ARTYKUŁ ORYGINALNY / ORYGINAL ARTICLE

Predictors of one-year outcome in patients hospitalised for heart failure: results from the Polish part of the Heart Failure Pilot Survey of the European Society of Cardiology

Paweł Balsam1, Agata Tymińska1, Agnieszka Kapłon-Cieślicka1, Krzysztof Ozierański1, Michał Peller1, Michalina Galas1, Michał Marchel1, Jarosław Drożdż2, Krzysztof J. Filipiak1, Grzegorz Opolski1

11st Chair and Department of Cardiology, Medical University of Warsaw, Warsaw, Poland
2Department of Cardiology, Medical University of Lodz, Lodz, Poland

Address for correspondence:
Agnieszka Kapłon-Cieślicka, MD, PhD, 1st Chair and Department of Cardiology, Medical University of Warsaw, ul. Banacha 1a, 02–097 Warszawa, Poland,
tel: +48 22 599 29 58, e-mail: agnieszka.kaplon@gmail.com
Received: 13.12.2014 Accepted: 23.04.2015 Available as AoP: 18.06.2015

Abstract Background: Over the last few decades, the incidence and prevalence of chronic heart failure (HF) have been constantly increasing. Aim: To identify predictors of one-year mortality and hospital readmissions in patients discharged after hospitalisation for HF. Methods: The study included Polish patients who agreed to participate in the Heart Failure Pilot Survey of the European Society of Cardiology and were followed for 12 months. The primary endpoint was all-cause death at 12 months. The secondary endpoint was a composite of all-cause death and readmission for cardiac causes at 12 months. Results: The final analysis included 629 patients. The primary end point occurred in 68 of 629 patients (10.8%). In multivariate analysis, independent predictors of one-year mortality were: higher New York Heart Association (NYHA) class at admission (odds ratio [OR] 1.90; 95% confidence interval [CI] 1.01–3.59; p = 0.0478), inotropic support during hospitalisation (OR 3.95; 95% CI 1.49–10.47; p = 0.0056), and lower glomerular filtration rate at discharge (OR 0.978; 95% CI 0.961–0.995; p = 0.0117). The secondary endpoint occurred in 278 of 503 patients (55.3%). In multivariate analysis, predictors of secondary endpoint were a history of previous coronary revascularisation (OR 2.403; 95% CI 1.221–4.701; p = 0.002) and inotropic support during hospitalisation (OR 2.521; 95% CI 1.062–5.651; p = 0.009). Conclusions: Patients discharged after hospitalisation for HF remained at high risk of death and hospital readmission. A previous history of coronary revascularisation, decreased renal function, and worse clinical status at admission with the need for inotropic support were predictors of one-year outcome in Polish patients hospitalised for HF. Key words: heart failure, hospitalisation, inotropic support, prognosis, registry Kardiol Pol 2016; 74, 1: 9–17

INTRODUCTION

Over the last few decades, the incidence and prevalence of chronic heart failure (HF) have been constantly increasing. This is the result of growing life expectancy and aging of modern societies, as well as advances in the treatment of acute coronary syndromes, which lead to an increased number of survivors with left ventricular (LV) dysfunction [1]. HF has become the leading cause of hospitalisation in patients older than 65 years [2]. Death rates appear excessive both during and after hospitalisation. High readmission rates reveal the failure of admission of guidelines that would result in effective long-term care [2]. These facts on the morbidity associated with HF are uncontested. Moreover, data on the clinical characteristics of patients and the impact of management on outcomes during admission are incomplete. Most information is derived from single-centre studies, clinical trials, and real-life registries, including the EuroHeart Failure Survey II, ADHERE, and ATTEND [3–5]. However, the recent advancement in HF treatment that includes diagnostic methods, pharmacotherapy, and interventional treatment are likely to change the patients’ profile and risk predictors for mortality and rehospitalisation. The aim of the Heart Failure Pilot Survey of the European Society of Cardiology (ESC) was to assess the clinical profile, pharmacotherapy, and one-year outcome in HF patients across Europe [6, 7].

The aim of our study was to identify predictors of one-year mortality and hospital readmissions in the Polish cohort enrolled in the Heart Failure Pilot Survey.

METHODS

Study population

The study included Polish patients discharged after hospitalisation for HF, who agreed to participate in the Heart Failure Pilot Survey of the ESC. It was a prospective, multicentre, observational survey of HF patients that was conducted in 12 European countries [7]. The survey enrolled adults (i.e. over 18 years old) with HF — both, outpatients with HF seen in ambulatory care, as well as patients admitted to hospital for acute or chronic HF. The diagnosis of HF was based on clinical (typical HF signs and symptoms), biochemical (increased concentrations of N-terminal pro-B-type natriuretic peptide [NT-proBNP] ≥ 125 pg/mL or B-type natriuretic peptide [BNP] ≥ 35 pg/mL), and echocardiographic findings (LV dysfunction, not obligatory). There were no specific exclusion criteria other than lack of informed consent.

Data were gathered by 136 European cardiology centres, including 29 centres from Poland, i.e. approx. 12% of all hospitals with acute cardiac care units. The methodology of the study has been described in a previous publication [8].

Approval for the study by the local Ethical Review Board was obtained in accordance with the rules of each participating country. Signed informed consent was required from each of the involved patients after providing them with detailed information about the study.

The current analysis included only Polish patients of the Heart Failure Pilot Survey, who were hospitalised and then followed for 12 months [9]. Patients who died during hospitalisation were not included in the current analysis. During one-year observation data on deaths and all the readmissions were collected.

Study endpoints

The primary endpoint was all-cause death at 12 months after discharge. The secondary endpoint was a composite of all-cause death and readmissions for cardiac causes at 12 months.

Statistical analysis

Categorical data were presented as numbers of patients and percentages. For continuous variables, median value and interquartile range were used. Fisher’s exact test and Mann-Whitney U test were performed for the comparison of both groups, for categorical variables, and continuous variables, respectively. To determine the risk factors of primary and secondary endpoints, logistic regression analysis was performed. All factors that were found to be statistically significant in univariate analyses were included into multivariate logistic regression analysis. Statistical significance was considered for p values lower than 0.05 for all tests. Statistical analyses were performed using SAS software, version 9.2.

RESULTS

Study group selection

The Heart Failure Pilot Survey enrolment started in October 2009 and was completed in May 2010. A total of 5,118 patients were included across Europe, 893 of them were enrolled in Polish centres. In the Polish cohort of the registry there were 650 patients admitted to the hospital. The final analysis included 629 patients — 21 patients who died in hospital were excluded from the analysis. Data on one-year survival were available for all of the patients. Data on secondary endpoint were available for 503 patients. This group included 480 patients with data on rehospitalisation and deaths and 23 patients who died during follow-up without data on rehospitalisation. For the remaining population (126 patients) there were no data on rehospitalisation, and those patients survived for one year. The flow chart of patient enrolment in the study is shown in Figure 1.

 

Figure 1. The flow chart of patient enrolment in the study

Study group characteristics

The median age in the analysed group was 69 years old, and 64.7% of the patients were male. Most patients had a prior history of HF (57.8%), mainly of ischaemic aetiology (60.4%). Thirty-eight per cent of patients had a history of atrial fibrillation and 33.5% — of percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). The causes of HF decompensation leading to index hospitalisation included: acute coronary syndrome in 31.0%, atrial fibrillation in 16.3%, uncontrolled hypertension in 14.6%, HF treatment non-compliance in 13.1%, infection in 8.7%, renal dysfunction in 7.9%, anaemia in 5.1%, ventricular arrhythmia in 4.0%, bradyarrhythmia in 3.0%, iatrogenic causes in 1.1%, and “other” causes in 38.3% of patients (with a possibility to name more than one triggering factor of worsening HF for each patient). Patient demographics, characteristics, and differences between patients who developed primary or secondary endpoint are summarised in Table 1.

Table 1. Baseline characteristics of patients who survived and patients who died in one-year follow-up. Continuous and ordinal variables are shown as a median value and interquartile range

Characteristics	Total Median (IQR)/%	Primary endpoint		P	Secondary endpoint		P
		Died (68/629 = 10.81%)	Alive (561/629 = 89.19%)		Died or rehospitalisation (278/503 = 55.27%)	Alive without rehospitalisation (225/503 = 44.73%)
Demographics
Age [years]	69 (58–77)	74 (63–81)	69 (58–77)	0.0008	69 (58–77)	71 (59–78)	0.3
BMI [kg/m2]	27.7 (24.7–31.3)	26.6 (23.2–29.4)	27.7 (24.8–31.3)	0.08	27.7 (24.7–31.1)	28.1 (25.0–31.6)	0.5
HF
LVEF [%]	37 (27–50)	34 (25–46)	38 (27–50)	0.1	37 (25–47)	38 (30–52)	0.03
Previous hospitalisation for HF	57.8%	61.8%	57.3%	0.5	63.7%	52.7%	0.01
Aetiology of HF
Ischaemic	60.4%	76.5%	58.5%	0.004	64.0%	63.1%	0.9
Previous medical history
Previous stroke or TIA	9.7%	2.9%	10.6%	0.049	10.4%	8.9%	0.7
Atrial fibrillation	38.3%	50.0%	36.9%	0.047	41.4%	34.7%	0.1
Ischaemic heart disease or MI	58.4%	70.6%	57.0%	0.04	58.3%	55.8%	0.6
Previous PCI or CABG	33.5%	45.6%	32.0%	0.03	41.0%	25.0%	< 0.0001
NYHA class at admission	3 (2–3)	3 (3–4)	3 (2–3)	0.003	3 (3–4)	3 (2–3)	0.009
Clinical findings at discharge
Systolic BP [mm Hg]	120 (110–130)	113 (100–130)	120 (110–130)	0.01	120 (110–130)	120 (110–130)	0.09
Diastolic BP [mm Hg]	70 (65–80)	70 (60–80)	70 (68–80)	0.02	70 (65–80)	74 (70–80)	0.1
HR [bpm]	70 (66–80)	70.5 (70.0 –80.0)	70 (66–80)	0.3	70 (68–80)	70 (66–80)	0.4
Sodium concentration [mmol/L]	138.0 (136.0–140.4)	137.0 (135.0–139.8)	138.0 (136.0–140.6)	0.04	138.0 (135.0–141.0)	138.2 (136.0–140.5)	0.6
eGFR [mL/min/1.73 m2]	65.4 (45.6–89.1)	53.2 (31.0–75.8)	68.3 (47.4–90.8)	0.0005	63.9 (44.7–85.4)	69.9 (45.4–88.8)	0.4
Hospital management
Inotropic agents	9.7%	27.9%	7.5%	0.0001	14.4%	5.4%	0.001
Nitrates i.v.	15.3%	14.7%	15.4%	1.0	14.8%	15.2%	0.9
Diuretics i.v.	77.7%	80.88%	77.3%	0.6	78.7%	71.6%	0.08
Medication at discharge
ACEI	74.4%	64.7%	75.6%	0.06	71.2%	76.4%	0.2
ARB	8.8%	5.9%	9.1%	0.5	9.4%	9.9%	0.9
Beta-blockers	88.2%	85.5%	88.4%	0.7	87.8%	87.1%	0.9
Aldosterone antagonists	64.2%	63.2%	63.8%	1.0	68.8%	58.3%	0.02
Diuretics	80.4%	85.3%	79.9%	0.3	83.5%	76.4%	0.06
Statins	70.0%	73.1%	69.6%	0.7	70.8%	68.8%	0.6
Antiplatelets	70.8%	70.1%	70.9%	0.9	69.0%	70.5%	0.8
Anticoagulants	38.5%	43.3%	37.9%	0.4	43.7%	33.9%	0.03
ACEI — angiotensin-converting-enzyme inhibitor; ARB — angiotensin receptor blocker; BMI — body mass index; BP — blood pressure; CABG — coronary artery bypass surgery; eGFR — estimated glomerular filtration rate; HF — heart failure; HR — heart rate; IQR — interquartile range, LVEF — left ventricular ejection fraction; MI — myocardial infarction; NYHA — New York Heart Association; PCI — percutaneous coronary intervention; TIA — transient ischaemic attack

Primary endpoint

The primary endpoint occurred in 68 patients (10.8% of the study group). Cardiovascular deaths accounted for 70.4% of total deaths, non-cardiovascular deaths — for 3.7%, while an unknown cause was reported in 25.9% of the cases. In univariate analysis the risk factors for death in one-year follow-up were: older age, history of atrial fibrillation, ischaemic aetiology of HF, previous PCI or CABG, worse clinical status (higher New York Heart Association [NYHA] class) at hospital admission, increased requirement for inotropic support during hospitalisation, lower systolic blood pressure (SBP) and diastolic blood pressure, and lower glomerular filtration rate (GFR) at discharge, as shown in Table 2. Gender, diabetes, tobacco smoking, thyroid dysfunction, and peripheral vascular disease were not predictors of mortality (data not shown).

Table 2. Univariate analyses of predictors for the long-term clinical outcomes

Variable	Primary endpoint		Secondary endpoint
	OR (95% CI)	P	OR (95% CI)	P
Age [1 year]	1.04 (1.02–1.06)	0.0009	1.0 (0.98–1.01)	0.5
Men	0.81 (0.48–1.36)	0.42	1.39 (0.96–2.0)	0.08
BMI [kg/m2]	0.94 (0.89–1.0)	0.049	1.0 (0.96–1.03)	0.65
LVEF [%]	0.98 (0.96–1.01)	0.1	0.99 (0.97–1.0)	0.03
Previous hospitalisation for HF	1.20 (0.72–2.02)	0.5	1.57 (1.10–2.25)	0.01
Previous stroke or TIA	0.26 (0.06–1.08)	0.06	1.19 (0.65–2.16)	0.6
History of atrial fibrillation	1.71 (1.03–2.84)	0.04	1.33 (0.92–1.91)	0.1
Ischaemic heart disease or MI	1.81 (1.05–3.14)	0.03	1.11 (0.78–1.58)	0.6
Previous PCI or CABG	1.78 (1.07–2.96)	0.03	2.09 (1.42–3.07)	0.0002
NYHA class at admission	1.73 (1.20–2.49)	0.003	1.36 (1.07–1.74)	0.01
Clinical findings at discharge
Systolic BP [mm Hg]	0.98 (0.96–1.0)	0.02	0.99 (0.98–1.0)	0.05
Diastolic BP [mm Hg]	0.97 (0.95–1.0)	0.03	0.99 (0.97–1.01)	0.2
Sodium concentration [mmol/L]	0.95 (0.89–1.01)	0.08	0.98 (0.93–1.04)	0.5
eGFR [mL/min/1.73 m2]	0.98 (0.97–0.99)	0.0009	1.0 (0.99–1.0)	0.3
Hospital management
Inotropic agents	4.78 (2.58–8.86)	0.0001	2.97 (1.52–5.81)	0.002
Medication at discharge
ACEI	0.59 (0.35–1.01)	0.05	0.76 (0.51–1.14)	0.2
ARB	0.63 (0.22–1.81)	0.4	0.95 (0.52–1.78)	0.9
Beta-blockers	0.86 (0.41–1.81)	0.7	1.06 (0.63–1.80)	0.8
Aldosterone antagonists	1.0 (0.59–1.70)	1.0	1.58 (1.09–2.29)	0.01
Diuretics	1.46 (0.73–2.95)	0.3	1.55 (1.0–2.42)	0.05
Statins	1.19 (0.67–2.10)	0.6	1.10 (0.75–1.61)	0.6
Antiplatelets	0.97 (0.55–1.68)	0.9	0.93 (0.63–1.36)	0.7
Anticoagulants	1.25 (0.75–2.09)	0.4	1.51 (1.05–2.18)	0.03
CI — confidence interval; ACEI — angiotensin-converting-enzyme inhibitor; ARB — angiotensin receptor blocker; BP — blood pressure; BMI — body mass index; CABG — coronary artery bypass surgery; eGFR — estimated glomerular filtration rate; HF — heart failure; LVEF — left ventricular ejection fraction; MI — myocardial infarction; NYHA — New York Heart Association; OR — odds ratio; PCI — percutaneous coronary intervention; TIA — transient ischaemic attack

Interestingly, patients who were at higher risk of one-year mortality were often taking suboptimal doses of angiotensin-converting enzyme inhibitors (ACEI), beta-blockers, or aldosterone receptor antagonists at the time of discharge.

In multivariate analysis, predictors of one-year mortality were: higher NYHA class at hospital admission (odds ratio [OR] 1.90; 95% confidence interval [CI] 1.01–3.59; p = 0.0478), inotropic support during hospitalisation (OR 3.95; 95% CI 1.49–10.47; p = 0.0056), and lower GFR at discharge (OR 0.978; 95% CI 0.961–0.995; p = 0.0117). A trend was observed for history of ischaemic heart disease and neglecting treatment with ACEI as predictive of one-year mortality.

Multivariable predictors of one-year clinical outcomes are shown in Table 3.

Table 3. Multivariate analysis of predictors of death at one year

Variable	Primary endpoint
	OR (95% CI)	P
Age [years]	0.99 (0.95–1.04)	0.9
Body mass index [kg/m2]	1.03 (0.96–1.11)	0.4
History of atrial fibrillation	1.71 (0.79–3.71)	0.2
Ischaemic heart disease or MI	2.55 (0.97–6.74)	0.06
Previous PCI or CABG	1.38 (0.60–3.15)	0.5
NYHA class at admission	1.90 (1.01–3.59)	0.0478
Systolic BP [mm Hg] at discharge	0.99 (0.95–1.02)	0.4
Diastolic BP [mm Hg] at discharge	0.97 (0.92–1.01)	0.2
eGFR at discharge [mL/min/1.73 m2]	0.98 (0.96–0.99)	0.0117
Inotropic agents in hospital	3.96 (1.49–10.47)	0.0056
ACEI at discharge	0.49 (0.23–1.06)	0.07
CI — confidence interval; ACEI — angiotensin-converting-enzyme inhibitor; BP — blood pressure; CABG — coronary artery bypass surgery; eGFR — estimated glomerular filtration rate; MI — myocardial infarction; NYHA — New York Heart Association; OR — odds ratio; PCI — percutaneous coronary intervention

Table 4. Multivariate analysis of predictors of death or rehospitalisation for heart failure at one year

Variable	Secondary endpoint
	OR (95% CI)	P
Left ventricular ejection fraction	1.003 (0.988–1.018)	0.71
Previous hospitalisation for HF	0.807 (0.530–1.230)	0.32
Previous PCI or CABG	2.403 (1.221–4.701)	0.002
NYHA class at admission	1.011 (0.711–1.652)	0.51
Inotropic agents in hospital	2.521 (1.062–5.651)	0.009
Aldosterone antagonists at discharge	0.681 (0.447–1.037)	0.07
Anticoagulants at discharge	0.789 (0.524–1.186)	0.26
CI — confidence interval; CABG — coronary artery bypass surgery; HF — heart failure; NYHA — New York Heart Association; OR — odds ratio; PCI — percutaneous coronary intervention

Secondary endpoint

The secondary endpoint occurred in 278 of 503 patients (55.3%). From 480 patients whose data on rehospitalisation were available, 53.1% were readmitted at least once for any cause during the one-year follow-up; 83.1% were readmitted for cardiovascular causes and 20.4% for non-cardiovascular causes, while hospitalisations due to HF accounted for 47.8% of total hospitalisations.

In univariate analysis the risk factors for the secondary endpoint were: a history of PCI/CABG, previous HF hospitalisation, lower ejection fraction, higher NYHA class at admission, more frequent use of inotropic support during hospitalisation, and the use of aldosterone antagonists and anticoagulants at discharge.

In multivariate analysis, predictors of secondary endpoint were a history of previous coronary revascularisation (OR 2.403; 95% CI 1.221–4.701; p = 0.002) and inotropic support during hospitalisation (OR 2.521; 95% CI 1.062–5.651; p = 0.009).

DISCUSSION

The Heart Failure Pilot Survey of the ESC is an epidemiological multicentre study of patients hospitalised for HF in Europe. It gives a unique insight into the characteristics of patients hospitalised for HF in Europe, including Poland. These data confirm that HF is a chronic disease with ischaemic aetiology in over 60% of Polish hospitalised patients, which is slightly higher than in other registries (ATTEND: 33%, ADHERE: 57%, EHFS-II: 30%, OPTIMIZE-HF: 46%) [3–5, 10]. Race and ethnic variations may be responsible for the differences in the causes of HF because the prevalence of ischaemic heart disease was also low in the studies held in Japan [3]. However, in the whole ESC HF Pilot registry the prevalence of ischaemic heart disease was lower than in Poland, at 50.7%. Patients included into the large American national OPTIMIZE-HF registry were also older compared to Polish patients with HF [10]. Development of HF at a younger age in the Polish population may reflect inadequate prevention and suboptimal treatment of diseases leading to this clinical syndrome.

Numerous randomised controlled trials have shown that ACEI, angiotensin receptor blockers, and beta-blockers improve the survival of patients with HF. The proportions of Polish patients actually receiving these drugs in the present study were 74.4%, 8.8%, and 88.2%, respectively. Those results are consistent with the data gathered from the ESC HF Pilot Survey in Eastern Europe [7].

One-year outcomes

While survival of patients with chronic HF seems to improve slowly over years, according to our data both in-hospital and one-year outcomes of patients admitted for acute HF are still very high [11, 12]. This can be explained by the fact that in-hospital therapeutic approaches to these patients have remained unchanged during recent decades. In contrast, several trials have been conducted in patients with chronic HF, allowing the inclusion of effective treatments in the recommendations of the current international guidelines widely adopted in clinical practice [13]. This is probably the most important reason for the observed improvement in outcomes. The one-year mortality rate of hospitalised HF patients in Poland was 10.8% (68 of 629 patients died in one-year observation) while in the whole registry it was 17.4% for Europe. For northern, eastern, southern and western Europe, one-year mortality rates were: 19.3%, 13%, 24.7%, and 18.4% respectively. The lower mortality in Polish hospitalised patients may be associated with the fact that there are few outpatient HF clinics in Poland. Due to this fact, patients hospitalised in Polish hospitals may have less severe advancement of HF.

In our analysis several risk factors were detected that can effectively identify patients at higher and lower risk of post-discharge clinical events. The determinants of all-cause mortality observed in our study were different from those described in previous studies conducted in hospitalised HF patients, including the population of European patients from the ESC HF Pilot registry [2, 7, 14–17]. In previous studies conducted in Europe and the United States, age, renal function, ejection fraction, and SBP are confirmed to be relevant prognostic markers in hospitalised patients, as well as the presence of pulmonary or peripheral congestion. This suggests the need to discharge patients only when signs of congestion are completely resolved and, when this is not possible, specifically to monitor and intensively care for those patients who are at high risk of subsequent events. In the Polish population of the ESC HF Pilot Survey the independent risk factors for death during one year of observation were: higher NYHA class at hospital admission, inotropic support during hospitalisation, and renal failure described as lower GFR. In the Korean HF registry the independent clinical risk factors included age, previous history of HF, anaemia, hyponatraemia, a high NT-proBNP level, and taking beta-blockers at discharge [18]. In the OPTIMIZE-HF study the 60- to 90-day post-discharge mortality rate was 8.6%, and 29.6% of patients were re-hospitalised. Factors predicting early post-discharge mortality included age, serum creatinine, reactive airway disease, liver disease, lower SBP, lower serum sodium, lower admission weight, and depression. Use of statins and beta-blockers at discharge was associated with significantly decreased mortality. In OPTIMIZE-HF, SBP was the most important determinant of post-discharge mortality; it was also highly predictive of death or rehospitalisation. Lower SBP was associated with higher risk of both outcomes, perhaps because SBP may be a marker of poor cardiac output in this setting, thus signalling a higher-risk patient [19]. In our study lower SBP was a significant risk factor for death in one-year observation only in univariate analysis.

On the other hand, the risk factors for the occurrence of secondary endpoint (death or rehospitalisation) were a history of previous PCI/CABG and inotropic support during hospitalisation. This probably results from the fact that patients with HF, who require revascularisation are in more severe condition with significantly worse function of the LV, which is closely related with the less favourable outcomes. The same endpoint occurred in 31% of patients from the IMPACT-HF study, but during 60 days of observation. In our analysis this endpoint occurred in 53.1% of patients, but in one-year follow-up. The most important predictors for the combined endpoint of death or rehospitalisation in the OPTIMIZE-HF study were admission serum creatinine, SBP, admission haemoglobin, discharge use of ACEI or angiotensin receptor blockers, and pulmonary disease [19].

In our previous publication of the results of the ESC HF Pilot registry on Polish hospitalised patients, the only independent risk factors for in-hospital mortality were: higher heart rate at admission and lower natrium concentration at admission [8].

Despite advances in treatment, hospitalised HF patients remain at high risk for adverse outcomes, including mortality and high rate of HF readmissions. It shows that outpatient care may be insufficient and require improved cooperation between doctor and patient and management according to guidelines. Here an essential role is played by epidemiological data and registries that analyse real-life patients and assess risk factors. The ability to quantify an individual patient’s risk is very important to make treatment decisions and discharge plans. Patients who are at higher risk may potentially benefit from closer follow-up and/or referral to HF disease management, heart transplantation evaluation, or evaluation for an LV assist device. Patients who are at lower risk could receive less intensive follow-up. Numerous risk assessment algorithms in HF have been developed; however, existing models only apply to outpatients or mortality before hospital discharge, or require invasive measures, thus limiting their usefulness [20–23].

Limitations of the study

Some important limitations of the survey must be acknowledged. First, criteria for HF diagnosis were discussed during the investigator meetings, and the guidelines of reference were commented on and circulated to all investigators [24]. However, the investigators made the diagnoses according to clinical judgement. Secondly, even though we tried to balance the methodological need for consecutiveness of enrolment with the practical feasibility by increasing the workload for centres by limiting recruitment to one day per week for eight months, we cannot prove the consecutiveness of patient enrolment. Thirdly, the patients were all enrolled in cardiology wards and clinics, and they did not include those presenting at emergency departments and/or those admitted to other hospital facilities. Accordingly, the population reported herein does not represent all HF patients. Most of the patients included in the Polish cohort where hospitalised in clinical hospitals. This may contribute to proceeding with patients, which is different to that of other countries. Finally, a formal committee did not adjudicate the ascertainment of cause of death.

CONCLUSIONS

Patients discharged after hospitalisation for HF remained at high risk of death and hospital readmission. A previous history of coronary revascularisation, decreased renal function, and worse clinical status at admission with the need for inotropic support were predictors of one-year outcome in Polish patients hospitalised for HF.

 

Participating centres, investigators and data collection officers:

1. 1. Zabrze (ul. Szpitalna): L. Poloński, M. Zembala, P. Rozentryt, J. Niedziela, J. Wacławski, M. Świetlińska
2. 2. Wrocław: P. Ponikowski, E. Jankowska
3. 3. Warszawa (ul. Banacha): G. Opolski, A. Kapłon-Cieślicka, M. Marchel, P. Balsam
4. 4. Wałbrzych: R. Szełemej, T. Nowak
5. 5. Biała: Z. Juszczyk, S. Stankala
6. 6. Kraków (ul. Skarbowa): E. Mirek-Bryniarska, M. Zabojszcz, A. Grzegórzko
7. 7. Zamość: A. Kleinrok, G. Prokop-Lewicka
8. 8. Łódź (ul. Sterlinga): J. Drożdż, K. Wojtczak-Soska, A. Retwiński
9. 9. Bydgoszcz: W. Sinkiewicz, W. Gilewski, J. Pietrzak
10. 10. Kielce: B. Wożakowska-Kapłon, B. Sosnowska-Posiarska, R. Bartkowiak
11. 11. Poznań: S. Grajek, E. Straburzyńska-Migaj, H. Wachowiak-Baszyńska, A. Katarzyńska-Szymańska
12. 12. Sochaczew: E. Piasecka-Krysiak, J. Zambrzycki
13. 13. Kraków (ul. Prądnicka): J. Nessler, K. Bury
14. 14. Łódź (ul. Kniaziewicza): M. Broncel, A. Poliwczak
15. 15. Zabrze (ul. M. Curie-Skłodowskiej): E. Nowalany-Kozielska, A. Rolnik, J. Jojko
16. 16. Kalisz: J. Tarchalski, G. Borej, R. Bartliński
17. 17. Suwałki: J. Korszun
18. 18. Bełchatów: D. Stachurski
19. 19. Gdańsk: A. Rynkiewicz, J. Bellwon
20. 20. Sieradz: P. Ruszkowski, G. Bednarczyk
21. 21. Warszawa (ul. Solec): A. Mamcarz, A. Folga, M. Wełnicki
22. 22. Kluczbork: A. Krzemiński
23. 23. Częstochowa: P. Kardaszewicz, J. Gabryel, M. Łazorko-Piega
24. 24. Gorlice: P. Kukla
25. 25. Chełmża: P. Kasztelowicz
26. 26. Sosnowiec: J. Olender
27. 27. Zielona Góra: B. Kudlińska
28. 28. Gostynin-Kruk: M. Pagórek, S. Olczyk
29. 29. Rzeszów: J. Kuźniar, T. Rzeszuto

Acknowledgements

All analyses were conducted based on data from the Polish part of the Heart Failure Pilot Survey, coordinated nationwide by Professor Jarosław Drożdż.

Conflict of interest: none declared

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Cite this article as: Balsam P, Tymińska A, Kapłon-Cieślicka A et al. Predictors of one-year outcome in patients hospitalised for heart failure: results from the Polish part of the Heart Failure Pilot Survey of the European Society of Cardiology. Kardiol Pol, 2016; 74: 9–17. doi: 10.5603/KP.a2015.0112.