Evidence map›Paper›PMID 24876570›Full record

ArticleJournal of diabetes science and technology2014

Monitoring Artificial Pancreas Trials Through Agent-based Technologies: A Case Report.

Giordano Lanzola, Stefania Scarpellini, Federico Di Palma, Chiara Toffanin, Simone Del Favero, Lalo Magni, Riccardo Bellazzi, on behalf of the AP@home consortium

Open access · bronzeAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.6field-weighted citation impact, top 6% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Review
  3. Designing an artificial pancreas architecture: the AP@home experience.Medical & biological engineering & computing · 2015
    Article
  4. Big Data Technologies: New Opportunities for Diabetes Management.Journal of diabetes science and technology · 2015
    Review
  5. Fault detection and safety in closed-loop artificial pancreas systems.Journal of diabetes science and technology · 2014
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Giordano LanzolaDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy giordano.lanzola@unipv.it.
Stefania ScarpelliniDepartment of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.
Federico Di PalmaDepartment of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.
Chiara ToffaninDepartment of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.
Simone Del FaveroDepartment of Information Engineering, University of Padova, Padova, Italy.
Lalo MagniDepartment of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.
Riccardo BellazziDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
on behalf of the AP@home consortium
University of Pavia · ITUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increase in the availability and reliability of network connections lets envision systems supporting a continuous remote monitoring of clinical parameters useful either for overseeing chronic diseases or for following clinical trials involving outpatients. We report here the results achieved by a telemedicine infrastructure that has been linked to an artificial pancreas platform and used during a trial of the AP@home project, funded by the European Union. The telemedicine infrastructure is based on a multiagent paradigm and is able to deliver to the clinic any information concerning the patient status and the operation of the artificial pancreas. A web application has also been developed, so that the clinic staff and the researchers involved in the design of the blood glucose control algorithms are able to follow the ongoing experiments. Albeit the duration of the experiments in the trial discussed in the article was limited to only 2 days, the system proved to be successful for monitoring patients, in particular overnight when the patients are sleeping. Based on that outcome we can conclude that the infrastructure is suitable for the purpose of accomplishing an intelligent monitoring of an artificial pancreas either during longer trials or whenever that system will be used as a routine treatment.

Indexed as

artificial pancreasclinical trialdiabetes mellitus type 1remote monitoringtelemedicine

Identifiers

PMID24876570
PMCPMC4455402
OpenAlexW2152929394

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.