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Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep
Despite being important, there are no equations for prediction of ionized calcium (iCa) in sheep and cattle. The objectives of this study were i) to create equations for the calculation of serum iCa concentration based on the serum concentrations of total calcium (tCa), albumin (Alb) and total prote...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Urmia University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840791/ https://www.ncbi.nlm.nih.gov/pubmed/36686876 http://dx.doi.org/10.30466/vrf.2021.139252.3096 |
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author | Katsoulos, Panagiotis Dimitrios Athanasiou, Labrini Vasileiou Dedousi, Anna Polizopoulou, Zoe |
author_facet | Katsoulos, Panagiotis Dimitrios Athanasiou, Labrini Vasileiou Dedousi, Anna Polizopoulou, Zoe |
author_sort | Katsoulos, Panagiotis Dimitrios |
collection | PubMed |
description | Despite being important, there are no equations for prediction of ionized calcium (iCa) in sheep and cattle. The objectives of this study were i) to create equations for the calculation of serum iCa concentration based on the serum concentrations of total calcium (tCa), albumin (Alb) and total proteins (TP) and ii) to investigate whether predicted serum iCa values are beneficial in clinical practice. Serum samples from 30 sheep and 30 dairy cattle were used. Serum tCa was determined colorimetrically, while serum iCa was determined with an ion selective electrode method. Serum Alb and TP concentration were determined using bromo-cresol green and biuret methods, respectively. Ionized calcium was also calculated based on serum tCa, using regression analysis, and with two equations based on Alb and TP concentration. Bland–Altman plots were plotted to evaluate the agreement between measured and predicted iCa; Passing and Bablok (P - B) regression analysis was used to assess their agreement. The initial equations were corrected using the P - B generated equation and Bland – Altman plots were run to evaluate the level of agreement between measured and predicted iCa using the final equations. Six equations were finally created for cattle and 6 for sheep. The total bias exceeded 10.00% in all of them indicating that they are clinically unacceptable for iCa prediction especially when the predicted result is very close to the cut-off point of < 1.00 mmol L(-1). So, it could be suggested that, when necessary, iCa concentration should be directly determined. |
format | Online Article Text |
id | pubmed-9840791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Urmia University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98407912023-01-20 Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep Katsoulos, Panagiotis Dimitrios Athanasiou, Labrini Vasileiou Dedousi, Anna Polizopoulou, Zoe Vet Res Forum Original Article Despite being important, there are no equations for prediction of ionized calcium (iCa) in sheep and cattle. The objectives of this study were i) to create equations for the calculation of serum iCa concentration based on the serum concentrations of total calcium (tCa), albumin (Alb) and total proteins (TP) and ii) to investigate whether predicted serum iCa values are beneficial in clinical practice. Serum samples from 30 sheep and 30 dairy cattle were used. Serum tCa was determined colorimetrically, while serum iCa was determined with an ion selective electrode method. Serum Alb and TP concentration were determined using bromo-cresol green and biuret methods, respectively. Ionized calcium was also calculated based on serum tCa, using regression analysis, and with two equations based on Alb and TP concentration. Bland–Altman plots were plotted to evaluate the agreement between measured and predicted iCa; Passing and Bablok (P - B) regression analysis was used to assess their agreement. The initial equations were corrected using the P - B generated equation and Bland – Altman plots were run to evaluate the level of agreement between measured and predicted iCa using the final equations. Six equations were finally created for cattle and 6 for sheep. The total bias exceeded 10.00% in all of them indicating that they are clinically unacceptable for iCa prediction especially when the predicted result is very close to the cut-off point of < 1.00 mmol L(-1). So, it could be suggested that, when necessary, iCa concentration should be directly determined. Urmia University Press 2022 2022-12-15 /pmc/articles/PMC9840791/ /pubmed/36686876 http://dx.doi.org/10.30466/vrf.2021.139252.3096 Text en https://creativecommons.org/licenses/by-nc-sa/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly.https://creativecommons.org/licenses/by-nc-sa/4.0/ |
spellingShingle | Original Article Katsoulos, Panagiotis Dimitrios Athanasiou, Labrini Vasileiou Dedousi, Anna Polizopoulou, Zoe Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep |
title | Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep |
title_full | Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep |
title_fullStr | Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep |
title_full_unstemmed | Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep |
title_short | Prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep |
title_sort | prediction of ionized calcium concentration based on total calcium and protein levels in cattle and sheep |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840791/ https://www.ncbi.nlm.nih.gov/pubmed/36686876 http://dx.doi.org/10.30466/vrf.2021.139252.3096 |
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