scholarly journals Influence of the stage of emergency declaration due to the coronavirus disease 2019 outbreak on plasma glucose control of patients with diabetes mellitus in the Saku region of Japan

2021 ◽  
Vol 16 (2) ◽  
pp. 98-101
Author(s):  
Takuya Watanabe ◽  
Yuichi Temma ◽  
Junichi Okada ◽  
Eijiro Yamada ◽  
Tsugumichi Saito ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Plasma Glucose ◽  
Glucose Control ◽  
Patients With Diabetes

scholarly journals Influence of Emergency Declaration Over Coronavirus Disease 2019 on Plasma Glucose Control of Patients With Diabetes Mellitus

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A347-A347
Author(s):  
Takuya Watanabe ◽  
Tetsuya Takamizawa ◽  
Junichi Okada ◽  
Eijiro Yamada ◽  
Tsugumichi Saito ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Plasma Glucose ◽  
Glucose Control ◽  
The State ◽  
The Self ◽  
State Of Emergency ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
The Mean ◽  
Hba1c Levels

Abstract COVID-19 pandemic poses problems that not only concern the economy but also the health of people all over the world. In Japan, despite the declaration of a “state of emergency”, no lockdown was implemented, and a request for self-restraint and avoidance of non-essential trips was instead issued. After a month, the state of emergency was lifted. Because patients with diabetes mellitus (DM) were forced to stay during the state of emergency, resulting in a lack of physical activity, concerns about their glycemic control were raised. Therefore, glycated hemoglobin (HbA1c) levels during different time periods were compared (May 2018, March 2019, June 2019, July 2019, May 2019, March 2020, June 2020, July 2020). We analyzed 165 patients with DM. The mean age of subjects was 67.8 + 11.5 years. Male comprised 67.3% of the participants. The mean body weight was 65.6 + 14.6 kg on July 2019 and 66.1 + 15.2 kg on July 2020. The mean body mass index (BMI) was 24.4 + 3.6 kg/m2 on July 2019 and 24.4 + 3.6 on July 2020. Patients with Type 2 DM (T2DM) comprised 90% of the participants, while the rest had T1DM. Mean duration of DM was 12.0 + 7.4 years. In order to assess the effect of the self-restraint on plasma glucose control, HbA1c levels during these periods were compared: May 2018, March 2019, June 2019, July 2019 (one year before COVID-19 pandemic.), and May 2019, March 2020, June 2020, July 2020 (The last three months during COVID-19). March 2020 is corresponded to a period before the request for self-restraint, while June and July 2020 corresponded to the periods right after the end of self-restraint. We also compared HbA1c levels between May 2019 and July 2020 using the Self-Monitoring of Blood Glucose (SMBG) to assess whether SMBG affected plasma glucose control during the period of self-restraint. HbA1c levels in May 2018, March 2019, June 2019, July 2019, May 2019, March 2020, June 2020, July 2020, were 7.32 + 1.23, 7.44 + 1.20, 7.16 + 1.06, 7.01 + 1.05, 7.23 + 1.06, 7.45 + 1.18, 7.15 + 10.7, and 7.11 + 1.17, respectively. Similarly, HbA1c levels between May 2019 without SMBG and May 2019 with SMBG were not statistically different. In this clinical study, we found that the request to avoid non-essential trips as a form of self-restraint during the country’s state of emergency did not affect plasma glucose control of patients with DM. We noted that the patients did not have signs of insulin resistance as their BMI on July 2019 and July 2020 were 24.4 + 3.6 and 24.4 + 3.6, respectively. Unexpectedly, the HbA1c levels were not affected by the absence or presence of SMBG. This could explain why HbA1c levels were not elevated, despite a temporarily sedentary lifestyle and a lack of exercise for a month. In addition, due to the self-restraint, the frequency of dining outside the house decreased, which could have contributed to the non-elevation of HbA1c levels.

Glucose Control

2020 ◽  
Author(s):  
Timothy P. Graham ◽  
Erich N. Marks ◽  
Joshua J. Sebranek ◽  
Douglas B. Coursin
Keyword(s):  
Diabetes Mellitus ◽  
Critically Ill ◽  
Glucose Control ◽  
Cost Of Care ◽  
Hospital Length Of Stay ◽  
Glucose Measurement ◽  
Key Words Diabetes Mellitus ◽  
Key Words Diabetes ◽  
Adult Intensive Care Unit ◽  
Patients With Diabetes

Patients with diabetes mellitus routinely require management in the adult intensive care unit (ICU). These patients have increased morbidity, mortality, hospital length of stay, cost of care, and frequency of hospital and ICU admission. Glucose control in these patients presents challenges for the clinician. In the critically ill, hyperglycemia does not occur exclusively in patients with diabetes or prediabetes but may be related to stress-induced hyperglycemia or iatrogenic causes. Hyperglycemia can contribute to decreased wound healing and immune function and a host of cellular and molecular dysfunctions and has been linked to increased hospital mortality. Hypoglycemia in the ICU is associated with patients with preexisting diabetes, those receiving insulin and other medications, and septic individuals, among others. Insulin therapy is the mainstay of glucose management in the critically ill. ICU practitioners should be aware that point-of-care glucose meters are not as accurate as core laboratory results. Finally, both hypoglycemia and wide fluctuations in blood glucose during critical illness are also associated with increased mortality, although clear cause-and-effect relationships have not been established. This review contains 1 figure, 8 tables, and 71 references. Key words: Diabetes mellitus, glucose measurement, glucose targets, hyperglycemia, hypoglycemia, insulin

scholarly journals Thyroid Disorders and Diabetes Mellitus

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Mirella Hage ◽  
Mira S. Zantout ◽  
Sami T. Azar
Keyword(s):  
Diabetes Mellitus ◽  
Glucose Control ◽  
Systematic Approach ◽  
Endocrine System ◽  
Thyroid Disorders ◽  
Patients With Diabetes

Studies have found that diabetes and thyroid disorders tend to coexist in patients. Both conditions involve a dysfunction of the endocrine system. Thyroid disorders can have a major impact on glucose control, and untreated thyroid disorders affect the management of diabetes in patients. Consequently, a systematic approach to thyroid testing in patients with diabetes is recommended.

scholarly journals Urogenital infections in patients with diabetes mellitus: Beyond the conventional aspects

2019 ◽  
Vol 33 ◽  
pp. 205873841986658
Author(s):  
Sandro La Vignera ◽  
Rosita A Condorelli ◽  
Rossella Cannarella ◽  
Filippo Giacone ◽  
Laura M Mongioi’ ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Glucose Control ◽  
Combined Treatment ◽  
Accessory Gland ◽  
Diabetic Patients ◽  
Proper Management ◽  
Urogenital Infections ◽  
Patients With Diabetes ◽  
Microbial Characterization ◽  
Tract Infections

Diabetes mellitus (DM) is a widespread disease in our country. Urogenital infections, including urinary tract infections, vaginitis, balanitis, balanoposthitis, and male accessory gland infections, show a higher risk of occurrence in patients with DM that non-diabetic subjects. Both non-drug-related and drug-related mechanisms are involved in their pathogenesis. These conditions may impact on glucose control and islets function in DM and more likely develop into adverse complications. A throughout microbial characterization, including the drug-sensitivity test, is required for a proper management. To reduce the risk of recurrence, combined treatment, including antibiotic, anti-inflammatory, and fibrinolytic molecules, should be prescribed also to the sexual partner. The choice of the antidiabetic drug to prescribe should take into consideration the presence of urogenital infections. In conclusion, urogenital infections may more likely lead to complication in diabetic than non-diabetic patients, affect fertility and glucose control. Therefore, they need proper management.

scholarly journals The Diabits App for Smartphone-Assisted Predictive Monitoring of Glycemia in Patients With Diabetes: Retrospective Observational Study (Preprint)

2020 ◽  
Author(s):  
Stan Kriventsov ◽  
Alexander Lindsey ◽  
Amir Hayeri
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Glucose Control ◽  
Reference Range ◽  
Blood Glucose Control ◽  
Data Set ◽  
Patients With Diabetes ◽  
Average Blood Glucose

BACKGROUND Diabetes mellitus, which causes dysregulation of blood glucose in humans, is a major public health challenge. Patients with diabetes must monitor their glycemic levels to keep them in a healthy range. This task is made easier by using continuous glucose monitoring (CGM) devices and relaying their output to smartphone apps, thus providing users with real-time information on their glycemic fluctuations and possibly predicting future trends. OBJECTIVE This study aims to discuss various challenges of predictive monitoring of glycemia and examines the accuracy and blood glucose control effects of Diabits, a smartphone app that helps patients with diabetes monitor and manage their blood glucose levels in real time. METHODS Using data from CGM devices and user input, Diabits applies machine learning techniques to create personalized patient models and predict blood glucose fluctuations up to 60 min in advance. These predictions give patients an opportunity to take pre-emptive action to maintain their blood glucose values within the reference range. In this retrospective observational cohort study, the predictive accuracy of Diabits and the correlation between daily use of the app and blood glucose control metrics were examined based on real app users’ data. Moreover, the accuracy of predictions on the 2018 Ohio T1DM (type 1 diabetes mellitus) data set was calculated and compared against other published results. RESULTS On the basis of more than 6.8 million data points, 30-min Diabits predictions evaluated using Parkes Error Grid were found to be 86.89% (5,963,930/6,864,130) clinically accurate (zone A) and 99.56% (6,833,625/6,864,130) clinically acceptable (zones A and B), whereas 60-min predictions were 70.56% (4,843,605/6,864,130) clinically accurate and 97.49% (6,692,165/6,864,130) clinically acceptable. By analyzing daily use statistics and CGM data for the 280 most long-standing users of Diabits, it was established that under free-living conditions, many common blood glucose control metrics improved with increased frequency of app use. For instance, the average blood glucose for the days these users did not interact with the app was 154.0 (SD 47.2) mg/dL, with 67.52% of the time spent in the healthy 70 to 180 mg/dL range. For days with 10 or more Diabits sessions, the average blood glucose decreased to 141.6 (SD 42.0) mg/dL (<i>P</i>&lt;.001), whereas the time in euglycemic range increased to 74.28% (<i>P</i>&lt;.001). On the Ohio T1DM data set of 6 patients with type 1 diabetes, 30-min predictions of the base Diabits model had an average root mean square error of 18.68 (SD 2.19) mg/dL, which is an improvement over the published state-of-the-art results for this data set. CONCLUSIONS Diabits accurately predicts future glycemic fluctuations, potentially making it easier for patients with diabetes to maintain their blood glucose in the reference range. Furthermore, an improvement in glucose control was observed on days with more frequent Diabits use. CLINICALTRIAL

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