liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A comprehensive assessment of the association between anemia, clinical covariates and outcomes in a population-wide heart failure registry
County Hospital Ryhov, Sweden.
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
Karolinska University Hospital, Sweden.
Karolinska Institute, Sweden; Karolinska University Hospital, Sweden.
Show others and affiliations
2016 (English)In: International Journal of Cardiology, ISSN 0167-5273, E-ISSN 1874-1754, Vol. 211, 124-131 p.Article in journal (Refereed) Published
Resource type
Text
Abstract [en]

Background: The aim was to investigate the prevalence of, predictors of, and association with mortality and morbidity of anemia in a large unselected cohort of patients with heart failure (HF) and reduced ejection fraction (HFrEF) and to explore if there were specific subgroups of high risk. Methods: In patients with HFrEF in the Swedish Heart Failure Registry, we assessed hemoglobin levels and associations between baseline characteristics and anemia with logistic regression. Using propensity scores for anemia, we assessed the association between anemia and outcomes with Cox regression, and performed interaction and sub-group analyses. Results: There were 24 511 patients with HFrEF (8303 with anemia). Most important independent predictors of anemia were higher age, male gender and renal dysfunction. One-year survival was 75% with anemia vs. 81% without (p < 0.001). In the matched cohort after propensity score the hazard ratio associated with anemia was for all-cause death 1.34 (1.28-1.40; p < 0.0001), CV mortality 1.28 (1.20-1.36; p < 0.0001), and combined CV mortality or HF hospitalization 1.24 (1.18-1.30; p < 0.0001). In interaction analyses, anemia was associated with greater risk with lower age, male gender, EF 30-39%, and NYHA-class I-II. Conclusion: In HFrEF, anemia is associated with higher age, male gender and renal dysfunction and increased risk of mortality and morbidity. The influence of anemia on mortality was significantly greater in younger patients, in men, and in those with more stable HF. The clinical implication of these findings might be in the future to perform targeted treatment studies. (C) 2016 Elsevier Ireland Ltd. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD , 2016. Vol. 211, 124-131 p.
Keyword [en]
Heart failure; Reduced ejection fraction; Anemia; Outcomes; Observational study
National Category
Mathematics Clinical Medicine
Identifiers
URN: urn:nbn:se:liu:diva-127741DOI: 10.1016/j.ijcard.2016.02.144ISI: 000373918100029PubMedID: 26999301OAI: oai:DiVA.org:liu-127741DiVA: diva2:927528
Note

Funding Agencies|Swedish National Board of Health and Welfare; Swedish Association of Local Authorities and Regions; Swedish Society of Cardiology; Linkoping University; Swedish HF Registry foundation

Available from: 2016-05-12 Created: 2016-05-12 Last updated: 2017-05-15
In thesis
1. How to create and analyze a Heart Failure Registry with emphasis on Anemia and Quality of Life
Open this publication in new window or tab >>How to create and analyze a Heart Failure Registry with emphasis on Anemia and Quality of Life
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background and aims

Heart failure (HF) is a major cause of serious morbidity and death in the population and one of the leading medical causes of hospitalization among people older than 60 years. The aim of this thesis was to describe how to create and how to analyze a Heart Failure Registry with emphasis on Anemia and Quality of Life. (Paper I) We described the creation of the Swedish Heart Failure Registry (SwedeHF) as an instrument, which may help to optimize the handling of HF patients and show how the registry can be used to improve the management of patients with HF. (Paper II) In order to show how to analyze a HF registry we investigated the prevalence of anemia, its predictors, and its association with mortality and morbidity in a large cohort of unselected patients with HFrEF included in the SwedeHF, and to explore if there are subgroups of HF patients identifying high--‐risk patients in need of treatment. (Paper III) In order to show another way of analyzing a HF registry we assessed the prevalence of, associations with, and prognostic impact of anemia in patients with HFmrEF and HFpEF. (Paper IV) Finally we examined the usefulness of EQ--‐ 5D as a measure of patient--‐reported outcomes among HF patients using different analytical models and data from the SwedeHF, and comparing results about HRQoL for patients with HFpEF and HFrEF.

Methods

An observational study based on the SwedeHF database, consisting of about 70 variables, was undertaken to describe how a registry is created and can be used (Paper I). One comorbidity (anemia) was applied to different types of HF patients, HFrEF (EF <40%) (II) and HFmrEF (EF 40--‐49% ) or HFpEF (> 50%) (III) analyzing the data with different statistical methods. The usefulness of EQ--‐5D as measure of patient--‐ reported outcomes was studied and the results about HRQoL were compared for patients with HFpEF and HFrEF (IV).

Results

In the first paper (Paper I) we showed how to create a HF registry and presented some characteristics of the patients included, however not adjusted since this was not the purpose of the study. In the second paper (Paper II) we studied anemia in patients with HFrEF and found that the prevalence of anemia in HFrEF were 34 % and the most important independent predictors were higher age, male gender and renal dysfunction. One--‐year survival was 75 % with anemia vs. 81 % without (p<0,001). In the matched cohort after propensity score the hazard ratio associated with anemia was for all--‐cause death 1.34. Anemia was associated with greater risk with lower age, male gender, EF 30--‐39%, and NYHA--‐class I--‐II. In the third paper (Paper III) we studied anemia in other types of HF patients and found that the prevalence in the overall cohort in patients with EF > 40% was 42 %, in HFmrEF 38 % and in HFpEF (45%). Independent associations with anemia were HFpEF, male sex, higher age, worse New York Heart Association class and renal function, systolic blood pressure <100 mmHg, heart rate ≥70 bpm, diabetes, and absence of atrial fibrillation. One--‐year survival with vs. without anemia was 74% vs. 89% in HFmrEF and 71% vs. 84% in HFpEF (p<0.001 for all). Thus very similar results in paper II and III but in different types of HF patients. In the fourth paper (Paper IV) we studied the usefulness of EQ--‐5D in two groups of patients with HF (HFpEF and HFrEF)) and found that the mean EQ--‐5D index showed small reductions in both groups at follow--‐up. The patients in the HFpEF group reported worsening in all five dimensions, while those in the HFrEF group reported worsening in only three. The Paretian classification showed that 24% of the patients in the HFpEF group and 34% of those in the HFrEF group reported overall improvement while 43% and 39% reported overall worsening. Multiple logistic regressions showed that treatment in a cardiology clinic affected outcome in the HFrEF group but not in the HFpEF group (Paper IV).

Conclusions

The SwedeHF is a valuable tool for improving the management of patients with HF, since it enables participating centers to focus on their own potential for improving diagnoses and medical treatment, through the online reports (Paper I). Anemia is associated with higher age, male gender and renal dysfunction and increased risk of mortality and morbidity (II, III). The influence of anemia on mortality was significantly greater in younger patients in men and in those with more stable HF (Paper II, III). The usefulness of EQ--‐5D is dependent on the analytical method used. While the index showed minor differences between groups, analyses of specific dimensions showed different patterns of change in the two groups of patients (HFpEF and HFrEF). The Paretian classification identified subgroups that improved or worsened, and can therefore help to identify needs for improvement in health services (Paper IV).

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. 75 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1570
Keyword
Heart failure, reduced ejection fraction, mid-­‐range ejection fraction, preserved ejection fraction, anemia, Health-­‐related quality of life, observational study, outcomes
National Category
Cardiac and Cardiovascular Systems Surgery Gastroenterology and Hepatology Rheumatology and Autoimmunity Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:liu:diva-137351 (URN)10.3384/diss.diva-137351 (DOI)9789176855522 (ISBN)
Public defence
2017-06-01, Belladonna, Campus US, Linköping, 13:00 (Swedish)
Opponent
Supervisors
Available from: 2017-05-15 Created: 2017-05-15 Last updated: 2017-05-15Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Hallberg, Ann-CharlotteDahlström, Ulf
By organisation
StatisticsFaculty of Arts and SciencesDivision of Cardiovascular MedicineFaculty of Medicine and Health SciencesDepartment of Cardiology in Linköping
In the same journal
International Journal of Cardiology
MathematicsClinical Medicine

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 78 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf