Primary prevention of heart failure

The sclerotic component of metabolic syndrome: Fibroblast activities may be the central common denominator driving organ function loss and death

Fibrosis is a common feature of more than 50 different diseases and the cause of more than 35% of deaths worldwide, of which liver, kidney, skin, heart and, recently, lungs are receiving the most attention. Tissue changes, resulting in loss of organ function, are both a cause and consequence of disease and outcome. Fibrosis is caused by an excess deposition of extracellular matrix proteins, which over time results in impaired organ function and organ failure, and the pathways leading to increased fibroblast activation are many. This narrative review investigated the common denominator of fibrosis, fibroblasts, and the activation of fibroblasts, in response to excess energy consumption in liver, kidney, heart, skin and lung fibrosis. Fibroblasts are the main drivers of organ function loss in lung, liver, skin, heart and kidney disease. Fibroblast activation in response to excess energy consumption results in the overproduction of a range of collagens, of which types I, III and VI seem to be the essential drivers of disease progression. Fibroblast activation may be quantified in serum, enabling profiling and selection of patients. Activation of fibroblasts results in the overproduction of collagens, which deteriorates organ function. Patient profiling of fibroblast activities in serum, quantified as collagen production, may identify an organ death trajectory, better enabling identification of the right treatment for use in different metabolic interventions. As metabolically activated patients have highly elevated risk of kidney, liver and heart failure, it is essential to identify which organ to treat first and monitor organ status to correct treatment regimes. In direct alignment with this, it is essential to identify the right patients with the right organ deterioration trajectory for enrolment in clinical studies.

Development of a tool to predict the risk of incident heart failure in a general population: the HUNT for HF risk score

AIMS

Currently, no incident heart failure (HF) risk score that is in regular use in a general population is available. We aimed to develop this and compare with existing HF risk scores.

METHODS AND RESULTS

Participants in the third wave (2006-08) of the population-based Trøndelag Health Study 3 (HUNT3) were included if they reported no previous HF. Any hospital diagnoses captured during follow-up (until the end of 2018) of HF, cardiomyopathy, or hypertensive heart disease were assessed by an experienced cardiologist. Valid HF events were defined as symptoms/signs of HF and objective evidence of structural/functional abnormality of the heart at rest. The model was compared with slightly modified HF risk scores (the Health Aging and Body Composition HF risk score, the Framingham HF risk score, the Pooled Cohort equations to Prevent HF risk score, and NORRISK 2). Among 36 511 participants (mean ± SD age of 57.9 ± 13.3 years, 55.4% female), with a mean follow-up of 10.2 ± 1.3 years, 1366 developed HF (incidence rate of 3.66 per 1000 participant years). Out of the 38 relevant clinical variables assessed, we identified 12 (atrial fibrillation being the strongest) that independently predicted an HF event. The final model demonstrated good discrimination (C statistics = 0.904) and calibration, was stable in internal validation, and performed well compared with existing risk scores. The model identified that, at enrolment, 31 391 (86%), 2386 (7%), 1246 (3%), and 1488 (4%) had low, low-intermediate, high-intermediate, and high 10-year HF risk, respectively.

CONCLUSIONS

Twelve clinical variables independently predicted 10-year HF risk. The model may serve well as the foundation of a practical, online risk score for HF in general practice.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04648852.

Alcohol consumption and the risk of heart failure: the Suita Study and meta-analysis of prospective cohort studies

BACKGROUND

Alcohol consumption is a modifiable lifestyle, but its role in heart failure (HF) development is controversial. Herein, we investigated the prospective association between alcohol consumption and HF risk.

METHODS

A total of 2,712 participants (1,149 men and 1,563 women) from the Suita Study were followed up every two years. Cox regression was applied to calculate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of HF risk for heavy drinking (≥46 g/day in men or ≥23 g/day in women) and never drinking compared to light drinking (<23 g/day in men or <11.5 g/day in women). Then, we combined the results of the Suita Study with those from other eligible prospective cohort studies in a meta-analysis using the random-effects model.

RESULTS

In the Suita Study, within a median follow-up period of 8 years, 319 HF cases (162 in men and 157 in women) were detected. In men, but not women, never and heavy drinking carried a higher risk of HF than light drinking: HRs (95% CIs) = 1.65 (1.00, 2.73) and 2.14 (1.26, 3.66), respectively. Alike, the meta-analysis showed a higher risk of HF among heavy drinkers: HR (95% CI) = 1.37 (1.15, 1.62) and abstainers: HR (95% CI) = 1.18 (1.02, 1.37).

CONCLUSION

We indicated a J-shaped association between alcohol consumption and HF risk among Japanese men. The results of the meta-analysis came in line with the Suita Study. Heavy-drinking men should be targeted for lifestyle modification interventions.

Predicting hospitalisation for heart failure and death in patients with, or at risk of, heart failure before first hospitalisation: a retrospective model development and external validation study

BACKGROUND

Identifying people who are at risk of being admitted to hospital (hospitalised) for heart failure and death, and particularly those who have not previously been hospitalised for heart failure, is a priority. We aimed to develop and externally validate a prognostic model involving contemporary deep phenotyping that can be used to generate individual risk estimates of hospitalisation for heart failure or all-cause mortality in patients with, or at risk of, heart failure, but who have not previously been hospitalised for heart failure.

METHODS

Between June 1, 2016, and May 31, 2018, 3019 consecutive adult patients (aged ≥16 years) undergoing cardiac magnetic resonance (CMR) at Manchester University National Health Service Foundation Trust, Manchester, UK, were prospectively recruited into a model development cohort. Candidate predictor variables were selected according to clinical practice and literature review. Cox proportional hazards modelling was used to develop a prognostic model. The final model was validated in an external cohort of 1242 consecutive adult patients undergoing CMR at the University of Pittsburgh Medical Center Cardiovascular Magnetic Resonance Center, Pittsburgh, PA, USA, between June 1, 2010, and March 25, 2016. Exclusion criteria for both cohorts included previous hospitalisation for heart failure. Our study outcome was a composite of first hospitalisation for heart failure or all-cause mortality after CMR. Model performance was evaluated in both cohorts by discrimination (Harrell's C-index) and calibration (assessed graphically).

FINDINGS

Median follow-up durations were 1118 days (IQR 950-1324) for the development cohort and 2117 days (1685-2446) for the validation cohort. The composite outcome occurred in 225 (7·5%) of 3019 patients in the development cohort and in 219 (17·6%) of 1242 patients in the validation cohort. The final, externally validated, parsimonious, multivariable model comprised the predictors: age, diabetes, chronic obstructive pulmonary disease, N-terminal pro-B-type natriuretic peptide, and the CMR variables, global longitudinal strain, myocardial infarction, and myocardial extracellular volume. The median optimism-adjusted C-index for the externally validated model across 20 imputed model development datasets was 0·805 (95% CI 0·793-0·829) in the development cohort and 0·793 (0·766-0·820) in the external validation cohort. Model calibration was excellent across the full risk profile. A risk calculator that provides an estimated risk of hospitalisation for heart failure or all-cause mortality at 3 years after CMR for individual patients was generated.

INTERPRETATION

We developed and externally validated a risk prediction model that provides accurate, individualised estimates of the risk of hospitalisation for heart failure and all-cause mortality in patients with, or at risk of, heart failure, before first hospitalisation. It could be used to direct intensified therapy and closer follow-up to those at increased risk.

FUNDING

The UK National Institute for Health Research, Guerbet Laboratories, and Roche Diagnostics International.

A population-based study of 92 clinically recognized risk factors for heart failure: co-occurrence, prognosis and preventive potential

AIMS

Primary prevention strategies for heart failure (HF) have had limited success, possibly due to a wide range of underlying risk factors (RFs). Systematic evaluations of the prognostic burden and preventive potential across this wide range of risk factors are lacking. We aimed at estimating evidence, prevalence and co-occurrence for primary prevention and impact on prognosis of RFs for incident HF.

METHODS AND RESULTS

We systematically reviewed trials and observational evidence of primary HF prevention across 92 putative aetiologic RFs for HF identified from US and European clinical practice guidelines. We identified 170 885 individuals aged ≥30 years with incident HF from 1997 to 2017, using linked primary and secondary care UK electronic health records (EHR) and rule-based phenotypes (ICD-10, Read Version 2, OPCS-4 procedure and medication codes) for each of 92 RFs. Only 10/92 factors had high quality observational evidence for association with incident HF; 7 had effective randomized controlled trial (RCT)-based interventions for HF prevention (RCT-HF), and 6 for cardiovascular disease prevention, but not HF (RCT-CVD), and the remainder had no RCT-based preventive interventions (RCT-0). We were able to map 91/92 risk factors to EHR using 5961 terms, and 88/91 factors were represented by at least one patient. In the 5 years prior to HF diagnosis, 44.3% had ≥4 RFs. By RCT evidence, the most common RCT-HF RFs were hypertension (48.5%), stable angina (34.9%), unstable angina (16.8%), myocardial infarction (15.8%), and diabetes (15.1%); RCT-CVD RFs were smoking (46.4%) and obesity (29.9%); and RCT-0 RFs were atrial arrhythmias (17.2%), cancer (16.5%), heavy alcohol intake (14.9%). Mortality at 1 year varied across all 91 factors (lowest: pregnancy-related hormonal disorder 4.2%; highest: phaeochromocytoma 73.7%). Among new HF cases, 28.5% had no RCT-HF RFs and 38.6% had no RCT-CVD RFs. 15.6% had either no RF or only RCT-0 RFs.

CONCLUSION

One in six individuals with HF have no recorded RFs or RFs without trials. We provide a systematic map of primary preventive opportunities across a wide range of RFs for HF, demonstrating a high burden of co-occurrence and the need for trials tackling multiple RFs.

Development and Validation of a Long-Term Incident Heart Failure Risk Model

BACKGROUND

Average lifetime risk for heart failure (HF) is high but differs significantly across and within sex-race groups. No models for estimating long-term risk for HF exist, which would allow for earlier identification and interventions in high-risk subsets. The authors aim to derive 30-year HF risk equations.

METHODS

Adults between the ages of 20 to 59 years and free of cardiovascular disease at baseline from 5 population-based cohorts were included. Among 24 838 participants (55% women, 25% Black based on self-report), follow-up consisted of 599 551 person-years. Sex- and race-specific 30-year HF risk equations were derived and validated accounting for competing risk of non-HF death. HF was based on a clinical diagnosis. Model discrimination and calibration were assessed using 10-fold cross-validation. Finally, the model was applied to varying risk factor patterns for systematic examination.

RESULTS

The rate of incident HF was 4.0 per 1000 person-years. Harrell C statistics were 0.82 (0.80-0.83) and 0.84 (0.82-0.85) in White and Black men and 0.84 (0.82-0.85) and 0.85 (0.83-0.87) in White and Black women, respectively. Hosmer-Lemeshow calibration was acceptable, with χ2 <30 in all subgroups. Risk estimation varied across sex-race groups: for example, in an average 40-year-old nonsmoker with an untreated systolic blood pressure of 140 mm Hg and body mass index of 30 kg/m2, risk was estimated to be 22.8% in a Black man, 13.7% in a White man, 13.0% in a Black woman, and 12.1% in a White woman.

CONCLUSIONS

Sex- and race-specific equations for prediction of long-term risk of HF demonstrated high discrimination and adequate calibration.

Metabolic syndrome and heart failure: mechanism and management

Heart failure (HF) and metabolic syndrome (MetS) are syndromes that affect a large proportion of the world population. MetS is known to be one of the risk factors of HF, and it can also act as comorbidity in HF. This review aims to further discuss the mechanism of MetS in causing HF, the management of MetS in order to prevent HF, and the management of MetS in HF patients. Visceral adiposity is the primary trigger of MetS which is followed by chronic inflammation, insulin resistance, and neurohormonal activation. All the mechanisms causing MetS play also an important role in the progression of HF. The MetS approach can be achieved by managing its components according to the current guidelines and careful management of MetS should be done in patients with HF. MetS is closely related to the progression of HF so that comprehensive management which involves a multidisciplinary team is necessary for managing patients with metabolic syndrome and heart failure.

Implications of the ACC/AHA risk score for prediction of heart failure: the Rotterdam Study

BACKGROUND

Despite the growing burden of heart failure (HF), there have been no recommendations for use of any of the primary prevention models in the existing guidelines. HF was also not included as an outcome in the American College of Cardiology/American Heart Association (ACC/AHA) risk score.

METHODS

Among 2743 men and 3646 women aged ≥ 55 years, free of HF, from the population-based Rotterdam Study cohort, 4 Cox models were fitted using the predictors of the ACC/AHA, ARIC and Health-ABC risk scores. Performance of the models for 10-year HF prediction was evaluated. Afterwards, performance and net reclassification improvement (NRI) for adding NT-proBNP to the ACC/AHA model were assessed.

RESULTS

During a median follow-up of 13 years, 429 men and 489 women developed HF. The ARIC model had the highest performance [c-statistic (95% confidence interval [CI]): 0.80 (0.78; 0.83) and 0.80 (0.78; 0.83) in men and women, respectively]. The c-statistic for the ACC/AHA model was 0.76 (0.74; 0.78) in men and 0.77 (0.75; 0.80) in women. Adding NT-proBNP to the ACC/AHA model increased the c-statistic to 0.80 (0.78 to 0.83) in men and 0.81 (0.79 to 0.84) in women. Sensitivity and specificity of the ACC/AHA model did not drastically change after addition of NT-proBNP. NRI(95%CI) was - 23.8% (- 19.2%; - 28.4%) in men and - 27.6% (- 30.7%; - 24.5%) in women for events and 57.9% (54.8%; 61.0%) in men and 52.8% (50.3%; 55.5%) in women for non-events.

CONCLUSIONS

Acceptable performance of the model based on risk factors included in the ACC/AHA model advocates use of this model for prediction of HF risk in primary prevention setting. Addition of NT-proBNP modestly improved the model performance but did not lead to relevant discrimination improvement in clinical risk reclassification.

Overview of the socio-economic consequences of heart failure

Heart failure (HF) is a frequent cause of morbidity and mortality worldwide. The prevalence of HF increases, and in high-income countries, 1-2% of total healthcare expenditure is spent on HF. This article gives an overview on the impact of HF on health-related quality of life (HRQoL) and the economic burden of HF. Those suffering from HF are associated with a substantial decrease of HRQoL compared to individuals with most other chronic diseases and to individuals without HF. Therapeutic approaches, which decrease risk factors and lead to an improvement of the clinical status of patients, have a positive effect on HRQoL of the patients. Hospitalization rates have been shown to be correlated with disease severity, mortality, and HRQoL. Inpatient treatments of HF patients are cost intensive and the most important component for the economic burden of HF, responsible for at least half of direct cost. Prevention strategies, diagnostic and therapeutic approaches should focus on avoiding need for hospitalizations, and in particular, readmissions. Outpatient care including medication represents the second largest cost component. The cost of HF varies from less than 1,000 USD per patient in low-income countries to between 5,000 and 15,000 EUR in Europe, and between 17,000 and 30,000 USD in the US. There is a lack of study results on indirect costs. All study results on the socio-economic burden of HF clearly underscore the public health relevance of HF, showing a large economic burden for healthcare systems all over the world and a considerable impact on patients' HRQoL. The results on HRQoL are relatively homogeneous, but there are large differences across countries in respect of the economic burden they have to bear. Despite the large number of studies on the socio-economic consequences of HF further research is necessary, especially on indirect cost and for low- and middle-income countries. Future studies would benefit from a greater standardization of methods and presentation of results.

Unravelling heart failure nurses' education: Content comparison of heart failure nurses' education in three European Society of Cardiology states and the Heart Failure Association heart failure curriculum

AIMS

The European Society of Cardiology (ESC) guidelines state that heart failure nurse specialists (heart-failure nurses) with specific competences are essential for a successful heart-failure-management programme. Thus, the Heart Failure Association (HFA) of the ESC developed the heart failure nurse curriculum (HFA curriculum). Several ESC member states developed cardiovascular education programmes to enable nurses to deliver high specialist care, but little is known of whether these curricula are in line with the HFA curriculum. Therefore, this paper describes the extent to which cardiovascular education programmes in Belgium, The Netherlands and Germany correspond to the HFA curriculum.

METHODS AND RESULTS

A case study approach was adopted to obtain an in-depth understanding of the programme contents in relation to the HFA curriculum. For this purpose, representatives of the educational programmes and/or delegates of the national cardiovascular nursing organization shared their educational curricula. All of the studied cardiovascular education programmes aim to provide heart failure and/or cardiovascular nurses with essential competences for implementation of evidence based and guideline derived care. However, every cardiovascular education programme has a different focus/area of attention. Cardiovascular education in Belgium discusses aspects of all core-learning objectives of the HFA curriculum and emphasizes mostly knowledge aspects of these. Learning objectives in cardiovascular education in The Netherlands focus on chronic diseases in general and on learning objectives concerning patient education, support in self-care and management of device and pharmacological therapy. Cardiovascular education in Germany discusses most learning objectives; however, not all learning objectives receive equal attention.

CONCLUSIONS

Although local cardiovascular education programmes adopt certain aspects of the HF curriculum, the curriculum as a whole is not adopted.

10-Year Risk Equations for Incident Heart Failure in the General Population

BACKGROUND

Primary prevention strategies to mitigate the burden of heart failure (HF) are urgently needed. However, no validated risk prediction tools are currently in use.

OBJECTIVES

This study sought to derive 10-year risk equations of developing incident HF.

METHODS

Race- and sex-specific 10-year risk equations for HF were derived and validated from individual-level data from 7 community-based cohorts with at least 12 years of follow-up. Participants who were recruited between 1985 and 2000, between 30 to 79 years, and were free of cardiovascular disease at baseline were included to create a pooled cohort (PC) and were randomly split for derivation and internal validation. Model performance was also assessed in 2 additional cohorts.

RESULTS

In the derivation sample of the PC (n = 11,771), 58% were women, 22% were black with a mean age of 52 ± 12 years, and HF occurred in 1,339 participants. Predictors of HF included in the race-sex-specific models were age, blood pressure (treated or untreated), fasting glucose (treated or untreated), body mass index, cholesterol, smoking status, and QRS duration. The PC equations to Prevent HF model had good discrimination and strong calibration in internal and external validation cohorts. A web-based tool was developed to facilitate clinical application of this tool.

CONCLUSIONS

The authors present a contemporary analysis from 33,010 men and women demonstrating the utility of the sex- and race-specific 10-year PC equations to Prevent HF risk score, which integrates clinical parameters readily available in primary care settings. This tool can be useful in risk-based decision making to determine who may merit intensive screening and/or targeted prevention strategies.

Life's Simple 7 and Incident Heart Failure: The Multi-Ethnic Study of Atherosclerosis

Background

The American Heart Association introduced the Life's Simple 7 (LS7) metrics to assess and promote cardiovascular health. We sought to examine the association between the LS7 metrics and incident heart failure (HF) in a multiethnic cohort.

Methods and Results

We analyzed data from 6506 participants of the Multi‐Ethnic Study of Atherosclerosis free of cardiovascular disease at baseline. The LS7 metrics (smoking, physical activity, body mass index, diet, blood pressure, total cholesterol, and blood glucose) were graded on a scale of 0 to 2, with 2 indicating “ideal” status, 1 “intermediate” status, and 0 “poor” status. Points were summed, thus the LS7 score ranged from 0 to 14. Cox proportional hazard ratios and incidence rates of HF per 1000 person‐years were calculated. During a median follow‐up of 12.2 years, 262 (4%) participants developed HF. Incidence of HF decreased as the number of ideal LS7 metrics increased; 5.9 per 1000 person‐years for participants with 0 to 1 ideal metrics and 0.6 per 1000 person‐years for those with 6 to 7 ideal metrics. Compared with inadequate scores (0–8 points), hazard ratios for HF were 0.57 (0.43–0.76) and 0.31 (0.19–0.49) for average (9–10 points) and optimal (11–14 points) scores, respectively. A similar pattern was observed when the results were stratified by 4 racial/ethnic groups: white, Chinese American, black, and Hispanic.

Conclusions

A lower risk of HF with more favorable LS7 status regardless of race/ethnicity suggests that efforts to achieve ideal cardiovascular health may reduce the burden of HF, a major source of morbidity and mortality.

Risk Prediction Models for Incident Heart Failure: A Systematic Review of Methodology and Model Performance

BACKGROUND

Numerous models predicting the risk of incident heart failure (HF) have been developed; however, evidence of their methodological rigor and reporting remains unclear. This study critically appraises the methods underpinning incident HF risk prediction models.

METHODS AND RESULTS

EMBASE and PubMed were searched for articles published between 1990 and June 2016 that reported at least 1 multivariable model for prediction of HF. Model development information, including study design, variable coding, missing data, and predictor selection, was extracted. Nineteen studies reporting 40 risk prediction models were included. Existing models have acceptable discriminative ability (C-statistics > 0.70), although only 6 models were externally validated. Candidate variable selection was based on statistical significance from a univariate screening in 11 models, whereas it was unclear in 12 models. Continuous predictors were retained in 16 models, whereas it was unclear how continuous variables were handled in 16 models. Missing values were excluded in 19 of 23 models that reported missing data, and the number of events per variable was < 10 in 13 models. Only 2 models presented recommended regression equations. There was significant heterogeneity in discriminative ability of models with respect to age (P < .001) and sample size (P = .007).

CONCLUSIONS

There is an abundance of HF risk prediction models that had sufficient discriminative ability, although few are externally validated. Methods not recommended for the conduct and reporting of risk prediction modeling were frequently used, and resulting algorithms should be applied with caution.

Prediction of 10-year Risk of Incident Heart Failure in Elderly Hypertensive Population: The ANBP2 Study

BACKGROUND

Multivariable risk prediction models consisting of routinely collected measurements can facilitate early detection and slowing of disease progression through pharmacological and nonpharmacological risk factor modifications. This study aims to develop a multivariable risk prediction model for predicting 10-year risk of incident heart failure diagnosis in elderly hypertensive population.

METHODS

The derivation cohort included 6083 participants aged 65 to 84 years at baseline (1995-2001) followed for a median of 10.8 years during and following the Second Australian National Blood Pressure Study (ANBP2). Cox proportional hazards models were used to develop the risk prediction models. Variables were selected using bootstrap resampling method, and Akaike and Bayesian Information Criterion and C-statistics were used to select the parsimonious model. The final model was internally validated using a bootstrapping, and its discrimination and calibration were assessed.

RESULTS

Incident heart failure was diagnosed in 319 (5.2%) participants. The final multivariable model included age, male sex, obesity (body mass index > 30kg/m²), pre-existing cardiovascular disease, average visit-to-visit systolic blood pressure variation, current or past smoking. The model has C-statistics of 0.719 (95% CI: 0.705-0.748) in the derivation cohort, and 0.716 (95% CI: 0.701-0.731) after internal validation (optimism corrected). The goodness-of-fit test showed the model has good overall calibration (χ ² = 1.78, P = 0.94).

CONCLUSION

The risk equation, consisting of variables readily accessible in primary and community care settings, allows reliable prediction of 10-year incident heart failure in elderly hypertensive population. Its application for the prediction of heart failure needs to be studied in the community setting to determine its utility for improving patient management and disease prevention.

The economic impact of patients with heart failure on the Lebanese healthcare system

AIMS

This paper aimed to calculate the annual cost for heart failure (HF) patients in Lebanon.

METHODS AND RESULTS

Heart failure care can reach up to $31 billion annually in the USA. Data in Lebanon are lacking. Estimating it based on USA data is biased; hence, collecting data from all healthcare providers will reflect the actual cost in Lebanon. Data were collected from all healthcare providers on HF hospitalization during the year 2012. In addition, data from 600 outpatient visits were collected by medical students to estimate the cost for outpatient care. The total cost was calculated by adding up all hospitalization cost-plus outpatient-estimated cost. There were 72 000 individuals suffering from HF. The hospitalization care in Lebanon is largely delivered by the public sector (91% public vs 9% private). However, the outpatient care is largely paid cash by patients. The direct cost for HF hospitalizations paid by the public and the private sector was $38 081 535. The average cost for each HF hospitalization was $3769. The direct cost for outpatients care was estimated at $65 592 000. The average cost for outpatient care was $911 per patient per year. The annual total direct cost was calculated at $103 673 535. The true cost was almost one third the extrapolated cost based on US statistics ($103 673 535 vs 268 370 607, respectively).

CONCLUSIONS

The annual total direct cost for HF patients in Lebanon in 2012 was $103 673 535, which is much less than the extrapolated cost based on US statistics.

Clinical prediction of incident heart failure risk: a systematic review and meta-analysis

BACKGROUND

Early treatment may alter progression to overt heart failure (HF) in asymptomatic individuals with stage B HF (SBHF). However, the identification of patients with SBHF is difficult. This systematic review sought to examine the strength of association of clinical factors with incident HF, with the intention of facilitating selection for HF screening.

METHODS

Electronic databases were systematically searched for studies reporting risk factors for incident HF. Effect sizes, typically HRs, of each risk variable were extracted. Pooled crude and adjusted HRs with 95% CIs were computed for each risk variable using a random-effects model weighted by inverse variance.

RESULTS

Twenty-seven clinical factors were identified to be associated with risk of incident HF in 15 observational studies in unselected community populations which followed 456 850 participants over 4-29 years. The strongest independent associations for incident HF were coronary artery disease (HR=2.94; 95% CI 1.36 to 6.33), diabetes mellitus (HR=2.00; 95% CI 1.68 to 2.38), age (HR (per 10 years)=1.80; 95% CI 1.13 to 2.87) followed by hypertension (HR=1.61; 95% CI 1.33 to 1.96), smoking (HR=1.60; 95% CI 1.45 to 1.77), male gender (HR=1.52; 95% CI 1.24 to 1.87) and body mass index (HR (per 5 kg/m(2))=1.15; 95% CI 1.06 to 1.25). Atrial fibrillation (HR=1.88; 95% CI 1.60 to 2.21), left ventricular hypertrophy (HR=2.46; 95% CI 1.71 to 3.53) and valvular heart disease (HR=1.74; 95% CI 1.07 to 2.84) were also strongly associated with incident HF but were not examined in sufficient papers to provide pooled hazard estimates.

CONCLUSIONS

Prediction of incident HF can be calculated from seven common clinical variables. The risk associated with these may guide strategies for the identification of high-risk people who may benefit from further evaluation and intervention.

Plasma fibroblast growth factor 23, parathyroid hormone, 25-hydroxyvitamin D3, and risk of heart failure: a prospective, case-cohort study

CONTEXT

Bone mineral metabolism may play a role in the development of heart failure (HF).

OBJECTIVE

The aim of the study was to investigate the relationships of plasma fibroblast growth factor (FGF) 23, PTH, and 25-hydroxyvitamin D3 [25(OH)D3] with incident congestive HF in a population-based cohort of men and women aged 40-65 and 35-65 years, respectively, at baseline.

DESIGN

We conducted a prospective case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort, including a randomly drawn sample of the total cohort free of HF and all incident HF cases that occurred during a mean follow-up of 8.2 ± 1.6 years.

PARTICIPANTS AND SETTING

A total of 221 incident congestive HF cases and 1228 individuals free of HF were included in the study.

MAIN OUTCOME MEASURES

Incident congestive HF was measured.

RESULTS

In a multivariable model, each doubling of FGF23 [ie, per log (base 2) unit higher FGF23] was associated with a 29% higher HF risk (hazard ratio, 1.29 [95% confidence interval (CI), 1.07-1.56]). After multivariable adjustment, including estimated glomerular filtration rate, PTH was not related to HF risk (hazard ratio per doubling of PTH, 1.21 [95% CI, 0.99-1.48]). However, an interaction was observed between PTH and obesity, suggesting a relationship with HF risk in obese, but not in nonobese individuals. The hazard ratio for HF per doubling of 25(OH)D3 was 1.02 (95% CI, 0.73-1.41).

CONCLUSIONS

Our findings provide epidemiological evidence for a positive relationship between FGF23 and risk of HF. The role of PTH in the development of HF remains unclear, in particular in obese individuals, until further confirmation in other studies. 25(OH)D3 was not related to HF.