Elsevier

International Journal of Cardiology

Volume 181, 15 February 2015, Pages 81-87
International Journal of Cardiology

Short- and long-term mortality and hospital readmissions among patients with new hospitalization for heart failure: A population-based investigation from Italy

https://doi.org/10.1016/j.ijcard.2014.12.004Get rights and content

Abstract

Objective

Predictors of mortality and readmission among patients hospitalized for the first time for heart failure (HF) were investigated for a large, unselected population.

Methods

The cohort of 13,171 patients in the Lombardy Region (Italy), all of whom were aged 50 years or older and survived their first hospitalization for HF during 2011, were followed after discharge. Mortality and readmission within 30 days and one year of index discharge were investigated. Kaplan–Meier estimator and Cox model were respectively used to estimate the cumulative proportions of patients experiencing the outcomes and the hazard ratio (HR) for the association between selected covariates and time of outcome onset.

Results

Within 30 days of index discharge, 4.7% and 4.3% of the cohort members died or were readmitted for HF, respectively, while 22.6% and 57.2% of them died or were readmitted for any cause within one year of index discharge. Older age was an independent predictor of mortality at both 30 days and one year. One-year mortality was affected by the use of diuretics, mineralocorticoid receptor antagonists and antigout preparations and by previous hospitalization for respiratory and cerebrovascular diseases. Younger age, use of antidiabetics, diuretics, other antihypertensives, NSAIDs and antigout preparations and previous hospitalization for renal, respiratory, coronary heart and cerebrovascular disease, were independent predictors of hospital readmission.

Conclusion

Short- and long-term mortality and readmissions after first hospitalization for HF are high and heterogeneous across different patient subgroups. Characterization of hospitalized HF is very important in assisting clinicians in decision-making and targeting treatment of high-risk patients.

Introduction

Heart failure (HF) is a clinical condition associated with adverse prognosis. Population-based studies have reported one-year mortality rates of between 35% and 40% [1], [2], [3], [4], [5], [6], [7], while hospital readmissions within 6 months and one-year of discharge regarded more than 50% of survivors of admission for HF [7], [8], [9], [10]. Although many strategies can be used to improve quality of care [11], we have little knowledge regarding predictors of mortality and hospital readmissions in the real-world population since available information is mainly based on clinical trials and observational studies generally conducted by cardiologists. Patients enrolled in clinical trials often do not represent HF patients from the community, who are likely to be older, female and affected by several comorbidities [12]. For example, although new hospitalized HF patients are on average 79 years old [13], most clinical trials have included younger patients with a mean age of about 60–65 years [14]. Most observational studies have been conducted by selected centres (e.g. cardiology units, such as in the Italian Network on Heart Failure Outcome Registry [15]), large hospitals which voluntarily participated in the EuroHeart Failure Survey [16], or non-European populations such as those from the United States (e.g. the Framingham Heart Study [17] and the Cardiovascular Health Study [18]), Canada [12] and Japan [19]. For more representative populations, such as those enrolled in the ADHERE registry, follow-up information is not available [20]. In addition, large HF registries and databases focus on patients who have already been hospitalized for decompensed HF [21], [22], [23], thus introducing a bias due to (a) a great heterogeneity in the patients' outcomes and probably to (b) a selective higher survival rate for those patients with favourable prognosis [24].

Accordingly, the purpose of this study was to identify short-term (30 days) and long-term (one year) prognostic factors for newly hospitalized HF patients generated in a large, unselected population in the Lombardy Region, in northern Italy.

Section snippets

Data source

The data used in the present study were retrieved from the Healthcare Utilization (HCU) Databases of the Lombardy Region, which accounts for about 16% (9,704,151) of the Italian population. In Italy, the National Health Service (NHS) provides universal health coverage, and since 1997 the Lombardy Region has used an automated system of databases which collects a variety of information including (1) a database of beneficiaries of NHS care (virtually the whole resident population), containing

Patients

The distribution of exclusion criteria is shown in Fig. 1. Of the 14,801 patients newly hospitalized for heart failure, 1329 (9%) died during index hospitalization. The 13,171 patients who survived the index admission and were aged 50 years or older were included in the study cohort and accumulated 137,275 and 89,279 person-months of observation according to whether one-year mortality or one-year hospital readmission was investigated.

The median age of patients at index admission was 81 years; 54%

Discussion

Our study confirms the high 30-day and one-year risk of mortality and hospital readmission after first admission for HF in a large, unselected patient population in the whole of the Lombardy Region, Italy. It also shows a substantial heterogeneity in mortality and hospital readmission across different patient subgroups. Prior use of antigout drugs, previous hospitalization for cancer and long stays in hospital during the index admission were negative prognostic factors for all of the outcomes

Conclusions

Short- and long-term mortality and readmission risks after first hospitalization for HF are extremely high. Our study has accurately determined significant predictors, which include age, drug treatments and comorbid conditions. Systematic characterization of HHF is crucial in assisting clinicians in decision-making and targeting treatment of high-risk patients.

Conflict of interest statement

None to declare.

Acknowledgement of grant support

The study was partially supported by an unrestricted grant from Novartis Farma S.p.A.

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    This author takes responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.

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