Nephrology Dialysis Transplantation, Vol 13, Issue 1 67-71, Copyright © 1998 by Oxford University Press
C Geddes, J Fox, M Allison, J Boulton-Jones and K Simpson
Background: The object of the study was to develop an
artificial neural network (ANN) to identify patients with IgA nephropathy
(IgAN) with a poor prognosis and to compare the predictions of the ANN with
the predictions of six experienced nephrologists.
Methods: The following data from the time of renal
biopsy were retrieved from the records of 54 patients with IgAN: age, sex,
systolic and diastolic blood pressure, number of prescribed
antihypertensive drugs, 24-h urine protein excretion, and serum creatinine.
Patients aged less than 14 years, or who had serum creatinine >350
&mgr;mol/l at presentation, liver disease or concomitant kidney disease
were excluded. Outcome was assigned as 'stable' if serum creatinine was
<150 &mgr;mol/l after 7 years and 'non-stable' if serum
creatinine was ⩾150 &mgr;mol/l. The ANN was trained and tested
using a 'jack-knife' sampling technique and performance evaluated in terms
of number of correct predictions, sensitivity and specificity. The six
nephrologists were asked to predict outcome at 7 years for each patient
using the same data as the ANN and their performance was assessed in the
same manner. Results: The ANN assigned the correct
outcome to 47/54 (87.0%) patients: sensitivity 19/22 (86.4%), specificity
28/32 (87.5%). The mean score for nephrologists was 37.5/54 (79.4%, range
35-40), mean sensitivity 72% and mean specificity 66%.
Conclusions: The ANN trained using routine clinical
information obtained at the time of diagnosis can potentially predict
7-year outcome for renal function in IgAN more accurately than experienced
nephrologists, and can therefore identify a group of high-risk patients
requiring close follow-up. Key words: age; artificial
neural network; computer; creatinine; hypertension; IgA nephropathy;
prediction; prognosis
ORIGINAL ARTICLES
An artificial network can select patients at high risk of developing progressive IgA nephropathy more accurately than experienced nephrologists
Renal Unit, Stobhill Hospital, Balornock Road, Glasgow G21 3UW, UK; Renal Unit, Glasgow Royal Infirmary, UK; Corresponding author
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