The CONSORT-EHEALTH checklist is intended for authors of randomized trials evaluating webbased and Internet-based applications/interventions, including mobile interventions, electronic games (incl multiplayer games), social media, certain telehealth applications, and other interactive and/or networked electronic applications. Some of the items (e.g. all subitems under item 5 -description of the intervention) may also be applicable for other study designs.The goal of the CONSORT EHEALTH checklist and guideline is to be a) a guide for reporting for authors of RCTs, b) to form a basis for appraisal of an ehealth trial (in terms of validity)CONSORT-EHEALTH items/subitems are MANDATORY reporting items for studies published in the Journal of Medical Internet Research and other journals / scienti䀒c societies endorsing the checklist.Items numbered 1., 2., 3., 4a., 4b etc are original CONSORT or CONSORT-NPT (non-pharmacologic treatment) items. Items with Roman numerals (i., ii, iii, iv etc.) are CONSORT-EHEALTH extensions/clari䀒cations.As the CONSORT-EHEALTH checklist is still considered in a formative stage, we would ask that you also RATE ON A SCALE OF 1-5 how important/useful you feel each item is FOR THE PURPOSE OF THE CHECKLIST and reporting guideline (optional).
Self-monitoring of blood glucose (SMBG) is an integral component of effective diabetes management, allowing patients to evaluate their individual response to therapy and assess whether individual glycemic targets are being achieved.1,2 Appropriate education addressing SMBG interpretation and particularly the response to "out of-range" blood glucose (BG) results are prerequisites for the useful performance of SMBG.3,4 Recent studies have highlighted the issue of interpreting and responding to SMBG. A study in 207 patients with T2DM 5 investigating perceptions of high BG results demonstrated that the subjects were more tolerant of high BG levels than is clinically advisable. In addition, a survey of 886 people with T2DM showed that about half of insulin and non-insulin-using patients with T2DM regularly took no action for out-of-range BG values (low or high) with any self-care adjustments. 6 We recently reported that a blood glucose meter (BGM) that provides automatic on-screen glucose range information using a color range indicator (CRI) We previously demonstrated that people with type 2 diabetes (T2DM) can improve their ability to categorize blood glucose (BG) results into low, in range, or high glycemic ranges after experiencing a color range indicator (CRI or ColorSure™ Technology) in a single meter. This study examined whether a CRI was effective in people with type 1 (T1) or T2DM when used in 3 glucose meters.Methods: A total of 179 subjects (139 T2DM and 40 T1DM) classified BG values as low, in range, or high based on individual current knowledge. Subjects then experienced the CRI which showed whether different BG values were low, in range, or high. After CRI interaction, subjects repeated the classification.
Results:Following interaction with the CRI, subjects significantly improved their ability to categorize BG results into low, in range, and high glycemic ranges by 27.9% (T2DM) and 27.2% (T1DM) (each P < .001). Improvement was not accompanied by an increase in time spent categorizing results. There was no difference in classification ability between subjects with T1 or T2DM. There was also no correlation between HbA1c, numeracy level, test frequency, or duration of diabetes and the ability to correctly classify results. Subjects agreed the CRI feature helped them easily interpret glucose values and improved their awareness of glucose ranges.
Conclusion:Interaction with a CRI improved the ability of subjects with T1 and T2DM to interpret and categorize BG values into recommended glycemic ranges, irrespective of the glucose meter providing the CRI insights.
Background: Cloud-connected diabetes applications enable health care professionals (HCPs) to monitor patient progress and offer the potential for remote consultations. OneTouch Reveal (OTR) is a cloud-based web application that aggregates data from blood glucose (BG) meters or insulin pumps and provides analytics to help patients and HCPs make more informed treatment and lifestyle decisions. This study assessed the experience of patients using OTR and the OneTouch Verio (OTV) BG meter and determined the extent of changes in glycemic control. Methods: Subjects with T1DM (23) or T2DM (17) uploaded BG meter results to OTR for 12 weeks. HCPs remotely reviewed progress using OTR and delivered telephone consultations at 4 and 8 weeks based on OTR insights. Results: After 12 weeks, mean HbA1c decreased by 0.4% ( P < .001) and 25% of subjects had a reduction of ≥1.0%. Reduction in HbA1c was similar in subjects with T1DM and T2DM, although subjects with T1DM started with higher baselines. In subjects with T2DM, mean BG decreased significantly from 175 to 161 mg/dl ( P < .001) with the percentage of above-range BG results decreasing from 33% to 24%. 80% of subjects confirmed OTR detected out-of-range glucose patterns and 84% of these subjects were able to correct the underlying pattern to get BG back in-range. Conclusions: OTR web application in combination with the OTV meter helped subjects with T1DM and T2DM effectively manage their diabetes and was associated with improved BG control over 12 weeks. Real-time visibility to subject data may help HCPs deliver focused and effective remote consultations.
This 7-year surveillance program showed the test strips to have excellent clinical accuracy at the outer ranges of subject blood glucose and hematocrit, based on assessment against the ISO 15197:2015 clinical accuracy criterion.
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