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A Simple and Early Prognostic Index for Acute Renal Failure Patients Requiring Renal Replacement Therapy
Author(s) -
Yuasa Shigekazu,
Takahashi Norihiro,
Shoji Tetsuo,
Uchida Koichi,
Kiyomoto Hideyasu,
Hashimoto Mayuko,
Fujioka Hiroshi,
Fujita Yoko,
Hitomi Hirofumi,
Matsuo Hirohide
Publication year - 1998
Publication title -
artificial organs
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.684
H-Index - 76
eISSN - 1525-1594
pISSN - 0160-564X
DOI - 10.1046/j.1525-1594.1998.06025.x
Subject(s) - renal replacement therapy , medicine , intensive care medicine , acute kidney injury , cardiology
Recent advances in technology have not substantially changed the high mortality rate associated with acute renal failure (ARF). To obtain a simple, valid prognostic index, we retrospectively evaluated the relative importance of demographic data, causes (acute insults) of renal failure, and comorbid clinical conditions for the outcome in 102 ARF patients who received renal replacement therapy with an overall mortality rate of 65% (66 of 102). There were no significant differences between survivors and nonsurvivors in age and gender. Mortality according to acute insults was similar to that of the whole population studied. Of the 10 clinical conditions at the time of the first renal replacement therapy, mechanical ventilation (p = 0.0002), cardiac failure (p = 0.0006), hepatic failure (p = 0.003), central nervous system dysfunction (p = 0.005), and oliguria (p = 0.04) were found to be significantly related to mortality by univariate analysis. Furthermore, multivariate analysis demonstrated that only mechanical ventilation, cardiac failure, and hepatic failure were significant risk factors. Survival was directly related to the number of significant variables in univariate analysis: zero, 89% (8 of 9); one, 62% (21 of 34); two, 19% (5 of 27); three, 10% (2 of 20); four, 0% (0 of 8); five, 0% (0 of 4). This simple and early prognostic index, derived from the assessment of clinical conditions which were easily de‐termined at the patient's bedside, could be useful for outcome prediction in ARF patients requiring renal replacement therapy.