Keywords
acute heart failure, prognosis, anemia
acute heart failure, prognosis, anemia
Statistical analysis was reconsidered and more emphasis was placed on correlations with renal function. The main message of the article remained the same.
To read any peer review reports and author responses for this article, follow the "read" links in the Open Peer Review table.
Anemia is relatively frequent in patients with heart failure (HF). In a population of patients with newly diagnosed HF the prevalence of anemia was 17%1. The presence of anemia is related to the severity of functional class (from 9% in NYHA class I to 79% in class IV)2. In acute heart failure (AHF) anemia, regardless of its etiology, could be an important extracardiac factor of decompensation; its diagnosis, evaluation and treatment being an important part of management. Also, the presence of anemia proved to be an important prognostic factor during the in-hospital and post-discharge period3.
The aim of this study was to assess a cohort of patients hospitalized with AHF for (1) the prevalence of anemia and (2) the existence of correlations parameters reflecting the severity of heart failure and the grade of anemia, with special accent on decreased renal function.
We collected data from 50 consecutive patients (34 men, 16 women, mean age 67.5 years) hospitalized with AHF (acute decompensated heart failure in 36 cases). At admission, all the patients signed the general consent form used at our institution, agreeing with anonymous data collection and usage for scientific purposes. Approval of the hospital ethical committee (permit number: 3865/01.03.2016) was obtained for data processing and publication. Exclusion criteria were: recent (<1 month) acute coronary syndrome, and advanced renal disease on hemodialysis. At admission and during hospital stay routine (part of usual care) clinical and paraclinical data were recorded in a dedicated database: demographic data, clinical diagnosis, triggering factors of decompensation, signs and symptoms at admission, ECG data, echocardiographic data, laboratory parameters at admission, and in-hospital treatment data. Anemia was defined as Hb<12 g/dL for women and Hb <13 g/dL for men. eGFR was estimated by the CKD-EPI equation.
Statistical analysis was performed with STATISTICA 5.0, using Fisher’s exact test for the comparison of discrete data, the Mann-Whitney U test for continuous parameters and the Spearman rank correlation for comparison analysis and multiple linear regression, to determine parameters influencing eGFR (α=0.05).
21 patients (14 men, 7 women, mean age 69.6 years), representing 42% of the cohort, had anemia at admission. The most common form was renal anemia (10 patients), while 8 patients suffered of iron deficiency anemia. We did not find significant differences between the two groups of patients, with and without anemia, with regards to gender (p=1) and age (p=0.57). Also, there were no significant differences regarding the presence of atrial fibrillation (p=0.75), diabetes (p=1), ischemic heart disease (p=1), hypotension (systolic blood pressure <90 mmHg) at admission (p=0.34), tachycardia>100 b/min at admission (p=0.75), severe aortic stenosis (0.12), pulmonary hypertension (0.13), the level of eGFR (p=0.33), left ventricular ejection fraction (EF) (p=0.95) and need of high dose (>80 mg/day) loop diuretic (p=0.23) (Table 1.).
We observed a significant positive correlation between eGFR and the ejection fraction (r=0,65, p=0,001) in patients with anemia, but not in those with normal hemoglobin levels (r=-0,13, p=0,48). In a multiple regression model, determining the eGFR quartiles, we found a significant effect of EF on eGFR (p=0,004).
There is general agreement that anemia is a good predictor of prognosis in patients with acute and chronic HF. Anemia is associated with increased mortality, however there are conflicted data whether this is an independent predictor or reflects the progression of HF and/or is related to the presence of more frequent comorbidities1,4,5. In the setting of AHF, anemia could also serve as a precipitating factor of decompensation.
In our cohort of patients the presence of anemia was not correlated with other factors related to AHF severity and prognosis. This fact suggests its independent role in influencing the clinical picture and prognosis. On the other hand, almost half of anemia patients suffered of chronic kidney disease, and this subgroup showed a significant association of low EF with low eGFR. Moreover, ejection fraction proved to have a significant effect on estimated glomerular filtration rate in a multiple regression model, suggesting that low EF in heart failure might cause the decrease of GFR, aggravating the chronic kidney disease and, consequently contributing to the development of renal anemia.
F1000Research: Dataset 1. Patient data, 10.5256/f1000research.7872.d1229026
Written informed consent for publication of their clinical details was obtained from the patients.
AF and ZF: study design, data collection, data processing and statistical analysis, manuscript preparation; IK: study design, data collection; LM: data processing and statistical analysis; EN: data processing and statistical analysis, manuscript preparation.
Views | Downloads | |
---|---|---|
F1000Research | - | - |
PubMed Central
Data from PMC are received and updated monthly.
|
- | - |
Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: cardiovascular pharmacology, cardiac electrophysiology
Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
Competing Interests: No competing interests were disclosed.
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | |||
---|---|---|---|
1 | 2 | 3 | |
Version 2 (revision) 18 Aug 17 |
read | read | read |
Version 1 26 May 16 |
read | read | read |
Click here to access the data.
Spreadsheet data files may not format correctly if your computer is using different default delimiters (symbols used to separate values into separate cells) - a spreadsheet created in one region is sometimes misinterpreted by computers in other regions. You can change the regional settings on your computer so that the spreadsheet can be interpreted correctly.
Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
Sign up for content alerts and receive a weekly or monthly email with all newly published articles
Already registered? Sign in
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
Comments on this article Comments (0)