Global Journal of Medical Research, F: Diseases, Volume 22 Issue 4

additionally be useful biomarker to identify individuals at risk for different vascular complications. 23,24,25 However, in our study, the duration of diabetes was set to 5 years after diagnosis. Our finding that the age at onset of diabetes is not associated with the development of diabetic nephropathy is com- mensurate with recent data 26 ; however, as in their study, we did not account for pubertal staging. 27 The results of our study, like many other reports, did not show an association between gender and the development of diabetic nephropathy. This contrasts with a previousfinding by Holl et al., showing an impact of female gender on the development of insidiousnephropathy. 28 Any association between gender and nephropathy should take into consideration the pubertal stage since the hormonal effects could be at the base of this difference. Data on the association between BMI, an index of metabolic state, and the development of diabetic nephropathy, is scarce. 28 In our study, BMI was measured at the first visit to the center, when most of the patients had poor metabolic control that might have negatively affected the weight. Although the baseline BMI was found to be associated with the development of microvascular complications 29 , the impact of BMI was apparent only at higher values. Follow- ing BMI longitudinally and accounting for pubertal changes would help in establishing the associations between BMI and diabetic nephropathy. Metabolic control was the only established and consistent predictor for the development of diabetic nephropathy. In reviewing the literature, different measures have been used in order to study the association between metabolic control and diabetic nephropathy. The mean HbA1C is repeatedly used 30,27 ; the median has also been used as a summary measure. 31 Based on the results of our study, the mean HbA1C remains the only significant predictor for the development of diabetic nephropathy in type 1 diabetic patients, even after adjusting for ‘‘fluctuations”. The use of ‘‘fluctuations” in HbA1C as a longitudinal measure for the change in the metabolic state is original. It may better reflect the changes in ambient glycemia within one individual. This latter was found to be the culprit in the development of diabetic nephropathy through activation of the proteinase C 32 , upregulating the heparanase expression 33 , enhancing sensitivity to TGF beta 1 34 and increasing VEGF (vascular endothelial growth factor) expression. 35 Our data showed that ‘‘fluctuations” in HbA1C predicted the incidence of nephropathy, based on the positive evidence that the model including fluctuations fits the data better. This may have many implications: first, these findings may help to achieve a better understanding of the pathophysiology of diabetic nephropathy, since they suggest that, although this latter is accelerated by the chronic hyperglycemia (manifested as mean HbA1C), it is much worse during acute increases in glycemia which is reflected by fluctuations in HbA1C. Second, our data highlight the issue that a single jump in HbA1C have a durable effect, this agrees with the hypothesis of ‘‘long time- glycemic memory” and supported by findings from DCCT on microvascular complications. Third, as diabetic nephropathy has an insidious onset, one large increment in HbA1C during the first 5 years, would be an indicator of a development of nephropathy well before the appearance of microalbuminuria. Nevertheless, our data were unable to establish the association betweenfluctuations in HbA1C and the development of nephropathy in diabetics with acceptable control. The sample size was small to permit the comparison between the different groups; this was well seen by the wide confidence intervals. Interestingly, taking the whole model, the mean HbA1C explains 10% the prediction for the development of diabetic nephropathy. Other factors, such as genetic predisposition, have been known to be associated with the development of nephropathy. Family history of hypertension 36 , kidney disease and other cardio- vascular risk factors 37 , were used as a measure for genetic predisposition. V. C onclusion We concluded that the type 1 diabetic patients who have a similar mean HbA1C, in the long run, may behave differently in terms of developing nephropathy, depending on the fluctuations in HbA1C and more precisely, depending on the frequency of the acute jumps in the HbA1C. R eferences R éférences R eferencias 1. American Diabetic Association. Standards of medical care in diabetes-2015. (Position State- ment). Diabetes care. 2015; 38 (suppl.1): 8-93. 2. Mogensen CE. Long-term antihypertensive treatment inhibiting progression of diabetic nephropathy. Br Med J.1982; 285: 685-688. 3. Parving H-H, Andersen AR, Smidt UM and Svendensen PA. Early and aggressive antihypertensive treatment reduces the rate of decline in kidney function in diabetic nephropathy. Lancet.1983; 1: 1175-1179. 4. Lewis EJ, Hunsicker LG, Bain RP and Rohde RD. The effect of angiotensin-converting-enzyme inhibition on diabetic nephropathy: the Collaborative Study Group. N Engl J Med.1993; 329: 1456-1462. 5. The DCCT Research group. The effect of intensive treatment of diabetes on the development and progression of long term complications in insulindependent diabetes mellitus: The Diabetes Control And Complications Trial Research Group. N Engl L Med. 1993; 329: 977-86. 6. McCane DR, Hanson RL, Charles MA, Jacobsson LTH, Pettitt DD, Bennett PH et al. Comparison of 6 Year 2022 Global Journal of Medical Research Volume XXII Issue IV Version I ( D ) F © 2022 Global Journals To Evaluate the Role of HbA1C as a Predictor for the Development of Diabetic Nephropathy in Type 1 Diabetic Patients