Failure Index Research Articles

Incidence and predictors of heart failure with reduced and preserved ejection fraction after ST-elevation myocardial infarction in the contemporary era of early percutaneous coronary intervention.

The development and incidence of de-novo heart failure after ST-elevation myocardial infarction (STEMI) in the contemporary era of rapid reperfusion are largely unknown. We aimed to establish the incidence of post-STEMI heart failure, stratified by left ventricular ejection fraction (LVEF) and to find predictors for its occurrence. Furthermore, we investigated the course of left ventricular systolic and diastolic function after STEMI. A total of 1172 all-comer STEMI patients from the CardioLines Biobank were included. Patients were predominantly male (74.5%) and 64 ± 12 years of age. During a median follow-up of 3.7 years (2.0, 5.5) we found a total incidence of post-STEMI heart failure of 10.9%, of which 52.1% heart failure with reduced ejection fraction (HFrEF), 29.4% heart failure with mildly reduced ejection fraction and 18.5% heart failure with preserved ejection fraction (HFpEF). Independent predictors for the development of HFrEF were male sex (β = 0.97, p = 0.009), lung crepitations (β = 1.09, p = 0.001), potassium level (mmol/L, β = 0.43, p = 0.012), neutrophil count (109/L, β = 0.09, p = 0.001) and a reduced LVEF (β = 1.91, p < 0.001) at baseline. Independent predictors for the development of HFpEF were female sex (β = 0.99, p = 0.029), pre-existing kidney failure (β = 1.95, p = 0.003) and greater left atrial volume index (β = 0.04, p = 0.033) at baseline. Follow-up echocardiography (median follow-up 20 months) showed an improvement in LVEF (p < 0.001), whereas changes in diastolic function parameters showed both improvement and deterioration. In the current era of early STEMI reperfusion, still one in 10 patients develops heart failure, with approximately half of the patients with a reduced and half with a mildly reduced or normal LVEF. Predictors for the development of HFrEF were different from HFpEF.

Effects of a transition care program on depression, self-efficacy, and self-care behaviors in heart failure patients

IntroductionHeart failure is a progressive and unpredictable heart disease. How to work with these patients to decrease their psychological distress and promote their self-care behaviors is important. Transition care is the continuity of medical care for heart failure patients returning home from the hospital. Intervention through transition care may improve the continuity of medical care for patients with heart failure but it has not been examined in clinical settings in Taiwan.ObjectivesThe aims of this study were to explore the effects of a newly developed transition care program on depression, self-efficacy, and self-care behavior of heart failure patients.Methods Using an experimental research design and block randomization, participants were divided into the experimental group (received transition care and routine care) and the control group (received routine care only). The Patient Health Questionnaire-9 (PHQ-9), the General Self-Efficacy Scale (GSES), and the Self-Care of Heart Failure Index (SCHFI version 6.2) were used to collect data before discharge and the first month after discharge.Results A total of 20 patients with heart failure were recruited. No significant differences were found between the experimental (n=10) and control groups (n=10) in the degree of depression (Z=-.077, p=.938), self-efficacy (Z=-1.214, p=.225), and three self-care behaviors subscales (self-care maintenance Z= -1.214, p=.225; self-care management Z= -.401, p=.689; self-care confidence Z=-.436, p=.663) at discharge. After the one-month posttest, only self-efficacy (Z=-2.545, p=.011) and three self-care behaviors subscales (self-care maintenance Z=-3.097, p=.002; self-care management Z= -2.595, p=.009; self-care confidence Z=-3.671, p&lt;.001) reached a statistical difference between the two groups.ConclusionsBased on the preliminary results, heart failure patients can improve their self-care behavior and self-efficacy but not depression through transitional care intervention.Disclosure of InterestNone Declared

A Nuphar lutea plant active ingredient, 6,6′-dihydroxythiobinupharidine, ameliorates kidney damage and inflammation in a mouse model of chronic kidney disease

Chronic Kidney Disease (CKD) associated complications are associated with increased inflammation through the innate immune response, which can be modulated with anti-inflammatory agents. An active ingredient derived from the Nuphar lutea aquatic plant, 6,6′-dihydroxythiobinupharidine (DTBN) has anti-inflammatory properties, mainly through the inhibition of NF-κB. We tested the effects of DTBN on mice with CKD. After preliminary safety and dosing experiments, we exposed 8 weeks old male C57BL/6J mice to adenine diet to induce CKD. Control and CKD animals were treated with IP injections of DTBN (25 μg QOD) or saline and sacrificed after 8 weeks. Serum urea and creatinine were significantly decreased in CKD-DTBN Vs CKD mice. Kidney histology showed a decrease in F4/80 positive macrophage infiltration, damaged renal area, as well as decreased kidney TGF-β in CKD-DTBN Vs CKD mice. Kidney inflammation indices (IL-1β, IL-6 and P-STAT3) were significantly decreased in CKD-DTBN as compared to CKD mice. DTBN treatment showed no apparent damage to tissues in control mice, besides a decrease in weight gain and mild hypoalbuminemia without proteinuria. Thus, DTBN significantly improved renal failure and inflammation indices in CKD mice. Therefore, this and similar substances may be considered as an additional treatment in CKD patients.

Prognostic Value of Cardiac Color Doppler Ultrasound in Patients with Chronic Heart Failure

Objective: To investigate the value of cardiac color Doppler ultrasound (CDUS) in determining the clinical characteristics and assessing the prognosis of patients with chronic heart failure (CHF). Methods: 200 patients with CHF admitted to our hospital from January 2021 to June 2023 were selected as the study subjects, and these 200 patients were followed up for 6 months, with 159 cases in the surviving group and 41 cases in the deceased group, and examined with a diagnostic CDUS instrument (model GEVividE95ACUSONSC2000). The detection rate of chronic heart failure and cardiac function indexes of the two groups were observed. Results: The deceased group showed a chronic heart failure detection rate of 92.68%, which was significantly higher than the surviving group (76.73%; P &lt; 0.05). Moreover, the cardiac function indexes of both groups were significantly different (P &lt; 0.05). Conclusion: By performing cardiac ultrasonography on patients with CHF, their cardiac function can be clearly understood and the changes can be timely detected during treatment, hence physicians can formulate a more reasonable treatment plan for patients and improve their quality of life.

Complex design and analysis of filament wound composite pressure vessels using data driven evolutionary algorithms

The typical composite pressure vessel manufactured by means of filament winding consists of three elementary construction parts, that is, cylindrical part, end dome and the junction between its cylindrical part and the end dome which are subject of this article. The pressure vessel may fail in each of these three parts. Therefore, all of them must be considered during the design process. This study shows the possible way how to design an optimal pressure vessel related to chosen parameters (which can be mass of the pressure vessel, depth of the end dome, magnitude of internal pressure etc.), so that it does not fail in any construction parts. Any decision, whether the pressure vessel comply or not in studied places, is based on Hoffman's failure index analysis. The finding of an optimal solution requires performing a multi-objective optimization task, which was solved here using data-driven evolutionary algorithms. From the input data, which were generated through analytical approaches, surrogate models were created using the Evolutionary Deep Neural Nets (EvoDN2). These surrogate models were further used as an input to the optimization module which is based upon Constrained Reference Vector Evolutionary Algorithm (cRVEA). The results show that the pressure vessel designed in this way comply in each analyzed location. Moreover, it also finds the most stressed location, which can be useful for the designers.

A novel conceptual design approach for autonomous underwater helicopter based on multidisciplinary collaborative optimization

Autonomous underwater helicopters (AUHs) are complex electromechanical systems consisting of multiple interconnected sub-disciplines, posing a significant challenge for traditional sequential design strategies in managing their interactions. To address this challenge, a multidisciplinary collaborative optimization (MCO) strategy is proposed, integrating structural, hydrodynamic, and energy disciplines to enhance AUH cruising range. Additionally, a novel approximation model is introduced, combining the Logistic-Tent chaos sparrow search algorithm (LTC-SSA) with the backpropagation neural network (BPNN) algorithm. This method aims to replace costly computational fluid dynamics (CFD) and structural mechanics calculations, thus reducing AUH optimization costs. The laminate design of the composite pressure hull follows classic lamination theory (CLT) and the Tsai-Wu failure criterion. Results demonstrate that the multidisciplinary co-design strategy significantly reduces optimization time costs of AUH, from several months to several days. Furthermore, the proposed LTC-SSA-BPNN algorithm accurately evaluates sailing resistance and Tsai-Wu failure index, with maximum errors of 1.64% and 9.32% respectively. Additionally, the composite pressure shell achieves a 30.4% weight reduction and a 4.1% reduction in sailing resistance while maintaining structural stability. Moreover, the maximum cruising range increases by 34.4%. This strategy offers theoretical support for AUH conceptual design and promises performance enhancement in practical engineering applications.

A strength optimization approach for manufacturable 3D printed variable stiffness laminates with a strain-based approximation

The 3D printed continuous carbon fiber reinforced polymers (CFRP) are promising lightweight structures with outstanding mechanical performance. In this work, we propose a structure-manufacture integrated optimization approach for strength maximization of variable stiffness 3D printed CFRP composites by tailoring the steered printing paths. The rule of mixture is modified to evaluate material properties and strength of the printed laminates considering the effect of fiber volume fraction. To make this approach applicable to CFRP with asymmetric layups, a strain-based two-level convex approximation for the failure index based on the Tsai–Wu failure criterion is proposed, which can take the tension-bending coupling effect into consideration. The local failure indices are aggregated using the p-norm formula to reduce the size of the strength optimization model. In order to guarantee the manufacturability of the optimal design, the curvature of the steered printing fiber paths is constrained using a hybrid control method within the approach. The numerical cases show that the strength enhancement of the 3D printed variable stiffness laminates depends on the load, where an improvement between 35% and 46% can be achieved under the tension. Moreover, the proposed method can not only converge stably, but also be capable of optimizing structures with complex geometry.

Disparities in 30-Day Readmission Between Medicare/Medicaid and Private Insurance Among Patients With Heart Failure Screened for Cognitive Impairment.

Racial disparities exist among patients with heart failure (HF). HF is often comorbid with cognitive impairment. Appropriate self-care can prevent HF hospital readmissions but requires access to resources through insurance. Racial differences exist between insurance types, and this may influence the disparity between races and patients with HF and cognitive impairment. The objectives of this study were to examine the relationships between insurance type and self-care stratified by race and to assess for differences in time-to-30-day readmission among patients with HF with cognitive impairment. This is a secondary analysis of data collected among hospitalized patients with HF with cognitive impairment. Patients completed surveys on self-care (Self-Care of Heart Failure Index), HF knowledge (Dutch Heart Failure Knowledge Scale), depression (Geriatric Depression Scale), and social support (Enhancing Recovery in Coronary Heart Disease Social Support Inventory). Socioeconomic data were collected. Linear models were created to examine the relationships between insurance type and self-care by race. Kaplan-Meier curves and Cox regression were used to assess readmission. The sample of 125 patients with HF with cognitive impairment was predominantly Black (68%, n = 85) and male (53%, n = 66). The sample had either Medicare/Medicaid (62%, n = 78) or private insurance (38%, n = 47). Black patients with HF with cognitive impairment and private insurance reported higher self-care confidence compared with Black patients with HF with cognitive impairment and Medicare/Medicaid (P < .05). Medicare/Medicaid was associated with a higher frequency of 30-day readmission and a faster time-to-readmission. Patients with HF with cognitive impairment and Medicare/Medicaid insurance reported lower self-care confidence and more likely to be readmitted within 30 days.

Fault Diagnosis and Detection for Battery System in Real-World Electric Vehicles Based on Long-Term Feature Outlier Analysis

Accurate detection and diagnosis battery faults are increasingly important to guarantee safety and reliability of battery systems. Developed methods for battery early fault diagnosis concentrate on short-term data to analyze the deviation of external features without considering the long-term latent period of faults. This work proposes a novel data-driven method to detect long-term latent fault and abnormality for electric vehicles based on real-world operation data. Specifically, the battery fault features are extracted from the incremental capacity curves, which are smoothed by advanced filter algorithms. Secondly, principal component analysis algorithm is utilized to reduce dimensionality and the cumulative percent variance is to determine the number of significant features. Based on the features, a cluster algorithm is employed to capture the battery potential failure information. Moreover, the cumulative root-mean-square-deviation is introduced to quantificationally analyze the degree of the battery failures using large-scale battery data to avoid the missing fault reports using short-term data. In addition, a battery system failure index is proposed to evaluate battery fault conditions. The results indicate that the proposed long-term feature analysis method can effectively detect and diagnose faults.

Growth Hormone Mediators and Glycemic Control in Youths With Type 2 Diabetes

Youth-onset type 2 diabetes (T2D) has a more aggressive phenotype than adult-onset T2D, including rapid loss of glycemic control and increased complication risk. To identify associations of growth hormone mediators with glycemic failure, beta cell function, and insulin sensitivity in youth-onset T2D. This post hoc secondary analysis of the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) randomized clinical trial, which enrolled participants from July 2004 to February 2009, included 398 participants from 15 university-affiliated medical centers with available plasma samples from baseline and 36 months. Participants were youths aged 10 to 17 years with a duration of T2D of less than 2 years who were randomized to metformin, metformin plus lifestyle intervention, or metformin plus rosiglitazone. Participants were followed up for a mean (SD) of 3.9 (1.5) years during the trial, ending in 2011. Statistical analysis was performed from August 2022 to November 2023. Plasma insulin-like growth factor-1 (IGF-1), growth hormone receptor (GHR), and insulin-like growth factor binding protein 1 (IGFBP-1). Main outcomes were (1) loss of glycemic control during the TODAY study, defined as hemoglobin A1c (HbA1c) level of 8% or more for 6 months or inability to wean from insulin therapy, and (2) baseline and 36-month measures of glycemia (fasting glucose, HbA1c), insulin sensitivity (1/fasting C-peptide), high-molecular-weight adiponectin, and beta cell function (C-peptide index, C-peptide oral disposition index). This analysis included 398 participants (mean [SD] age, 13.9 [2.0] years; 248 girls [62%]; 166 Hispanic participants [42%]; 134 non-Hispanic Black participants [34%], and 84 non-Hispanic White participants [21%]). A greater increase in IGF-1 level between baseline and 36 months was associated with lower odds of glycemic failure (odds ratio [OR], 0.995 [95% CI, 0.991-0.997]; P < .001) and higher C-peptide index per 100-ng/mL increase in IGF-1 (β [SE], 0.015 [0.003]; P < .001). A greater increase in log2 GHR level between baseline and 36 months was associated with higher odds of glycemic failure (OR, 1.75 [95% CI, 1.05-2.99]; P = .04) and lower C-peptide index (β [SE], -0.02 [0.006]; P < .001). A greater increase in log2 IGFBP-1 level between baseline and 36 months was associated with higher odds of glycemic failure (OR, 1.37 [95% CI, 1.09-1.74]; P = .007) and higher high-molecular-weight adiponectin (β [SE], 431 [156]; P = .007). This study suggests that changes in plasma growth hormone mediators are associated with loss of glycemic control in youth-onset T2D, with IGF-1 associated with lower risk and GHR and IGFBP-1 associated with increased risk. ClinicalTrials.gov Identifier: NCT00081328.

Neural networks modeling of strain energy density and Tsai-Wu index in laminated composites

In laminated composite materials design, optimization mainly targets the stacking sequence configuration, which is defined by the lamina thickness and fiber orientations within each layer. Recent studies emphasize the increasing role of Machine Learning in promoting innovative composite designs by facilitating the accurate modeling of essential properties such as strength and stiffness. This study introduces two metamodels that utilize feed-forward artificial neural networks, taking laminate thickness and fiber steering angles as input parameters. The output variables, including strain energy density and the Tsai-Wu failure index, enable the prediction of stacking sequence configurations for laminated materials, a capability confirmed in a case study. The results showcase neural network models with the ability to predict these variables, achieving coefficients of determination above 0.90 for testing data. Consequently, this modeling approach has the potential to be a tool for designers, aiding in decision-making processes for the subsequent optimization of stiffness and strength in structural components made of laminated composite materials.

Key Characteristics of Asthma Patients with COVID-19 Vary Substantially by Age.

Assessing COVID-19 risk in asthma patients is challenging due to disease heterogeneity and complexity. We hypothesized that potential risk factors for COVID-19 may differ among asthma age groups, hindering important insights when studied together. We included a population-based cohort of asthma patients from the Swedish National Airway Register (SNAR) and linked to data from several national health registers. COVID-19 outcomes included infection, hospitalization, and death from Jan 2020 until Feb 2021. Asthma patients were grouped by ages 12-17, 18-39, 40-64, and ≥65 years. Characteristics of asthma patients with different COVID-19 outcomes were compared with those in their age-corresponding respective source population. Among 201,140 asthma patients studied, 11.2% were aged 12-17 years, 26.4% 18-39, 37.6% 40-64, and 24.9% ≥65 years. We observed 18,048 (9.0%) COVID-19 infections, 2172 (1.1%) hospitalizations, and 336 (0.2%) COVID-19 deaths. Deaths occurred only among patients aged ≥40. When comparing COVID-19 cases to source asthma populations by age, large differences in potential risk factors emerged, mostly for COVID-19 hospitalizations and deaths. For ages 12-17, these included education, employment, autoimmune, psychiatric, and depressive conditions, and use of short-acting β-agonists (SABA) and inhaled corticosteroids (ICS). In the 18-39 age group, largest differences were for age, marital status, respiratory failure, anxiety, and body mass index. Ages 40-64 displayed notable differences for sex, birth region, cancer, oral corticosteroids, antihistamines, and smoking. For those aged ≥65, largest differences were observed for cardiovascular comorbidities, type 1 diabetes, chronic obstructive pulmonary disease, allergic conditions, and specific asthma treatments (ICS-SABA, ICS-long-acting bronchodilators (LABA)). Asthma control and lung function were important across all age groups. We identify distinct differences in COVID-19-related risk factors among asthma patients of different ages. This information is essential for assessing COVID-19 risk in asthma patients and for tailoring patient care and public health strategies accordingly.

Full-scale static behaviour of prestressed geopolymer concrete sleepers reinforced with steel fibres

Profusive cracking leading to the deterioration of prestressed concrete sleepers has retained the sleepers from being exploited to their full extent. In addition, excess utilization of cement in producing the same has paved the way for developing its counterpart, geopolymer concrete (GPC), involving primary industrial residues as their precursors. This study presents a comprehensive investigation into the development and performance of high-strength geopolymer concrete sleepers for railway applications. The research focuses on the complete replacement of ordinary Portland cement with Fly ash and Ground Granulated Blast Furnace Slag in the geopolymer concrete mix, for mainline prestressed railway sleepers following Indian Railway Standards (IRS). Notably, the study includes experimental validations of long steel fibers as secondary reinforcement to the primary prestressing strands, aiming to enhance the ductility of the member. Experimental validations were performed on full-scale (1:1) sleeper members under static loading conditions. The main aim of this article was to assess the load carrying capacity at cracking and ultimate limits, rail seat bending moment, ductility indices, failure mechanism, electrical impedance, bond strength, and the eco-efficiency for the proposed prestressed geopolymer concrete sleeper members (with and without steel fibres) with reference to the conventional prestressed cement concrete sleepers. The considered GPC mix was found to achieve higher load and moment carrying capacity by about 8.3% and 8.54% respectively compared to the conventional concrete mix. The addition of steel fibres in the GPC increased the load and moment capacity of sleepers by 23% and 24.21% respectively. Additionally, the steel fibre reinforced GPC showed improved displacement ductility demand over the plain geopolymer concrete averaging 25%, 28.5%, and 3% corresponding to ultimate, failure, and residual ductility index respectively. Though inclusion of steel fibers improves the performance of sleepers in terms of load and ductility, they were found incompatible with regard to the electrical impedance property when used in conjunction with the pre-stressing strands.

Contribution of informal caregivers to self-care in individuals with heart failure.

to evaluate the contribution of informal caregivers to the self-care of individuals with heart failure. a cross-sectional study was conducted with 87 caregivers from March to October 2022 in the city of João Pessoa/PB. The caregivers' contribution was assessed using the Caregiver Contribution to Self-Care of Heart Failure Index instrument. Scores ≥ 70 points indicate adequate contribution. Data were analyzed using descriptive statistics and Spearman's correlation. the sample consisted of 81.6% female caregivers. Median scores obtained for the self-care contribution scales were: 63.3 for maintenance; 55.5 for management; and 66.6 for confidence. Caregivers never or rarely recommended monitoring body weight, regular physical exercise, extra use of diuretics, and fluid restriction. informal caregivers showed inadequate contribution in the areas of maintenance, management, and confidence in self-care of individuals with heart failure.

Do Clinical Outcomes and Quality of Life Differ by the Number of Antianginals for Stable Ischemic Heart Disease? Insights from the BARI 2D Trial

Medical therapy, including antianginal treatment, is the cornerstone in the management of stable ischemic heart disease (SIHD). However, it remains unclear whether combining antianginal agents provides benefits beyond monotherapy in terms of quality of life (QoL) and cardiovascular outcomes. We used data from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial, which compared cardiovascular and QoL outcomes in patients with SIHD and diabetes mellitus randomized to revascularization with intensive medical therapy or intensive medical therapy alone. We categorized patients into 3 groups: ≥2 versus 1 versus 0 antianginals. We compared patient characteristics, QoL metrics, and cardiovascular end points at baseline and at 5 years, creating a multivariable model to adjust for key clinical confounders. Of 2,368 patients, 348 patients (14.7%) were on 0 antianginals, 1,020 patients (43.1%) were on 1 antianginal, and 1,000 patients (42.2%) were on ≥2 antianginals at baseline. The most common antianginal class was β blockers. At baseline, patients on 0 antianginals had better QoL metrics (self-health score, Duke activity status index, and energy rating) than patients on ≥2 antianginals. However, at the 1-year follow-up, patients taking only 1 antianginal showed greater QoL improvement than those taking 0 antianginal, without any incremental benefit in QoL metrics seen in patients taking ≥2 antianginal agents, even after adjusting for multiple covariates such as age, heart failure, diabetes control, and myocardial jeopardy index. Lastly, at the 5-year follow-up, after adjustment, there were no differences in all-cause mortality, major adverse cardiovascular events, or myocardial infarction between patients taking different numbers of antianginals. Adults on a single antianginal for SIHD and diabetes mellitus had similar or better improvements in QoL than those on 2 or more antianginal agents at 1 year of follow-up. These findings merit further research to better understand the impact of medical therapy intensity on QoL in patients with SIHD and associated co-morbidities.

Implementing Reliability Analysis of a Soil Slope using First-Order Second Moment Method, Monte-Carlo Simulation Method and Subset Simulation Method in a MS-Excel Spreadsheet

The spatial variation in the soil properties affects the analysis and design of geotechnical structures such as slope stability analysis. This paper presents the reliability analysis of a soil slope using three different methods namely, first-order second moment (FOSM) method, Monte-Carlo simulation (MCS) method and Subset simulation (SS) method. The analysis has been carried out by considering the spatial variation of the soil properties of the slope. The correlation function and the correlation distance (λ) for the uncertain parameters are modelled using random field theory developed by Vanmarcke. The factor of safety (FOS) of the slope is determined using Ordinary method of slices. The reliability based probabilistic slope stability analysis has been carried out in a MS-Excel spreadsheet to determine the probability of failure (P_f ) and reliability index (β) of the slope. The spreadsheet mainly consists of three parts i.e., deterministic analysis, uncertainty analysis and uncertainty propagation. The study shows that the SS method has shown better performance as compared to FOSM method and MCS method especially at low failure probability levels. Also, SS method ensures the generation of samples in the failure region which is not always possible in MCS method.

A novel artificial neural network approach for residual life estimation of paper insulation in oil‐immersed power transformers

AbstractAvoiding financial losses requires preventing catastrophic oil‐filled power transformer breakdowns. Continuous online transformer monitoring is needed. The authors use paper insulation to evaluate transformer health for continuous online transformer monitoring. The study suggests a new artificial intelligence method for estimating paper insulation residual life in oil‐immersed power transformers. The four artificial intelligence models use backpropagation‐based neural networks to predict paper insulation lifespan. Four primary transformer insulating paper failure indices—degree of polymerisation, 2‐furfuraldehyde, carbon monoxide, and carbon dioxide—form the basis of these models. Each model, including the backpropagation‐based neural networks, estimates paper insulation life using one failure index, along with moisture and temperature data. Optimisation techniques enhance hidden layer neurons and epoch count for improved performance. Results are validated against literature‐based life models, establishing a precise input–output correlation. This method accurately predicts the remaining useable life of power transformer paper insulation, enabling utilities to take proactive measures for safe and efficient transformer operation.

Mediators of the Association Between Cognitive Function and Self-care Behaviors in Patients Hospitalized With an Exacerbation of Heart Failure.

Patients with heart failure (HF) must engage in self-care, yet their self-care is often poor. Cognitive function commonly is impaired in HF and is associated with poor self-care. Heart failure knowledge and self-care confidence also are needed to preform self-care. Few investigators have examined mediators of the association of cognitive function with self-care. The aim of this study was to determine whether HF knowledge and self-care confidence mediated the association of cognitive function with self-care maintenance and management among patients with HF. This was a cross-sectional observational study of 164 patients with HF. Cognitive function was assessed using the Montreal Cognitive Assessment. Self-care maintenance and self-care management behaviors and self-care confidence were measured using the Self-care of Heart Failure Index. Heart failure knowledge was measured using the Dutch Heart Failure Knowledge Scale. We conducted 2 parallel mediation analyses using the PROCESS macro in SPSS, one for self-care maintenance and one for self-care management. Cognitive function was indirectly associated with self-care maintenance through HF knowledge (indirect effect, 0.54; 95% confidence interval, 0.10-1.02) and self-care confidence (indirect effect, 0.26; 95% confidence interval, 0.04-0.54). Those with better cognitive function had more HF knowledge and self-care confidence. Better cognitive function was not directly associated with self-care management but indirectly associated with better self-care management through higher self-care confidence (indirect effect, 0.50; 95% confidence interval, 0.04-1.05). Both HF knowledge and self-care confidence mediated the association of cognitive function with self-care maintenance, and only self-care confidence mediated the association between cognitive function and self-care management. Interventions targeting HF knowledge and self-care confidence may improve self-care even for those with lower cognitive function and need to be developed and tested.

ASD and LRFD: Reliability comparison for designs subjected to wind loads

Current design practice in the United States allows engineers to use either Allowable Strength Design (ASD) or Load and Resistance Factor Design (LRFD) method, under the assumption that both methods provide similar levels of economy (available design strengths) and safety (probabilities of failure and reliability indices) regardless of the design conditions. Recent studies have demonstrated that significant differences in economy can arise between ASD- and LRFD-based designs subjected to combinations of gravity and wind loads, suggesting inconsistencies between the safety levels. This study investigates the safety levels provided by the ASD and LRFD methods for such design cases. The safety levels were estimated using a formal reliability analysis with consideration of geometrically non-linear second-order effects. The reliability analysis was performed using Monte Carlo simulations with appropriate probability distributions for the random variables associated with both resistance and loads. The findings of this study indicate that generally accepted uniformity of reliabilities achieved by the ASD and LRFD methods does not hold for design cases governed by wind loads. The safety levels achieved by using the ASD method are less consistent than those achieved by using the LRFD method. The use of the ASD method generally entails the acceptance of failure risks many times greater than for those of the LRFD method, and target safety levels lower than those stipulated by the ASCE 7 Standard. These results highlight the need for a reevaluation of the current design practices to ensure that the required target levels of structural safety are consistently met.

Impact of serum haemoglobin-to-creatinine ratio after transcatheter aortic valve implantation

ObjectiveThe association between a combined anaemia and renal failure index and 1-year prognosis of patients undergoing transcatheter aortic valve implantation (TAVI) is unexplored. We aimed to investigate a simple risk...