Multivariate analysis using a linear discriminant function for predicting the prognosis of congestive heart failure.

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Abstract
Some of cases of congestive heart failure (CHF) are intractable or refractory and respond poorly to conventional treatment. We have examined factors which may influence the clinical course and prognosis. The subjects were 114 hospitalized patients with CHF. Of these, 77 had a good response to treatment and were classified as the curative group (Group C) while the remaining 37 who were difficult to treat, including those with poor prognosis, were designated the refractory group (Group R). Of the various clinical background factors including the findings of laboratory and other examinations, the following 8 variables made a significant contribution to differentiation between the 2 groups: 1) heart rate (X1), 2) hemoglobin content (X2), 3) serum K (X3), 4) serum total protein (X4), 5) A/G (X5), 6) BUN (X6), 7) grade of hepatomegaly (X7), and 8) number of previous CHF episodes (X8). The linear discriminant function represented by the following equation using these 8 variables showed an excellent result in differentiating the 2 groups. Y = -9.64 - 0.0686X1 + 0.345X2 + 1.351X3 + 1.513X4 + + 1.988X5 - 0.0876X6 - 0.792X7 - 0.737X8 When Y value is over 0, Group C is judged. When Y value is under 0, group R is judged. We concluded that the discriminant equation covering these 8 factors is a useful means of predicting the prognosis in CHF and the response to treatment.

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