Dataset Information

Comorbidity health pathways in heart failure patients: A sequences-of-regressions analysis using cross-sectional data from 10,575 patients in the Swedish Heart Failure Registry.

ABSTRACT:

Background

Optimally treated heart failure (HF) patients often have persisting symptoms and poor health-related quality of life. Comorbidities are common, but little is known about their impact on these factors, and guideline-driven HF care remains focused on cardiovascular status. The following hypotheses were tested: (i) comorbidities are associated with more severe symptoms and functional limitations and subsequently worse patient-rated health in HF, and (ii) these patterns of association differ among selected comorbidities.

Methods and findings

The Swedish Heart Failure Registry (SHFR) is a national population-based register of HF patients admitted to >85% of hospitals in Sweden or attending outpatient clinics. This study included 10,575 HF patients with patient-rated health recorded during first registration in the SHFR (1 February 2008 to 1 November 2013). An a priori health model and sequences-of-regressions analysis were used to test associations among comorbidities and patient-reported symptoms, functional limitations, and patient-rated health. Patient-rated health measures included the EuroQol-5 dimension (EQ-5D) questionnaire and the EuroQol visual analogue scale (EQ-VAS). EQ-VAS score ranges from 0 (worst health) to 100 (best health). Patient-rated health declined progressively from patients with no comorbidities (mean EQ-VAS score, 66) to patients with cardiovascular comorbidities (mean EQ-VAS score, 62) to patients with non-cardiovascular comorbidities (mean EQ-VAS score, 59). The relationships among cardiovascular comorbidities and patient-rated health were explained by their associations with anxiety or depression (atrial fibrillation, odds ratio [OR] 1.16, 95% CI 1.06 to 1.27; ischemic heart disease [IHD], OR 1.20, 95% CI 1.09 to 1.32) and with pain (IHD, OR 1.25, 95% CI 1.14 to 1.38). Associations of non-cardiovascular comorbidities with patient-rated health were explained by their associations with shortness of breath (diabetes, OR 1.17, 95% CI 1.03 to 1.32; chronic kidney disease [CKD, OR 1.23, 95% CI 1.10 to 1.38; chronic obstructive pulmonary disease [COPD], OR 95% CI 1.84, 1.62 to 2.10) and with fatigue (diabetes, OR 1.27, 95% CI 1.13 to 1.42; CKD, OR 1.24, 95% CI 1.12 to 1.38; COPD, OR 1.69, 95% CI 1.50 to 1.91). There were direct associations between all symptoms and patient-rated health, and indirect associations via functional limitations. Anxiety or depression had the strongest association with functional limitations (OR 10.03, 95% CI 5.16 to 19.50) and patient-rated health (mean difference in EQ-VAS score, -18.68, 95% CI -23.22 to -14.14). HF optimizing therapies did not influence these associations. Key limitations of the study include the cross-sectional design and unclear generalisability to other populations. Further prospective HF studies are required to test the consistency of the relationships and their implications for health.

Conclusions

Identification of distinct comorbidity health pathways in HF could provide the evidence for individualised person-centred care that targets specific comorbidities and associated symptoms.

SUBMITTER: Lawson CA

PROVIDER: S-EPMC5870940 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceAccurate prediction of risk of death or hospitalizations in patients with heart failure (HF) may allow physicians to explore how more accurate decisions regarding appropriateness and timing of disease-modifying treatments, advanced therapies, or the need for end-of-life care can be made.ObjectiveTo develop and validate a prognostic model for patients with HF.Design, setting, and participantsMultivariable analyses were performed in a stepwise fashion. Harrell C statistic was used to assess the discriminative ability. The derivation cohort was Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure trial (PARADIGM-HF) participants. The models were validated using the Aliskiren Trial to Minimize Outcomes in Patients with Heart Failure Trial (ATMOSPHERE) study and in the Swedish Heart Failure Registry (SwedeHF). A total of 8399 participants enrolled in PARADIGM-HF. Data were analyzed between June 2016 and June 2018.Main outcomes and measuresCardiovascular death, all-cause mortality, and the composite of cardiovascular death or HF hospitalization at both 1 and 2 years.ResultsComplete baseline clinical data were available for 8011 patients in PARADIGM-HF. The mean (SD) age of participants was 64 (11.4) years, 78.2% were men (n = 6567 of 8399), and 70.6% were New York Heart Association class II (n = 5919 of 8399). During a mean follow-up of 27 months, 1546 patients died, and 2031 had a cardiovascular death or HF hospitalization. The common variables were: male sex, race/ethnicity (black or Asian), region (Central Europe or Latin America), HF duration of more than 5 years, New York Heart Association class III/ IV, left ventricular ejection fraction, diabetes mellitus, β-blocker use at baseline, and allocation to sacubitril/valsartan. Ranked by χ2, N-terminal pro brain natriuretic peptide was the single most powerful independent predictor of each outcome. The C statistic at 1 and 2 years was 0.74 (95% CI, 0.71-0.76) and 0.71 (95% CI, 0.70-0.73) for the primary composite end point, 0.73 (95% CI, 0.71-0.75) and 0.71 (95% CI, 0.69-0.73) for cardiovascular death, and 0.71 (95% CI, 0.69-0.74) and 0.70 (95% CI, 0.67-0.74) for all-cause death, respectively. When validated in ATMOSPHERE, the C statistic at 1 and 2 years was 0.71 (95% CI, 0.69-0.72) and 0.70 (95% CI, 0.68-0.71) for the primary composite end point, 0.71 (95% CI, 0.69-0.74) and 0.70 (95% CI, 0.69-0.72) for cardiovascular death, and 0.71 (95% CI, 0.69-0.74) and 0.70 (95% CI, 0.68-0.72) for all-cause death, respectively. An online calculator was created to allow calculation of an individual's risk (http://www.predict-hf.com).Conclusions and relevancePredictive models performed well and were developed and externally validated in large cohorts of geographically representative patients, comprehensively characterized with clinical and laboratory data including natriuretic peptides, who were receiving contemporary evidence-based treatment.