European Journal of Cardiovascular Medicine

Diabetes is a chronic disease that occurs either when the pancreas does not produceenough insulin or when the body cannot effectively use the insulin it produces. Thehormone that regulates blood sugar is Insulin. Worldwide between 2000 and 2016, therewas a 5% increase in premature mortality from diabetes. According to WHO, in 2019, diabetes was the ninth leading cause of death with an estimated 1.5 million deathsdirectly caused by diabetes. In 2014, 8.5% of adults aged 18 years and older haddiabetes.[1] There were 65·0 million prevalent cases of diabetes in India in 2016, compared with 26·0 million (23·4–28·6) in 1990. The crude prevalence of diabetes inadults aged 20 years or older in India increased by 39·4%. [2] According to NFHS 4 in2015-2016, the prevalence of women with blood sugars more than 140mg/dl is 5.8%and men with blood sugars more than 140 mg/dl is 8%. [3]

Hyperglycaemia, an effect of uncontrolled diabetes, over time leads to serious damageto many of the body's systems, especially the nerves and blood vessels. Uncontrolleddiabetes adults have higher risk of various diseases like heart attacks, strokes andinfection and blindness. Adults with diabetes have a two- to three-fold increased riskof heart attacks and strokes. Combined with reduced blood flow, neuropathy (nervedamage) in the feet increases the chance of foot ulcers, infection and eventual need forlimb amputation. Diabetic retinopathy is an important cause of blindness, and occursas a result of long-term accumulated damage to the small blood vessels in the retina.Close to 1 million people are blind due to diabetes. Diabetes is among the leadingcauses of kidney failure [1] Studies show that poor glycaemic control leads to highvascular complication rate and suboptimal diabetes therapy is contributing to burden ofthe type 2 diabetes worldwide. [4]

C-peptide is commonly used in preference to insulin measurement whenassessing b-cell function in clinical practice. [5] C-peptide levels acts as proxy for themeasurement of the insulin production in the body. C-peptide is a useful indicator ofbeta cell function, allowing discrimination between insulin-sufficient and insulindeficientindividuals with diabetes. Studies have showed that C-peptide may also beuseful in predicting future levels of glycaemic control, response to hypoglycaemicsagents, and risk of future diabetes complications. An early prospective cohort studydetermined that a peak GST c-peptide of less than 0.6 nmol/l was associated with latertreatment with insulin. [6]

Age is a factor which is a determinant of functionality of the human body. Hence itneeded to assess the effect of aging on the c-peptide levels i.e., the insulin productionin the body. Early initiation of the insulin treatment for the patients of diabetes isdepended on the c-peptide levels. This necessitates the need to understand the c-peptidelevels as a proxy of insulin levels amongst the diabetics and the correlation between theage of the diabetes and the c-peptide levels.

OBJECTIVES

1. To estimate the level of C-peptide in patients with newly diagnosed type 2Diabetes Mellitus.
2. To correlate C-peptide levels in different age groups of newly diagnosed type 2Diabetics Mellitus.

Study design: Cross Sectional study

Study Setting: A Government Tertiary care hospital in Mysuru city.

Study Population:

Population element: Newly diagnosed Diabetes Mellitus

Sampling element: Newly diagnosed Diabetes Mellitus at the studysetting.

Study Period: June 2019 to May 2021

Sampling technique:

Purposive sampling was used. Specifically, patients who were newly diagnosed with

type 2 diabetes mellitus according to ADA 2018 [6] criteria were chosen.

Eligibility Criteria:

Inclusion Criteria:

1. Subjects who are newly diagnosed with type 2 diabetes mellitus

according to ADA 2018 criteria

Exclusion Criteria:

1. Type 1 Diabetics
2. Type 2 Diabetics who are already on treatment
3. Patients with chronic kidney disease
4. Pregnancy
5. Age less than 18 years
6. Known case of LADA, Diabetes secondary to chronic pancreatitis

Tools Used:

1. A proforma which was predesigned, pretested and semi structured proformawas used after piloting and expert validation of the proforma. Content and Facevalidation of the proforma was done by experts. Piloting of the proforma wasdone for finalizing the proforma and to see the feasibility of the study. Proformaincludes the following details: Demographics, history, examination,investigation. The proforma is annexed.
2. Investigations
3. Serum C-peptide level
4. Fasting and Post prandial Blood Sugars
5. Glycated Hemoglobin levels [HbA1c]

Statistical methods to be employed:

Data was entered in licensed version 2016 of Microsoft excel spread sheet. To addressthe objectives, descriptive statistics like frequency, percentages and graphs were used.Pearson’s Correlation was used to address the second objective. SPSS software was used for the analysis. The level of significance[α] was 5% i.e., p-value<0.05 is considered statistically significant.

Ethical Considerations:

Ethical clearance was taken from the institutional ethical committee.

Table 1: Age wise distribution of the study participants. [n=105]

SD- Standard deviation

Table 6.1 shows the age wise distribution of the study participants. Around 50% of the patients belonged to the age group of 30-40 years. While 21.9% belong to 51-60 years. Mean age was 49.45 years. 5.71% of them fall under 71-80 years of age category. 

Table 2: Gender distribution of the study participants. [n=105]

As shown in the table, 52.38% of the study participants were males while 47.61% were females.

Table 3: Prevalence of various Symptoms among the study participants. [n=105]

*Numbers do not add up-to total number of sample size because each study participant may have more than one symptom, and some may not have any symptoms.

Newly detected diabetes mellitus patients present with various symptoms. 82.85% of them complaints of tiredness followed by 50.47% complains of polyuria. Polydipsia is reported by 35.23% of them and 24.76% presented with the complaints of chronic non- healing wounds. Polyphagia is depicted in 21.9% of the patients. Minority of the patients compliant of weight loss and giddiness.

Table 4: Average values of Diabetic Profile of the study participants. [n=105]

Mean Fasting blood sugars and Post Prandial blood sugars of the newly diagnosed diabetes mellitus study participants are 217.85 mg/dl and 342.42 mg/dl respectively. The mean glycosylated haemoglobinwas 10.71% among the patients.

Table 5: C-Peptide levels [ng/ml] among the study participants. [n=105]

SD- Standard deviation

68.57% of the newly detected diabetes mellitus in our study have high c-peptide levels while 31.42% of them have low c-peptide levels. Mean c-peptide levels among the study participants is 6.51 ng/ml with standard deviation of 1.14 ng/ml.

Table 6: Haemoglobin levels [g/dl] among the study participants. [n=105]

SD- Standard deviation

*Normal Haemoglobin in Females-12.1-15.1 mg/dl and in Males-13.8-17.2 mg/dl

61.90% of the study participants were anaemic classified according to the national anaemia control programme cut-offs of the haemoglobin for females and males accordingly. The normal values considered as mentioned in the above table and figure.

Figure 1: Correlation between the C-peptide levels and age among the newly diagnosed Diabetic Mellitus.

Figure shows the correlation between the c-peptide levels and age among the study participants. The scatter plot shows the negative slope indicating the negative correlation between the variables, i.e., as the age increases the c-peptide levels in the body decreases. The decrease in the c-peptide levels indicates low insulin production by the beta cells of pancreases. As we can also see that by the age of 50-55 years c- peptide levels are dropping below the normal [<6ng/dl]. The strength of correlation is indicated by Pearson’s correlation co-efficient denoted by r. the Pearson’s correlation in the present study is minus 0.81 which indicates strong negative correlation between the c-peptide levels and age among the study participants.

Figure 2: Correlation between the C-peptide levels and Fasting Blood Sugars among the newly diagnosed Diabetic Mellitus

Figure shows the correlation between the c-peptide levels and Fasting blood sugar levels among the study participants. The scatter plot shows no slope indicating no correlation between the variables, the strength of correlation is indicated by Pearson’s correlation co-efficient denoted by r. the Pearson’s correlation is 0.08 which indicates no correlation between the c-peptide levels and Fasting blood sugar levels.

Figure 3: Correlation between the C-peptide levels and Post Prandial Blood Sugars among the newly diagnosed Diabetic Mellitus

Figure shows the correlation between the c-peptide levels and Post Prandial blood sugar levels among the study participants. The scatter plot shows no slope indicating no correlation between the variables, the strength of correlation is indicated by Pearson’s correlation co-efficient denoted by r. the Pearson’s correlation is 0.1 which indicates no correlation between the c-peptide levels and Post Prandial blood sugar levels.

Figure 4: Correlation between the C-peptide levels and Glycosylated Haemoglobin levels among the newly diagnosed Diabetic Mellitus.

Figure shows the correlation between the c-peptide levels and Glycosylated Haemoglobin levels among the study participants. The scatter plot shows no slope indicating no correlation between the variables, the strength of correlation is indicated by Pearson’s correlation co-efficient denoted by r. the Pearson’s correlation is 0.2 which indicates no correlation between the c-peptide levels and Glycosylated Haemoglobin levels.

In our study, around 50% of the patients belonged to the age group of 30-40 years. While 21.9% belong to 51-60 years. Mean age was 49.45 years. 5.71% of them fall under 71-80 years of age category.

Roy William Mayega et al. in their article describing the clinical presentation of the newly detected diabetes patients in eastern Uganda, say that the mean age of their participants was 49 years. [7] This is like our study indicating the similar social factors in our country and the African countries.

Bilal Bin Abdullah et al. in their study to find the significance of C – Peptide in Type 2 Diabetics found that maximum of 32 (43%) patients were between the age groups of 50-59 years, followed by 26 (35 %) patients in the age group of 40-49 years. 10 (13%) patients out of 75 study patients were in the age group of 30-39 years. [8] These findings are far more relatable to our study findings.

Bilal Bin Abdullah et al. in their study presented that 42 (56%) patients were females, while 33 (44%) were males. [8] Similarly, Roy William Mayega et al. presents that 47.6% of their study subjects were males and 52.4% were females. [7] In contrast to this, our study has 52.38% of the study participants as males while 47.61% as females. This points out the gender difference in the prevalence of the diabetes in our study population. This is in consensus with national data which depicts the higher prevalence of diabetes in among the males and higher proportion of undiagnosed diabetes among females.

Symptoms of the patients in a newly diagnosed diabetes mellitus:

Presentation of the newly detected diabetes mellitus were as follows in our study. 82.85% of them complaints of tiredness followed by 50.47% complains of polyuria. Polydipsia is reported by 35.23% of them and 24.76% presented with the complaints of chronic non-healing wounds. Polyphagia is depicted in 21.9% of the patients. Minority of the patients compliant of weight loss and giddiness.

Roy William Mayega et al. in their article describing the clinical presentation of the newly detected diabetes patients in eastern Uganda presents that the most common symptom at presentation of new diabetes patients was frequent passing of urine. This symptom was reported by every patient assessed. Frequent urination was followed by frequent drinking/thirst (81/103, i.e.79% of all new patients) and general body weakness (52/103, i.e.51%). Moderately occurring symptoms included: blurred vision (38%), frequent eating (33%), excessive sweating (27%), joint pains (22%),numbness (21%) and headache (21%). [7]

On observing the findings of the two studies, we can appreciate that the symptoms presented by the newly detected diabetes patients are similar. However, the frequency of the occurrence of each of the individual symptom is widely varied in the comparison to the two studies. This depicts that clinical presentation of the diabetes patients can be outspread.

Diabetic Profile of the study participants:

In the present study, Mean Fasting blood sugars and Post Prandial blood sugars of the newly diagnosed diabetes mellitus study participants were 217.85 mg/dl and342.42 mg/dl respectively. The mean glycosylated haemoglobin is 10.71% among the patients.

ShamhaBeegum Mariyam et al. conducted a study to assess the difference between obese and non-obese patients with type 2 diabetes with respect to serum c- peptide levels. Their findings are as follows: Mean FBS of the study population was175.53 mg/dL. 18% of the study population had an HbA1c level above 8%, which included 26.7% of the obese and 10% of nonobese patients indicating poor control of diabetes mellitus. [9] The findings are more relatable to the finding of our study.

Hardeep Singh Deep et al. evaluated serum c-peptide levels in type 2 diabetics in 2017 in Punjabi population. It was demonstrated in their study that Mean fasting blood sugar (FBS) of all patients in the study was 213.21 mg/dl and Mean HbA1c was 10.17%. [10] Alike findings are found in this study and our study, indicating the similarity in the epidemiology and clinical features across the country.

In the study by Bilal Bin Abdullah et al. in 2010, the mean HbA1c level of the study was 9.585%. The mean plasma glucose level of the study was 222.9 mg/dl. [8] The values of the fasting blood sugars are similar in both the studies. But the value of the HbA1c is lower in the study compared to our study. There is an increase in the prevalence of the diabetes among the population from 2010 to the present date. This also indicates that there is poor glycaemic control due to delayed diagnosis amongst our participants.

Table 7.1: Summary of the Diabetic profile discussion.

C-peptide levels:

The findings of our study show that, 68.57% of the newly detected diabetes mellitus in our study have high c-peptide levels while 31.42% of them have low c- peptide levels. Mean c-peptide levels among the study participants is 6.51 ng/ml.

ShamhaBeegum Mariyam et al. in their study depicts that 65% of the study population had a C-peptide value above 3.2 ng/ml and 35% had a value between 0.5 and 3.2 ng/ml. Mean c-peptide levels were 6.31 ng/ml and 3.53 ng/ml among obese and non-obese respectively. [9] Proportion of the participants having low c-peptide levels are almost same in both the studies. However, the mean c-peptide levels of our study are in consensus with the c-peptide levels of the obese patients of the other study. Yet indicating the higher c-peptide in obese towards insulin resistance not insulin deficiency.

Hardeep Singh Deep et al. evaluated serum c-peptide levels in type 2 diabetics. It was demonstrated in their study that Mean C peptide levels was 7.9 ng/ml. C peptide levels were below normal (< 0.5 ng/ml) in 2%, normal (0.5 - 3.2 ng/ml) in 38% and above normal (> 3.2 ng/ml) in 60 % patients. [10] This study has higher c-peptide levels compared to our study indicating higher insulin resistance in their population.

In the study by Bilal Bin Abdullah et al. shows considerably low levels of c- peptides among their study participants. The mean fasting c-peptide level of the study was 1.315ng/ml. [8] This enormous difference in the c-peptide levels among the participants of similar age group can be possibly attributed to two reasons. One the technical difference that the c-peptide levels measured in the present study was random C– peptide levels and it is fasting levels in the above-mentioned study. Secondly, there could be decreased insulin producing capacity among their study participants.

Table : Summary of the C-peptide level discussion.

Correlation between c-peptide levels and the age of the study participants:

The scatter plot shows the negative slope indicating the negative correlation between the variables, i.e., as the age increases the c-peptide levels in the body decreases. The decrease in the c-peptide levels indicates low insulin production by thebeta cells of pancreases. As we can also see that by the age of 50-55 years c-peptide levels are dropping below the normal [<6ng/dl]. The strength of correlation is indicated by Pearson’s correlation co-efficient denoted by r. the Pearson’s correlation in the present study is minus 0.81 which indicates strong negative correlation between the c- peptide levels and age among the study participants.

ShamhaBeegum Mariyam et al. assessed the correlation between the c-peptide levels and age of the patients. Serum C-peptide showed weak correlation with age and HbA1c. The Pearson’s correlation [r] is 0.074 for the correlation between the c-peptide levels and age of the patients. [9] There is a difference in the correlation between the two studies.

Francesco Panero et al. compared the plasma c-peptide levels and vascular complications in type 1 diabetics. In the univariate analysis of the results showed that, fasting C-peptide values were positively correlated with age at diagnosis (r = 0.32; P<0.0001), triglycerides (r = 0.14; P= 0.0002), and BMI (r = 0.11; P <0.006) and negatively with diabetes duration (r = 0.34; P= 0.0001) and HDL cholesterol (r = 0.16; P = 0.0001), whereas no significant correlations were found with age, A1C, blood pressure, or total or LDL cholesterol. In multivariate linear regression analysis, fasting plasma C-peptide values were positively associated with age at diagnosis and BMI and inversely associated with duration of disease. [11] The difference in the correlation results between the two studies could be due to the major differences in the study population. Our study had type 2 diabetics as the study population and the other study describes type 1 diabetics patients.

Table 7.3: Summary of the correlation between age of the participantsand C-peptide levels.

Correlation between c-peptide levels and diabetic profiles of the study participants:

In our study, it has been seen that the scatter plot shows no slope indicating no correlation between the C-peptide levels and fasting blood sugar levels, post prandial blood sugar levels and glycosylated haemoglobin levels. The strength of correlation is indicated by Pearson’s correlation co-efficient denoted by r. the Pearson’s correlation is 0.08, 0.1 and 0.2 for the variables in the order, fasting blood sugar levels, post prandial blood sugar levels and glycosylated haemoglobin levels.

ShamhaBeegum Mariyam et al. assessed the correlation. Serum C-peptide showed weak correlation with FBS and HbA1c. The Pearson’s correlation [r] is 0.246 for the correlation between the c-peptide levels and HbA1c of the patients. The Pearson’s correlation [r] is 0.334 for the correlation between the c-peptide levels and FBS of the patients [9]

Hardeep Singh Deep et al. showed that increase in fasting c-peptide levels were associated with increased fasting plasma glucose due to insulin resistance. A positive

correlation exists in their study with r value of 0.523. The study shows that increase in fasting c-peptide levels were associated with increased HbA1C levels due to insulin resistance. A positive correlation exists with r value of 0.440. [10]

In the study by Bilal Bin Abdullah et al. we can find that there is a moderate positive correlation (r=0.532) (p=0.000). The positive correlation indicates that as the fasting c-peptide level increases, the FBS level also increases, but not in a linear fashion. [8]

This difference in the correlation findings of our study and all the other above- mentioned studies indicates the following points: firstly, as there is no correlation [or slightly negative correlation minus 0.08] between the FBS and c-peptide levels indicating the random c-peptide levels in the present study. Also, indicating the true deficiency in the insulin production in our participants which bring the need for the early initiation of the insulin therapy, at the time of diagnosis in a newly detected type 2 diabetes mellitus.

Overall, it was found that there are several similarities in the finding of our study and other studies. Also, there are few contradictory presentations with respect to the correlation of c-peptide levels and other variables.

The present studyconcludes that there is a strong negative correlation between the c-peptide levels andage among the study participants [r= minus 0.81] i.e., as the age increases the c-peptidelevels in the body decreases. 31.42% of the study participants have low c-peptide levels[< 6 ng/ml].

This indicates the true deficiency in the insulin production in our participantswhich bring the need for the early initiation of the insulin therapy, at the time ofdiagnosis in a newly detected type 2 diabetes mellitus. Hence, c-peptide levelsmeasured at diagnosis or earlier after the diagnosis of diabetes mellitus at any age helpsin understanding the insulin reserve of the patients. Thus, better treatment can be givenby seeing the c-peptide levels to have good control of blood sugar levels and inpreventing the complication of diabetes mellitus.

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