Evidence map›Paper›PMID 37676398›Full record

ReviewEndocrine2023

An updated algorithm for an effective choice of continuous glucose monitoring for people with insulin-treated diabetes.

Maria Ida Maiorino, Raffaella Buzzetti, Concetta Irace, Luigi Laviola, Nicola Napoli, Dario Pitocco, Katherine Esposito, LIVE CGM working group

Erratum issuedOpen access · hybridAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Endocrine, 2023. 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
1.2field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Observational
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 6 institutions in 1 country.

Maria Ida MaiorinoUnit of Endocrinology and Metabolic Diseases, University Hospital Luigi Vanvitelli, Piazza Miraglia 2, 80138, Naples, Italy. mariaida.maiorino@unicampania.it.ORCID http://orcid.org/0000-0003-4659-7546
Raffaella BuzzettiDepartment of Experimental Medicine, "Sapienza" University of Rome, Viale Regina Elena 324, 00161, Rome, Italy.ORCID http://orcid.org/0000-0003-1490-6041
Concetta IraceDepartment of Health Science, University Magna Graecia, Viale Europa, 88100, Catanzaro, Italy.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, Piazza Giulio Cesare 11, 70124, Bari, Italy.ORCID http://orcid.org/0000-0001-8860-5845
Nicola NapoliFondazione Policlinico Universitario Campus Bio-Medico, Research Unit of Endocrinology and Diabetes, Department of Medicine and Surgery, Università Campus Bio-Medico of Rome, Via Alvaro del Portillo 21, 00128, Rome, Italy.ORCID http://orcid.org/0000-0002-3091-8205
Dario PitoccoDiabetes Care Unit, Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Francesco Vito 1, 00168, Rome, Italy.ORCID http://orcid.org/0000-0002-6220-686X
Katherine EspositoUnit of Endocrinology and Metabolic Diseases, University Hospital Luigi Vanvitelli, Piazza Miraglia 2, 80138, Naples, Italy.ORCID http://orcid.org/0000-0002-3652-5154
LIVE CGM working group
University of Campania "Luigi Vanvitelli" · ITMagna Graecia University · ITSapienza University of Rome · ITUniversità Campus Bio-Medico · ITUniversità Cattolica del Sacro Cuore · ITUniversity of Bari Aldo Moro · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeContinuous Glucose Monitoring (CGM) is a key tool for insulin-treated people with diabetes (PwD). CGM devices include both real-time CGM (rtCGM) and intermittently scanned CGM (isCGM), which are associated with an improvement of glucose control and less hypoglycemia in clinical trials of people with type 1 and type 2 diabetes.

methodsThis is an expert position to update a previous algorithm on the most suitable choice of CGM for insulin-treated PwD in light of the recent evidence and clinical practice.

resultsWe identified six different clinical scenarios, including type 1 diabetes, type 2 diabetes, pregnancy on intensive insulin therapy, regular physical exercise, new onset of diabetes, and frailty. The use of rtCGM or isCGM is suggested, on the basis of the predominant clinical issue, as suboptimal glucose control or disabling hypoglycemia, regardless of baseline HbA

conclusionThe present algorithm may help to select the best CGM device based on patients' clinical characteristics, needs and clinical context, offering a further opportunity of a "tailored" therapy for people with insulin-treated diabetes.

Indexed as

Diabetes Mellitus, Type 2HypoglycemiaBlood GlucoseBlood Glucose Self-MonitoringHumansHypoglycemic AgentsInsulinBlood GlucoseHypoglycemic AgentsInsulinAlgorithmContinuous glucose monitoringHypoglycemiaInsulin-treated diabetesisCGMrtCGM

Identifiers

PMID37676398
PMCPMC10543826
OpenAlexW4386498091

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.