Assessment of cut-off for average glucose metabolic index-a new scoring for pre-diabetes: Evaluated among population of South Gujarat

Introduction

In the tenth edition of IDF reporting it was found that the prevalence of Diabetes mellitus in the world is around 9% (537 million adults) in 2021 [1] . Also 541 million people are found to be having decreased glucose tolerance. In Diabetes Atlas 10 th edition it was given that one in six pregnancy is prone to Hyperglycaemia in pregnancy and also 45 % of diabetes in the world are undiagnosed which is mostly Type 2 .So we require a more advanced method for diagnosing Diabetes. Diabetes have become a threat to low and middle income countries and also India So it requires multipronged strategy to tackle it efficiently [2] . Fasting Blood Glucose is the first parameter that is used to diagnose diabetes. HbA1c is glycated haemoglobin percentage which suggests elevated blood glucose level in the blood for prolonged periods for approximately 3-6 months. Glucose tolerance test helps us to determine the type of diabetes in patients. But we need screening test to detect diabetes early in pre diabetic stage so that we can treat it early HOMA IR scoring evaluate Insulin resistance in prediabetis individuals but it has its own limitations [4,5,6] . Fasting Blood glucose and insulin are measure at a particular point of time and it can vary over time.

The validity of HOMA IR should be carefully evaluated in individuals with low BMI, beta cell dysfunction and patients on oral hypoglycaemic drugs. Other scoring available is METS IR, QUICKI, and SPICE IR scoring which are not usually used clinically, because these are not having well defined cut-offs for comparison and also they focus mostly in insulin activity and resistance [6] . Insulin test is costly in low and middle income countries and rural areas .Treatment of hyperglycaemia in pregnancy also need early diagnosis and intervention [7] . Hypolemmal is a danger in diabetic patients on insulin and oral hypoglycaemic drugs which requires accurate assessment of dosage for prevention [8] . Basal Metabolic Rate is widely accepted parameter to evaluate daily requirement of calorie per day in both men and women. We are using BMR and FBS to come up with a simple formula to screen diabetes early. Treatment of hyperglycaemia in pregnancy also need early diagnosis and intervention.

Methods and Materials Study populations

The study is conducted at the New Civil Hospital, Surat, which is located in the South Gujarat region. It is a government hospital and so patients from faraway areas consult the hospital for treatment. Our study population included people attending Niramaya health camp which is conducted to screen for prevalence of any health condition in the Police officers of the Surat District. Our sample size is 122. The study population include individuals aging from 18 years till 45 years of both sexes .No one is excluded from the study.

Statistical analysis

The Formula for Average Glucose Metabolic Index is given by, AGMI = BMR/(15.5*FBS)

We have evaluated the population, collected the general details including age by questionnaire and the height and weight is measured. We also collected details of FBS from the laboratory reports. BMR is calculated by: Mifflin-St Jeor Equation Mean value of AGMI is calculated from the collected data and 2 standard deviations above and below the mean is taken as the reference interval. The calculated BMI is plotted against AGMI to determine the coefficient of determination.

Ethical considerations

We had taken approval from Ethical committee of Government Medical college, Surat to conduct cross sectional study on patients consulting in New Civil Hospital to evaluate risk factors of Diabetes.

All the participants were informed about the study. The study is a cross sectional study and the data were collected through questionnaire.

Results

From the study we could come to mean value for Average Glucose Metabolic Index (AGMI). We calculated the value separately for males and females. We found that reference range for AGMI in South Gujarat population is 0.8-1 kcal/min in females and 1-1.2 kcal/min in males. We got mean value as 1.1 kcal/min in males with standard deviation of 0.1 and 1 kcal/min in females with standard deviation of 0.1.

Baseline characteristics

Conclusions

Average Glucose Metabolic Index helps to compare the metabolic rate in POV of FBS and BMR. BMR is calculated as the Metabolic rate at the sedentary state or rest. So individuals with high AGMI will be having either high BMR or the person may be having low FBS. An individual with high AGMI will be more prone to hypoglycaemia. And an individual with low AGMI is more prone to hyperglycaemia or diabetes. So AGMI can be used as a tool to predict diabetes and screen pre-diabetes in undiagnosed population. AGMI is not associated with BMI. So BMI cannot be used to determine the chance of diabetes in an individual. AGMI can also be used to predict chance of hyperglycaemia in pregnancy and also insulin and OHD dose calculation.

References

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