Prediction of Type 2 Diabetes Mellitus using a Logistic Regression Model
<strong>Foundation:</strong> type 2 diabetes mellitus constitutes a growing epidemic and represents a substantial economic burden for health systems. Detecting the disease at an early stage helps reduce medical costs and the risk of patients having more complicated health problems. <s...
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| Format: | Article |
| Language: | Spanish |
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Centro Provincial de Información de Ciencias Médicas. Cienfuegos
2024-01-01
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| Series: | Medisur |
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| Online Access: | http://medisur.sld.cu/index.php/medisur/article/view/45108 |
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| author | Olivia Altamirano Guerrero Ronelsys Martínez Martínez Jhonny Alejandro Rodríguez Gutiérrez |
| author_facet | Olivia Altamirano Guerrero Ronelsys Martínez Martínez Jhonny Alejandro Rodríguez Gutiérrez |
| author_sort | Olivia Altamirano Guerrero |
| collection | DOAJ |
| description | <strong>Foundation:</strong> type 2 diabetes mellitus constitutes a growing epidemic and represents a substantial economic burden for health systems. Detecting the disease at an early stage helps reduce medical costs and the risk of patients having more complicated health problems. <strong><br />Objective:</strong> to design a mathematical model to predict the type 2 diabetes mellitus probability of existence in patients treated at a hospital in Guayaquil, Ecuador. <br /><strong>Method:</strong> a descriptive and cross-sectional study was carried out. The population was made up of 324 patients. The statistical procedure was based on the binary logistic regression application. To evaluate the predictive capacity of the model, Cohen's Kappa test was used. <br /><strong>Results:</strong> high blood pressure was a positive risk factor for type 2 diabetes mellitus, with a probability coefficient of 1.415. Positive family history influenced the increased probability. Alcohol consumption was a positive risk factor and the coefficient of 0.790 indicated how much it contributed to the increased probability. The Kappa coefficient had a value of 0.434; with approximate T of 7.809 and p < 0.001, it indicated greater prevalence than bias and greater agreement between what was predicted in the model and what was observed. <br /><strong>Conclusions:</strong> the presence of high blood pressure, positive family history and alcohol consumption were significant factors that increased the probability of developing type 2 diabetes mellitus. Early detection and management of these risk factors is important in the prevention and management of the illness. |
| format | Article |
| id | doaj-art-493be2f2a4364fe982786f0ce88e1662 |
| institution | Kabale University |
| issn | 1727-897X |
| language | Spanish |
| publishDate | 2024-01-01 |
| publisher | Centro Provincial de Información de Ciencias Médicas. Cienfuegos |
| record_format | Article |
| series | Medisur |
| spelling | doaj-art-493be2f2a4364fe982786f0ce88e16622025-01-30T21:29:02ZspaCentro Provincial de Información de Ciencias Médicas. CienfuegosMedisur1727-897X2024-01-0121676822435Prediction of Type 2 Diabetes Mellitus using a Logistic Regression ModelOlivia Altamirano Guerrero0Ronelsys Martínez Martínez1Jhonny Alejandro Rodríguez Gutiérrez2Universidad Regional Autónoma de los Andes. Ambato. Ecuador.Universidad Regional Autónoma de los Andes. Ambato. Ecuador.Universidad Regional Autónoma de los Andes. Ambato. Ecuador.<strong>Foundation:</strong> type 2 diabetes mellitus constitutes a growing epidemic and represents a substantial economic burden for health systems. Detecting the disease at an early stage helps reduce medical costs and the risk of patients having more complicated health problems. <strong><br />Objective:</strong> to design a mathematical model to predict the type 2 diabetes mellitus probability of existence in patients treated at a hospital in Guayaquil, Ecuador. <br /><strong>Method:</strong> a descriptive and cross-sectional study was carried out. The population was made up of 324 patients. The statistical procedure was based on the binary logistic regression application. To evaluate the predictive capacity of the model, Cohen's Kappa test was used. <br /><strong>Results:</strong> high blood pressure was a positive risk factor for type 2 diabetes mellitus, with a probability coefficient of 1.415. Positive family history influenced the increased probability. Alcohol consumption was a positive risk factor and the coefficient of 0.790 indicated how much it contributed to the increased probability. The Kappa coefficient had a value of 0.434; with approximate T of 7.809 and p < 0.001, it indicated greater prevalence than bias and greater agreement between what was predicted in the model and what was observed. <br /><strong>Conclusions:</strong> the presence of high blood pressure, positive family history and alcohol consumption were significant factors that increased the probability of developing type 2 diabetes mellitus. Early detection and management of these risk factors is important in the prevention and management of the illness.http://medisur.sld.cu/index.php/medisur/article/view/45108diabetes mellitus tipo 2predicciónfactores de riesgomodelos logísticosdiagnósticoecuador |
| spellingShingle | Olivia Altamirano Guerrero Ronelsys Martínez Martínez Jhonny Alejandro Rodríguez Gutiérrez Prediction of Type 2 Diabetes Mellitus using a Logistic Regression Model Medisur diabetes mellitus tipo 2 predicción factores de riesgo modelos logísticos diagnóstico ecuador |
| title | Prediction of Type 2 Diabetes Mellitus using a Logistic Regression Model |
| title_full | Prediction of Type 2 Diabetes Mellitus using a Logistic Regression Model |
| title_fullStr | Prediction of Type 2 Diabetes Mellitus using a Logistic Regression Model |
| title_full_unstemmed | Prediction of Type 2 Diabetes Mellitus using a Logistic Regression Model |
| title_short | Prediction of Type 2 Diabetes Mellitus using a Logistic Regression Model |
| title_sort | prediction of type 2 diabetes mellitus using a logistic regression model |
| topic | diabetes mellitus tipo 2 predicción factores de riesgo modelos logísticos diagnóstico ecuador |
| url | http://medisur.sld.cu/index.php/medisur/article/view/45108 |
| work_keys_str_mv | AT oliviaaltamiranoguerrero predictionoftype2diabetesmellitususingalogisticregressionmodel AT ronelsysmartinezmartinez predictionoftype2diabetesmellitususingalogisticregressionmodel AT jhonnyalejandrorodriguezgutierrez predictionoftype2diabetesmellitususingalogisticregressionmodel |