Literature DB >> 26586851

The predictive value of low plasma copper and high plasma zinc in detecting zinc-induced copper deficiency.

Andrew Duncan1, Dinesh Talwar2, Ian Morrison3.   

Abstract

BACKGROUND: Zinc-induced copper deficiency is a condition whose diagnosis is often delayed allowing severe and usually irreversible neurology symptoms to develop. Plasma copper concentrations are usually low and plasma zinc concentrations high. The aim of this study was to measure the predictive value of this combination of results as a means of facilitating its early diagnosis.
METHODS: Low plasma copper (≤6 µmol/L) and high plasma zinc results (>18 µmol/L) were retrieved from the laboratory database from 2000 to 2014. Medical records and laboratory notes of the corresponding 20 patients found were accessed to determine which were likely to have zinc-induced copper deficiency.
RESULTS: Fifteen (75%) patients were diagnosed with zinc-induced copper deficiency which was symptomatic in 13. Of the five remaining patients, two were treated with zinc because of Wilson's disease which was the cause of hypocupraemia, two were treated parenterally with zinc, and insufficient information was available in the final patient.
CONCLUSIONS: The combination of a low plasma copper and high plasma zinc is strongly predictive for the diagnosis of zinc-induced copper deficiency. There is the therefore an opportunity for the reporting biochemist to facilitate in its earlier diagnosis so enabling treatment to be implemented before the condition deteriorates.
© The Author(s) 2016.

Entities:  

Keywords:  Epidemiology studies; clinical studies; haemoglobin disorders; neurological disorders

Mesh:

Substances:

Year:  2015        PMID: 26586851     DOI: 10.1177/0004563215620821

Source DB:  PubMed          Journal:  Ann Clin Biochem        ISSN: 0004-5632            Impact factor:   2.057


  3 in total

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Journal:  EJHaem       Date:  2021-08-26

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Authors:  Takako Suzuki; Yukio Nakamura; Hiroyuki Kato
Journal:  Nutrients       Date:  2017-08-13       Impact factor: 5.717

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Authors:  Keizo Nishime; Morihiro Kondo; Kazuhiro Saito; Hisashi Miyawaki; Takahiko Nakagawa
Journal:  Nutrients       Date:  2020-02-23       Impact factor: 5.717

  3 in total

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