Elsevier

International Journal of Cardiology

Volume 183, 15 March 2015, Pages 111-116
International Journal of Cardiology

An early warning scoring system for the prevention of acute heart failure

https://doi.org/10.1016/j.ijcard.2015.01.076Get rights and content

Abstract

Background

Early prediction and identification of the onset of acute heart failure (AHF) in high-risk patients are of great significance for preemptive treatment and a better prognosis. We sought to find a scoring system to predict the onset of AHF in patients in the acute heart failure unit (AHFU).

Methods

Data for 433 patients at of AHF in the AHFU were analyzed. We recorded sex, age, history of coronary artery disease, hypertension, diabetes, and primary percutaneous coronary intervention. We also reviewed temperature, pulse, SpO2, respiratory rate, urine volume, and emotional state every hour before the onset of AHF. All admission and follow-up data were retrieved from hospital charts. Factors were analyzed using a binary logistic regression model to create the SUPER (SpO2, urine volume, pulse, emotional state, and respiratory rate) scoring model. We divided the scoring system into four levels: low-, intermediate-, high-, and extremely high-risk. Patients fitting the four risk levels were followed up for 6 to 24 months.

Results

SpO2, hourly urine volume, pulse, emotional state and respiratory rates were associated with an independent increased risk for the onset of AHF. The SUPER score for the patients in the AHFU predicted the onset of AHF 3.90 ± 1.94 h (1–17 h) earlier. The areas under the ROC curve for the SUPER score and the modified early warning score were 0.811 and 0.662 (p < 0.05), indicating that the SUPER score provided a better warning of the AHF. A low-, intermediate-, high-, and very high-risk SUPER predicted the likelihood of AHF at 17.3%, 61.3%, 84.4%, and 94.0%, respectively. The differences in mortality rates between the four levels were statistically significant (p < 0.05).

Conclusions

In patients at high risk of AHF, the SUPER scoring system could predict the onset of AHF 2 to 6 h earlier. Preemptive treatment according to the SUPER score may prevent or delay AHF occurrence to improve quality of life and reduce mortality.

Introduction

Acute heart failure (AHF) describes the rapid onset of, or changes in, symptoms and signs of heart failure (HF) [1], and needs immediate medical attention on the emergent condition. In most cases, AHF is performed as the first presentation of HF. AHF may be caused by an inherited or acquired abnormality of any aspect of cardiac function. There is often a clear incentive or precipitant in patients with pre-existing HF, such as severe anemia, arrhythmia, volume overload, oliguria and hypoxemia. In the 'acute' phase, cardiac dysfunction can exacerbate in a period of days or even weeks, but others developing HF within hours to minutes (e.g. during the event of acute myocardial infarction). However, until now there have been no methods for predicting the onset of AHF within hours to minutes. A prediction model could enable AHF therapy to be different from the traditional treatment of acute or chronic heart failure.

AHF has emerged as a major public health problem over the past decade. Acute coronary syndrome (ACS) is one of commonest illnesses seen in chest pain centers (CPCs). In 2009, close to 1.2 million hospital discharges in CPCs of the United States had an ACS diagnosis [2]. ACS results in significant morbidity and mortality [3], with HF as a frequent complication [4], [5]. Additionally, nearly 700,000 emergency department (ED) visits in 2009 were due to AHF [6]. According to the survey of American Heart Association, the prevalence of HF is increasing from 2.8% in 2010 to 3.5% in 2030, which means an additional 3 million patients will be affected [7]. It produces a 215% increase in projected direct medical costs (from $24.7 billion to $77.7 billion) and an 80% increase in projected indirect costs (from $9.7 billion to $17.4 billion) from 2010 to 2030 [8].

The modified early warning score (MEWS) [9] was a simple physiological scoring system suitable for bedside application in the ED which could be used to identify medical patients at the risk of catastrophic deterioration in a busy clinical area. MEWS is also regarded as a useful tool on routinely recorded physiological data in the intensive care unit. Similarly, a new scoring system for early warning the onset of AHF was needed in the AHFU.

Usually the treatment strategy of acute and chronic heart failure was different; chronic heart failure was often combined with liver and renal insufficiency, poor activity tolerance, high level of N-terminal B-type natriuretic peptide (NT-proBNP), and moderately elevated of cardiac tropin I (cTnI). In cases of factors such as mood changes, anemia, fatigue, or iatrogenic factors, AHF may be judged to have occurred according to clinical observation. Vital signs and other monitoring factors appear to be changed before the onset of AHF. For example, patients may experience increases in heart rate, breathing rate, blood oxygen saturation, hourly urine rate, or abnormal emotions (e.g. restlessness, excitement, agitation, overstimulation, delirium, depression, apathy, unresponsiveness, lethargy, drowsiness, or coma). Emergent treatment at the onset of AHF is expected to provide advance intervention and may be able to reduce a heart attack. The treatment of acute and chronic heart failure may be combined by an appropriate cutoff point, which could not only improve the quality of survival, but may improve the prognosis of patients with the risk of AHF.

Section snippets

Study design and patient population

This study was performed at the AHFU and CPC of Qilu Hospital. Inclusion criteria were any patient admitted to the clinic room who was triaged to the CPC or AHFU owing to a high-risk first assessment. Patients in the AHFU have a higher risk of death and heart failure. We recorded sex, age, history of coronary artery disease (CAD), hypertension, diabetes, and primary percutaneous coronary intervention (PPCI), and then reviewed temperature, pulse, SpO2, respiratory rate, blood pressure, urine

Baseline characteristics

Data for 433 patients assessed in the CPC or AHFU of Qilu Hospital of Shandong University from November 2011 to June 2014 were included; 83 patients died in hospital. A total of 420 AHF in-hospital events were recorded.

The study population included 264 men (61.0%) and 169 women (39.0%), and the mean age was 64.08 ± 15.67 years (15–89 years). All patients had one or more risk factors for AHF, such as NYHA classes III to IV, advanced age, ACS, PPCI for ST segment elevation myocardial infarction

Discussion

AHF is defined as the acute onset of signs and symptoms due to heart failure necessitating emergency therapy. In-hospital mortality rate is as high as 10% and in cardiogenic shock it increases to 50–70% [10]. A study indicated that patients with non-ST-segment elevation acute coronary syndrome presenting with or developing HF during hospitalization were older, more often female, and had a higher risk of death at 30 days than patients without HF [11]. Rapid diagnosis and causal therapy are

Study limitations

This study is a single-center, retrospective cohort study. Its purpose was to establish a scoring system guided by the simple vital signs, not traditional risk factors, such as NT-proBNP, cTnI, BUN, and Cr. We used this scoring system ahead of AHF as a guide for preemptive therapy in order to try and decrease the incidence of AHF and improve the patients' quality of life and prognosis. The treatment strategies for both acute and chronic heart failure are different, and the SUPER was intended to

Conclusions

The SUPER score could predict the onset of AHF before 2 to 6 h for patients with the risk of heart failure. The higher the patient's score, the higher was their mortality. We expect this to help in risk stratification for AHF.

Funding sources

This study was supported by the National Natural Science Foundation of China (81170136, 81100147, 81300103, 81300219), Taishan Scholar Program of Shandong Province (ts20130911), Specialized Research Fund for the Doctoral Program of Higher Education (20130131110048), grant from Department of Science and Technology of Shandong Province (2011GSF11806), Shandong Provincial Outstanding Medical Academic Professional Program, 1020 Program from the Health Department of Shandong Province, China, and the

Conflict of interest

The authors report no relationships that could be construed as a conflict of interest.

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