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.
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.
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DOI:
10.1371/journal.pmed.1002540
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发表时间:
2018-03
期刊:
影响因子:
15.8
通讯作者:
Stromberg A
中科院分区:
文献类型:
--
作者:
Lawson CA;Solis-Trapala I;Dahlstrom U;Mamas M;Jaarsma T;Kadam UT;Stromberg A
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. 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. Identification of distinct comorbidity health pathways in HF could provide the evidence for individualised person-centred care that targets specific comorbidities and associated symptoms. Using cross-sectional data from the Swedish Heart Failure Registry, Claire Lawson and colleagues examine the comorbidity patient-rated health pathways in heart failure patients Heart failure is an increasingly common condition, and patients often experience persistent symptoms and poor quality of life, even when they are receiving the best possible treatment for their heart failure. Most heart failure patients have other conditions that dominate their health experience, yet heart failure treatment focuses on their cardiovascular status. There is a lack of understanding about the relationships among different comorbidities and quality of life in heart failure, which are important to guide individualised treatment plans for patients. We used an established health-related quality of life model to develop and test a new heart failure health model that included the most common heart failure comorbidities. We tested this model by examining the postulated relationships among comorbidities, symptoms and functional limitations reported by patients, and their overall health experience, using a national register of heart failure patients in Sweden. We found that non-cardiovascular comorbidities were associated with much higher overall symptom burden and more severe symptoms than cardiovascular comorbidities. Predominant symptoms for cardiovascular comorbidities were pain and anxiety, whereas for non-cardiovascular comorbidities they were shortness of breath and fatigue. Heart failure optimising therapies did not influence these symptoms, functional limitations, or quality of life. Current guidelines in heart failure focus on improving cardiovascular status in response to common heart failure symptoms (shortness of breath, fatigue, and leg swelling). Our study shows that for some patients, these symptoms might be driven by non-cardiovascular conditions such as diabetes and renal disease, rather than their cardiovascular status. We found that cardiovascular comorbidities were more likely to be associated with pain and anxiety than shortness of breath or fatigue. To improve health-related quality of life, heart failure guideline-driven care needs to include optimal management of the most prevalent non-cardiovascular comorbidities and routine management of pain and anxiety or depression. To provide individualised patient care, guidelines need to better align symptoms with the cardiovascular and non-cardiovascular status of the patient.
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影响因子:
37.8
作者:
Shah SJ;Kitzman DW;Borlaug BA;van Heerebeek L;Zile MR;Kass DA;Paulus WJ
通讯作者:
Paulus WJ
影响因子:
3.5
作者:
Rushton, C. A.;Kadam, U. T.
通讯作者:
Kadam, U. T.
影响因子:
18.2
作者:
Jaarsma, Tiny;Beattie, James M.;McMurray, John
通讯作者:
McMurray, John
影响因子:
5.9
作者:
Comin-Colet, Josep;Anguita, Manuel;Enjuanes, Cristina
通讯作者:
Enjuanes, Cristina
DOI:
10.1007/s11936-013-0249-2
发表时间:
2013-08-01
影响因子:
--
作者:
Lewis, Eldrin F
通讯作者:
Lewis, Eldrin F