scholarly journals Vércukor-önellenőrzési adatok intelligens értelmezése

2015 ◽  
Vol 156 (29) ◽  
pp. 1165-1173 ◽  
Author(s):  
Mihály Dió ◽  
Tibor Deutsch ◽  
Tímea Biczók ◽  
Judit Mészáros
Keyword(s):  
Blood Glucose ◽  
Diabetes Management ◽  
Glucose Variability ◽  
Self Monitoring ◽  
Systematic Methodology ◽  
Patients With Diabetes ◽  
Recorded Data ◽  
Improved Methods ◽  
Clinical Problems

Self monitoring of blood glucose is the cornerstone of diabetes management. However, the data obtained by self monitoring of blood glucose have rarely been used with the highest advantage. Few physicians routinely download data from memory-equipped glucose meters and analyse these data systematically at the time of patient visits. There is a need for improved methods for the display and analysis of blood glucose data along with a modular approach for identification of clinical problems. The authors present a systematic methodology for the analysis and interpretation of self monitoring blood glucose data in order to assist the management of patients with diabetes. This approach utilizes the followings 1) overall quality of glycemic control; 2) severity and timing of hypoglycemia and hyperglycemia; 3) variability of blood glucose readings; 4) various temporal patterns extracted from recorded data and 5) adequacy of self monitoring blood glucose data. Based on reliable measures of the quality of glycaemic control and glucose variability, a prioritized problem list is derived along with the probable causes of the detected problems. Finally, problems and their interpretation are used to guide clinicians to choose therepeutic actions and/or recommend behaviour change in order to solve the problems that have been identified. Orv. Hetil., 2015, 156(29), 1165–1173.

scholarly journals Comparing effects of continuous glucose monitoring systems (CGMs) and self monitoring of blood glucose (SMBG) among adults with type 2 diabetes mellitus: A systematic review protocol

2020 ◽  
Author(s):  
Mingyue Zheng ◽  
Yunting Luo ◽  
Wei Lin ◽  
Adeel Khoja ◽  
Qian He ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Glucose Control ◽  
Diabetes Management ◽  
Self Monitoring ◽  
Glucose Levels

Abstract Background: Continuous glucose monitors (CGMs) have been used to manage diabetes with reasonable glucose control among patients with type 2 diabetes (T2D) in recent decades. CGM systems measure interstitial fluid glucose levels to provide information about glucose levels, which identifies fluctuation that would not have been identified with conventional self-monitoring. Self-monitoring of blood glucose (SMBG) is a classical tool to achieve glycaemic control. However, the effectiveness of glucose control, costs, and quality of life are needed to evaluate and compare CGM and SMBG among adults with T2D.Methods: The review will compare the various forms of CGM systems (i.e flash-CGM, real-time-CGM, retrospective-CGM) versus SMBG/usual intervention regarding diabetes management among adults with T2D. The following databases will be searched: Cochrane Library, Science Direct, PubMed, EMBASE, CINAHL, PsycINFO, Scopus and grey literature for the identification of studies. The studies involving adults (aged ≥ 18 years old) will be included. We will include and summararize randomised clinical trials (RCTs) with respect to authors, publication type, year, status, and type of devices. Studies published in English between February 2010 and March 2020 will be included as the field of CGMs among T2D patients has emerged over the last decade. Primary outcomes that will be measured will be; HbA1c, body weight, time spent with hypoglycaemia or hyperglycaemia, blood pressure, quality of life. Secondary outcome measured will be morbidity, all-cause mortality, user satisfaction, and barriers. Study selection, data extraction, and risk of bias assessment will be conducted independently by at least two authors. A third author will determine and resolve discrepancies. Moreover, the quality of the evidence of the review will be assessed according to the Grading of Recommendations Assessment, Development and Evaluation Tool (GRADE).Discussion: The systematic review will synthesise evidence on the comparison between using CGMs and SMBG. The results will support researchers and health care professionals to determine the most effective methods/technologies in the overall diabetes management. Moreover, this review will provide more detailed information about the barriers of using CGMs to improve implementation.Systematic review registration: PROSPERO CRD42020149212

scholarly journals Instruments for Self-Monitoring of Blood Glucose: Comparisons of Testing Quality Achieved by Patients and a Technician

2002 ◽  
Vol 48 (7) ◽  
pp. 994-1003 ◽  
Author(s):  
Svein Skeie ◽  
Geir Thue ◽  
Kari Nerhus ◽  
Sverre Sandberg
Keyword(s):  
Blood Glucose ◽  
Laboratory Method ◽  
Medical Laboratory ◽  
Healthcare Personnel ◽  
Analytical Quality ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
Quality Specifications ◽  
The Difference

Abstract Background: Instruments for self-monitoring of blood glucose (SMBG) are increasingly used by patients with diabetes. The analytical quality of meters in routine use is poorly characterized. Methods: We compared SMBG performance achieved by patients and by a medical laboratory technician. Imprecision was calculated from duplicate measurements, and deviation as the difference between the first measurement and the mean of duplicate laboratory-method results (calibrated with NIST material). Analytical quality for five groups of SMBG instruments was compared with quality specifications for BG measurements. All participants completed a questionnaire assessing both SMBG training and use of the meters. Results: We recruited 159 SMBG users from a hospital outpatient clinic and 263 others from 65 randomly selected general practices (total of 422). Most (two thirds) used insulin. CVs for the five meter types were 7%, 11%, 18%, 18%, and 20% in the hands of patients and 2.5–5.9% for the technician. For three of five meter types, patients’ BG measurements had larger deviations from the laboratory results than did the technician’s results. The technician’s performance could not predict the patients’. No instrument when used by patients (but two operated by the technician) met published quality specifications. The analytical quality of patients’ results was not related to whether they had chosen the instruments on advice from healthcare personnel (one-third of patients), were only self-educated in SMBG (50%), or performed SMBG fewer than seven times/week (62%). Conclusions: The analytical quality of SMBG among patients was poorer than, and could not be predicted from, the performance of the meters in the hands of a technician. We suggest that new instruments be tested in the hands of patients who are trained on meter use in a routine way.

scholarly journals Assessing quality of glycemic control: Hypo- and hyperglycemia, and glycemic variability using mobile self-monitoring of blood glucose system

2019 ◽  
Vol 26 (1) ◽  
pp. 287-297 ◽  
Author(s):  
Sophie Huey-Ming Guo
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Health Care Providers ◽  
Mobile Applications ◽  
Diabetes Management ◽  
Glycemic Variability ◽  
Care Providers ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
Glucose System

Although mobile applications bring potential benefits of metabolic control for patients with diabetes, their effect on glycemic fluctuation has been less widely explored. The goal of this study was to utilize data from the Mobile Self-Monitoring of Blood Glucose System to obtain a picture of the metabolic progression. Twenty-seven adults with type 2 diabetes mellitus were recruited to receive a mobile diabetes self-care system for a six-week period. The approach to the interpretation of glycemic control patterns, utilizes the following methods: 1) Graphical displays of the percentage of hyper-and-hypoglycemia episodes; 2) Pattern recognition of glycemic variability based on a simple equation involving both the standard deviation and the mean. Analytical results reveal that short-term usage of the developed system stabilizes the week-by-week glycemic fluctuations. Four categories were established to distinguish different patterns of patients’ glycemic variation. If patterns of glycemic control can be recognized or interpreted by newly designed mobile applications, then the collection and analysis of metabolic variation will greatly help both health care providers and patients in effective diabetes management.

The role of blood glucose self-monitoring in assessing glycemic variability in patients with type 1 diabetes mellitus

2021 ◽  
Vol 22 (2) ◽  
pp. 152-155
Author(s):  
A. S. Sudnitsyna ◽  
◽  
L. A. Suplotova ◽  
N. V. Romanova ◽  
◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Variability ◽  
Self Monitoring ◽  
Glucose Levels ◽  
Treatment And Prevention ◽  
Blood Glucose Levels ◽  
Patients With Diabetes ◽  
Blood Glucose Self Monitoring

In the context of the increasing prevalence of diabetes, an important task is to educate the patient on the mandatory self-monitoring of blood glucose levels (SMBG), which is an integral component of the treatment and prevention of acute and chronic complications of the disease. On the basis of the SMBG data, it is possible to assess the parameters of glycemic variability, which is the fluctuations in blood glucose during the day and differences in blood glucose levels at the same time on different days. Due to the fact that GV is one of the main criteria for assessing the quality of glycemic control, its correction is considered as a new goal in the treatment of patients with diabetes.

Self-monitoring of blood glucose and perceived obstacles in Turkish patients with diabetes mellitus

2014 ◽  
Author(s):  
Ozlem Turhan Iyidir ◽  
Mustafa Unubol ◽  
Bulent Ogun Hatipoglu ◽  
Ceyla Konca Degertekin
Keyword(s):  
Diabetes Mellitus ◽  
Blood Glucose ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
Turkish Patients

Effects of wearable technology on patients with diabetes: A systematic review and meta-analysis (Preprint)

2020 ◽  
Author(s):  
Dongjun Wu ◽  
Nicholas Buys ◽  
Guandong Xu ◽  
Jing Sun
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Relapse Prevention ◽  
Diabetes Management ◽  
Meta Analysis ◽  
Intervention Group ◽  
Wearable Technologies ◽  
Patients With Diabetes ◽  
Hba1c Levels

UNSTRUCTURED Aims: This systematic review and meta-analysis aimed to evaluate the effects of wearable technologies on HbA1c, blood pressure, body mass index (BMI), and fastening blood glucose (FBG) in patients with diabetes. Methods: We searched PubMed, Scopus, Embase, the Cochrane database, and the Chinese CNKI database from last 15 years until August 2021. The quality of the 16 included studies was assessed using the PEDro scale, and random effect models were used to estimate outcomes, with I2 used for heterogeneity testing. Results: A significant reduction in HbA1c (-0.475% [95% CI -0.692 to -0.257, P<0.001]) was found following telemonitoring. However, the results of the meta-analysis did not show significant changes in blood pressure, BMI, and glucose, in the intervention group (P>0.05), although the effect size for systolic blood pressure (0.389) and diastolic blood pressure may indicate a significant effect. Subgroup analysis revealed statistically significant effects of wearable technologies on HbA1c when supported by dietetic interventions (P<0.001), medication monitoring (P<0.001), and relapse prevention (P<0.001). Online messages and telephone interventions significantly affected HbA1c levels (P<0.001). Trials with additional online face-to-face interventions showed greater reductions in HbA1c levels. Remote interventions including dietetic advice (P<0.001), medication (P<0.001), and relapse prevention (P<0.001) during telemonitoring showed a significant effect on HbA1c, particularly in patients attending ten or more intervention sessions (P<0.001). Conclusion: Wearable technologies can improve diabetes management by simplifying self-monitoring, allowing patients to upload their live measurement results frequently and thereby improving the quality of telemedicine. Wearable technologies also facilitate remote medication management, dietetic interventions, and relapse prevention.

scholarly journals Insulin Glargine and Acarbose in the treatment of elderly patients with diabetes

2019 ◽  
Vol 35 (3) ◽  
Author(s):  
Jing Li ◽  
Jinzhi Ji ◽  
Fuyan Liu ◽  
Lingling Wang
Keyword(s):  
Quality Of Life ◽  
Blood Glucose ◽  
Elderly Patients ◽  
Insulin Glargine ◽  
Adverse Reactions ◽  
Postprandial Blood Glucose ◽  
Control Group ◽  
Observation Group ◽  
Patients With Diabetes

Objective: To investigate the clinical efficacy of insulin glargine combined with acarbose in the treatment of elderly patients with diabetes. Methods: One hundred and forty-four elderly patients with diabetes who received treatment between December 2016 and December 2017 in Binzhou People’s Hospital, China, were selected and divided into a control group and an observation group, 72 each, using random number table. The control group was treated with insulin glargine, while the observation group was treated with insulin glargine combined with acarbose. The therapeutic effect, improvement of quality of life and adverse reactions were compared between the two groups. Results: After treatment, fasting blood glucose (FBG), 2h postprandial blood glucose (PBG) and glycosylated hemoglobin (Hb Alc) of the two groups were lower than those before treatment, and the decrease degree of the observation group was significantly larger than that of the control group (P<0.05). The time needed for blood glucose reaching the standard level and daily insulin dosage of the observation group were significantly lower than that of the control group, and the differences were statistically significant (P<0.05). SF-36 scale score of the observation group was significantly better than the control group, and the difference was statistically significant (P<0.05). There was no significant difference in the incidence of adverse reactions between the two groups (P>0.05). Conclusion: The combination of insulin Glargine and Acarbose can significantly control the blood glucose level of elderly patients with diabetes, improve the biochemical indicators, and enhance the quality of life. It is worth promotion in clinical practice. doi: https://doi.org/10.12669/pjms.35.3.86 How to cite this:Li J, Ji J, Liu F, Wang L. Insulin Glargine and Acarbose in the treatment of elderly patients with diabetes. Pak J Med Sci. 2019;35(3):---------. doi: https://doi.org/10.12669/pjms.35.3.86 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology

2021 ◽  
pp. 193229682110541
Author(s):  
Farid Sanai ◽  
Arshman S. Sahid ◽  
Jacqueline Huvanandana ◽  
Sandra Spoa ◽  
Lachlan H. Boyle ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Blood Glucose ◽  
Real World ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Self Monitoring ◽  
Non Invasive ◽  
Adult Participants ◽  
Blood Glucose Monitor

Background: Frequent blood glucose level (BGL) monitoring is essential for effective diabetes management. Poor compliance is common due to the painful finger pricking or subcutaneous lancet implantation required from existing technologies. There are currently no commercially available non-invasive devices that can effectively measure BGL. In this real-world study, a prototype non-invasive continuous glucose monitoring system (NI-CGM) developed as a wearable ring was used to collect bioimpedance data. The aim was to develop a mathematical model that could use these bioimpedance data to estimate BGL in real time. Methods: The prototype NI-CGM was worn by 14 adult participants with type 2 diabetes for 14 days in an observational clinical study. Bioimpedance data were collected alongside paired BGL measurements taken with a Food and Drug Administration (FDA)-approved self-monitoring blood glucose (SMBG) meter and an FDA-approved CGM. The SMBG meter data were used to improve CGM accuracy, and CGM data to develop the mathematical model. Results: A gradient boosted model was developed using a randomized 80-20 training-test split of data. The estimated BGL from the model had a Mean Absolute Relative Difference (MARD) of 17.9%, with the Parkes error grid (PEG) analysis showing 99% of values in clinically acceptable zones A and B. Conclusions: This study demonstrated the reliability of the prototype NI-CGM at collecting bioimpedance data in a real-world scenario. These data were used to train a model that could successfully estimate BGL with a promising MARD and clinically relevant PEG result. These results will enable continued development of the prototype NI-CGM as a wearable ring.

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