Evidence mapPaperPMID 37915365Full record

ReviewHealth science reports2023

Transform diabetes care with precision medicine.

Sharumathy Kannan, Dinesh Kumar Chellappan, Chia Siang Kow, Dinesh Sangarran Ramachandram, Manisha Pandey, Jayashree Mayuren, Kamal Dua, Mayuren Candasamy

Open access · goldAbstract readReview
In one paragraph

Review in Health science reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. 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

8 authors at 4 institutions in 3 countries.

Sharumathy KannanSchool of Health Sciences International Medical University Kuala Lumpur Malaysia.
Dinesh Kumar ChellappanDepartment of Life Sciences, School of Pharmacy International Medical University Kuala Lumpur Malaysia.
Chia Siang KowDepartment of Pharmacy Practice, School of Pharmacy International Medical University Kuala Lumpur Malaysia.ORCID 0000-0002-8186-2926
Dinesh Sangarran RamachandramSchool of Pharmacy Monash University Malaysia Subang Jaya Selangor Malaysia.
Manisha PandeyDepartment of Pharmaceutical Sciences Central University of Haryana Mahendergarh India.
Jayashree MayurenDepartment of Pharmaceutical Technology, School of Pharmacy International Medical University Kuala Lumpur Wilayah Persekutuan Malaysia.
Kamal DuaFaculty of Health, Australian Research Centre in Complementary and Integrative Medicine University of Technology Sydney Ultimo New South Wales Australia.
Mayuren CandasamyDepartment of Life Sciences, School of Pharmacy International Medical University Kuala Lumpur Malaysia.
IMU University · MYCentral University of Haryana · INMonash University Malaysia · MYUniversity of Technology Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Diabetes is a global concern. This article took a closer look at diabetes and precision medicine. Methods: A literature search of studies related to the use of precision medicine in diabetes care was conducted in various databases (PubMed, Google Scholar, and Scopus). Results: Precision medicine encompasses the integration of a wide array of personal data, including clinical, lifestyle, genetic, and various biomarker information. Its goal is to facilitate tailored treatment approaches using contemporary diagnostic and therapeutic techniques that specifically target patients based on their genetic makeup, molecular markers, phenotypic traits, or psychosocial characteristics. This article not only highlights significant advancements but also addresses key challenges, particularly focusing on the technologies that contribute to the realization of personalized and precise diabetes care. Conclusion: For the successful implementation of precision diabetes medicine, collaboration and coordination among multiple stakeholders are crucial.

Indexed as

artificial intelligencebeta cell transplantationdiabetesdiabetes nanomedicineprecision medicine

Identifiers

PMID37915365
PMCPMC10616361
OpenAlexW4388044283

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.