Study of Glycemic Variability in Well-controlled Type 2 Diabetic Patients Using Continuous Glucose Monitoring System.

INTRODUCTION: The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS). AIM AND OBJECTIVE: To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c. MATERIALS AND METHODS: A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over a period of 7 days by using FreeStyle® Libre Pro™, which is a flash glucose monitoring system. The CGM sensor was attached to the left upper arm of the patient on day 0 and removed on day 7. The data recorded in the sensor was then retrieved using pre-installed computer software and analyzed using standard CGM metrics like standard deviation (SD), percentage coefficient of variation (%CV), time above range (TAR), time below range (TBR), and time in range (TIR), out of which %CV was used to quantify GV. %CV has been used to cluster patients into four cohorts from best to worst, namely: best/low CV ≤ 10%, intermediate CV from 10 to 20%, high CV from 20 to 30%, and very high CV of >30%. Scatterplots are used to establish correlations between various parameters. RESULT: Data from a total of 30 patients were analyzed using CGMS and thus used for calculating standard CGM metrics; glucose readings every 15 minutes were recorded consecutively for 7-day periods, making it a total of 672 readings for each patient. Interpreting the CGM data of all 30 patients, the following results were found: the mean blood glucose of all cases is 134.925 ± 22.323 mg/dL, the mean SD of blood glucose of all cases is 35.348 ± 9.388 mg/dL, the mean of %CV of all cases is 26.376 ± 6.193%. CGM parameters of time are used in the form of percentages, and the following results were found: the mean of TAR, TBR, and TIR is 14.425 ± 13.211, 5.771 ± 6.808, and 82.594 ± 12.888%, respectively. Clustering the patients into cohorts, the proportion of patients exhibiting best/low %CV (10%) is 0, intermediate %CV (10-20%) is 16.67% (five out of 30 patients), high %CV (20-30%) is 50% (15 out of 30 patients) and very high %CV (>30%) is 33.33% (10 out of 30 patients). Also, there is no significant correlation found between HbA1c and %CV (ρ = 0.076, p-value = 0.690); a significant negative correlation was found between %CV and TIR (ρ = -0.604, p < 0.001S); a positive correlation of %CV with TAR and TBR is significant (ρ = 0.816, p-value of <0.001). CONCLUSION: Using a flash CGMS device and considering %CV as the parameter and primary measure of GV, the study demonstrated the overall instability of a person's glycemic control, making note of unrecognized events of hypoglycemia and hyperglycemia in asymptomatic well-controlled T2DM patients, revealing the overall volatile glycemic control. The most important finding of this study is that even those diabetics who are considered well-controlled experience a great degree of GV as assessed by CGM-derived metrics. This study also demonstrated that there is no significant correlation between HbA1c and GV, suggesting that patients may not have optimal control of their diabetes despite having "normal HbA1c" values; hence, GV can be considered an HbA1c-independent danger factor, having more harmful effects than sustained hyperglycemia in the growth of diabetic complications. So, by using CGM-derived metrics, the measurement of GV has the potential to complement HbA1c data. In this manner, a more comprehensive assessment of glycemic excursions can be provided for better treatment decisions, thereby facilitating optimal glycemic control, which is essential for reducing overall complications and promoting good quality of life.

A Case Series on Neuropathogenic Nature of an Ancient Disease ----Tuberculosis.

Tuberculosis is one of the oldest diseases known to affect humans and the top cause of infectious death worldwide caused by M. tuberculosis complex. Tuberculosis may be pulmonary, extra-pulmonary or both. Nervous system tuberculosis is relatively rare and has protean nature of symptoms so poses diagnostic difficulty. Neurological manifestations of tuberculosis includes 1) intracranial 2) spinal 3) peripheral nerve tuberculosis. Central nervous system tuberculosis accounts about 5% of extra pulmonary cases and 1% all tuberculosis. MATERIAL: Here we are presenting the series of 10 cases which have wide variety of neuropathogenic nature of tuberculosis. OBSERVATION: Here we are presenting the series of 10 cases which have wide variety of neuropathogenic nature of tuberculosis. These includes 1) Tubercular cortical vein thrombosis -patient who is a known case of pulmonary tuberculosis presented with severe headache, seizure and altered behavior, MRI brain shows cortical vein thrombosis and normal coagulation profile (Review of literature shows only 4 cases). 2)Tubercular myelitis/ arachnoiditis-presented with low backache and bilateral lower limb weakness,CSF panel and MRI L S spine shows tubercular arachnoiditis/myelitis. 3)Tubercular peripheral neuropathy; patient who is a non- diabetic presented with pain abdomen and bilateral lower limb tingling and numbness with no past history of treatment with anti-tubercular drug, CECT abdomen shows ileocecal tuberculosis and NCS study shows sensory affection of lower limb nerve. 4)Tuberculoma-patient presented with severe headache, seizure and altered behavior, MRI brain shows tuberculoma. 5) and 6) are tubercular vascular infarct in 1 of these 2 cases patient was having multiple necrotic foci and few foci of cavitation in left hilar region which is extending into left inferior pulmonary vein and even reaching upto left atrium. 7) and 8) cases are pott's spine who presented with low backache. 9) and 10) are tubercular meningitis and tubercular meningitis with hydrocephalus respectively. These patients were treated according to their diagnosis and for focal neurological deficit physiotherapy was advised. Except a case of septic foci emboli from left atrium which shows moderate recovery rest all cases shows good recovery at discharge. CONCLUSION: There is paucity of literature on neuropathogenic nature of tuberculosis. In this case series we are presenting the series of 10 cases of tubercular nervous system manifestations so that it will helps to diagnose the disease as early as possible and allows us to initiate the prompt treatment so that we can mitigate the significant morbidity and mortality among survivors of nervous system tubercular disease.