Evidence map›Paper›PMID 24971031›Full record

ReviewPharmacogenomics and personalized medicine2014

Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach.

Antonio Ceriello, Marco Gallo, Riccardo Candido, Alberto De Micheli, Katherine Esposito, Sandro Gentile, Gerardo Medea

Open access · goldAbstract readReview
In one paragraph

Review in Pharmacogenomics and personalized medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
3.2field-weighted citation impact, top 8% 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 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

7 authors at 4 institutions in 2 countries.

Antonio CerielloDepartment of Endocrinology, Hospital Clinic de Barcelona, Institut d'Investigacions Biomèdiques August Pi iSunyer, Barcelona, Spain ; Centro de Investigacion Biomèdica en Red de Diabetes y Enfermedades Metabolicas Asociadas, Barcelona, Spain.
Marco GalloOncological Endocrinology, AOU Città della Salute e della Scienza-Molinette, Turin, Italy.
Riccardo CandidoDiabetes Center, ASS 1 Triestina, Trieste, Italy.
Alberto De MicheliLigurian Health Agency, Genoa, Italy.
Katherine EspositoDepartment of Clinical and Experimental Medicine, Second University of Naples, Naples, Italy.
Sandro GentileDepartment of Clinical and Experimental Medicine, Second University of Naples, Naples, Italy.
Gerardo MedeaItalian College of General Practitioners, Florence, Italy.
University of Campania "Luigi Vanvitelli" · ITAgenzia Regionale per la Protezione dell'ambiente ligure · ITAzienda Sanitaria Universitaria Integrata di Trieste · ITCentro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas Asociadas · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes is a progressive disease with a complex and multifactorial pathophysiology. Patients with type 2 diabetes show a variety of clinical features, including different "phenotypes" of hyperglycemia (eg, fasting/preprandial or postprandial). Thus, the best treatment choice is sometimes difficult to make, and treatment initiation or optimization is postponed. This situation may explain why, despite the existing complex therapeutic armamentarium and guidelines for the treatment of type 2 diabetes, a significant proportion of patients do not have good metabolic control and at risk of developing the late complications of diabetes. The Italian Association of Medical Diabetologists has developed an innovative personalized algorithm for the treatment of type 2 diabetes, which is available online. According to the main features shown by the patient, six algorithms are proposed, according to glycated hemoglobin (HbA1c, ≥9% or ≤9%), body mass index (≤30 kg/m(2) or ≥30 kg/m(2)), occupational risk potentially related to hypoglycemia, chronic renal failure, and frail elderly status. Through self-monitoring of blood glucose, patients are phenotyped according to the occurrence of fasting/preprandial or postprandial hyperglycemia. In each of these six algorithms, the gradual choice of treatment is related to the identified phenotype. With one exception, these algorithms contain a stepwise approach for patients with type 2 diabetes who are metformin-intolerant. The glycemic targets (HbA1c, fasting/preprandial and postprandial glycemia) are also personalized. This accessible and easy to use algorithm may help physicians to choose a personalized treatment plan for each patient and to optimize it in a timely manner, thereby lessening clinical inertia.

Indexed as

Italian algorithmItalian Association of Medical Diabetologistspersonalized treatmenttreatment guidelinestype 2 diabetes

Identifiers

PMID24971031
PMCPMC4070713
OpenAlexW2044710714

What OpenQuestion holds

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LicenceCC BY-NC
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.