Evidence map›Paper›PMID 23392700›Full record

SynthesisJournal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao. Yixue Yingdewen ban2013

A meta-analysis of salicylates for type 2 diabetes mellitus.

Fang Fang, Yu Lu, De-Lin Ma, Ting-Ting Du, Shi-Ying Shao, Xue-Feng Yu

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Journal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao. Yixue Yingdewen ban, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

7 citing papers in PubMed, 18 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Article
  6. Potential Anti-Diabetic Activity ofMolecules (Basel, Switzerland) · 2020
    Article
  7. 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

6 authors at 2 institutions in 1 country.

Fang FangDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Yu LuDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
De-Lin MaDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Ting-Ting DuDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Shi-Ying ShaoDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Xue-Feng YuDepartment of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. xfyu188@163.com.
Tongji Hospital · CNHuazhong University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to assess the effects and safety of salicylates on type 2 diabetes mellitus (T2DM). We searched six databases (Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, CBM, CNKI and VIP) for all randomized controlled trials (RCTs) and self-control studies which investigated the effects of salicylates on T2DM. We included 34 RCTs and 17 self-control studies involving 13 464 patients with T2DM. It was demonstrated that salicylates had obvious effects on several parameters for patients with T2DM. (1) Any dose of salicylates could significantly reduce HbA1c level [mean difference (MD) -0.39%; 95% CI -0.47 to -0.32] in RCTs, but only high doses of salicylates (≥3000 mg/day) could effectively reduce fasting plasma glucose (FPG) level [standardized mean difference (SMD) -1.05; 95% CI -1.47 to -0.62] for patients with T2DM in both RCTs and self-control studies. Furthermore, high doses of salicylates could also increase plasma fasting insulin level (MD 12.20 mU/L; 95% CI 3.33 to 21.07); (2) In both RCTs and self-control studies, high doses of salicylates could significantly reduce plasma triglycerides concentration. The results for RCTs were MD -0.44 mmol/L, 95% CI -0.71 to -0.18, and those for self-control studies were 227±29 mg/dL (pre-treatment) and 117±8 mg/dL (post-treatment) (P=0.009); (3) All trials which reported cardiovascular events were RCTs using low doses (<1000 mg/day) of salicylates, and it was revealed that aspirin could significantly reduce the risk of myocardial infarction (OR 0.73; 95% CI 0.57 to 0.92); (4) Two RCTs and two self-control studies with ≥3000 mg/day salicylates reported adverse effects, and the overall effects were mild, and tinnitus occurred most frequently. No evidence of gastrointestinal bleeding was found in all these studies. In conclusion, from our systematic review, the anti-diabetic effect of salicylates is in a dose-dependent manner. High doses of salicylates may have beneficial effects on reducing FPG, HbA1c level and increasing fasting insulin concentration, and may also have some positive effects on lipidemia and inflammation-associated parameters for patients with T2DM, without serious adverse effects.

Indexed as

Anti-Inflammatory Agents, Non-SteroidalCardiovascular DiseasesComorbidityDiabetes Mellitus, Type 2HumansIncidenceRandomized Controlled Trials as TopicRisk FactorsSalicylatesSurvival RateTreatment OutcomeAnti-Inflammatory Agents, Non-SteroidalSalicylates

Identifiers

PMID23392700
OpenAlexW126011744

What OpenQuestion holds

Textmetadata
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.