Release date: 2016-04-27
Recently, Thomas H. Marwick and others from the Menzies Medical Research Center of the University of Tasmania in Australia developed a new risk prediction model. Compared with the existing model, this new model can more accurately predict the 30-day readmission and death risk of patients with heart failure. Unlike other predictive models, the new model includes individual patient echocardiographic results, mental health, cognitive function, and socioeconomic status.
Pre-admission
The researchers said that many patients with heart failure will be hospitalized again due to heart failure, and this risk is difficult to predict. They believe that the existing risk score does not cover all important patient characteristics. The researchers developed this new score by analyzing 430 patients with heart failure (mean age 74 years, 64% male) and in 161 patients with heart failure (mean age 78 years, 55% male, 6 Verification was carried out in the absence of heart failure during the month.
The investigators evaluated 30-day mortality or readmission predictors for heart failure patients, including solitary (OR = 2.05; 95% CI, 1.12-3.76), fatal arrhythmias (OR = 2.92; 95% CI, 1.2- 7.13), winter discharge (OR = 1.61; 95% CI, 1-3.31), heart rate increase of 5bpm (OR = 1.12; 95% CI, 1.01-1.24), NYHA classification (OR = 1.95; 95% CI, 1.35-2.84) ), Montreal Cognitive Assessment Score (OR = 0.9; 95% CI, 0.86-0.95), Patient Health Questionnaire (OR = 1.04; 95% CI, 1-1.08), right atrial pressure (HR = 1.06; 95% CI) , 1.01-1.12), left atrial volume index (OR = 1.02; 95% CI, 1.01-1.03), blood urea nitrogen (OR = 1.04; 95% CI, 1.01-1.08) and serum albumin (OR = 0.95; 95) % CI, 0.91-0.99). 
Related risk factors
According to Marwick, cognitive impairment is a difficult factor to measure, and the model contains this factor. The model can be used in patients requiring close follow-up to reduce readmission. It is very important to educate patients about self-care, which of course is based on cognitive integrity.
Accurate identification
Of the 430 patients, 9% died within 30 days of discharge and 21% re-admitted. The investigators believe that the model showed good recognition ability in predicting 30-day death or readmission (C stat = 0.82; 95% CI, 0.77-0.87), and was able to predict 30-day mortality very accurately in the validation cohort. Or re-admission (C statistic = 0.8; 95% CI, 0.69-0.91).
Marwick suggested that future research should analyze whether the enhancement of patient surveillance can benefit, and whether other educational models can benefit patients with cognitive impairment, these measures may reduce the risk of readmission in patients with heart failure.
Compiled from: Score predicts 30-day death, readmission risk in patients with HF. Healio. April 25, 2016
Source: Medical Pulse
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