Comparing the accuracy of transcutaneous sensor and 90-day implantable glucose sensor.

BACKGROUND AND AIMS: Continuous glucose monitoring improves glycemic control in diabetes. This study compared the accuracy of the Dexcom G5 Mobile (Dexcom, San Diego, CA) transcutaneous sensor (DG5) and the first version of Eversense (Senseonics,Inc., Germantown, MD) implantable sensor (EVS). METHODS AND RESULTS: Subjects with type 1 diabetes (T1D) and using EVS wore simultaneously DG5 for seven days. At day 3, patients were admitted to a clinical research center (CRC) to receive breakfast with delayed and increased insulin bolus to induce glucose excursions. At CRC, venous glucose was monitored every 15 min (or 5 min during hypoglycemia) for 6 h by YSI 2300 STAT PLUS™ glucose and lactate analyzer. At home patients were requested to perform 4 fingerstick glucose measurements per day. Eleven patients (9 males, age 47.4 ± 11.3 years, M±SD) were enrolled. During home-stay the median [25th-75th percentile] absolute relative difference (ARD) over all CGM-fingerstick matched-pairs was 11.64% [5.38-20.65]% for the DG5 and 10.75% [5.15-19.74]% for the EVS (p-value = 0.58). At CRC, considering all the CGM-YSI matched-pairs, the DG5 showed overall smaller median ARD than EVS, 7.91% [4.14-14.30]% vs 11.4% [5.04-18.54]% (p-value<0.001). Considering accuracy during blood glucose swings, DG5 performed better than EVS when glucose rate-of-change was -0.5 to -1.5 mg/dL/min, with median ARD of 7.34% [3.71-12.76]% vs 13.59% [4.53-20.78]% (p-value<0.001), and for rate-of-change < -1.5 mg/dl/min, with median ARD of 5.23% [2.09-15.29]% vs 12.73% [4.14-20.82]% (p-value = 0.02). CONCLUSIONS: DG5 was more accurate than EVS at CRC, especially when glucose decreased. No differences were found at home.

Efficacy of telemedicine for persons with type 1 diabetes during Covid19 lockdown.

BACKGROUND: Starting March 2020 the Italian Government imposed a lockdown to limit the spread of SARS-CoV-2. During lockdown outpatient visits were limited and telemedicine (TM) was encouraged. METHODS: We retrospectively analyzed data from continuous or flash glucose monitoring systems shared through different cloud systems during the lockdown by subjects with type 1 diabetes and compared data obtained 4 weeks before and 4 weeks after structured telephonic visit. Variables considered were mean glucose, time spent in target (70-180 mg/dl), hypoglycemia (<70 mg/dl) and hyperglycemia (>180 mg/dl), coefficient of variation, and length of sensor use. RESULTS: During the 4 weeks following the telephonic visit there was an improvement of glycemic control, with a significant reduction of mean glucose values (161.1 before vs 156.3 mg/dl after, p = 0.001), an increase of the time spent in target (63.6 vs 66.3, p = 0.0009) and a reduction of time spent in hyperglycemia (33.4 vs 30.5, p = 0.002). No changes were observed regarding glucose variability, time spent in hypoglycemia, and length of sensor use. Similar results were observed in subjects treated with multiple daily injections or continuous subcutaneous insulin infusion. CONCLUSIONS: A structured telephonic visit appears to be an effective way to replace or integrate routine visits in particular conditions.

Performance of the Steno type 1 risk engine for cardiovascular disease prediction in Italian patients with type 1 diabetes.

BACKGROUND AND AIMS: Premature cardiovascular disease cause excess mortality in type 1 diabetes (T1D). The Steno T1D Risk Engine was developed and validated in northern European countries but its validity in other populations is unknown. We evaluated the performance of the Steno T1D Risk Engine in Italian patients with T1D. MATERIALS AND METHODS: We included patients with T1D with a baseline visit between July 2013 and April 2014, who were free of cardiovascular disease and had complete information to estimate risk. The estimated cardiovascular risk score was compared with the 5-year rate of cardiovascular events by means of logistic regression. RESULTS: Among 223 patients (mean age 43 ± 13 years, 34.5% male, mean duration of diabetes 22 ± 12 years) the mean estimated cardiovascular risk at 5 years was 5.9% (95% C.I. 5.2-6.5%). At baseline, high estimated risk discriminated the presence of asymptomatic atherosclerosis better than microangiopathy, and was not associated with markers of inflammation or endothelial activation. After a mean follow-up of 4.7 ± 0.5 years, only 3 cardiovascular events were observed and nonetheless the risk score was significantly associated with their incidence (OR 1.22; 95% C.I. 1.08-1.39, p = 0.001). However, the observed event rate was significantly lower than the estimated one (3 vs 13; 95% C.I. 12-14; p < 0.001). CONCLUSION: The Steno T1D Risk Score identified subjects with subclinical atherosclerosis and high cardiovascular risk in an Italian T1D population. However, the absolute risk was significantly overestimated. Further studies in larger population are needed to confirm these results.

Impaired cognitive processing speed in type 1 diabetic patients who had severe/recurrent hypoglycaemia.

AIMS: To detect whether adults with type 1 diabetes mellitus (T1DM) have lower cognitive performance than healthy individuals and to detect risk factors for low cognitive performance. METHODS: Twenty-six adults with T1DM and twenty-six healthy subjects matched for age, gender and educational level were compared for cognitive performance by a chronometric computerized test measuring visuo-spatial working memory (N-Back) and by two validated neuropsychological tests (Mini Mental State Examination, Animal Naming Test). Clinical data about diabetes duration, average daily insulin dosage, glycated haemoglobin, retinopathy, urine albumin-creatinine ratio, previous hypoglycaemic coma and awareness of hypoglycaemia were obtained from medical records. Basal pre-test glycemia and blood pressure were measured for each patient. RESULTS: No differences were found between patients (n = 26) and healthy controls (n = 26) in neuropsychological tests. Within diabetic patients, those with impaired awareness of hypoglycaemia (n = 7) or history of coma in the recent 1-3 years (n = 5) had psychomotor slowing at the N-Back test (592 ±â€¯35 vs. 452 ±â€¯21 ms and 619 ±â€¯40 vs. 462 ±â€¯19 ms, respectively; both p < 0.01). The variables related to diabetic severity did not show a relationship with reaction times of the N-Back test. CONCLUSION: Psychomotor speed slowing is detectable in patients with T1DM who have a history of previous hypoglycaemic episodes or coma.