Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study.
Diabetes Metab Res Rev
; 40(5): e3832, 2024 Jul.
Article
em En
| MEDLINE
| ID: mdl-39031573
ABSTRACT
INTRODUCTION:
Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post-challenge hyperglycemia (IPH), that is., patients with normal fasting plasma glucose (<7.0 mmoL/L) and abnormal 2-h postprandial blood glucose (≥11.1 mmoL/L). We aimed to develop a model to differentiate individuals with IPH from the normal population.METHODS:
Data from 54301 eligible participants were obtained from the Risk Evaluation of Cancers in Chinese Diabetic Individuals a longitudinal (REACTION) study in China. Data from 37740 participants were used to develop the diagnostic system. External validation was performed among 16561 participants. Three machine learning algorithms were used to create the predictive models, which were further evaluated by various classification algorithms to establish the best predictive model.RESULTS:
Ten features were selected to develop an IPH diagnosis system (IPHDS) based on an artificial neural network. In external validation, the AUC of the IPHDS was 0.823 (95% CI 0.811-0.836), which was significantly higher than the AUC of the Taiwan model [0.799 (0.786-0.813)] and that of the Chinese Diabetes Risk Score model [0.648 (0.635-0.662)]. The IPHDS model had a sensitivity of 75.6% and a specificity of 74.6%. This model outperformed the Taiwan and CDRS models in subgroup analyses. An online site with instant predictions was deployed at https//app-iphds-e1fc405c8a69.herokuapp.com/.CONCLUSIONS:
The proposed IPHDS could be a convenient and user-friendly screening tool for diabetes during health examinations in a large general population.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Glicemia
/
Aprendizado de Máquina
/
Teste de Tolerância a Glucose
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Hiperglicemia
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
País/Região como assunto:
Asia
Idioma:
En
Revista:
Diabetes Metab Res Rev
Assunto da revista:
ENDOCRINOLOGIA
/
METABOLISMO
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China
País de publicação:
ENGLAND
/
ESCOCIA
/
GB
/
GREAT BRITAIN
/
INGLATERRA
/
REINO UNIDO
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SCOTLAND
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UK
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UNITED KINGDOM