Evidence mapPaperPMID 35707783Full record

ReviewGlobal medical genetics2022

Determinants in Tailoring Antidiabetic Therapies: A Personalized Approach.

Aliya A Rizvi, Mohammad Abbas, Sushma Verma, Shrikant Verma, Almas Khan, Syed T Raza, Farzana Mahdi

Open access · diamondAbstract readReview
In one paragraph

Review in Global medical genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 33% 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, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Review
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 1 institution in 1 country.

Aliya A RizviDepartment of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India.
Mohammad AbbasDepartment of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India.
Sushma VermaDepartment of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India.
Shrikant VermaDepartment of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India.
Almas KhanDepartment of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India.
Syed T RazaDepartment of Biochemistry, Era University, Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India.
Farzana MahdiDepartment of Personalized and Molecular Medicine, Era University, Lucknow, Uttar Pradesh, India.
Era's Lucknow Medical College and Hospital · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes has become a pandemic as the number of diabetic people continues to rise globally. Being a heterogeneous disease, it has different manifestations and associated complications in different individuals like diabetic nephropathy, neuropathy, retinopathy, and others. With the advent of science and technology, this era desperately requires increasing the pace of embracing precision medicine and tailoring of drug treatment based on the genetic composition of individuals. It has been previously established that response to antidiabetic drugs, like biguanides, sulfonylureas, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide 1 (GLP-1) agonists, and others, depending on variations in their transporter genes, metabolizing genes, genes involved in their action, etc

Indexed as

diabetesdrug responsepharmacogenomicsprecision medicine

Identifiers

PMID35707783
PMCPMC9192178
OpenAlexW4206909472

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.