Featured PapersFrom statistical significance to clinical relevance: A simple algorithm to integrate brain natriuretic peptide and the Seattle Heart Failure Model for risk stratification in heart failure
Section snippets
Derivation cohort
We identified a retrospectively compiled cohort of consecutive HF patients seen at Mayo outpatient clinics and associated hospitals in Rochester, Minnesota, from July 1, 2007 through December 31, 2007, a time-frame intentionally chosen to pre-date the era of widespread LVAD referrals. Using a modification of a previously described natural language processing program,20 all electronic clinical notes were searched for non-negated terms (refer to Table S1 in Supplementary material available online
Baseline characteristics and outcomes
In the derivation cohort, of the 441 consecutive patients identified, 268 (61%) were community patients (residing within 100 miles of center) and 308 (70%), 101 (23%) and 32 (7%) were seen in cardiovascular, non-cardiovascular sub-specialty and primary care settings, respectively. In the validation cohort, 1,513 patients were included. Baseline characteristics from each cohort are shown in Table 1. Missing data were rare, with 1 patient having no creatinine level, 12 having no NYHA
Discussion
In a single-center, retrospectively defined, derivation cohort of patients with HFrEF seen across a spectrum of care environments and providers, application of a simple SHFM+BNP risk stratification algorithm revealed that, regardless of patients’ SHFM predicted category of risk, a BNP ≥700 pg/ml identifies patients with ≥2-fold risk of mortality than the SHFM would suggest , whereas a BNP <700 pg/ml identifies patients in whom the SHFM risk is well calibrated. In an external, prospective,
Limitations
Our study should be interpreted in the context of inherent methodological limitations of retrospective studies. NYHA, comorbidities and medications were obtained by individualized chart review and were limited by care providers’ documentation. Missing values were imputed for calculation of composite scores. Other studies validating composite risk scores have been retrospective and had similar rates of missing data that had to be imputed.5 The similar performance in a prospectively enrolled
Disclosure statement
T.P.C. has received support for running biomarker assays from Abbott Diagnostics. A.S.J. has or presently consults for most of the major diagnostic companies, including those whose assays are used in this analysis. The remaining authors have no conflicts of interest to disclose. O.F.A. was supported by the National Institutes of Health (Training Grant T-91160), and support for his mentorship was provided by the Heart Failure Clinical Research Network Skills Development Core (HL 84907).
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Risk Prediction in Transition: MAGGIC Score Performance at Discharge and Incremental Utility of Natriuretic Peptides
2020, Journal of Cardiac FailureCitation Excerpt :For example, a recent publication by Sawano et al47 utilizing the MAGGIC score and discharge BNP in Japanese patients demonstrated an improvement in risk prediction (note the authors suggest that because of the longer length of stay typical in Japan that these values are most appropriately compared with ambulatory, compensated, patients with HF in the United States). Levy et al31 showed the addition of BNP accurately predicted a 3-fold increase in mortality compared with the original Seattle heart failure model, whereas Salah et al17 showed 62% improvement in NRI of the ELAN-HF Score with the addition of NT-proBNP.48 The reasons for this could be multifactorial, such as acute elevations of NP being more indicative of the patient's current state rather than longer-term risk once optimized.
Use of speckle tracking to assess heart failure with preserved ejection fraction
2019, Journal of CardiologyCitation Excerpt :For a given BNP level, the prognosis in patients with HFpEF is similar to that in patients with HFrEF, although criteria vary based on assay and consideration of sensitivity versus specificity. Age, gender, weight, and comorbidities can impact levels of these factors [53,56]. HFpEF is a malady of fatigue and exertional dyspnea in which STE plays a key role in both the evaluation and management of the syndrome [57].
Risk scores and biomarkers in heart failure: A journey to predictive accuracy and clinical utility
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