Evidence map›Paper›PMID 26424241›Full record

ArticleJournal of diabetes science and technology2015

Development of a Smartphone Application to Capture Carbohydrate, Lipid, and Protein Contents of Daily Food: Need for Integration in Artificial Pancreas for Patients With Type 1 Diabetes?

Omar Diouri, Jerome Place, Magali Traverso, Vera Georgescu, Marie-Christine Picot, Eric Renard

Open access · bronzeAbstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes science and technology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. Trial
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

6 authors at 4 institutions in 1 country.

Omar DiouriInstitute of Functional Genomics, CNRS UMR 5203, INSERM U1191, University of Montpellier, Montpellier, France.
Jerome PlaceInstitute of Functional Genomics, CNRS UMR 5203, INSERM U1191, University of Montpellier, Montpellier, France.
Magali TraversoMontpellier University Hospital, Department of Endocrinology, Diabetes, Nutrition, Montpellier, France.
Vera GeorgescuMontpellier University Hospital, Department of Medical Information, Unit of Clinical and Epidemiological Research, Montpellier, France.
Marie-Christine PicotMontpellier University Hospital, Department of Medical Information, Unit of Clinical and Epidemiological Research, Montpellier, France INSERM Clinical Investigation Centre 1411, Montpellier, France.
Eric RenardInstitute of Functional Genomics, CNRS UMR 5203, INSERM U1191, University of Montpellier, Montpellier, France Montpellier University Hospital, Department of Endocrinology, Diabetes, Nutrition, Montpellier, France Montpellier University Hospital, Department of Medical Information, Unit of Clinical and Epidemiological Research, Montpellier, France e-renard@chu-montpellier.fr.
Centre Hospitalier Universitaire de Montpellier · FRUniversité de Montpellier · FRCentre National de la Recherche Scientifique · FRInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeal lipids (LIP) and proteins (PRO) may influence the effect of insulin doses based on carbohydrate (CHO) counting in patients with type 1 diabetes (T1D). We developed a smartphone application for CHO, LIP, and PRO counting in daily food and assessed its usability in real-life conditions and potential usefulness.

methodsTen T1D patients used the android application for 1 week to collect their food intakes. Data included meal composition, premeal and 2-hour postmeal blood glucose, corrections for hypo- or hyperglycemia after meals, and time for entering meals in the application. Meal insulin doses were based on patients' CHO counting (application in blinded mode). Linear mixed models were used to assess the statistical differences.

resultsIn all, 187 meals were analyzed. Average computed CHO amount was 74.37 ± 31.78 grams; LIP amount: 20.26 ± 14.28 grams and PRO amount: 25.68 ± 16.68 grams. Average CHO, LIP, and PRO contents were significantly different between breakfast and lunch/dinner. The average time for meal entry in the application moved from 3-4 minutes to 2.5 minutes during the week. No significant impact of LIP and PRO was found on available blood glucose values.

conclusionOur study shows CHO, LIP, and PRO intakes can be easily captured by an application on smartphone for meal entry used by T1D patients. Although LIP and PRO meal contents did not influence glucose levels when insulin doses were based on CHO in this pilot study, this application could be used for further investigation of this topic, including in closed-loop conditions.

Indexed as

Diet, DiabeticMobile ApplicationsPancreas, ArtificialSmartphoneAdultBiomarkersBlood GlucoseDiabetes Mellitus, Type 1Dietary CarbohydratesDietary FatsDietary ProteinsEquipment DesignFemaleGlycated HemoglobinHumansHypoglycemic AgentsBiomarkersBlood GlucoseDietary CarbohydratesDietary FatsDietary ProteinsGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsInsulincarbohydratesglucose controllipidsproteinssmartphone applicationtype 1 diabetes

Identifiers

PMID26424241
PMCPMC4667322
OpenAlexW2176057119

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.