Global Comparison of Readmission Rates for Patients With Heart Failure

The effectiveness of nursing interventions to improve self-care for patients with heart failure at home: a systematic review and meta-analysis

BACKGROUND

Self-care plays an important role in the treatment of patients with heart failure (HF) and adequately performed self-care at home can contribute to fewer hospitalizations, lower mortality risk and require less emergency care. The aim of this systematic review and meta-analysis was to synthesise evidence on the effectiveness of nursing interventions on HF-related self-care at home.

METHODS

Medline, Scopus, Cumulative Index to Nursing and Allied Health Literature, Cochrane database, Web of Science, PsycInfo, and trial registers were searched up to 31st December 2022. We aimed to include experimental and observational studies with a control group investigating nursing interventions including transitional care, home care programs, phone calls, digital interventions, or a combination thereof on self-care of patients with HF. Outcomes were self-care maintenance, self-care management, and self-care behaviours, measured with various instruments. The screening and data extraction were performed independently by two reviewers, and disagreements were solved by a third reviewer. Cochrane risk of bias tool for randomised trials and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach were used.

RESULTS

Twenty-seven studies were included (2176 participants), of which 24 were randomised controlled trials. Three categories of interventions emerged, called "transitional care", "home care", and "remote interventions". Transitional care aimed at caring for patients at their homes after discharge through phone calls, digital interventions, and home visits may result in little to no difference in self-care maintenance (MD 7.26, 95% CI 5.20, 9.33) and self-care management (MD 5.02, 95% CI 1.34, 8.69) while contrasting results emerged in self-care behaviours since two out of six studies reported no improvements in self-care. Home care combined with phone calls or digital interventions likely increase self-management and self-care behaviours (MD -7.91, 95% CI -9.29, -6.54). Remote care could improve self-care behaviours when delivered as phone call programs, but they are ineffective on all outcomes when delivered as digital interventions alone.

CONCLUSION

Transitional care and home care combined with phone calls and digital interventions, and phone calls caring for patients at their home could slightly improve self-care in patients with HF. However, more research is needed to study the effects across different domains of self-care and of interventions delivered through digital interventions alone.

Renal Artery Denervation Combined with Pulmonary Vein Isolation in Patients with Heart Failure and Atrial Fibrillation: Pilot Study: Renal Artery Denervation in Treatment of Atrial Fibrillation and Heart Failure

Background: Heart failure (HF) is a progressive condition associated with reduced life expectancy and quality of life. Atrial fibrillation (AF), the most common arrhythmia in HF patients, significantly worsens symptoms and outcomes. The coexistence of HF and AF is linked to higher morbidity and mortality rates, with a bidirectional relationship exacerbating both conditions. The recent evidence has suggested that combining pulmonary vein isolation (PVI) with renal denervation (RDN) may offer a promising strategy for reducing AF burden and enhancing patient outcomes. Methods: This prospective interventional clinical trial aimed to assess the safety and effectiveness of a combined RDN and PVI approach compared to PVI alone. Eighteen patients, aged 18 to 80 years, with paroxysmal or persistent AF and HF (left ventricular ejection fraction [LVEF] < 50%) were enrolled. RDN was performed under general anesthesia using the four-electrode Symplicity Spyral catheter and Symplicity G3 radiofrequency generator (Medtronic). Patients were randomized to the RDN+PVI group (n = 7) or the PVI-only group (n = 11). The groups were similar in age (59 ± 8.4 years vs. 62.5 ± 11.08 years, p = NS) and baseline characteristics, including hypertension, obesity, and impaired left ventricular function (LVEF 35.86% vs. 38.54%, RDN+PVI vs. PVI only; p = NS). Results: Over a mean follow-up of 24 months, one patient died, ten were hospitalized, six underwent repeat PVI, and eight achieved AF freedom. Patients in the RDN+PVI group were significantly more likely to remain AF-free (n = 6 vs. 2; p = 0.0063). The need for repeat ablation was higher in the PVI-only group (54.5% vs. 0%), though this did not reach statistical significance. Hospitalization rates and changes in ejection fraction were similar between groups. Importantly, no procedural complications were observed. Conclusions: Combining RDN with PVI is a safe hybrid approach for AF management in HF patients, showing promising efficacy in reducing AF recurrence. Larger randomized studies are needed to confirm these findings and further explore this novel therapeutic strategy.

Patient Interpretations of Heart Failure Symptom Recognition and Self-Management Using Vignettes: A Pilot Study

BACKGROUND

Heart failure is a condition with significant symptom burden and high hospitalization rates. Effective self-management, including recognizing symptoms and making behavior changes, is crucial but often inadequately addressed by current educational methods. To improve this, heart failure self-care vignettes were developed to measure knowledge of managing physical and psychological symptoms. However, the vignettes' face validity and reliability have not been thoroughly evaluated.

OBJECTIVE

To ensure the understandability of a novel instrument to measure knowledge of heart failure symptom recognition and self-management and to examine its inter-rater reliability with individuals diagnosed with heart failure.

METHODS

Cognitive interviews were conducted with heart failure patients admitted to an academic hospital in the Midwest U.S. Vignette segments and interview questions were analyzed, totaling 74 items. Five patients aged 65 and older, participated without cognitive, visual, or hearing impairments. The interviews were coded by two independent raters using a cognitive interview coding book. Vignettes were evaluated qualitatively with a 3-point Likert scale (1 = misunderstanding, 2 = partial understanding, and 3 = full understanding). Inter-rater reliability was assessed using percent agreement and Cohen's kappa.

RESULTS

Patients understood an average of 76% of the psychological and 83% of the physical vignette items, indicating acceptable preliminary understandability. Inter-rater reliability was moderate, with Cohen's kappa values of 0.39 (psychological) and 0.43 (physical).

CONCLUSIONS

This pilot study suggests that vignettes could be a useful tool for assessing knowledge of symptom recognition and self-management. Cognitive interviewing helped evaluate how vignette segments were interpreted before using them in future data collection.

Effect of early readmission on subsequent hospital admissions within 1 year in patients with heart failure: A retrospective cohort study

This study aimed to identify the factors influencing multiple admissions within 1 year for patients with heart failure (HF) and to examine the impact of early readmission on subsequent admissions. A retrospective questionnaire survey was conducted on 498 patients with HF admitted to our hospital's Cardiology department between January 1, 2020, and December 31, 2022. Multivariate regression analysis identified factors influencing multiple admissions, and propensity score matching (PSM) assessed the impact of readmissions within 30 days and 31 to 90 days post-discharge on unplanned admissions within a year. The incidence of multiple admissions was 22.09% (110/498), with first readmissions within 30 days post-discharge at 13.25% (66/498) and within 31 to 90 days at 15.86% (79/498). Influential factors for multiple unplanned hospital admissions included age, history of atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease, New York Heart Association grade ≥ III, hemoglobin (Hb) < 110g/L, taking 7 or more medications, and readmission within 31 to 90 days (P < .05). Post-PSM analysis showed that the first admission within 30 days (odds ratio [OR] = 6.400, 95% confidence interval [Cl] = 2.638-15.527, P = .001), and the first admission within 31 to 90 days significantly increased the risk of multiple admissions (OR = 5.694, 95% Cl = 2.615-12.402, P = .001). Patients with HF exhibit a high rate of numerous readmissions within 1 year. Clinical medical staff should focus more on patients with early readmissions, enhance self-management, and improve management of comorbidities and medications through a multidisciplinary team approach. Enhancing continuous nursing and improving access to medical services may reduce patient readmission rates.

Effectiveness of a nurse practitioner-led collaborative health care model on self-care, functional status, rehospitalization and medical costs in heart failure patients: A randomized controlled trial

BACKGROUND

Heart failure is a serious and common condition that has garnered significant attention in the global public health domain. It often results in impaired function and reduced cardiac function status, leading to difficulties in self-care and diminished quality of life. To effectively address these complex challenges, the collaborative health care model has been proposed. This approach has proven effective in reducing rehospitalization and lowering medical costs.

OBJECTIVE

To evaluate the effects of a nurse practitioner-led collaborative health care model on the self-care, functional status, rehospitalization and medical costs of patients with heart failure.

DESIGN

A randomized controlled trial design.

SETTING

Cardiology department of a regional teaching hospital in Southern Taiwan.

PARTICIPANTS

100 patients diagnosed with heart failure.

METHODS

Patients diagnosed with heart failure were recruited through random allocation and. randomly assigned to two groups. The control group included 50 patients who received routine nursing guidance; the experimental group also included 50 patients who participated in a 12-week collaborative health care program. Key outcomes, including self-care, functional status, rehospitalization, and medical costs, which were evaluated at 12, 16, and 20 weeks post-discharge.

RESULTS

The intervention of the collaborative healthcare program significantly impacted self-care, functional status, rehospitalization, and medical costs. Significant improvements in self-care and functional status were observed at 20 weeks (Self-Care: β = 31.52, 95 % CI: 25.96 to 37.07, p < 0.001; Functional Status: χ2 = 22.42, p < 0.001). Regarding rehospitalization, the average rehospitalization duration for the experimental group significantly increased compared to 1.45 months for the control group, with the experimental group averaging 3.00 months at the 20-week follow-up. Moreover, the experimental group also demonstrated a reduction in rehospitalization medical costs, particularly with significant effects observed in the early stages of intervention (β = -6147.94, 95 % CI: -10,763.99 to -1531.88, p = 0.009).

CONCLUSION

The use of a nurse practitioner-led collaborative health care model significantly improved self-care, function status and reduced rehospitalization while effectively lowering medical costs for patients with heart failure. Through professional team communication and collaboration, this approach provides more effective and comprehensive care, enhances patient self-management capabilities, and improves overall treatment outcomes. These results hold significant implications for clinical practice and provide empirical support for future heart failure care programs, warranting their widespread implementation in clinical settings.

REGISTRATION

This study was registered on ClinicalTrials.gov under the identifier NCT04860596 on April 22, 2021, and participant recruitment was initiated in April 2023.

TWEETABLE ABSTRACT

Effectiveness of a Nurse Practitioner-Led Collaborative Care Model: Reduces rehospitalization and medical costs, while improving self-care and functional status in heart failure patients. A Randomized Controlled Trial. #HeartFailure #HealthCare #SelfCare.

Association Between the Albumin-Bilirubin (ALBI) Score and All-cause Mortality Risk in Intensive Care Unit Patients with Heart Failure

Background

The albumin-bilirubin (ALBI) score has demonstrated prognostic value in a range for liver and heart diseases. However, its association with all-cause mortality in intensive care unit (ICU) patients with heart failure remains uncertain.

Objective

This study sought to investigate the relationship between the ALBI score and the risk of all-cause mortality in ICU patients with heart failure.

Methods and results

The ICU patients diagnosed with heart failure were selected from the Medical Information Mart for Intensive Care IV database (MIMIC-IV, version 2.2) and stratified into tertiles according to their ALBI scores. The primary outcome of interest was the occurrence of all-cause mortality within 365 days post-discharge. The analysis encompassed a cohort of 4,239 patients, with Kaplan-Meier curves indicating that individuals with higher ALBI levels exhibited an elevated risk of all-cause mortality (log-rank p < 0.001). Multivariate adjusted Cox regression and subgroup analysis demonstrated that individuals in T2 (hazard ratio (HR) 1.09, 95% CI 0.99-1.21) and T3 (HR 1.17, 95% CI 1.02-1.34) had an increased risk of mortality compared to individuals in T1 (p for trend < 0.001), and each incremental tertile in ALBI was linked to a 10% rise in mortality risk, while each individual unit increase in ALBI was associated with a 36% increase in mortality risk. This relationship was consistently observed across most subgroups, except for using or not using inotropes or vasopressors, different ages, different creatinine levels. The restricted cubic spline (RCS) analysis indicated a linear relationship between ALBI levels and the risk of all-cause mortality.

Conclusion

The ALBI scores are independently associated with the risk of all-cause mortality in ICU patients with heart failure, particularly in those not using inotropes or vasopressors, younger patients, and with lower levels of creatinine. ALBI may help identify high-risk patients and optimize risk stratification in this population.

Combination decoction of Astragalus mongholicus and Salvia miltiorrhiza mitigates pressure-overload cardiac dysfunction by inhibiting multiple ferroptosis pathways

Background

Astragalus mongholicus (AM) and Salvia miltiorrhiza (SM) are commonly used in traditional Chinese medicine to treat heart failure (HF). Ferroptosis has been studied as a key factor in the occurrence of HF. It remains unclear whether the combined use of AM and SM can effectively improve HF and the underlying mechanisms.

Objective

This study aims to explore whether the combined use of AM and SM can improve HF by inhibiting ferroptosis. It also examines the roles and interactions of the pathways associated with GPX4, FSP1, and DHODH.

Methods

In vitro experiments used angiotensin II-induced (4 μM for 48 h) hypertrophic H9c2 cells, while in vivo studies employed a rat model of transverse aortic constriction-induced (to 1 mm for 8 weeks) HF. Interventions included decoctions of AM and SM (for animal experiments) and medicated serum (for cell experiments), along with specific pathway inhibitors such as erastin, FSP1 inhibitor and brequinar. Subsequently, various molecular biology methods were used to measure the protein levels of GPX4, FSP1, and DHODH, as well as each sample group's ferroptosis-related and HF-related indicators, to elucidate the underlying mechanisms.

Results

The combined use of AM and SM can effectively restore the levels of GPX4, FSP1, and DHODH that are reduced after HF, as well as improve indicators related to ferroptosis and HF. When GPX4, FSP1, or DHODH is inhibited, the ferroptosis-inhibiting effect and the ability of AM and SM to improve HF are both weakened. When two of the three proteins are inhibited, the protective effect of HDC is strongest when GPX4 is retained, followed by FSP1, and weakest when DHODH is retained.

Conclusion

This study confirms that the combined use of AM and SM inhibits ferroptosis and alleviates HF by increasing GPX4, FSP1, and DHODH levels. It shows that the protective effect is strongest through GPX4, followed by FSP1, and weakest through DHODH. These findings provide new insights into the therapeutic mechanisms of this combination of botanical drugs.

Cumulative Incidence and Prognostic Value of Readmissions in Patients With Heart Failure: Data From a Large Cohort Study of Real Clinical Practice in St. Petersburg

Aim    To evaluate the cumulative incidence and prognostic value of rehospitalizations in patients with heart failure (HF) within one year after discharge.Material and methods    The data of patients with HF hospitalized for the first time (code I50.x in the diagnosis) for the period from January 01, 2022 through February 13, 2024 were selected from the St. Petersburg Chronic Heart Failure Registry. Age and gender characteristics, comorbidities, risk of rehospitalization and death after discharge from the hospital depending on the number of rehospitalizations were analyzed. Descriptive statistics methods, Kaplan-Meier survival analysis, and the Fine and Gray competing risks model were used. P<0.001 was considered significant.Results    The study included 43,143 patients with HF who were hospitalized for the first time. During a median observation time of 242 days, 6,395 (14.8%) patients were readmitted, most often once (78.4%). A greater number of rehospitalizations was typical for men, patients with HF of ischemic genesis, atrial fibrillation, diabetes mellitus, obstructive pulmonary diseases, and a history of COVID-19. The cumulative incidence of rehospitalizations for HF during 1, 3, 6, and 12 months was 3.2%, 7.0%, 10.8%, and 17.2%, respectively, taking into account the competing risk of death. With an increasing number of hospitalizations, the median time to the next hospitalization decreased, and the risk of readmission increased (p<0.001). The probability of death within a year of the index hospitalization was 14.9% (95% confidence interval [CI]: 14.5%-15.3%). The all-cause death rate was 30, 44, and 54 cases per 100 patient-years for patients with one, two, and at least three readmissions vs. 19 cases per 100 patient-years for those without readmissions. Readmitted patients were characterized by an increased risk of death: the adjusted hazard ratios of death in patients with one, two, and at least three readmissions were 1.47 (95% CI: 1.36-1.59), 1.97 (95% CI: 1.69-2.30), and 2.24 (95% CI: 1.81-2.78), respectively.Conclusion    In patients hospitalized with HF for the first time, the cumulative one-year HF readmission rate adjusted for the competing risk of death was 17.2%. Increased readmission rates were independently associated with increased odds of readmission and death.

Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization

INTRODUCTION

Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical models (CSM), but the calibration of such models is unclear.

OBJECTIVES

To compare models developed using ML with those developed using CSM to predict 30-day readmission for cardiovascular and noncardiovascular causes in HF patients.

METHODS

We retrospectively enrolled 10,919 patients with HF (> 18 years) discharged alive from a hospital or emergency department (2004-2007) in Ontario, Canada. The study sample was randomly divided into training and validation sets in a 2:1 ratio. CSMs to predict 30-day readmission were developed using Fine-Gray subdistribution hazards regression (treating death as a competing risk), and the ML algorithm employed random survival forests for competing risks (RSF-CR). Models were evaluated in the validation set using both discrimination and calibration metrics.

RESULTS

In the validation sample of 3602 patients, RSF-CR (c-statistic=0.620) showed similar discrimination to the Fine-Gray competing risk model (c-statistic=0.621) for 30-day cardiovascular readmission. In contrast, for 30-day noncardiovascular readmission, the Fine-Gray model (c-statistic=0.641) slightly outperformed the RSF-CR model (c-statistic=0.632). For both outcomes, The Fine-Gray model displayed better calibration than RSF-CR using calibration plots of observed vs predicted risks across the deciles of predicted risk.

CONCLUSIONS

Fine-Gray models had similar discrimination but superior calibration to the RSF-CR model, highlighting the importance of reporting calibration metrics for ML-based prediction models. The discrimination was modest in all readmission prediction models regardless of the methods used.

Can Timely Outpatient Visits Reduce Readmissions and Mortality Among Heart Failure Patients?

BACKGROUND

Outpatient follow-up after a hospital discharge may reduce the risk of readmissions, but existing evidence has methodological limitations.

OBJECTIVES

To assess effect of outpatient follow-up within 7, 14, 21 and 30 days of a hospital discharge on 30-day unplanned readmissions or mortality among heart failure (HF) patients; and whether this varies for patients with different clinical complexities.

DESIGN

We analyzed medical records between January 2016 and December 2021 from a prospective cohort study. Using time varying mixed effects parametric survival models, we examined the association between not having an outpatient follow-up and risk of adverse events. We used interaction models to assess if the effect of outpatient follow-up visit on outcomes varies with patients' clinical complexity (comorbidities, grip strength, cognitive impairment and length of inpatient stay).

PARTICIPANTS

Two hundred and forty-one patients with advanced HF.

MAIN MEASURES

30-day all-cause (or cardiac) adverse event defined as all cause (or cardiac) unplanned readmissions or death within 30 days of an unplanned all-cause (or cardiac) admission or emergency department visit.

KEY RESULTS

We analyzed 1595 all-cause admissions, inclusive of 1266 cardiac admissions. Not having an outpatient follow-up (vs having an outpatient follow-up) significantly increased the risk of 30-day all-cause adverse event. (risk [95% CI] - 14 days: 35.1 [84.5,-1.1]; 21 days: 43.9 [48.2,6.7]; 30 days: 31.1 [48.5, 7.9]) The risk (at 21 days) was higher for those with one co-morbidity (0.25 [0.11,0.58]), mild (0.67 [0.45, 1.00]) and moderate cognitive impairment (0.38 [0.17, 0.84]), normal grip strength (0.57 [0.34, 0.96]) and length of inpatient stay 7-13 days (0.45 [0.23, 0.89]).

CONCLUSION

Outpatient follow-up within 30 days after a hospital discharge reduced risk of 30-day adverse events among HF patients, the benefit varying according to clinical complexity. Results suggest the need to prioritize patients who benefit from outpatient follow-up for these visits.

Transforming Health Care from Volume to Value: Targeting Essential Therapies for Improved Health

The healthcare landscape is evolving rapidly due to escalating costs from the traditional fee-for-service model. Value-based care has emerged as a viable solution, and initiatives focus on areas prone to overuse, waste, or high costs, such as advanced imaging and avoidable acute care resource utilization. Improving medication use is an important component of this work, and it requires organizational commitment, interdisciplinary collaboration, and targeted strategies for specific therapeutic areas. This review article discusses the value-based care approach to optimizing medications and blood product prescribing, spotlighting opportunities to reduce the overuse of opioid, antimicrobial, and proton pump inhibitor medications, alongside the underuse of guideline-based medical therapies in managing chronic diseases like coronary artery disease, heart failure, and chronic obstructive pulmonary disease.

Impact of the method of calculating 30-day readmission rate after hospitalization for heart failure. Data from the VancOuver CoastAL Acute Heart Failure (VOCAL-AHF) registry

BACKGROUND

Thirty-day readmission rate after heart failure (HF) hospitalization is widely used to evaluate healthcare quality. Methodology may substantially influence estimated rates. We assessed the impact of different definitions on HF and all-cause readmission rates.

METHODS

Readmission rates were examined in 1835 patients discharged following HF hospitalization using 64 unique definitions derived from five methodological factors: (1) International Classification of Diseases-10 codes (broad vs. narrow), (2) index admission selection (single admission only first-in-year vs. random sample; or multiple admissions in year with vs. without 30-day blanking period), (3) variable denominator (number alive at discharge vs. number alive at 30 days), (4) follow-up period start (discharge date vs. day following discharge), and (5) annual reference period (calendar vs. fiscal). The impact of different factors was assessed using linear regression.

RESULTS

The calculated 30-day readmission rate for HF varied more than two-fold depending solely on the methodological approach (6.5-15.0%). All-cause admission rates exhibited similar variation (18.8-29.9%). The highest rates included all consecutive index admissions (HF 11.1-15.0%, all-cause 24.0-29.9%), and the lowest only one index admission per patient per year (HF 6.5-11.3%, all-cause 18.8-22.7%). When including multiple index admissions and compared with blanking the 30-day post-discharge, not blanking was associated with 2.3% higher readmission rates. Selecting a single admission per year with a first-in-year approach lowered readmission rates by 1.5%, while random-sampling admissions lowered estimates further by 5.2% (P < 0.001).

CONCLUSION

Calculated 30-day readmission rates varied more than two-fold by altering methods. Transparent and consistent methods are needed to ensure reproducible and comparable reporting.

Cost-Effectiveness of Sotagliflozin in SOLOIST-WHF

BACKGROUND

The efficacy of sotagliflozin in patients with diabetes and recent worsening of heart failure was shown in the SOLOIST-WHF trial. However, the cost-effectiveness of sotagliflozin in these patients has not been previously investigated.

OBJECTIVES

The authors sought to determine the cost-effectiveness of sotagliflozin in patients with diabetes and recent worsening of heart failure.

METHODS

Based on SOLOIST-WHF trial data (N = 1,222), the authors constructed a Markov model to estimate the lifetime impact of sotagliflozin from a U.S. health care sector perspective. Cost data were sourced from the National Inpatient Sample. Life expectancy was modeled from census data and modified by the mortality rate in SOLOIST-WHF. Fatal and nonfatal event rates were carried forward from the trial data. Utility was assessed from the published reports.

RESULTS

Lifetime quality-adjusted life-years (QALYs) were 4.43 and 4.04 in the sotagliflozin and placebo groups, respectively, and lifetime costs were $220,113 and $188,198 in the sotagliflozin and placebo groups, respectively. The point estimate incremental cost-effectiveness ratio was $81,823 per QALY gained. The probability of being cost-effective was 3.6%, 67.5%, and 89.4% at willingness-to-pay thresholds of $50,000, $100,000, and $150,000, respectively, per QALY gained.

CONCLUSIONS

In patients with diabetes and recent worsening of heart failure, sotagliflozin is cost-effective in the U.S. using commonly accepted willingness-to-pay thresholds. (Effect of Sotagliflozin on Cardiovascular Events in Participants With Type 2 Diabetes Post Worsening Heart Failure [SOLOIST-WHF]; NCT03521934).

Elevated plasma solMER concentrations link ambient PM2.5 and PAHs to myocardial injury and reduced left ventricular systolic function in children

Exposure to fine particulate matter (PM2.5) and polycyclic aromatic hydrocarbons (PAHs) is known to be associated with the polarization of pro-inflammatory macrophages and the development of various cardiovascular diseases. The pro-inflammatory polarization of resident cardiac macrophages (cMacs) enhances the cleavage of membrane-bound myeloid-epithelial-reproductive receptor tyrosine kinase (MerTK) and promotes the formation of soluble MerTK (solMER). This process influences the involvement of cMacs in cardiac repair, thus leading to an imbalance in cardiac homeostasis, myocardial injury, and reduced cardiac function. However, the relative impacts of PM2.5 and PAHs on human cMacs have yet to be elucidated. In this study, we aimed to investigate the effects of PM2.5 and PAH exposure on solMER in terms of myocardial injury and left ventricular (LV) systolic function in healthy children. A total of 258 children (aged three to six years) were recruited from Guiyu (an area exposed to e-waste) and Haojiang (a reference area). Mean daily PM2.5 concentration data were collected to calculate the individual chronic daily intake (CDI) of PM2.5. We determined concentrations of solMER and creatine kinase MB (CKMB) in plasma, and hydroxylated PAHs (OH-PAHs) in urine. LV systolic function was evaluated by stroke volume (SV). Higher CDI values and OH-PAH concentrations were detected in the exposed group. Plasma solMER and CKMB were higher in the exposed group and were associated with a reduced SV. Elevated CDI and 1-hydroxynaphthalene (1-OHNa) were associated with a higher solMER. Furthermore, increased solMER concentrations were associated with a lower SV and higher CKMB. CDI and 1-OHNa were positively associated with CKMB and mediated by solMER. In conclusion, exposure to PM2.5 and PAHs may lead to the pro-inflammatory polarization of cMacs and increase the risk of myocardial injury and systolic function impairment in children. Furthermore, the pro-inflammatory polarization of cMacs may mediate cardiotoxicity caused by PM2.5 and PAHs.

SHAP based predictive modeling for 1 year all-cause readmission risk in elderly heart failure patients: feature selection and model interpretation

Heart failure (HF) is a significant global public health concern with a high readmission rate, posing a serious threat to the health of the elderly population. While several studies have used machine learning (ML) to develop all-cause readmission risk prediction models for elderly patients with HF, few have integrated ML-selected features with those chosen by human experts to assess HF patients readmission. A retrospective analysis of 8396 elderly HF patients hospitalized at the Affiliated Hospital of North Sichuan Medical College from January 1, 2018 to December 31, 2021 was conducted. Variables selected by XGBoost, LASSO regression, and random forest constituted the machine group, while the human expert group comprised variables chosen by two experienced cardiovascular professors. The variables selected by both groups were combined to form a human-machine collaboration group. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) method was used to elucidate the importance of each predictive feature, explain the impact of individual features on the model, and provide visual representation. A total of 73 features were included for model development. The human-machine collaboration model, utilizing CatBoost, achieved an AUC of 0.83617, an F1-score of 0.73521, and a Brier score of 0.16536 on the validation set. This model demonstrated superior predictive performance compared to those created solely by human experts or machine. The SHAP plot was then used to visually display the feature analysis of the human-machine collaboration model, revealing HGB, NT-proBNP, smoking history, NYHA classification, and LVEF as the 5 most important features. This study indicate that the human-machine collaboration model outperforms those relying solely on human expert selection or machine algorithm at predicting all-cause readmission in elderly HF patients. The application of the SHAP method enhanced the interpretability of the model outcomes, aiding clinicians in accurately pinpointing risk factors associated with HF readmission. This advancement enables the formulation of tailored treatment strategies, offering a more personalized approach to patient care.

Exo-miR-144-3p as a promising diagnostic biomarker for depressive symptoms in heart failure

AIMS

The prevalence of depression is higher in heart failure (HF) patients. Early screening of depressive symptoms in HF patients and timely intervention can help to improve patients' quality of life and prognosis. This study aims to explore diagnostic biomarkers by examining the expression profile of serum exosomal miRNAs in HF patients with depressive symptoms.

METHODS

Serum exosomal RNA was isolated and extracted from 6 HF patients with depressive symptoms (HF-DS) and 6 HF patients without depressive symptoms (HF-NDS). High-throughput sequencing was performed to obtain miRNA expression profiles and target genes were predicted for the screened differentially expressed miRNAs. Biological functions of the target genes were analyzed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, we collected serum exosomal RNAs from HF-DS (n = 20) and HF-NDS (n = 20). The differentially expressed miRNAs selected from the sequencing results were validated using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Finally, the diagnostic efficacy of the differentially expressed exosomal miRNAs for HF-DS was evaluated by using receiver operating characteristic (ROC) curves.

RESULTS

A total of 19 significantly differentially expressed exosomal miRNAs were screened by high-throughput sequencing, consisting of 12 up-regulated and 7 down-regulated exosomal miRNAs. RT-qPCR validation demonstrated that the expression level of exo-miR-144-3p was significantly down-regulated in the HF-DS group, and the expression levels of exo-miR-625-3p and exo-miR-7856-5p were significantly up-regulated. In addition, the expression level of exo-miR-144-3p was negatively correlated with the severity of depressive symptoms in HF patients, and that the area under the curve (AUC) of exo-miR-144-3p for diagnosing HF-DS was 0.763.

CONCLUSIONS

In this study, we examined the serum exosomal miRNA expression profiles of HF patients with depressive symptoms and found that lower level of exo-miR-144-3p was associated with more severe depressive symptoms. Exo-miR-144-3p is a potential biomarker for the diagnosis of HF-DS.

Acute Heart Failure Is a Malignant Process: But We Can Induce Remission

Acute heart failure is a common and increasingly prevalent condition, affecting >10 million people annually. For those patients who survive to discharge, early readmissions and death rates are >30% everywhere on the planet, making it a malignant condition. Beyond these adverse outcomes, it represents one of the largest drivers of health care costs globally. Studies in the past 2 years have demonstrated that we can induce remissions in this malignant process if therapy is instituted rapidly, at the first acute heart failure episode, using full doses of all available effective medications. Multiple studies have demonstrated that this goal can be achieved safely and effectively. Now the urgent call is for all stakeholders, patients, physicians, payers, politicians, and the public at large to come together to address the gaps in implementation and enable health care providers to induce durable remissions in patients with acute heart failure.