DETERMINE-AHF Composite Outcome Calculator

DETERMINE-AHF Composite Outcome Algorithm — Explanation and Clinical Context This page implements a prototype calculator designed to estimate the probability of a pre-specified composite adverse outcome in acute heart failure (AHF) using a logistic regression style formula. The prototype accepts common, admission-time clinical variables (age, systolic blood pressure, heart rate, creatinine, BUN, NT-proBNP, LVEF, and presence of chronic kidney disease) and calculates a logistic probability from a linear predictor formed by coefficients multiplied by each variable. The code intentionally uses placeholder coefficients and a placeholder intercept; the authentic DETERMINE-AHF model requires the exact coefficients, variable transforms, and intercept reported in the original publication.

Once the original paper's coefficients and exact variable definitions (including units and any logarithmic transforms) are inserted into the PHP block, the calculator will produce the model's original predicted probabilities and risk categories. This approach (logistic linear predictor → logistic transform → probability) is a standard and transparent method for deployment of clinical prediction models in web calculators; care must be taken to preserve exact variable scaling and transformations from the source publication when implementing a published model. Reference / Context: I could not locate an accessible original full-text description of the DETERMINE-AHF coefficients during searching; therefore for clinical context and alternative validated AHF risk models consult reviews and well-known scores such as MEESSI-AHF and contemporary reviews of AHF risk stratification.

See references below for context on acute heart failure risk scores and prognostic model reporting.