Using Hemoglobin A1C as a Predicting Model for Time Interval from Pre-Diabetes Progressing to Diabetes

Autor: Zih Fang Chen, Phung Anh Nguyen, Chung Huei Hsu, Usman Iqbal, Daniel L. Clinciu, Wen-Shan Jian, Yi Hsin Elsa Hsu, Chen-Ling Huang
Rok vydání: 2014
Předmět:
Blood Glucose
Male
Time Factors
Epidemiology
Global Health
Computer Applications
Endocrinology
Risk Factors
Medicine and Health Sciences
Public and Occupational Health
Stage (cooking)
Aged
80 and over
Multidisciplinary
Applied Mathematics
Middle Aged
Prognosis
Research Design
Pre diabetes
Physical Sciences
Disease Progression
Medicine
Female
Information Technology
Algorithms
Research Article
Computer Modeling
Adult
Computer and Information Sciences
medicine.medical_specialty
Clinical Research Design
Science
Oral Medicine
Research and Analysis Methods
Prediabetic State
Internal medicine
Diabetes mellitus
Linear regression
medicine
Humans
Hospital patients
Primary Care
Nutrition
Aged
Glycated Hemoglobin
business.industry
Biology and Life Sciences
medicine.disease
Computing Methods
Surgery
Health Care
Standard error
Diabetes Mellitus
Type 2
Metabolic Disorders
Interval (graph theory)
Hemoglobin
business
Mathematics
Zdroj: PLoS ONE
PLoS ONE, Vol 9, Iss 8, p e104263 (2014)
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0104263
Popis: ObjectiveThe early identification of subjects at high risk for diabetes is essential, thus, random rather than fasting plasma glucose is more useful. We aim to evaluate the time interval between pre-diabetes to diabetes with anti-diabetic drugs by using HbA1C as a diagnostic tool, and predicting it using a mathematic model.MethodsWe used the Taipei Medical University Affiliated Hospital Patient Profile Database (AHPPD) from January-2007 to June-2011. The patients who progressed and were prescribed anti-diabetic drugs were selected from AHPPD. The mathematical model used to predict the time interval of HbA1C value ranged from 5.7% to 6.5% for diabetes progression.ResultsWe predicted an average overall time interval for all participants in between 5.7% to 6.5% during a total of 907 days (standard error, 103 days). For each group found among 5.7% to 6.5% we determined 1169.3 days for the low risk group (i.e. 3.2 years), 1080.5 days (i.e. 2.96 years) for the increased risk group and 729.4 days (i.e. 1.99 years) for the diabetes group. This indicates the patients will take an average of 2.49 years to reach 6.5%.ConclusionThis prediction model is very useful to help prioritize the diagnosis at an early stage for targeting individuals with risk of diabetes. Using patients' HbA1C before anti-diabetes drugs are used we predicted the time interval from pre-diabetes progression to diabetes is 2.49 years without any influence of age and gender. Additional studies are needed to support this model for a long term prediction.
Databáze: OpenAIRE
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