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SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool
Disclosure: D. Awad: None. S. Kunwar: None. C.V. Desouza: None. Introduction: Maturity-onset diabetes of the young (MODY) is often misdiagnosed as type 1 or type 2 diabetes and is estimated to occur between 1-3% of all cases of diabetes. This leads to unnecessary treatments. There are no systemwide...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10554896/ http://dx.doi.org/10.1210/jendso/bvad114.948 |
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author | Awad, Dana Hashmi, Sulman Kunwar, Sandeep Desouza, Cyrus V |
author_facet | Awad, Dana Hashmi, Sulman Kunwar, Sandeep Desouza, Cyrus V |
author_sort | Awad, Dana |
collection | PubMed |
description | Disclosure: D. Awad: None. S. Kunwar: None. C.V. Desouza: None. Introduction: Maturity-onset diabetes of the young (MODY) is often misdiagnosed as type 1 or type 2 diabetes and is estimated to occur between 1-3% of all cases of diabetes. This leads to unnecessary treatments. There are no systemwide surveillance tools to identify these patients.Methods: This is a single center, cross sectional probable prevalence study of MODY in University of Nebraska medical center (UNMC). The medical records for all outpatients seen at UNMC within the past 5 years with the diagnosis of type 2 DM were reviewed. We included those with a diagnosis of type 2 DM who were <35 years old at the time of diagnosis, had A1C of < 7.6% and had a body mass index (BMI) < 30. We identified a total of 129 patients. 61 were excluded as they did not meet criteria. On the 68 remaining patients, the risk of MODY was calculated using the MODY probability calculator, which was developed by Exeter university. The calculator has the following variables: Age at diagnosis, current age, A1C, BMI, current diabetes treatment, time to insulin treatment, family history of diabetes, ethnicity, other associated features like renal cysts, deafness, lipodystrophy or other syndromic features. Results: Of the 68 included patients, 48% were females and 52% were males. Mean A1C was 6.3%, mean age at diagnosis was 28, mean BMI was 27. Thirty-four had at least one parent with diabetes. 54 were on diabetes treatment (17 on insulin and 37 on oral hypoglycemic agents). On the MODY calculator, 10 patients had a probability score of 75.5%, 3 had a score of 62.4%, 2 had a score of 58%, 3 had a score of 49%, and 3 had a score of 45.5%. The rest had a low probability score. The primary care physicians were informed of these results. The next step is to see how many of the primary care physicians utilize this information to screen patients. Conclusion: The MODY probability calculator is a good systemwide surveillance tool to identify patients with possible MODY and thereby inform providers taking care of those patients, which may result in management changes. Presentation: Saturday, June 17, 2023 |
format | Online Article Text |
id | pubmed-10554896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-105548962023-10-06 SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool Awad, Dana Hashmi, Sulman Kunwar, Sandeep Desouza, Cyrus V J Endocr Soc Diabetes And Glucose Metabolism Disclosure: D. Awad: None. S. Kunwar: None. C.V. Desouza: None. Introduction: Maturity-onset diabetes of the young (MODY) is often misdiagnosed as type 1 or type 2 diabetes and is estimated to occur between 1-3% of all cases of diabetes. This leads to unnecessary treatments. There are no systemwide surveillance tools to identify these patients.Methods: This is a single center, cross sectional probable prevalence study of MODY in University of Nebraska medical center (UNMC). The medical records for all outpatients seen at UNMC within the past 5 years with the diagnosis of type 2 DM were reviewed. We included those with a diagnosis of type 2 DM who were <35 years old at the time of diagnosis, had A1C of < 7.6% and had a body mass index (BMI) < 30. We identified a total of 129 patients. 61 were excluded as they did not meet criteria. On the 68 remaining patients, the risk of MODY was calculated using the MODY probability calculator, which was developed by Exeter university. The calculator has the following variables: Age at diagnosis, current age, A1C, BMI, current diabetes treatment, time to insulin treatment, family history of diabetes, ethnicity, other associated features like renal cysts, deafness, lipodystrophy or other syndromic features. Results: Of the 68 included patients, 48% were females and 52% were males. Mean A1C was 6.3%, mean age at diagnosis was 28, mean BMI was 27. Thirty-four had at least one parent with diabetes. 54 were on diabetes treatment (17 on insulin and 37 on oral hypoglycemic agents). On the MODY calculator, 10 patients had a probability score of 75.5%, 3 had a score of 62.4%, 2 had a score of 58%, 3 had a score of 49%, and 3 had a score of 45.5%. The rest had a low probability score. The primary care physicians were informed of these results. The next step is to see how many of the primary care physicians utilize this information to screen patients. Conclusion: The MODY probability calculator is a good systemwide surveillance tool to identify patients with possible MODY and thereby inform providers taking care of those patients, which may result in management changes. Presentation: Saturday, June 17, 2023 Oxford University Press 2023-10-05 /pmc/articles/PMC10554896/ http://dx.doi.org/10.1210/jendso/bvad114.948 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Diabetes And Glucose Metabolism Awad, Dana Hashmi, Sulman Kunwar, Sandeep Desouza, Cyrus V SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool |
title | SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool |
title_full | SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool |
title_fullStr | SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool |
title_full_unstemmed | SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool |
title_short | SAT082 Utility Of A MODY Probability Calculator As A Systemwide Surveillance Tool |
title_sort | sat082 utility of a mody probability calculator as a systemwide surveillance tool |
topic | Diabetes And Glucose Metabolism |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10554896/ http://dx.doi.org/10.1210/jendso/bvad114.948 |
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