Analyzing pulsatile endocrine data in patients with chronic renal failure: a brief review of deconvolution techniques

Johannes D. Veldhuis, Michael L. Johnson, Warren K. Bolton

Research output: Contribution to journalReview articlepeer-review

14 Scopus citations

Abstract

Deconvolution analysis provides an important new technique to evaluate underlying hormone secretory rates quantitatively based upon serially measured plasma hormone concentrations with or without prior knowledge of the half-time of hormone disappearance from the blood. Information about endocrine gland secretion is particularly important in chronic renal failure, wherein the decreased metabolic clearance rates of various hormones would otherwise confound the interpretation of plasma hormone concentrations. Here we review two particularly useful techniques of deconvolution, one of which is a waveformdefined algorithm and the other waveform independent. The first method can be used to estimate both hormone half-life and secretory rates in vivo. The second methodology allows calculation of in vivo hormone secretion rates without assuming any special form for the secretion event, but requires a priori knowledge of hormone half-life. We illustrate examples of these two deconvolution approaches, and discuss why the interpretations of hormone concentration measurements in earlier studies (where deconvolution methods were not employed) must be viewed with caution. Based on such considerations, additional investigations of in vivo hormone secretory pathophysiology will be required in children and adults with chronic renal failure.

Original languageEnglish (US)
Pages (from-to)522-528
Number of pages7
JournalPediatric Nephrology
Volume5
Issue number4
DOIs
StatePublished - Jul 1991

Keywords

  • Chronic renal failure
  • Deconvolution analysis
  • Hormone secretory rate

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Nephrology

Fingerprint

Dive into the research topics of 'Analyzing pulsatile endocrine data in patients with chronic renal failure: a brief review of deconvolution techniques'. Together they form a unique fingerprint.

Cite this