TY - JOUR

T1 - The impact of creating mathematical formula to predict cardiovascular events in patients with heart failure

AU - Sakamoto, Mari

AU - Fukuda, Hiroki

AU - Kim, Jiyoong

AU - Ide, Tomomi

AU - Kinugawa, Shintaro

AU - Fukushima, Arata

AU - Tsutsui, Hiroyuki

AU - Ishii, Akira

AU - Ito, Shin

AU - Asanuma, Hiroshi

AU - Asakura, Masanori

AU - Washio, Takashi

AU - Kitakaze, Masafumi

PY - 2018/12/1

Y1 - 2018/12/1

N2 - Since our retrospective study has formed a mathematical formula, α = f(x 1, .., x 252), where α is the probability of cardiovascular events in patients with heart failure (HF) and x 1 is each clinical parameter, we prospectively tested the predictive capability and feasibility of the mathematical formula of cardiovascular events in HF patients. First of all, to create such a mathematical formula using limited number of the parameters to predict the cardiovascular events in HF patients, we retrospectively determined f(x) that formulates the relationship between the most influential 50 clinical parameters (x) among 252 parameters using 167 patients hospitalized due to acute HF; the nonlinear optimization could provide the formula of α = f(x 1, .., x 50) which fitted the probability of the actual cardiovascular events per day. Secondly, we prospectively examined the predictability of f(x) in other 213 patients using 50 clinical parameters in 3 hospitals, and we found that the Kaplan-Meier curves using actual and estimated occurrence probabilities of cardiovascular events were closely correlated. We conclude that we created a mathematical formula f(x) that precisely predicted the occurrence probability of future cardiovascular outcomes of HF patients per day. Mathematical modelling may predict the occurrence probability of cardiovascular events in HF patients.

AB - Since our retrospective study has formed a mathematical formula, α = f(x 1, .., x 252), where α is the probability of cardiovascular events in patients with heart failure (HF) and x 1 is each clinical parameter, we prospectively tested the predictive capability and feasibility of the mathematical formula of cardiovascular events in HF patients. First of all, to create such a mathematical formula using limited number of the parameters to predict the cardiovascular events in HF patients, we retrospectively determined f(x) that formulates the relationship between the most influential 50 clinical parameters (x) among 252 parameters using 167 patients hospitalized due to acute HF; the nonlinear optimization could provide the formula of α = f(x 1, .., x 50) which fitted the probability of the actual cardiovascular events per day. Secondly, we prospectively examined the predictability of f(x) in other 213 patients using 50 clinical parameters in 3 hospitals, and we found that the Kaplan-Meier curves using actual and estimated occurrence probabilities of cardiovascular events were closely correlated. We conclude that we created a mathematical formula f(x) that precisely predicted the occurrence probability of future cardiovascular outcomes of HF patients per day. Mathematical modelling may predict the occurrence probability of cardiovascular events in HF patients.

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U2 - 10.1038/s41598-018-22347-0

DO - 10.1038/s41598-018-22347-0

M3 - Article

C2 - 29507373

AN - SCOPUS:85043265996

VL - 8

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 3986

ER -