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Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood

An assessment of levels of Insulin in cadaveric fluids, to estimate the postmortem interval (PMI) was carried out. To profile postmortem changes of Insulin, it was extracted at different intervals i.e. (0, 3, 6, 12, 24 h), from the heart of 22 human cadavers. The cases included were the subjects of...

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Autores principales: Kumar, Sachil, Verma, Anoop K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4781973/
https://www.ncbi.nlm.nih.gov/pubmed/26977436
http://dx.doi.org/10.1016/j.dib.2016.02.059
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author Kumar, Sachil
Verma, Anoop K.
author_facet Kumar, Sachil
Verma, Anoop K.
author_sort Kumar, Sachil
collection PubMed
description An assessment of levels of Insulin in cadaveric fluids, to estimate the postmortem interval (PMI) was carried out. To profile postmortem changes of Insulin, it was extracted at different intervals i.e. (0, 3, 6, 12, 24 h), from the heart of 22 human cadavers. The cases included were the subjects of accidental deaths without any prior history of disease and their exact time of death was known. Immunoanalyzer Cobas e-411 instrument was used to detect the relationship between the amount of Insulin and PMI. Level of Insulin was measured in cardiac blood. Statically, significant correlations between levels of Insulin and PMI were studied and correlation coefficients were calculated. SPSS (version 12.0) was used for statistical analysis. Insulin levels in cadaver blood are correlated significantly with PMI with a p value of <0.001. When insulin level increases by 1 unit the duration decreases by 0.93 units. The least square regression line is: [Duration(Y)=22.71−0.93 Insulin level (X)]
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spelling pubmed-47819732016-03-14 Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood Kumar, Sachil Verma, Anoop K. Data Brief Data Article An assessment of levels of Insulin in cadaveric fluids, to estimate the postmortem interval (PMI) was carried out. To profile postmortem changes of Insulin, it was extracted at different intervals i.e. (0, 3, 6, 12, 24 h), from the heart of 22 human cadavers. The cases included were the subjects of accidental deaths without any prior history of disease and their exact time of death was known. Immunoanalyzer Cobas e-411 instrument was used to detect the relationship between the amount of Insulin and PMI. Level of Insulin was measured in cardiac blood. Statically, significant correlations between levels of Insulin and PMI were studied and correlation coefficients were calculated. SPSS (version 12.0) was used for statistical analysis. Insulin levels in cadaver blood are correlated significantly with PMI with a p value of <0.001. When insulin level increases by 1 unit the duration decreases by 0.93 units. The least square regression line is: [Duration(Y)=22.71−0.93 Insulin level (X)] Elsevier 2016-03-02 /pmc/articles/PMC4781973/ /pubmed/26977436 http://dx.doi.org/10.1016/j.dib.2016.02.059 Text en © 2016 Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Kumar, Sachil
Verma, Anoop K.
Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood
title Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood
title_full Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood
title_fullStr Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood
title_full_unstemmed Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood
title_short Estimation of postmortem interval using the data of insulin level in the cadaver׳s blood
title_sort estimation of postmortem interval using the data of insulin level in the cadaver׳s blood
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4781973/
https://www.ncbi.nlm.nih.gov/pubmed/26977436
http://dx.doi.org/10.1016/j.dib.2016.02.059
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