This retrospective study will take advantage of an existing EU-funded dataset, the BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF), which was designed to identify biomarkers related to the response to guideline directed medical therapy, and coordinated by UMCG. The availability of this comprehensive dataset of patients with severe HFrEF, prospectively and consistently collected, with the possibility to access a biobank to re-assay samples with novel biomarkers, provides a unique opportunity to derive preliminary data about the interaction between biomarkers of congestion and diuretic doses, that were prescribed based on clinical judgement, and therefore derive a machine learning-based algorithm than could be tested to guide the management of diuretic therapy
This is a retrospective study based on the index and the validation cohorts of the BIOSTAT-CHF project. The index cohort consists of a prospectively enrolled series of 2516 patients from 69 centres in 11 European countries recruited between December 2010 and December 2012 and with a median follow-up of 21 months \[interquartile range (IQR) 15 - 27 months\]. Validation cohort was designed as well as a multicentre, prospective, observational study, which included 1738 patients from six centres in Scotland, United Kingdom. BIOSTAT-CHF samples and data will be re-analysed to include additional congestion biomarkers, to obtain the BIOTOOL-CHF DISCO dataset. The latter has been used to derive a predictive model for congestion-related adverse events, priming the design of a prospective randomized study (the BIOTOOL-CHF VALID study). Preliminary analysis reported advanced age, higher blood urea nitrogen and N-terminal pro-B-type natriuretic peptide (NT-proBNP), lower haemoglobin, and failure to prescribe a beta-blocker as the five strongest predictors of mortality. Moreover, the five strongest predictors of hospitalisation due to decompensated HF were more advanced age, previous hospitalisation owing to HF, presence of oedema, lower systolic blood pressure and lower estimated glomerular filtration rate. Capitalizing from these preliminary results, the BIOTOOL-CHF VALID study will test the score derived from the analysis of the BIOTOOL-CHF DISCO dataset, in order to guide therapy management in HF patients.
Study Type
OBSERVATIONAL
Enrollment
4,254
Heart Failure and Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna
Bologna, Emilia-Romagna, Italy
The primary endpoint of the study will be time to death or first-hospitalisation for HF in the nine months after study entry
Time frame: 9 month
- Variability in the congestion score assessed from baseline to Month 9 - Variability in the Kansas City Cardiomyopathy Questionnaire from baseline to month 9
Time frame: 9 months
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