AIMS:Metabolic dysregulation accompanies heart failure (HF), yet coordinated biochemical shifts are rarely quantified for prognostication. We investigated whether early metabolic profiles predict morbidity and mortality in HF with preserved (HFpEF) or reduced ejection fraction (HFrEF). METHODS AND RESULTS:In the PEOPLE and SHOP cohorts (n = 1520), 288 plasma metabolites were quantified by tandem mass spectrometry. Weighted co-expression network analysis produced metabolic indices that were regressed against all-cause mortality and composite outcomes (death or readmission) using multivariable proportional hazards and win-ratio models. In HFpEF, metabolic indices of nitric oxide signalling and glycaemic control (netNO-pEF) and purine metabolism (netPurine-pEF) predicted outcomes. In HFrEF, indices of acylcarnitine (netACa-rEF) and amino acids (netAA-rEF) predicted outcomes. Every 20% higher netNO-pEF was associated with adjusted hazard ratios (HR20%higher) of 0.64 [95% CI 0.49-0.84] in PEOPLE-HFpEF and 0.40 [0.20-0.83] in SHOP-HFpEF; HR20%higher for netPurine-pEF were 1.71 [1.30-2.24] in PEOPLE-HFpEF and 1.96 [1.08-3.55] in SHOP-HFpEF; HR20%higher for netACa-rEF were 1.48 [1.23-1.79] in PEOPLE-HFrEF and 1.39 [1.15-1.68] in SHOP-HFrEF; HR20%higher for netAA-rEF were 0.75 [0.62-0.91] in PEOPLE-HFrEF and 0.51 [0.39-0.67] in SHOP-HFrEF. Adjusted inverse win-ratios were concordant: 1/WR20%higher for netACa-rEF were 1.40 [1.19-1.64] in PEOPLE-HFrEF and 1.17 [1.02-1.34] in SHOP-HFrEF; 1/WR20%higher for netNO-pEF were 0.74 [0.54-1.00] in PEOPLE-HFrEF and 0.55 [0.33-0.89] in SHOP-HFrEF. netNO-pEF was negatively associated with body surface area among HFpEF with concomitant hypertension and diabetes, but only in SHOP-HFpEF. Adding orotic acid, a constituent metabolite of netNO-pEF, to a base model containing five risk indices (MAGGIC score, NT-proBNP, hsTnT, GDF15, and E/e' ratio) incrementally improved 2-year mortality prediction (AUROC: 0.82→0.83 in PEOPLE; 0.74→0.79 in SHOP). CONCLUSION:Differential metabolic signatures tied to metabolic inflammation in HFpEF and impaired energy metabolism in HFrEF enhance risk stratification and point to therapeutic targets.

Heart failure is a major healthcare problem in New Zealand. The Acute Decompensated Heart Failure (ADHF) Registry was introduced in 2015, and has identified the need for quality improvement strategies to improve care of patients hospitalised with heart failure. In this paper, we describe the implementation of the revised ANZACS-QI Heart Failure Registry, which has a primary aim to support evidence-based management of and quality improvement measures for patients who are hospitalised with heart failure in New Zealand. Taking the learnings from the initial experience with the ADHF Registry, the revised ANZACS-QI Heart Failure Registry i) utilises age-stratified sampling of hospital discharge coding to identify a representative heart failure cohort, ii) utilises existing ANZACS-QI infrastructure for data-linkage to reduce the burden of manual data entry, iii) receives governance from the Heart Failure Working Group, and iv) focusses on established quality improvement indicators for heart failure management.

INTRODUCTION:In all countries people experience different social circumstances that result in avoidable differences in health. In New Zealand, Māori, Pacific peoples, and those with lower socioeconomic status experience higher levels of chronic illness, which is the leading cause of mortality, morbidity and inequitable health outcomes. Whilst the health system can enable a fairer distribution of good health, limited national data is available to measure health equity. Therefore, we sought to find out whether health services in New Zealand were equitable by measuring the level of development of components of chronic care management systems across district health boards. Variation in provision by geography, condition or ethnicity can be interpreted as inequitable.METHODS:A national survey of district health boards (DHBs) was undertaken on macro approaches to chronic condition management with detail on cardiovascular disease, chronic obstructive pulmonary disease, congestive heart failure, stroke and diabetes. Additional data from expert informant interviews on program reach and the cultural needs of Māori and Pacific peoples was sought. Survey data were analyzed on dimensions of health equity relevant to strategic planning and program delivery. Results are presented as descriptive statistics and free text. Interviews were transcribed and NVivo 8 software supported a general inductive approach to identify common themes.RESULTS:Survey responses were received from the majority of DHBs (15/21), some PHOs (21/84) and 31 expert informants. Measuring, monitoring and targeting equity is not systematically undertaken. The Health Equity Assessment Tool is used in strategic planning but not in decisions about implementing or monitoring disease programs. Variable implementation of evidence-based practices in disease management and multiple funding streams made program implementation difficult. Equity for Māori is embedded in policy, this is not so for other ethnic groups or by geography. Populations that conventional practitioners find hard to reach, despite recognized needs, are often underserved. Nurses and community health workers carried a disproportionate burden of care. Cultural and diversity training is not a condition of employment.CONCLUSIONS:There is a struggle to put equity principles into practice, indicating will without enactment. Equity is not addressed systematically below strategic levels and equity does not shape funding decisions, program development, implementation and monitoring. Equity is not incentivized although examples of exceptional practice, driven by individuals, are evident across New Zealand.