequencing. Compared with other genomic assays, readouts of which provide a snapshot at the time of harvest, Calling Cards enables correlation of historical molecular states to eventual outcomes or phenotypes. To achieve this, Calling Cards uses the piggyBac transposase to insert self-reporting transposon "Calling Cards" into the genome, leaving permanent marks at interaction sites. Calling Cards can be deployed in a variety of in vitro and in vivo biological systems to study gene regulatory networks involved in development, aging, and disease. Out of the box, it assesses enhancer usage but can be adapted to profile-specific transcription factor (TF) binding with custom TF-piggyBac fusion proteins. The Calling Cards workflow has five main stages: delivery of Calling Cards reagents, sample preparation, library preparation, sequencing, and data analysis. Here, we first present a comprehensive guide for experimental design, reagent selection, and optional customization of the platform to study additional TFs. Then, we provide an updated protocol for the five steps, using reagents that improve throughput and decrease costs, including an overview of a newly deployed computational pipeline. This protocol is designed for users with basic molecular biology experience to process samples into sequencing libraries in 2 days. Familiarity with bioinformatic analysis and command line tools is required to set up the pipeline in a high-performance computing environment and to conduct downstream analyses. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Preparation and delivery of Calling Cards reagents Support Protocol 1: Next-generation sequencing quantification of barcode distribution within self-reporting transposon plasmid pool and adeno-associated virus genome Basic Protocol 2: Sample collection and RNA purification Support Protocol 2: Library density quantitative PCR Basic Protocol 3: Sequencing library preparation Basic Protocol 4: Library pooling and sequencing Basic Protocol 5: Data analysis.

Calling Cards: a customizable platform to longitudinally record protein-DNA interactions over time in cells and tissues.

Calling Cards is a platform technology to record a cumulative history of transient protein-DNA interactions in the genome of genetically targeted cell types. The record of these interactions is recovered by next generation sequencing. Compared to other genomic assays, whose readout provides a snapshot at the time of harvest, Calling Cards enables correlation of historical molecular states to eventual outcomes or phenotypes. To achieve this, Calling Cards uses the piggyBac transposase to insert self-reporting transposon (SRT) "Calling Cards" into the genome, leaving permanent marks at interaction sites. Calling Cards can be deployed in a variety of in vitro and in vivo biological systems to study gene regulatory networks involved in development, aging, and disease. Out of the box, it assesses enhancer usage but can be adapted to profile specific transcription factor binding with custom transcription factor (TF)-piggyBac fusion proteins. The Calling Cards workflow has five main stages: delivery of Calling Card reagents, sample preparation, library preparation, sequencing, and data analysis. Here, we first present a comprehensive guide for experimental design, reagent selection, and optional customization of the platform to study additional TFs. Then, we provide an updated protocol for the five steps, using reagents that improve throughput and decrease costs, including an overview of a newly deployed computational pipeline. This protocol is designed for users with basic molecular biology experience to process samples into sequencing libraries in 1-2 days. Familiarity with bioinformatic analysis and command line tools is required to set up the pipeline in a high-performance computing environment and to conduct downstream analyses. Basic Protocol 1: Preparation and delivery of Calling Cards reagentsBasic Protocol 2: Sample preparationBasic Protocol 3: Sequencing library preparationBasic Protocol 4: Library pooling and sequencingBasic Protocol 5: Data analysis.

Sex differences in the nonlinear association of triglyceride glucose index with all-cause and cardiovascular mortality in the general population.

BACKGROUND: The evidence on the association between the triglyceride glucose (TyG) index and the risk of death in the general population remains controversial. This study aims to investigate the relationship between the TyG index and all-cause and cardiovascular mortality in the general population, with a focus on sex differences. METHODS: This prospective cohort study analyzed data from the National Health and Nutrition Examination Survey (1999-2002), comprising 7,851 US adults. The study employed multivariate Cox proportional hazards regression and two-segment Cox hazard regression models to evaluate the sex-specific differences in the relationship between the TyG index and all-cause and cardiovascular mortality. RESULTS: After 11,623 person-years of follow-up, there were 539 deaths, with 10.56% due to all-cause mortality and 2.87% due to cardiovascular mortality. After adjusting for multiple variables, our study found a U-shaped association of the TyG index with all-cause and cardiovascular mortality, with inflection points at 9.36 and 9.52. A significant sex difference was observed in the association between the TyG index and mortality. Below the inflection point, the relationship between the TyG index and mortality was consistent in males and females. However, above the inflection point, only males exhibited a positive association between the TyG index and all-cause mortality (adjusted hazard risk [HR], 1.62, 95% confidence interval [CI], 1.24-2.12) and cardiovascular mortality (adjusted HR, 2.28, 95% CI, 1.32-3.92). CONCLUSIONS: Our study showed a U-shaped association between the TyG index and all-cause and cardiovascular mortality in the general population. Furthermore, sex differences were observed in the association between the TyG index and mortality once it exceeded a certain threshold.

Zinc cluster transcription factors frequently activate target genes using a non-canonical half-site binding mode.

Gene expression changes are orchestrated by transcription factors (TFs), which bind to DNA to regulate gene expression. It remains surprisingly difficult to predict basic features of the transcriptional process, including in vivo TF occupancy. Existing thermodynamic models of TF function are often not concordant with experimental measurements, suggesting undiscovered biology. Here, we analyzed one of the most well-studied TFs, the yeast zinc cluster Gal4, constructed a Shea-Ackers thermodynamic model to describe its binding, and compared the results of this model to experimentally measured Gal4p binding in vivo. We found that at many promoters, the model predicted no Gal4p binding, yet substantial binding was observed. These outlier promoters lacked canonical binding motifs, and subsequent investigation revealed Gal4p binds unexpectedly to DNA sequences with high densities of its half site (CGG). We confirmed this novel mode of binding through multiple experimental and computational paradigms; we also found most other zinc cluster TFs we tested frequently utilize this binding mode, at 27% of their targets on average. Together, these results demonstrate a novel mode of binding where zinc clusters, the largest class of TFs in yeast, bind DNA sequences with high densities of half sites.

Prognostic Implications of Left Ventricular Ejection Fraction and Left Ventricular End-Diastolic Diameter on Clinical Outcomes in Patients with ICD.

Background: Left ventricular ejection fraction (LVEF) is a suboptimal indicator of risk stratification for patients with an implantable cardioverter defibrillator (ICD). Studies have shown that left ventricular end-diastolic diameter (LVEDD) was associated with all-cause mortality and ventricular arrhythmias. We examined the quantified prognostic value of LVEF and LVEDD for clinical outcomes, respectively. Method: This study retrospectively enrolled patients with ICD implantation in a single center. The associations between LVEF or LVEDD and all-cause mortality and appropriate shocks were analyzed using Cox regression and Fine-gray competing risk regression, respectively. Result: During a median follow up of 59.6 months, 168/630 (26.7%) patients died. LVEF and LVEDD were strongly associated with all-cause mortality (LVEF per 10%: HR 0.77, 95%CI 0.64−0.93, p = 0.006; LVEDD per 10 mm: HR 1.54, 95%CI 1.27−1.85, p < 0.001). After a median interrogation time of 37.1 months, 156 (24.8%) patients received at least one shock. LVEF was not associated with appropriate shock, whereas larger LVEDD (per 10 mm) was significantly associated with a higher risk of shock (HR: 1.27, 95%CI 1.06−1.52, p = 0.008). The addition of LVEF or LVEDD to clinical factors provided incremental prognostic value and discrimination improvement for all-cause mortality, while only the addition of LVEDD to clinical factors improved prognostic value for shock intervention. Conclusions: Baseline LVEF and LVEDD show a linear relationship with all-cause mortality in patients with ICD. However, whereas LVEF is not associated with shock, a linear relationship exists between LVEDD and appropriate shock. LVEDD adds more predictive value in relation to all-cause mortality and appropriate shocks than LVEF.

Independent and Joint Association of Statin Therapy with Adverse Outcomes in Heart Failure Patients with Atrial Fibrillation Treated with Cardiac Resynchronization Therapy.

Background: The joint association of atrial fibrillation (AF) and statin therapy with adverse outcomes in heart failure (HF) patients with cardiac resynchronization therapy (CRT) has not been fully investigated so far. The purpose of this study was to explore the independent and joint association of AF and statin therapy with adverse outcomes. Methods: Study patients were divided into four groups according to AF status and statin use: Non-AF/Statin, Non-AF/Non-Statin, AF/Statin, and AF/Non-Statin. Multivariate Cox proportional hazards regression models were used to evaluate the independent and joint association of AF and statin therapy with poor prognosis. Results: Among 685 CRT patients, there were 180 deaths (26.5%) and 198 HF hospitalization (29.6%) during the 14 years of follow-up. AF was associated with a 46% increased risk of all-cause mortality (HR, 1.46; 95% CI, 1.03-2.07) and a 59% increased risk of HF hospitalization (HR, 1.59; 95% CI, 1.16-2.20) than those without AF. However, statin therapy failed to improve the prognosis. In the joint analysis, compared with the Non-AF/Statin group, the AF/Non-Statin group suffered a higher risk of all-cause mortality (HR, 1.75; 95% CI, 1.04-2.93) and HF hospitalization (HR, 1.76; 95% CI, 1.08-2.86). Furthermore, adding AF to the traditional risk factor model significantly improved the predictive value for death (C-statistic from 0.654 to 0.691) and HF (C-statistic from 0.613 to 0.675). Conclusion: AF was associated with poor prognosis, and statin use failed to improve the prognosis. Further analysis showed that statin therapy is ineffective in improving prognosis and fails to attenuate the adverse effects of AF.

Combined association of triglyceride-glucose index and systolic blood pressure with all-cause and cardiovascular mortality among the general population.

BACKGROUND: The combined association of triglyceride-glucose (TyG) index and different systolic blood pressure (SBP) levels with all-cause and cardiovascular mortality among the general population remains unclear. METHODS: In this study, 6245 individuals were from the National Health and Nutrition Examination Survey (1999-2002). The study endpoints were all-cause and cardiovascular mortality. Multivariate Cox proportional hazards regression models were used to explore the combined association of TyG index and different SBP levels with all-cause and cardiovascular mortality. RESULTS: During a mean follow-up period of 66.8 months, a total of 284 all-cause deaths (331/100000 person-years) and 61 cardiovascular deaths (66/100000 person-years) were recorded. Multivariate Cox regression analysis revealed that the combination of low TyG index and low SBP (< 120 mmHg and < 130 mmHg) was associated with a reduced risk of all-cause and cardiovascular mortality than others. However, survival benefit was not observed in the combined group with the low TyG index and SBP < 140 mmHg. Furthermore, the mortality rate in the combined group of low TyG index and low SBP gradually increased with the elevation of SBP level. CONCLUSION: The combination of low TyG index and low SBP (< 120 mmHg and < 130 mmHg) was associated with a lower risk of all-cause and cardiovascular mortality. However, no survival benefit was observed in the combined group of low TyG index and SBP < 140 mmHg.

Length of Hospitalization-Related Differences and Associated Long-Term Prognosis of Patients with Cardiac Resynchronization Therapy: A Propensity Score-Matched Cohort.

Previous studies indicated that prolonged lengths of hospitalization (LOH) during cardiac resynchronization therapy (CRT) implantation are associated with poorer physical status and higher in-hospital mortality. However, evidence on the impact of LOH on the long-term prognosis of CRT patients is limited. The purpose of this study was to assess LOH-related prognostic differences in CRT patients. In the propensity score-matched cohort, patients with standard LOH (≤7 days, n = 172) were compared with those with prolonged LOH (>7 days, n = 172) for cardiac function and study outcomes during follow-up. The study outcomes were all-cause death and heart failure (HF) hospitalization. In addition, cardiac function and changes in cardiac function at the follow-up period were used for comparison. At a mean follow-up of 3.36 years, patients with prolonged LOH, as compared with those with standard LOH, were associated with a significantly higher risk of all-cause death (hazard ratio [HR] 1.87, 95% confidence interval [CI] 1.18−2.96, p = 0.007), and a higher risk of HF hospitalization (HR 1.68, 95% CI 1.08−2.63, p = 0.023). Moreover, patients with standard LOH had a more significant improvement in cardiac function and a pronounced reduction in QRS duration during follow-up than those with prolonged LOH. LOH-associated differences were found in the long-term prognosis of CRT patients. Patients with prolonged LOH had a worse prognosis than those with standard LOH.

Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes.

Calling cards technology using self-reporting transposons enables the identification of DNA-protein interactions through RNA sequencing. Although immensely powerful, current implementations of calling cards in bulk experiments on populations of cells are technically cumbersome and require many replicates to identify independent insertions into the same genomic locus. Here, we have drastically reduced the cost and labor requirements of calling card experiments in bulk populations of cells by introducing a DNA barcode into the calling card itself. An additional barcode incorporated during reverse transcription enables simultaneous transcriptome measurement in a facile and affordable protocol. We demonstrate that barcoded self-reporting transposons recover in vitro binding sites for four basic helix-loop-helix transcription factors with important roles in cell fate specification: ASCL1, MYOD1, NEUROD2 and NGN1. Further, simultaneous calling cards and transcriptional profiling during transcription factor overexpression identified both binding sites and gene expression changes for two of these factors. Lastly, we demonstrated barcoded calling cards can record binding in vivo in the mouse brain. In sum, RNA-based identification of transcription factor binding sites and gene expression through barcoded self-reporting transposon calling cards and transcriptomes is an efficient and powerful method to infer gene regulatory networks in a population of cells.

Toward Better Risk Stratification for Implantable Cardioverter-Defibrillator Recipients: Implications of Explainable Machine Learning Models.

Background: Current guideline-based implantable cardioverter-defibrillator (ICD) implants fail to meet the demands for precision medicine. Machine learning (ML) designed for survival analysis might facilitate personalized risk stratification. We aimed to develop explainable ML models predicting mortality and the first appropriate shock and compare these to standard Cox proportional hazards (CPH) regression in ICD recipients. Methods and Results: Forty-five routine clinical variables were collected. Four fine-tuned ML approaches (elastic net Cox regression, random survival forests, survival support vector machine, and XGBoost) were applied and compared with the CPH model on the test set using Harrell's C-index. Of 887 adult patients enrolled, 199 patients died (5.0 per 100 person-years) and 265 first appropriate shocks occurred (12.4 per 100 person-years) during the follow-up. Patients were randomly split into training (75%) and test (25%) sets. Among ML models predicting death, XGBoost achieved the highest accuracy and outperformed the CPH model (C-index: 0.794 vs. 0.760, p < 0.001). For appropriate shock, survival support vector machine showed the highest accuracy, although not statistically different from the CPH model (0.621 vs. 0.611, p = 0.243). The feature contribution of ML models assessed by SHAP values at individual and overall levels was in accordance with established knowledge. Accordingly, a bi-dimensional risk matrix integrating death and shock risk was built. This risk stratification framework further classified patients with different likelihoods of benefiting from ICD implant. Conclusions: Explainable ML models offer a promising tool to identify different risk scenarios in ICD-eligible patients and aid clinical decision making. Further evaluation is needed.

Independent and joint association of N-terminal pro-B-type natriuretic peptide and left ventricular mass index with heart failure risk in elderly diabetic patients with right ventricular pacing.

Background: Elevated levels of N-terminal pro-B natriuretic peptide (NT-proBNP) and left ventricular hypertrophy (LVH) are independent risk factors for heart failure (HF). In addition, right ventricular pacing (RVP) is an effective treatment strategy for bradyarrhythmia, but long-term RVP is associated with HF. However, there is limited evidence on the independent and combined association of NT-proBNP and left ventricular mass index (LVMI) with HF risk in elderly diabetic patients with long-term RVP. Methods: Between January 2017 and January 2018, a total of 224 elderly diabetic patients with RVP at Fuwai Hospital were consecutively included in the study, with a 5-year follow-up period. The study endpoint was the first HF readmission during follow-up. This study aimed to explore the independent and joint relationship of NT-proBNP and LVMI with HF readmission in elderly diabetic patients with long-term RVP, using a multivariate Cox proportional hazards regression model. Results: A total of 224 (11.56%) elderly diabetic patients with RVP were included in the study. During the 5-year follow-up period, a total of 46 (20.54%) patients suffered HF readmission events. Multivariate Cox proportional hazards regression analysis showed that higher levels of NT-proBNP and LVMI were independent risk factors for HF readmission [NT-proBNP: hazard risk (HR) = 1.05, 95% confidence interval (CI): 1.01-1.10; LVMI: HR = 1.14, 95% CI: 1.02-1.27]. The optimal cut-off point of NT-proBNP was determined to be 330 pg/ml by receiver operating characteristic (ROC) curve analysis. Patients with NT-proBNP > 330 pg/ml and LVH had a higher risk of HF readmission compared to those with NT-proBNP ≤ 330 pg/ml and non-LVH (39.02% vs. 6.17%; HR = 7.72, 95% CI: 1.34-9.31, P < 0.001). Conclusion: In elderly diabetic patients with long-term RVP, NT-proBNP and LVMI were associated with the risk of HF readmission. Elevated NT-proBNP combined with LVH resulted in a significantly higher risk of HF readmission.

Association of QTc Interval and V4-S Wave With Appropriate ICD Therapy in Hypertrophic Cardiomyopathy.

Background: Ventricular arrhythmias in patients with hypertrophic cardiomyopathy (HCM) may lead to sudden cardiac death (SCD). We aimed to investigate the relationship between electrocardiogram (ECG) indicators and the risk of appropriate implantable cardioverter-defibrillator (ICD) therapy in HCM. Methods: The HCM patients receiving ICD implantation were enrolled consecutively. QT interval correction (QTc) was calculated using Bazett's formula. Long or deep S wave in V4 lead was defined as duration time >50 ms and/or voltage amplitude >0.6 mV. The endpoint in our study was at least one ICD appropriate therapy triggered by ventricular tachyarrhythmia (VT) or ventricular fibrillation (VF), including anti-tachyarrhythmia pacing (ATP) and electrical shock. Results: A total of 149 patients with HCM (mean age 53 ± 14 years, male 69.8%) were studied. Appropriate ICD therapies occurred in 47 patients (31.5%) during a median follow-up of 2.9 years. Cox regression analysis showed that long or deep S wave in V4 lead [hazard ratio (HR) 1.955, 95% confidence interval (CI) 1.017-3.759, P = 0.045] and QTc interval (HR 1.014, 95% CI 1.008-1.021, P < 0.001) were independent risk factors for appropriate ICD therapy. The ROC showed that the optimal cut-off point value for the QTc interval to predict the appropriate ICD therapy was 464 ms, and the AUC was 0.658 (95% CI 0.544-0.762, P = 0.002). The AUC for S wave anomalies in V4 lead was 0.608 (95% CI 0.511-0.706, P = 0.034). We developed a new model that combined the QTc interval and S wave anomalies in V4 lead based on four patient groups. Patients with QTc ≥464 ms and long or deep V4-S wave had the highest risk of developing appropriate ICD therapy (log-rank P < 0.0001). After adding QTc interval and V4-S wave anomalies into the HCM-risk-SCD model, the prediction effect of the new model was significantly improved, and the NRI was 0.302. Conclusions: In this HCM cohort, QTc and S wave anomalies in V4 lead were found to be significant and strong predictors of the risk of appropriate ICD therapy. Patients with QTc ≥464 ms and long or deep S wave had the highest risk. After QTc interval and V4-S wave anomalies adding to the HCM-risk-SCD model, the prediction effect is significantly improved.