Journal
HYPERTENSION RESEARCH
Volume 36, Issue 5, Pages 450-456Publisher
SPRINGERNATURE
DOI: 10.1038/hr.2012.200
Keywords
heart failure; mathematical model; prognosis; rehospitalization
Categories
Funding
- Japanese Ministry of Health, Labor and Welfare [H23-Nanchi-Ippan-22]
- Japanese Ministry of Education, Culture, Sports, Science and Technology [21390251]
- Japan Heart Foundation
- Japan Cardiovascular Research Foundation
- Grants-in-Aid for Scientific Research [21390251] Funding Source: KAKEN
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The prognoses for patients with certain diseases are estimated by averaging the results of clinical trials. To investigate the possibility of deriving a mathematical formula for the estimation of prognosis, we formulated the equation tau = f(x(1), ..., x(p)), where x(1), ..., x(p) are clinical features and tau represents the clinical outcome for heart failure (HF). We attempted to determine the function to mathematically formulate the relationship between clinical features and outcomes for these patients. We followed 151 patients (mean age: 68.6 +/- 14.6 years; men: 61.6%) who were consecutively hospitalized and discharged as a result of acute decompensated HF (ADHF) between May 2006 and December 2009. The mathematical analysis was performed through a probabilistic modeling of the relational data by assuming a Poisson process for rehospitalization owing to HF and by linearly approximating the relationship between the clinical factors and the mean elapsed time to rehospitalization. The former assumption was validated by a statistical test of the data, and the contribution of each parameter was assessed based on the coefficients of the linear relation. Using a regularization method to analyze 402 clinical parameters, we identified 252 factors that substantially influenced the elapsed time until rehospitalization. With the probability model based on the Poisson process, the actual (X; 388 +/- 377 days) and estimated (Y; 398 +/- 381 days) elapsed times to rehospitalization were tightly correlated (Y = 1.0076X + 6.5531, R-2 = 0.9879, P<0.0001). We established a mathematical formula that closely predicts the clinical outcomes of patients who are hospitalized with ADHF and discharged after appropriate treatment.
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