Evidence map›Paper›PMID 32928790›Full record

ArticleBMJ open diabetes research & care2020

Determinants of good metabolic control without weight gain in type 2 diabetes management: a machine learning analysis.

Carlo Bruno Giorda, Federico Pisani, Alberto De Micheli, Paola Ponzani, Giuseppina Russo, Giacomo Guaita, Rita Zilich, Nicoletta Musacchio, Associazione Medici Diabetologi (AMD) Annals Study Group

Open access · goldAbstract read
In one paragraph

Article in BMJ open diabetes research & care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

Carlo Bruno GiordaDiabetes and Endocrinology Unit, ASL TO5, Chieri, Turin, Italy carlogiordaposta@gmail.com.ORCID 0000-0002-4709-8696
Federico PisaniFreelance Artificial Intelligence Expert, Ivrea (TO), Ivrea, Italy.ORCID 0000-0001-8125-8553
Alberto De MicheliACISMOM, Genova, Italy.
Paola PonzaniOperative Unit of Diabetology, La Colletta Hospital, ASL 3, Genova, Italy.
Giuseppina RussoInternal Medicine, University of Messina, Messina, Italy.
Giacomo GuaitaDiabetology, Endocrinology and Metabolic Diseases Service, ATS Sardegna-ASSL, Carbonia, Italy.
Rita ZilichMix-x Partner, Milano, Italy.
Nicoletta MusacchioAssociazione Medici Diabetologi (AMD), "Fondazione AMD", Roma, Italy.
Associazione Medici Diabetologi (AMD) Annals Study Group
Associazione Medici Diabetologi · ITATS Sardegna (Italy) · ITUniversity of Messina · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe aim of this study was to investigate the factors (clinical, organizational or doctor-related) involved in a timely and effective achievement of metabolic control, with no weight gain, in type 2 diabetes. RESEARCH DESIGN AND

methodsOverall, 5.5 million of Hab1c and corresponding weight were studied in the Associazione Medici Diabetologi Annals database (2005-2017 data from 1.5 million patients of the Italian diabetes clinics network). Logic learning machine, a specific type of machine learning technique, was used to extract and rank the most relevant variables and to create the best model underlying the achievement of HbA1c<7 and no weight gain.

resultsThe combined goal was achieved in 37.5% of measurements. High HbA1c and fasting glucose values and slow drop of HbA1c have the greatest relevance and emerge as first, main, obstacles the doctor has to overcome. However, as a second line of negative factors, markers of insulin resistance, microvascular complications, years of observation and proxy of duration of disease appear to be important determinants. Quality of assistance provided by the clinic plays a positive role. Almost all the available oral agents are effective whereas insulin use shows positive impact on glucometabolism but negative on weight containment. We also tried to analyze the contribution of each component of the combined endpoint; we found that weight gain was less frequently the reason for not reaching the endpoint and that HbA1c and weight have different determinants. Of note, use of glucagon-like peptide-1 receptor agonists (GLP1-RA) and glifozins improves weight control.

conclusionsTreating diabetes as early as possible with the best quality of care, before beta-cell deterioration and microvascular complications occurrence, make it easier to compensate patients. This message is a warning against clinical inertia. All medications play a role in goal achievements but use of GLP1-RAs and glifozins contributes to overweight prevention.

Indexed as

Diabetes Mellitus, Type 2Body WeightHumansItalyMachine LearningWeight Gaindisease management

Identifiers

PMID32928790
PMCPMC7490948
OpenAlexW3085751993

What OpenQuestion holds

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Registered trials

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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.