The epidemiology of heart failure in the general Australian community - study of heart failure in the Australian primary carE setting (SHAPE): methods

Development and validation of the self-volume management behaviour questionnaire for patients with chronic heart failure

AIMS

We aim to develop and validate a questionnaire on the behaviour of self-volume management of patients with chronic heart failure.

METHODS AND RESULTS

Based on the specific situation theory of heart failure self-care, the items of this questionnaire were formed through literature review and expert consultation. Content validity is judged by expert consultation. Item analysis was used for further filter entries. Cronbach's alpha and retest were used for reliability. Exploratory factor analysis and confirmatory factor analysis were used to test the structural validity. The questionnaire finally contained 3 subscales and 22 items. The Cronbach's α was between 0.732 and 0.797. The reliability of the retest was between 0.983 and 0.998. In expert consultation, the I-CVI of each item was 0.92-1, and the S-CVI of each subscale was 0.99, 1.00, and 0.99. In exploratory factor analysis, each subscale has two factors. In confirmatory factor analysis, the model fits of the three subscales were good: χ2/df < 3, RMSEA < 0.08, CFI > 0.9, TLI > 0.9, and SRMR < 0.05.

CONCLUSIONS

The study has shown that the questionnaire on the behaviour of self-volume management of patients with chronic heart failure has good reliability and validity. It can be used as an evaluation tool for evaluating the self-volume management behaviour of patients with chronic heart failure.

A Proposal of a Cost-Effectiveness Modeling Approach for Heart Failure Treatment Assessment: Considering the Short- and Long-Term Impact of Hospitalization on Event Rates

BACKGROUND

The rate of events such as recurrent heart failure (HF) hospitalization and death are known to dramatically increase directly after HF hospitalization. Furthermore, the number of HF hospitalizations is associated with irreversible long-term disease progression, which is in turn associated with increased event rates. However, cost-effectiveness models of HF treatments commonly fail to capture both the short- and long-term association between HF hospitalization and events.

OBJECTIVE

The aim of this study was to provide a decision-analytic model that reflects the short- and long-term association between HF hospitalization and event rates. Furthermore, we assess the impact of omitting these associations.

METHODS

We developed a life-time Markov cohort model to evaluate HF treatments, and modeled the short-term impact of HF hospitalization on event rates via a sequence of tunnel states, with transition probabilities following a parametric survival curve. The corresponding long-term impact was modeled via hazard ratios per HF hospitalization. We obtained baseline event rates and utilities from published literature. Subsequently, we assessed, for a hypothetical HF treatment, how omitting the modeled associations (through a simple two-state model) affects incremental quality-adjusted life-years (QALYs).

RESULTS

We developed a model that incorporates both short- and long-term impacts of HF hospitalizations. Based on an assumed treatment effect of a 20% risk reduction for HF hospitalization (and associated reductions in all-cause mortality of 15%), omitting the short-term, the long-term, or both associations resulted in a 5%, 1%, and 22% decrease in QALYs gained, respectively.

CONCLUSION

For both modeling components, i.e., the short- and long-term implications of HF hospitalization, the impact on incremental outcomes associated with treatment was substantial. Considering these aspects as proposed within this modeling approach better reflects the natural course of this progressive condition and will enhance the evaluation of future HF treatments.

The association between urinary sodium concentration (UNa) and outcomes of acute heart failure: a systematic review and meta-analysis

AIMS

Urinary sodium concentration (UNa) is a simple test advocated to assess diuretics efficacy and predict outcomes in acute heart failure (AHF). We performed a systematic review and meta-analysis to examine the association of UNa with outcomes of AHF.

METHODS AND RESULTS

We searched Embase and Medline for eligible studies that reported the association between UNa and outcomes of urinary output, weight loss, worsening renal function, length of hospital stay, re-hospitalization, worsening heart failure, and all-cause mortality in AHF. Nineteen observational studies out of 1592 screened records were included. For meta-analyses of outcomes, we grouped patients into high vs. low UNa, with most studies defining high UNa as &gt;48-65 mmol/L. In the high UNa group, pooled data showed a higher urinary output (mean difference 502 mL, 95% CI 323-681, P &lt; 0.01), greater weight loss (mean difference 1.6 kg, 95% CI 0.3-2.9, P = 0.01), and a shorter length of stay (mean difference -1.4 days, 95% CI -2.8 to -0.1, P = 0.03). There was no significant difference in worsening kidney function (OR 0.54, 95% CI 0.25-1.16, P = 0.1). Due to the small number of studies, we did not report pooled estimates for re-hospitalization and worsening heart failure. High UNa was associated with lower odds of 30-day (OR 0.27; 95% CI 0.14-0.49, P &lt; 0.01), 90-day (OR 0.39,95% CI 0.25-0.59, P &lt; 0.01) and 12-month (OR 0.35; 95% CI 0.20-0.61, P &lt; 0.01) mortality.

CONCLUSION

High UNa after diuretic administration is associated with higher urinary output, greater weight loss, shorter length of stay, and lower odds of death. UNa is a promising marker of diuretic efficacy in AHF which should be confirmed in randomized trials.

Clinical characteristics of people with heart failure in Australian general practice: results from a retrospective cohort study

Aims

Heart failure (HF) causes significant morbidity and mortality, but the rates and characteristics of people with HF in Australia are not well studied. SHAPE set out to describe the characteristics of HF patients seen in the real‐world setting.

Methods

We analysed anonymized patient data extracted from the clinical software of 43 participating GP clinics for the 5 year period from 1 July 2013 to 30 June 2018. Patients were stratified into ‘definite’ and ‘probable’ HF based on a hierarchy of selection criteria and analysed for their clinical characteristics. Symptoms and signs of HF and ejection fraction data were searched for within the free text of the medical notes.

Results

Of the 1.12 million adults seen regularly, 20 219 were classified as having definite or probable HF. The mean age of the population was 69.8 years, 50.6% were female, and mean body mass index was 31.2 kg/m². Fewer than 1 in 6 had the HF diagnosis optimally recorded. Only 3.2% (650 patients) had their left ventricular ejection fraction (EF) quantified: 40.9% had an EF ≥50% and 59.1% had an EF <50%. The most common comorbidities in people with HF were hypertension (41.1%), chronic obstructive pulmonary disease/asthma (25.1%) and depression/anxiety (18.4%). Hypotension (2.3%), bradycardia (6.3%), severe renal impairment (6.4%) and hyperkalaemia (2.0%) were uncommon. Just over one‐third (37.8%) had iron deficiency. Loop diuretic use was common (56.7%) but only 33.7% were on a guideline recommended beta‐blockers. Use of ivabradine (1.4%) and sacubitril/valsartan (1.2%) was very low, while 39.9% had been prescribed an angiotensin‐converting enzyme inhibitor, 31.6% an angiotensin receptor blocker and 16.0% spironolactone. Many patients were prescribed medications that may worsen HF or are relatively contraindicated, such as macrolide antibiotics (29.9%), corticosteroids (25.8%), nonsteroidal anti‐inflammatory drugs (23.9%), and tricyclic antidepressants (9.4%).

Conclusions

Heart failure is poorly documented in general practice records and may be contributing to untoward downstream effects, such as low documentation of echocardiography, poor use of guideline recommended therapies and frequent use of medications that may worsen HF.

Epidemiology of heart failure: Study of Heart failure in the Australian Primary carE setting (SHAPE)

Aims

At present, there is no robust information on the prevalence and incidence of heart failure (HF) in the general Australian community. The present study of primary care data sought to estimate the prevalence and incidence of HF in the community and to describe the demographic and clinical profile of Australians with HF.

Methods and results

We undertook a retrospective cohort study based on analysis of anonymized medical records of adult patients cared for at 43 Australian general practices between 1 July 2013 and 30 June 2018. Data were extracted from coded and uncoded fields in electronic medical records. The prevalence and annual incidence of HF were calculated, along with 95% confidence intervals, using the ‘active’ population of people who were regular attenders at the practices. Age‐standardized estimates were also derived using the 2017 Australian population as reference. The mean age of the population with HF was 69.8 years, 50.6% were female, and mean body mass index was 31.2 kg/m². The age‐standardized prevalence was 2.199% [95% confidence interval (CI): 2.168–2.23%], and the age‐standardized annual incidence was 0.348% (95% CI: 0.342–0.354%). These estimates accord with almost 420 000 people living with HF in Australia in 2017, and >66 000 new cases of HF occurring that year. Only 18.9% of patients with definite HF had this formally captured as a ‘diagnosis’ in their medical record. HF was more frequent among those of lower socio‐economic status.

Conclusions

HF is common in Australia. The majority of HF patients do not have this diagnosis optimally noted in their primary care medical records.