Critical evaluation of equations for serum osmolality: Proposals for effective clinical utility.

Equations Formula Harmonization Osmolal gap Serum osmolality Serum osmolarity Standardization

Journal

Clinica chimica acta; international journal of clinical chemistry
ISSN: 1873-3492
Titre abrégé: Clin Chim Acta
Pays: Netherlands
ID NLM: 1302422

Informations de publication

Date de publication:
Nov 2020
Historique:
received: 14 06 2020
revised: 26 06 2020
accepted: 26 06 2020
pubmed: 6 7 2020
medline: 22 6 2021
entrez: 6 7 2020
Statut: ppublish

Résumé

Many studies have assessed the predictive accuracy of serum osmolality equations. Different approaches for selecting a usable equation were compared using thirty published equations and patient data from a regional hospital laboratory. Laboratory records were extracted with same-sample results for measured serum osmolality, sodium, potassium, urea and glucose analysed in a regional hospital laboratory between 1/1/2017-31/12/2018. Differences were analysed using Passing-Bablok and difference (Bland-Altman) analysis. Three approaches were compared: the shotgun approach, adjusting for bias, and deriving a novel equation using multivariate analysis. The criteria for success included bias ≤0.7%, a 230 - 400 mOsm/kg range, and osmolal gap (OG) 95% reference limits within ±10 mOsm/kg. The majority of equations produced proportionally negative-biased results. The shotgun approach identified two equations (EQ19, EQ6) with bias ≤0.7% but unworkable OG reference limits. The bias adjustment approach produced several equations with bias ≤ 0.7% and OG reference limits within or equivalent to ±10 mOsm/kg. A novel equation generated by us (1.89Na Few published equations are immediately usable. Adjustment of bias derives several usable equations of which the best had OG ranges <20 mOsm/kg. We conclude that adjustment of bias can generate equations of equal or superior performance to that of novel equations.

Sections du résumé

BACKGROUND BACKGROUND
Many studies have assessed the predictive accuracy of serum osmolality equations. Different approaches for selecting a usable equation were compared using thirty published equations and patient data from a regional hospital laboratory.
METHODS METHODS
Laboratory records were extracted with same-sample results for measured serum osmolality, sodium, potassium, urea and glucose analysed in a regional hospital laboratory between 1/1/2017-31/12/2018. Differences were analysed using Passing-Bablok and difference (Bland-Altman) analysis. Three approaches were compared: the shotgun approach, adjusting for bias, and deriving a novel equation using multivariate analysis. The criteria for success included bias ≤0.7%, a 230 - 400 mOsm/kg range, and osmolal gap (OG) 95% reference limits within ±10 mOsm/kg.
RESULTS RESULTS
The majority of equations produced proportionally negative-biased results. The shotgun approach identified two equations (EQ19, EQ6) with bias ≤0.7% but unworkable OG reference limits. The bias adjustment approach produced several equations with bias ≤ 0.7% and OG reference limits within or equivalent to ±10 mOsm/kg. A novel equation generated by us (1.89Na
CONCLUSION CONCLUSIONS
Few published equations are immediately usable. Adjustment of bias derives several usable equations of which the best had OG ranges <20 mOsm/kg. We conclude that adjustment of bias can generate equations of equal or superior performance to that of novel equations.

Identifiants

pubmed: 32622969
pii: S0009-8981(20)30307-7
doi: 10.1016/j.cca.2020.06.043
pii:
doi:

Substances chimiques

Urea 8W8T17847W
Sodium 9NEZ333N27
Potassium RWP5GA015D

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

79-87

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Auteurs

Emmanuel O Ebonwu (EO)

Tshwane University of Technology (TUT), Staatsartillerie Rd, Pretoria-West, Pretoria 0183, South Africa; Department of Chemical Pathology, Faculty of Health Sciences, University of Pretoria and National Health Laboratory Service (NHLS) Tshwane Academic Division, Pretoria, South Africa.

Susanna E Nagel (SE)

Department of Chemical Pathology, Faculty of Health Sciences, University of Pretoria and National Health Laboratory Service (NHLS) Tshwane Academic Division, Pretoria, South Africa.

Lisa Repsold (L)

Tshwane University of Technology (TUT), Staatsartillerie Rd, Pretoria-West, Pretoria 0183, South Africa.

Tahir S Pillay (TS)

Department of Chemical Pathology, Faculty of Health Sciences, University of Pretoria and National Health Laboratory Service (NHLS) Tshwane Academic Division, Pretoria, South Africa; Division of Chemical Pathology, Faculty of Health Sciences, University of Cape Town, South Africa. Electronic address: tspillay@gmail.com.

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Classifications MeSH