click for large version
click for large version
Mortality prediction. Nearly 3.5% of admitted heart failure patients will die during their hospitalization. For perspective, the rate of hospital mortality with acute myocardial infarction is 7%. BNP serves as a powerful and independent predictor of inpatient mortality. The ADHERE (Acute Decompensated Heart Failure National Registry) study showed that when divided into BNP quartiles of <430 pg/mL, 430 pg/mL to 839 pg/mL, 840 pg/mL to 1,729 pg/mL, and >1,730 pg/mL, patients’ risk of inpatient death was accurately predicted as 1.9%, 2.8%, 3.8%, and 6.0%, respectively.10 Even when adjusted for other risk factors, BNP remained a powerful predictor; the mortality rate more than doubled from the lowest to highest quartile.
Different strategies have been proposed to improve the outcomes in these highest-risk patients; however, to date, no evidence-based strategy offers a meaningful way to reduce inpatient mortality beyond the current standard of care.
Readmission and 30-day mortality. The 30-day readmission rate after discharge for ADHF is more than than 25%. A study of Medicare patients showed that more than $17 billion (more than 15% of all Medicare payments to hospitals) was associated with unplanned rehospitalizations.11 As bundling payment trends develop, hospitals have an enormous incentive to identify CHF patients with the highest risk of readmission and attempt to mitigate that risk.
From a patient-centered view, upon hospital discharge a patient with ADHF also realizes a 1 in 10 chance of dying within the first 30 days.
At discharge, BNP serves as a powerful and independent marker of increased risk of readmission, morbidity, and mortality. O’Connor et al developed a discharge risk model in patients with severe left ventricular dysfunction; the ESCAPE risk model and discharge score showed elevated BNP was the single most powerful predictor of six-month mortality.12 For every doubling of the BNP, the odds of death at six months increased by 1.4 times.
After combining discharge BNP with other factors, the ESCAPE discharge score was fairly successful at discriminating between patients who would and would not survive to six months. By identifying these outpatients, intensive management strategies could be focused on individuals with the highest risk. The data support the idea that readmission reductions are significant when outpatients obtain early follow-up. Many healthcare centers struggle to schedule early follow-up for all heart failure patients.
As such, the ability to target individuals with the highest discharge scores for intensive follow-up might improve outcomes. These patients could undergo early evaluation for such advanced therapies as resynchronization, left ventricular assist device implantation, or listing for transplantation. Currently, this strategy is not proven. It also is possible that these high-risk patients might have such advanced diseases that their risk cannot be modified by our current medications and advanced therapies.
Back to the Case
This patient has symptoms and signs that could be caused by ADHF or COPD. Her presentation is consistent with an intermediate probability of ADHF. A rapid BNP reveals a level of 950 pg/mL.
Even considering the higher cutoff required because of her coexistent atrial fibrillation, her BNP is consistent with ADHF. Additionally, her obesity likely has decreased the true value of her BNP. A previous BNP drawn when the patient was not in ADHF was 250 ng/mL, meaning that at least a 70% increase is present.
She was admitted and treated with intravenous diuretics with improvement in her congestion and relief of her symptoms. Daily BNPs were not drawn and her diuretics were titrated based on bedside clinical assessments. Her admission BNP elevation would predict a moderately high risk of short- and intermediate term of morbidity and mortality.