Predictors of one-year outcomes in chronic heart failure: the portrait of a middle income country

Association of depressive symptoms and engagement in physical activity with event-free survival in patients with heart failure

BACKGROUND

Heart failure (HF) subtype, depressive symptoms, and physical inactivity independently contribute to survival outcomes, but the effect of the interaction of these variables on survival outcomes remains unknown.

OBJECTIVES

We aimed to determine whether depressive symptoms and engagement in physical activity differentially interact to predict the combined endpoint of all-cause death or rehospitalization among patients with HF and reduced (HFrEF) or preserved ejection fraction (HFpEF).

METHODS

This study was a secondary analysis. The sample was categorized by the presence or absence of depressive symptoms, and engagement or non-engagement in physical activity. Cox proportional hazard modeling was used to predict the combined endpoint of all-cause death or rehospitalization.

RESULTS

A total of 1002 patients with HF were included (mean age 64.3 ± 12.7 years; 637 males [64 %]; 844 White [84 %]). Among them, 35.3 % did not engage in physical activity, while 64.7 % engaged in any level of physical activity, and 29.7 % had depressive symptoms. In both subtypes, depressive symptoms were associated with the highest risk of all-cause death or rehospitalization. Among patients with HFrEF, those with depressive symptoms who did not engage in physical activity were associated with a 136 % higher risk of the combined endpoint, while among those with HFpEF, depressive symptoms and engagement in physical activity were associated with a 78 % higher risk.

CONCLUSIONS

Depressive symptoms and lack of physical activity predicted the combined endpoint of all-cause death or rehospitalization among patients with HFrEF, while depressive symptoms alone were the strongest predictor among patients with HFpEF.

Rosa dos Ventos Multicenter Cohort Study of Patients with Reduced or Mildly Reduced Ejection Fraction Heart Failure in Brazil: Rationale and Design

BACKGROUND

Brazil is a country with different biomes and social disparities. There are limited data available on regional differences and prognosis of heart failure (HF) in the country.

OBJECTIVE

The Rosa dos Ventos study aims to investigate regional differences and the current prognosis of HF outpatients with reduced or mildly reduced ejection fraction in Brazil.

METHODS

This is a prospective, multicenter, observational cohort study that will include outpatients older than 18 years with HF and an ejection fraction < 50% in 30 public and private centers distributed in all Brazilian regions. A total of 2,500 patients will be enrolled from June 2021 and October 2023, with a 12-month follow-up period. We will collect data on socioeconomic and clinical status, medical prescription and results of cardiology tests. Follow-up phone calls will be made at 6 and 12 months after inclusion to collect information regarding emergency room visits, hospitalization and mortality.

CONCLUSION

The Rosa dos Ventos study will allow a more accurate characterization of chronic HF in Brazil. This initiative will provide relevant information for the development of effective management strategies to mitigate the impact of this condition on patients and the healthcare system.

American Registry of Ambulatory or acutely decompensated heart failure (AMERICCAASS Registry): First 1000 patients

BACKGROUND

About 80% of cardiovascular diseases (including heart failure [HF]) occur in low-income and developing countries. However, most clinical trials are conducted in developed countries.

HYPOTHESIS

The American Registry of Ambulatory or Acutely Decompensated Heart Failure (AMERICCAASS) aims to describe the sociodemographic characteristics of HF, comorbidities, clinical presentation, and pharmacological management of patients with ambulatory or acutely decompensated HF in America.

METHODOLOGY

Descriptive, observational, prospective, and multicenter registry, which includes patients >18 years with HF in an outpatient or hospital setting. Collected information is stored in the REDCap electronic platform. Quantitative variables are defined according to the normality of the variable using the Shapiro-Wilk test.

RESULTS

This analysis includes data from the first 1000 patients recruited. 63.5% were men, the median age of 66 years (interquartile range 56.7-75.4), and 77.6% of the patients were older than 55 years old. The percentage of use of the four pharmacological pillars at the time of recruitment was 70.7% for beta-blockers (BB), 77.4% for angiotensin-converting enzyme inhibitor (ACEI)/angiotensin II receptor blocker (ARB II)/angiotensin receptor-neprilysin inhibitor (ARNI), 56.8% for mineralocorticoid receptor antagonists (MRA), and 30.7% for sodium-glucose cotransporter type-2 inhibitors (SGLT2i). The main cause of decompensation in hospitalized patients was HF progression (64.4%), and the predominant hemodynamic profile was wet-warm (68.3%).

CONCLUSIONS

AMERICCAASS is the first continental registry to include hospitalized or outpatient patients with HF. Regarding optimal medical therapy, approximately a quarter of the patients still need to receive BB and ACEI/ARB/ARNI, less than half do not receive MRA, and more than two-thirds do not receive SGLT2i.

Predicting mortality and re-hospitalization for heart failure: a machine-learning and cluster analysis on frailty and comorbidity

BACKGROUND

Machine-learning techniques have been recently utilized to predict the probability of unfavorable outcomes among elderly patients suffering from heart failure (HF); yet none has integrated an assessment for frailty and comorbidity. This research seeks to determine which machine-learning-based phenogroups that incorporate frailty and comorbidity are most strongly correlated with death or readmission at hospital for HF within six months following discharge from hospital.

METHODS

In this single-center, prospective study of a tertiary care center, we included all patients aged 65 and older discharged for acute decompensated heart failure. Random forest analysis and a Cox multivariable regression were performed to determine the predictors of the composite endpoint. By k-means and hierarchical clustering, those predictors were utilized to phenomapping the cohort in four different clusters.

RESULTS

A total of 571 patients were included in the study. Cluster analysis identified four different clusters according to frailty, burden of comorbidities and BNP. As compared with Cluster 4, we found an increased 6-month risk of poor outcomes patients in Cluster 1 (very frail and comorbid; HR 3.53 [95% CI 2.30-5.39]), Cluster 2 (pre-frail with low levels of BNP; HR 2.59 [95% CI 1.66-4.07], and in Cluster 3 (pre-frail and comorbid with high levels of BNP; HR 3.75 [95% CI 2.25-6.27])).

CONCLUSIONS

In older patients discharged for ADHF, the cluster analysis identified four distinct phenotypes according to frailty degree, comorbidity, and BNP levels. Further studies are warranted to validate these phenogroups and to guide an appropriate selection of personalized, model of care.

Analysis of respiratory muscle strength and its relationship with functional capacity between different field tests in patients with heart failure

OBJECTIVE

To analyze respiratory muscle strength of patients with heart failure (HF) and correlate with functional capacity.

METHODS

This cross-sectional study involved patients with compensated HF of both sexes, aged above 18 years. Respiratory muscle strength was assessed by measuring maximum inspiratory (MIP) and expiratory pressures (MEP) using a manovacuometer. Patients were randomized into two groups to assess functional capacity: six-minute walk test (6MWT) and incremental shuttle walk test (ISWT).

RESULTS

Forty-eight patients were evaluated (23 from 6MWT and 25 from ISWT group). Most were male (67.8%), with mean age of 62.3 years and left ventricular ejection fraction of 40.8%. Mean predicted values of MIP [81.2% (74.7-87.8%)] and MEP [95.6% (88.2-103.0%)] did not indicate respiratory muscle weakness. The higher the New York Heart Association (NYHA) functional class, the lower the MIP (p = .011) and MEP (p = .016) values. Physically active patients presented higher respiratory muscle strength than those sedentary (MIP: 104.5 vs. 71.9 cmH2O, p < .001; MEP: 120.0 vs. 91.1 cmH2O, p = .004). Functional capacity was impaired [6MWT: 416.0 m (372.8-459.3 m); ISWT: 304 m (263.4-344.9 m)], and distance covered in the ISWT was shorter than 6MWT group (p < .001). Distance covered in the ISWT group presented a moderate positive correlation with MIP (r = 0.45; p = .022) and MEP (r = 0.41; p = .041).

CONCLUSION

Most patients with HF presented respiratory muscle strength close to predicted values; however, sedentary patients and those with high NYHA functional class, showed reduced MIP and MEP. Functional capacity was reduced, and MIP and MEP correlated with distance covered in the ISWT.

Predictive value of blood urea nitrogen in heart failure: a systematic review and meta-analysis

Background

The mortality rate of patients with heart failure (HF) remains high, and when heart failure occurs, blood urea nitrogen (BUN) is involved in the perfusion of renal blood flow. Some studies have shown an association between heart failure prognosis and blood urea nitrogen, but the results of some other studies were inconsistent. Therefore, we conducted a comprehensive meta-analysis to investigate the value of BUN on the prognosis of patients with heart failure.

Methods

A computerized systematic search of all English literature was performed in four databases, PubMed, Cochrane, Embase and Web of Science, from their inception to May 2022. The data of BUN were classified into continuous and categorical variables after passing the inclusion and exclusion criteria. The BUN data of both types were extracted separately into stata15.0 for statistical analysis.

Results

A total of 19 cohort studies involving 56,003 patients were included. When BUN was used as a categorical variable, the risk of death in heart failure was 2.29 times higher for high levels of BUN than for low levels of BUN (RR = 2.29, 95% CI:1.42-3.70, P < 0.001). The results showed statistical significance in multifactorial and univariate groups, the prospective cohort, and European and Asian groups. When BUN was used as a continuous variable, the risk of death in heart failure was 1.02 times higher for each unit increase in BUN (RR = 1.02, 95% CI:1.01-1.03, p < 0.001). Subgroup analysis showed statistical significance in retrospective cohort, American and Asian.

Conclusion

High BUN is an independent predictor of all-cause mortality in heart failure. Lower BUN was associated with better prognosis in patients with heart failure.

Spatial Distribution of Mortality for Heart Failure in Brazil, 1996 - 2017

BACKGROUND

Heart failure (HF) is a leading cause of mortality and morbidity worldwide, and is associated with the high use of resources and healthcare costs. In Brazil, the HF prevalence is around 2 million patients, and its incidence is of approximately 240,000 new cases per year.

OBJECTIVE

The present investigation aimed to analyze the spatiotemporal trend of mortality caused by HF in Brazil, from 1996 to 2017.

METHODS

This is an ecological study developed with secondary data on HF mortality in Brazil. During the period, 1,242,014 cases of death caused by heart failure were analyzed. The existence of spatial autocorrelation of cases was calculated using the Global Moran Index (GMI) and, when significant, the Local Moran Index, considering p<0.05. The relative risk of the clusters was calculated.

RESULTS

The mortality rate due to HF was diversified in all Brazilian regions, with an emphasis in the South, Southeast, and Northeast. The GMI indicated positive spatial autocorrelation (p=0.01) in all periods. Municipalities located in the South, Southeast, Northeast, and Midwest showed a higher Relative Risk for mortality from HF, and most municipalities in the North were classified as a protective factor against this cause of death.

CONCLUSIONS

The study showed a decline in mortality rates across the national territory. The highest concentration of mortality rates is in the North and Northeast regions, highlighting priority vulnerable areas in the planning and controlling strategies of health services.

Content validation of the nursing outcome Knowledge Heart Failure Management: Brazilian nurses' opinions

PURPOSE

To estimate the content validity of the outcome Knowledge: Heart Failure Management (1835) of the Nursing Outcomes Classification (NOC).

METHODS

A methodological study conducted in Brazil with nurses with expertise in cardiovascular nursing and nursing process. The nurse experts evaluated the relevance of the indicators for the nursing outcome on a 5-point Likert scale. A total of 55 indicators were analyzed, including 50 NOC indicators, four indicators located from a scoping review, and one suggested by an expert during the content validation process. The relevance ratio supported the categorization of indicators as critical, supplemental, or unnecessary. Relevance ratios of critical and supplemental indicators were summed and divided by the total number of the indicators to calculate the outcome content validity (OCV) score of the nursing outcome.

FINDINGS

Fifteen nurse experts, mostly females (n = 13) with a mean age of 36.0 ± 6.3 years, 13.9 ± 6.5 years of professional experience, and extensive use of the nursing process in their clinical practice (n = 10), teaching (n = 13), and research (n = 11), participated in this study. Regarding the content validation, 43 (78.2%) out of 55 indicators were categorized as critical (relevance ratio .80-.98), 11 (20%) as supplemental (relevance ratio .67-.79), and one indicator (1.8%) was categorized as unnecessary (relevance ratio .48). The OCV score of the nursing outcome was .87.

CONCLUSION

The study provided evidence of content validity of 49 indicators of the NOC outcome, Knowledge: Heart Failure Management, and five new indicators identified through the validation process based on nurse experts' opinions.

IMPLICATIONS FOR THE NURSING PRACTICE

These findings provide evidence-based indicators for the measurement of heart failure patients' knowledge about disease management. As a result, nurses can test the effectiveness of nursing interventions based on valid outcome indicators.

Combined B-type Natriuretic Peptide as strong predictor of short-term mortality in patients after Liver Transplantation

Background: B-type natriuretic peptide (BNP) is a well-known predictor for prognosis in patients with cardiac and renal diseases. However, there is a lack of studies in patients with advanced hepatic disease, especially patients who underwent liver transplantation (LT). We evaluated whether BNP could predict the prognosis of patients who underwent LT. Material and Methods: The data from a total of 187 patients who underwent LT were collected retrospectively. The serum levels of BNP were acquired at four time points, the pre-anhepatic (T1), anhepatic (T2), and neohepatic phases (T3), and on postoperative day 1 (T4). The patients were dichotomized into survival and non-survival groups for 1-month mortality after LT. Combined BNP (cBNP) was calculated based on conditional logistic regression analysis of pairwise serum BNP measurements at two time points, T2 and T4. The area under the receiver operating characteristic curve (AUROC) was analyzed to determine the diagnostic accuracy and cut-off value of the predictive models, including cBNP. Results: Fourteen patients (7.5 %) expired within one month after LT. The leading cause of death was sepsis (N = 9, 64.3 %). The MELD and MELD-Na scores had an acceptable predictive ability for 1-month mortality (AUROC = 0.714, and 0.690, respectively). The BNPs at each time point (T1 - T4) showed excellent predictive ability (AUROC = 0.864, 0.962, 0.913, and 0.963, respectively). The cBNP value had an outstanding predictive ability for 1-month mortality after LT (AUROC = 0.976). The optimal cutoff values for cBNP at T2 and T4 were 137 and 187, respectively. Conclusions: The cBNP model showed the improved predictive ability for mortality within 1-month of LT. It could help clinicians stratify mortality risk and be a useful biomarker in patients undergoing LT.