Evidence map›Paper›PMID 38779284›Full record

ReviewCureus2024

Utilizing Artificial Intelligence Among Patients With Diabetes: A Systematic Review and Meta-Analysis.

Abdullah Alhalafi, Saif M Alqahtani, Naif A Alqarni, Amal T Aljuaid, Ghade T Aljaber, Lama M Alshahrani, Hadeel Mushait, Partha A Nandi

RetractedAbstract readReviewRetracted Publication
In one paragraph

Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Abdullah AlhalafiDepartment of Family and Community Medicine, University of Bisha, Bisha, SAU.
Saif M AlqahtaniCollege of Medicine, University of Bisha, Bisha, SAU.
Naif A AlqarniCollege of Medicine, University of Bisha, Bisha, SAU.
Amal T AljuaidCollege of Medicine, University of Bisha, Bisha, SAU.
Ghade T AljaberDepartment of Medicine, Batterjee Medical College, Aseer, SAU.
Lama M AlshahraniCollege of Medicine, King Khalid University, Abha, SAU.
Hadeel MushaitCollege of Medicine, King Khalid University, Abha, SAU.
Partha A NandiDepartment of Family and Community Medicine, University of Bisha, Bisha, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus, a condition characterized by dysregulation of blood glucose levels, poses significant health challenges globally. This meta-analysis and systematic review aimed to evaluate the effectiveness of artificial intelligence (AI) in managing diabetes, underpinned by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review scrutinized articles published between January 2019 and February 2024, sourced from six electronic databases: Web of Science, Google Scholar, PubMed, Cochrane Library, EMBASE, and MEDLINE, using keywords such as "Artificial intelligence use in medicine, Diabetes management, Health technology, Machine learning, Diabetic patients, AI applications, and Health informatics." The analysis revealed a notable variance in the prevalence of diabetes symptoms between patients managed with AI models and those receiving standard treatments or other machine learning models, with a risk ratio (RR) of 0.98 (95% CI: 0.88-1.08, I

Indexed as

ai modelsartificial intelligencediabetes mellitusmiddle eastnorth africa region

Identifiers

PMID38779284
PMCPMC11110080

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.