Evidence map›Paper›PMID 39347900›Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2024

Criteria for Personalised Choice of a Continuous Glucose Monitoring System: An Expert Opinion.

Sergio Di Molfetta, Antonio Rossi, Federico Boscari, Concetta Irace, Luigi Laviola, Daniela Bruttomesso

Erratum issuedAbstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Sergio Di Molfetta *Department of Precision and Regenerative Medicine and Ionian Area, Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, University of Bari Aldo Moro, 70124, Bari, Italy.ORCID http://orcid.org/0000-0003-3454-7330
Antonio Rossi *IRCCS Ospedale Galeazzi-Sant'Ambrogio, Department of Biomedical and Clinical Sciences, University of Milan, 20157, Milan, Italy.ORCID http://orcid.org/0000-0002-8660-2146
Federico BoscariUnit of Metabolic Diseases, University Hospital of Padua, 35128, Padua, Italy.ORCID http://orcid.org/0000-0002-9670-615X
Concetta IraceDepartment of Health Science, University Magna Græcia Catanzaro, Viale Europa Località Germaneto, 88100, Catanzaro, Italy. irace@unicz.it.ORCID http://orcid.org/0000-0001-5182-5473
Luigi LaviolaDepartment of Precision and Regenerative Medicine and Ionian Area, Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, University of Bari Aldo Moro, 70124, Bari, Italy.ORCID http://orcid.org/0000-0001-8860-5845
Daniela BruttomessoUnit of Metabolic Diseases, University Hospital of Padua, 35128, Padua, Italy.ORCID http://orcid.org/0000-0002-2426-8955

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the growing evidence supporting the outpatient use of continuous glucose monitoring (CGM) for improving glycaemic control and reducing hypoglycaemia, there is a need for a detailed understanding of the specific features of CGM devices that best meet individual patient needs. This expert opinion, based on a comprehensive literature review and the personal perspectives of clinicians, aims to provide the healthcare professionals (HCPs) with a comprehensive framework for selecting CGM devices. It evaluates the current state of CGM technology, categorizing features into essential features, major drivers of choice, and additional/useful features. Moreover, the practical model presented outlines a patient's journey with CGM, emphasising the importance of aligning device features with patient needs. This includes understanding the patient's lifestyle, clinical conditions, and personal preferences to optimize CGM use and improve diabetes management outcomes.

Indexed as

Choice-driving factorsContinuous glucose monitoringDiabetes technologySensor features

Identifiers

PMID39347900
PMCPMC11467157

What OpenQuestion holds

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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.