Trial reportNagoya journal of medical science2017
Randomized controlled trial for assessment of Internet of Things system to guide intensive glucose control in diabetes outpatients: Nagoya Health Navigator Study protocol.
Trial report in Nagoya journal of medical science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis.Sensors (Basel, Switzerland) · 2020Pooled it
- Internet of things-based approach for glycemic control in people with type 2 diabetes: A randomized controlled trial.Journal of diabetes investigation · 2024Trial
- Non-Invasive Wearable Devices for Monitoring Vital Signs in Patients with Type 2 Diabetes Mellitus: A Systematic Review.Bioengineering (Basel, Switzerland) · 2023Review
- Article
- Article
- Medical Equipment Comprehensive Management System Based on Cloud Computing and Internet of Things.Journal of healthcare engineering · 2021Article
- Noninvasive Continuous Monitoring of Vital Signs With Wearables: Fit for Medical Use?Journal of diabetes science and technology · 2021Article
- Scoping Review of Healthcare Literature on Mobile, Wearable, and Textile Sensing Technology for Continuous Monitoring.Journal of healthcare informatics research · 2021Article
- Towards an Architecture to Guarantee Both Data Privacy and Utility in the First Phases of Digital Clinical Trials.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Internet of Things (IoT) allows collecting vast amounts of health-relevant data such as daily activity, body weight (BW), and blood pressure (BP) automatically. The use of IoT devices to monitor diabetic patients has been studied, but could not evaluate IoT-dependent effects because health data were not measured in control groups. This multicenter, open-label, randomized, parallel group study will compare the impact of intensive health guidance using IoT and conventional medical guidance on glucose control. It will be conducted in outpatients with type 2 diabetes for a period of 6 months. IoT devices to measure amount of daily activity, BW, and BP will be provided to IoT group patients. Healthcare professionals (HCPs) will provide appropriate feedback according to the data. Non-IoT control, patients will be given measurement devices that do not have a feedback function. The primary outcome is glycated hemoglobin at 6 months. The study has already enrolled 101 patients, 50 in the IoT group and 51 in the non-IoT group, at the two participating outpatient clinics. The baseline characteristics of two groups did not differ, except for triglycerides. This will be the first randomized, controlled study to evaluate IoT-dependent effects of intensive feedback from HCPs. The results will validate a new method of health-data collection and provision of feedback suitable for diabetes support with increased effectiveness and low cost.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.