A combined insulin reduction and carbohydrate feeding strategy 30 min before running best preserves blood glucose concentration after exercise through improved fuel oxidation in type 1 diabetes mellitus

Regular aerobic exercises are beneﬁ cial not only for healthy people. Physical activity plays a big part in the lives of children and adolescents with type 1 diabetes mellitus too. Walking, biking, swimming, dancing, and many other activities are considered to be aerobic exercises and they are all healthy. What kind of physical exercises are the most useful for the youth with type 1 diabetes mellitus? So, the aim of the present study was to estimate and compare the effect of aerobic exercise such as swimming and aerobics, on blood glucose concentration of young girls. 19 girls aged 16.5 ± 0.24 years with the duration of diabetes for 8.1 ± 0.9 years and 28 healthy girls aged 16.9 ± 0.36 years participated in the study. Two experiments were carried out. The ﬁ rst experiment was a 7-day physical exercise program, consisting of aerobics and swimming training sessions each day. The other experiment was a 14-week swimming program, where all the participants attended swimming training sessions two times per week, and there were all in all 28 training sessions. Glycemia control was assessed by blood glucose level (mmol / l) monitored before and after every training sessions during the 7-day and 14-week physical programs. After the analysis of blood test it was found, that the 7-day physical program decreased blood glucose concentration for all subjects (p < 0.05) but, swimming had a greater effect on blood glucose control for girls with type 1 diabetes mellitus than aerobics (p < 0.01). After the 14-week duration swimming program, hyperglycemia signiﬁ cantly decre-ased for all subjects too, but it’s response to the regular physical activity in the water was the highest for diabetics (p < 0.001).The evidence obtained in this study showed that both swimming and aerobics decreased blood glucose concentration for healthy subject and for subjects with diabetes. But swimming had a greater effect on the dynamics of blood glucose level for girls with type 1 diabetes mellitus than aerobics.Keywords: type 1 diabetes mellitus, swimming, aerobics, blood glucose, glycemia.

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The genetic variant of lactase persistence C/T (13910) and blood glucose control in type 1 diabetes mellitus patients

Mediterranean Journal of Nutrition and Metabolism ◽

10.3233/s12349-008-0027-y ◽

2009 ◽

Vol 1 (3) ◽

pp. 181-185

Author(s):

Rossana Mineri ◽

Giosuè Ghilardi ◽

Simona Brambilla ◽

Tiziana Sarno ◽

Muriel Bologna ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 1 Diabetes ◽

Blood Glucose ◽

Type 1 Diabetes Mellitus ◽

Glucose Control ◽

Genetic Variant ◽

Blood Glucose Control ◽

Lactase Persistence

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A Comparison of Feature Selection and Forecasting Machine Learning Algorithms for Predicting Glycaemia in Type 1 Diabetes Mellitus

Applied Sciences ◽

10.3390/app11041742 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1742

Author(s):

Ignacio Rodríguez-Rodríguez ◽

José-Víctor Rodríguez ◽

Wai Lok Woo ◽

Bo Wei ◽

Domingo-Javier Pardo-Quiles

Keyword(s):

Diabetes Mellitus ◽

Machine Learning ◽

Type 1 Diabetes ◽

Feature Selection ◽

Blood Glucose ◽

Type 1 Diabetes Mellitus ◽

Support Vector ◽

Chronic Hyperglycemia ◽

Predictive Algorithms

Type 1 diabetes mellitus (DM1) is a metabolic disease derived from falls in pancreatic insulin production resulting in chronic hyperglycemia. DM1 subjects usually have to undertake a number of assessments of blood glucose levels every day, employing capillary glucometers for the monitoring of blood glucose dynamics. In recent years, advances in technology have allowed for the creation of revolutionary biosensors and continuous glucose monitoring (CGM) techniques. This has enabled the monitoring of a subject’s blood glucose level in real time. On the other hand, few attempts have been made to apply machine learning techniques to predicting glycaemia levels, but dealing with a database containing such a high level of variables is problematic. In this sense, to the best of the authors’ knowledge, the issues of proper feature selection (FS)—the stage before applying predictive algorithms—have not been subject to in-depth discussion and comparison in past research when it comes to forecasting glycaemia. Therefore, in order to assess how a proper FS stage could improve the accuracy of the glycaemia forecasted, this work has developed six FS techniques alongside four predictive algorithms, applying them to a full dataset of biomedical features related to glycaemia. These were harvested through a wide-ranging passive monitoring process involving 25 patients with DM1 in practical real-life scenarios. From the obtained results, we affirm that Random Forest (RF) as both predictive algorithm and FS strategy offers the best average performance (Root Median Square Error, RMSE = 18.54 mg/dL) throughout the 12 considered predictive horizons (up to 60 min in steps of 5 min), showing Support Vector Machines (SVM) to have the best accuracy as a forecasting algorithm when considering, in turn, the average of the six FS techniques applied (RMSE = 20.58 mg/dL).

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Influence of initial insulin dosage on blood glucose dynamics of children and adolescents with newly diagnosed type 1 diabetes mellitus

Pediatric Diabetes ◽

10.1111/pedi.12374 ◽

2016 ◽

Vol 18 (3) ◽

pp. 196-203 ◽

Cited By ~ 3

Author(s):

Yi Wang ◽

Chunxiu Gong ◽

Bingyan Cao ◽

Xi Meng ◽

Liya Wei ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 1 Diabetes ◽

Blood Glucose ◽

Type 1 Diabetes Mellitus ◽

Children And Adolescents ◽

Insulin Dosage ◽

Newly Diagnosed ◽

Glucose Dynamics

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Comparative analysis of different drug delivery methods of injectable hydrogel nanomaterials of insulin biomaterials via multiple daily injections and continuous subcutaneous insulin infusion in the treatment of type 1 diabetes mellitus in children

Materials Express ◽

10.1166/mex.2021.2022 ◽

2021 ◽

Vol 11 (7) ◽

pp. 1154-1160

Author(s):

Yan Sun ◽

Haoshu Niu ◽

Zhixia Wang ◽

Ying Wang ◽

Xuechun Li ◽

...

Keyword(s):

Diabetes Mellitus ◽

Drug Delivery ◽

Type 1 Diabetes ◽

Blood Glucose ◽

Type 1 Diabetes Mellitus ◽

Continuous Subcutaneous Insulin Infusion ◽

Insulin Infusion ◽

Insulin Dosage ◽

Subcutaneous Insulin

The aim of this study was to investigate the difference between multiple daily injections (MDI) and continuous subcutaneous insulin infusion (CSII) in blood glucose control during the treatment of type 1 diabetes mellitus (T1DM) in children. under the nano-hydrogel delivery carrier. In order to improve the efficiency and therapeutic effect of the experiment, this paper adopts injectable nanomaterial-polymer composite hydrogel as drug delivery system to cooperate with insulin injection to improve the effective utilization of drugs. Eighty children diagnosed with T1DM by the department of Endocrinology, Genetics, and Metabolism of INNER MONGOLIA BAOGANG Hospital from October 2018 to December 2019 were selected as research subjects for this study. The children were randomly divided into MDI group (treated with MDI) and CSII group (treated with CSII), with 40 children in each group. The basic data of the children were compared, and changes in hemoglobin A1c (HbA1c) at admission and 1, 2, and 3 months after treatment were detected. During the detection, the blood glucose level, therapeutic time of blood glucose normalization, and daily insulin dosage were recorded. The HbA1c and fasting blood glucose (FBG) were followed up three months after discharge, and incidences of hypoglycemia in the two groups were observed. The results showed that the mean value of HbA1c in the MDI group was higher than that in the CSII group (P < 0.05). Each patient was assessed for the number of times their blood sugar was allowed to dip below normal levels; patients with less hypoglycemia had a higher rate of blood sugar control. The control rates of blood glucose in the MDI and CSII groups were 19.21% and 23.50%, respectively. The CSII group showed significantly higher blood glucose rates than the MDI group (P < 0.05). The therapeutic time of blood glucose normalization in the MDI group was significantly longer than that in the CSII group (P < 0.05). There was no significant difference in the average daily insulin dosage between the MDI and CSII groups (P > 0.05), which indicated that CSII therapy had significant advantages in reducing blood glucose in children with T1DM.

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Programmed Cell Death-1 Monoclonal Antibody Therapy and Type 1 Diabetes Mellitus: A Review of the Literature

Journal of Pharmacy Practice ◽

10.1177/0897190019850929 ◽

2019 ◽

pp. 089719001985092 ◽

Cited By ~ 2

Author(s):

Kyle A. Farina ◽

Michael P. Kane

Keyword(s):

Diabetes Mellitus ◽

Cell Death ◽

Type 1 Diabetes ◽

Blood Glucose ◽

Programmed Cell Death ◽

Type 1 Diabetes Mellitus ◽

Inhibitor Therapy ◽

Blood Glucose Monitoring ◽

Programmed Cell Death 1

Two Food and Drug Administration-approved programmed cell death-1 (PD-1) inhibitors, nivolumab (Opdivo®), and pembrolizumab (Keytruda®), are indicated for treatment-resistant malignancies. Inhibition of PD-1 also inhibits T-cell peripheral tolerance, enhancing autoimmunity. Various autoimmune conditions have been reported with the use of these agents, including type 1 diabetes mellitus (T1DM). This article reviews literature regarding the development of T1DM in patients treated with PD-1 inhibitors and identifies strategies for the appropriate identification, monitoring, and follow-up of these patients. Published cases of T1DM related to PD-1 inhibitor therapy were identified using PubMed. Eighty-three identified publications were reviewed, of which 37 publications involving 42 cases of anti-PD-1 therapy-induced T1DM were identified. The average age of patients at presentation was 62 years and 59.5% were male. The mean number of PD-1 inhibitor doses received was 5, with a mean time to presentation of 11 weeks. Initial presentation of diabetic ketoacidosis was reported in 69% of cases, with an average blood glucose of 660 mg/dL and an average HbA1cof 8.7%. The exact mechanism PD-1 inhibitor therapy-induced T1DM is unknown. Blood glucose monitoring is recommended for all patients receiving anti-PD-1 therapy. Further research is needed to delineate the frequency of this adverse effect, as well as to evaluate potential risk factors and ideal management strategies.

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