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Newspaper reporting on events at the Boston University School of Medicine in the 1960s

Hypoglycemia and Diabetes: A Report of a Workgroup of the American Diabetes Association and The Endocrine Society

OBJECTIVE To review the evidence about the impact of hypoglycemia on patients with diabetes that has become available since the past reviews of this subject by the American Diabetes Association and The Endocrine Society and to provide guidance about how this new information should be incorporated into clinical practice. PARTICIPANTS Five members of the American Diabetes Association and five members of The Endocrine Society with expertise in different aspects of hypoglycemia were invited by the Chair, who is a member of both, to participate in a planning conference call and a 2-day meeting that was also attended by staff from both organizations. Subsequent communications took place via e-mail and phone calls. The writing group consisted of those invitees who participated in the writing of the manuscript. The workgroup meeting was supported by educational grants to the American Diabetes Association from Lilly USA, LLC and Novo Nordisk and sponsorship to the American Diabetes Association from Sanofi. The sponsors had no input into the development of or content of the report. EVIDENCE The writing group considered data from recent clinical trials and other studies to update the prior workgroup report. Unpublished data were not used. Expert opinion was used to develop some conclusions. CONSENSUS PROCESS Consensus was achieved by group discussion during conference calls and face-to-face meetings, as well as by iterative revisions of the written document. The document was reviewed and approved by the American Diabetes Association’s Professional Practice Committee in October 2012 and approved by the Executive Committee of the Board of Directors in November 2012 and was reviewed and approved by The Endocrine Society’s Clinical Affairs Core Committee in October 2012 and by Council in November 2012. CONCLUSIONS The workgroup reconfirmed the previous definitions of hypoglycemia in diabetes, reviewed the implications of hypoglycemia on both short- and long-term outcomes, considered the implications of hypoglycemia on treatment outcomes, presented strategies to prevent hypoglycemia, and identified knowledge gaps that should be addressed by future research. In addition, tools for patients to report hypoglycemia at each visit and for clinicians to document counseling are provided

Use of Flash Glucose-Sensing Technology for 12 months as a Replacement for Blood Glucose Monitoring in Insulin-treated Type 2 Diabetes

Introduction: Published evaluations of sensor glucose monitoring use in insulin treated type 2 diabetes are limited. The aim of this study was to assess the impact of flash glucose-sensing technology as a replacement for self-monitoring of blood glucose (SMBG) over a 12-month period in participants with type 2 diabetes who were on intensive insulin therapy. Methods: An open-label, randomized, controlled study in adults with type 2 diabetes on intensive insulin therapy from 26 European diabetes centers aimed at assessing flash glucose sensing technology was conducted. Participants (N = 224) were randomized (1:2 respectively) to a control group (n = 75) that used SMBG (FreeStyle Lite™) or to an intervention group (n = 149) which used sensor glucose data (FreeStyle Libre™ Flash Glucose Monitoring System) for self-management over 6 months. All intervention group participants who completed the 6-month treatment phase continued into an additional 6-month open-access phase. Results: A total of 139 intervention participants completed the 6-month treatment phase and continued into the open-access phase. At 12 months (end of open-access period), time in hypoglycemia [sensor glucose <3.9 mmol/L (70 mg/dL)] was reduced by 50% compared to baseline [−0.70 ± 1.85/24 h (mean ± standard deviation); p = 0.0002]. Nocturnal hypoglycemia [2300 to 0600 hours, <3.9 mmol/L (70 mg/dL)] was reduced by 52%; p = 0.0002. There was no change in time in range [sensor glucose 3.9–10.0 mmol/L (70–180 mg/dL)]. SMBG testing fell from a mean of 3.9 (median 3.9) times/day at baseline to 0.2 (0.0), with an average frequency of sensor scanning of 7.1 (5.7) times/day at 12 months, and mean sensor utilization was 83.6 ± 13.8% (median 88.3%) during the open-access phase. During this 6-month extension period no device-related serious adverse events were reported. Nine participants reported 16 instances of device-related adverse events (e.g. infection, allergy) and 28 participants (20.1%) experienced 134 occurrences of anticipated skin symptoms/sensor-insertion events expected with device use (e.g. erythema, itching and rash). Conclusion: The use of flash glucose-sensing technology for glycemic management in individuals with type 2 diabetes treated by intensive insulin therapy over 12 months was associated with a sustained reduction in hypoglycemia and safely and effectively replaced SMBG. Trial Registration: ClinicalTrials.gov identifier, NCT02082184

Environment, human reproduction, menopause, and andropause.

As the hypothalamic gonadotropin-releasing hormone (GnRH) pulse generator is an integrator of hormonal, metabolic, and neural signals, it is not surprising that the function of the hypothalamogonadal axis is subject to the influence of a large array of environmental factors. Before puberty, the central nervous system (CNS) restrains the GnRH pulse generator. Undernutrition, low socioeconomic status, stress, and emotional deprivation, all delay puberty. During reproductive life, among peripheral factors that effect the reproductive system, stress plays an important role. Stress, via the release of corticotropin-releasing factor (CRF), eventually triggered by interleukin 1, inhibits GnRH release, resulting in hypogonadism. Effects of CRF are probably mediated by the opioid system. Food restriction and underweight (anorexia nervosa), obesity, smoking, and alcohol all have negative effects on the GnRH pulse generator and gonadal function. Age and diet are important determinants of fertility in both men and women. The age-associated decrease in fertility in women has as a major determinant chromosomal abnormalities of the oocyte, with uterine factors playing a subsidiary role. Age at menopause, determined by ovarian oocyte depletion, is influenced by occupation, age at menarche, parity, age at last pregnancy, altitude, smoking, and use of oral contraceptives. Smoking, however, appears to be the major determinant. Premature menopause is most frequently attributable to mosaicism for Turner Syndrome, mumps ovaritis, and, above all, total hysterectomy, which has a prevalence of about 12-15% in women 50 years old. Premature ovarian failure with presence of immature follicles is most frequently caused by autoimmune diseases or is the consequence of irradiation or chemotherapy with alkylating cytostatics. Plasma estrogens have a physiological role in the prevention of osteoporosis. Obese women have osteoporosis less frequently than women who are not overweight. Early menopause, suppression of adrenal function (corticoids), and thyroid hormone treatment all increase the frequency of osteoporosis. Aging in men is accompanied by decreased Leydig cell and Sertoli cell function, which has a predominantly primary testicular origin, although changes also occur at the hypothalamopituitary level. Plasma testosterone levels, sperm production, and sperm quality decrease, but fertility, although declining, is preserved until senescence. Stress and disease states accelerate the decline on Leydig cell function. Many occupational noxious agents have a negative effect on fertility.(ABSTRACT TRUNCATED AT 400 WORDS

Flash Glucose-Sensing Technology as a Replacement for Blood Glucose Monitoring for the Management of Insulin-Treated Type 2 Diabetes: a Multicenter, Open-Label Randomized Controlled Trial

Introduction Glycemic control in participants with insulin-treated diabetes remains challenging. We assessed safety and efficacy of new flash glucose-sensing technology to replace self-monitoring of blood glucose (SMBG). Methods This open-label randomized controlled study (ClinicalTrials.gov, NCT02082184) enrolled adults with type 2 diabetes on intensive insulin therapy from 26 European diabetes centers. Following 2 weeks of blinded sensor wear, 2:1 (intervention/control) randomization (centrally, using biased-coin minimization dependant on study center and insulin administration) was to control (SMBG) or intervention (glucose-sensing technology). Participants and investigators were not masked to group allocation. Primary outcome was difference in HbA1c at 6 months in the full analysis set. Prespecified secondary outcomes included time in hypoglycemia, effect of age, and patient satisfaction. Results Participants (n = 224) were randomized (149 intervention, 75 controls). At 6 months, there was no difference in the change in HbA1c between intervention and controls: −3.1 ± 0.75 mmol/mol, [−0.29 ± 0.07% (mean ± SE)] and −3.4 ± 1.04 mmol/mol (−0.31 ± 0.09%) respectively; p = 0.8222. A difference was detected in participants aged <65 years [−5.7 ± 0.96 mmol/mol (−0.53 ± 0.09%) and −2.2 ± 1.31 mmol/mol (−0.20 ± 0.12%), respectively; p = 0.0301]. Time in hypoglycemia <3.9 mmol/L (70 mg/dL) reduced by 0.47 ± 0.13 h/day [mean ± SE (p = 0.0006)], and <3.1 mmol/L (55 mg/dL) reduced by 0.22 ± 0.07 h/day (p = 0.0014) for intervention participants compared with controls; reductions of 43% and 53%, respectively. SMBG frequency, similar at baseline, decreased in intervention participants from 3.8 ± 1.4 tests/day (mean ± SD) to 0.3 ± 0.7, remaining unchanged in controls. Treatment satisfaction was higher in intervention compared with controls (DTSQ 13.1 ± 0.50 (mean ± SE) and 9.0 ± 0.72, respectively; p < 0.0001). No serious adverse events or severe hypoglycemic events were reported related to sensor data use. Forty-two serious events [16 (10.7%) intervention participants, 12 (16.0%) controls] were not device-related. Six intervention participants reported nine adverse events for sensor-wear reactions (two severe, six moderate, one mild). Conclusion Flash glucose-sensing technology use in type 2 diabetes with intensive insulin therapy results in no difference in HbA1c change and reduced hypoglycemia, thus offering a safe, effective replacement for SMBG

Real-world flash glucose monitoring patterns and associations between self-monitoring frequency and glycaemic measures: A European analysis of over 60 million glucose tests

Aims Randomised controlled trials demonstrate that using flash glucose monitoring improves glycaemic control but it is unclear whether this applies outside trial conditions. We investigated glucose testing patterns in users worldwide under real life settings to establish testing frequency and association with glycaemic parameters. Methods Glucose results were de-identified and uploaded onto a dedicated database once readers were connected to an internet-ready computer. Data between September 2014 and May 2016, comprising 50,831 readers and 279,446 sensors worldwide, were analysed. Scan rate per reader was determined and each reader was sorted into twenty equally-sized rank-ordered groups, categorised by scan frequency. Glucose parameters were calculated for each group, including estimated HbA1c, time above, below and within range identified as 3.9–10.0 mmol/L. Results Users performed a mean of 16.3 scans/day [median (IQR): 14 (10–20)] with 86.4 million hours of readings and 63.8 million scans. Estimated HbA1c gradually reduced from 8.0% to 6.7% (64 to 50 mmol/mol) as scan rate increased from lowest to highest scan groups (4.4 and 48.1 scans/day, respectively; p < .001). Simultaneously, time below 3.9, 3.1 and 2.5 mmol/L decreased by 15%, 40% and 49%, respectively (all p < .001). Time above 10.0 mmol/L decreased from 10.4 to 5.7 h/day (44%, p < .001) while time in range increased from 12.0 to 16.8 h/day (40%, p < .001). These patterns were consistent across different countries. Conclusions In real-world conditions, flash glucose monitoring allows frequent glucose checks with higher rates of scanning linked to improved glycaemic markers, including increased time in range and reduced time in hyper and hypoglycaemia

Thyroid dysfunction in patients with diabetes: clinical implications and screening strategies

Background: Patients with diabetes mellitus are at an increased risk of thyroid disease. The frequency of thyroid dysfunction in diabetic patients is higher than that of the general population and up to a third of patients with type-1 diabetes (T1DM) ultimately develop thyroid dysfunction. Unrecognised thyroid dysfunction may impair metabolic control and add to cardiovascular disease risk in diabetic patients. Aims: Our aims were to review the current literature on the association between thyroid dysfunction and diabetes mellitus, to highlight relevant clinical implications, and to examine present thyroid disease screening strategies in routine diabetes care. Results: The pleiotropic effects of thyroid hormones on various metabolic processes are now better understood. Uncontrolled hyperthyroidism in diabetic patients may trigger hyperglycaemic emergencies while recurrent hypoglycaemic episodes have been reported in diabetic patients with hypothyroidism. Furthermore, thyroid dysfunction may amplify cardiovascular disease risk in diabetic patients through inter-relationships with dyslipidaemia, insulin resistance and vascular endothelial dysfunction. However, the significance of subclinical degrees of thyroid dysfunction remains to be clarified. While these developments have implications for diabetic patients a consensus is yet to be reached on optimal thyroid screening strategies in diabetes management. Conclusions: The increased frequency of thyroid dysfunction in diabetic patients and its likely deleterious effects on cardiovascular and metabolic function calls for a systematic approach to thyroid disease screening in diabetes. Routine annual thyroid testing should be targeted at diabetic patients at risk of thyroid dysfunction such as patients with T1DM, positive thyroid autoantibodies or high-normal TSH concentrations