How accurately do nephrologists predict the need for dialysis within one year?

Darren Green, James P Ritchie, David I New, Philip A Kalra

Research output: Contribution to journalArticlepeer-review


BACKGROUND/AIMS: Knowing when patients with chronic kidney disease will need dialysis can improve patient counselling and timing of vascular access. We aimed to assess the accuracy of clinician judgement in predicting the need for dialysis within 12 months.

METHODS: We asked the nephrologists in a dedicated pre-dialysis clinic to predict the time until initiation of dialysis for patients. We compared predicted with actual time to dialysis and the accuracy of predictions made by different grades of clinician. Multivariate logistic regression compared clinical parameters that correlated with predicted and actual time to dialysis.

RESULTS: One hundred and eighty-four patients were included. The sensitivity of clinician judgement as a predictor of dialysis within 12 months was 95% and the specificity was 62%. Consultants were correct in 71% of cases and trainees in 68% of cases. Estimated glomerular filtration rate (eGFR) was the only independent correlate of predicted time to dialysis [odds ratio (OR) = 1.6 per 1 ml/min/1.73 m(2) reduction, p < 0.001]. eGFR was also associated with actual time to dialysis (OR = 1.6 per 1 ml/min/1.73 m(2), p < 0.001) along with age (OR = 0.94 per year increase, p = 0.005) and itch (OR = 3.7, p = 0.048).

CONCLUSION: Clinical judgement is sensitive but not specific in predicting the need for dialysis. Educating the clinicians may improve the specificity of judgement and improve the accuracy of prognostic information given to patients.

Original languageEnglish
Pages (from-to)102-6
Number of pages5
JournalNephron - Clinical Practice
Issue number3-4
Publication statusPublished - 2012


  • Decision Making
  • Female
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Needs Assessment
  • Nephrology
  • Patient Care Planning
  • Prognosis
  • Renal Dialysis
  • Renal Insufficiency, Chronic
  • Reproducibility of Results
  • Risk Factors
  • Sensitivity and Specificity
  • Treatment Outcome
  • United Kingdom
  • Clinical Trial
  • Journal Article


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