Evidence map›Paper›PMID 29296240›Full record

ArticleOncotarget2017

Sulfonylurea for the treatment of neonatal diabetes owing to K

Hongliang Zhang, Xiaobin Zhong, Zhenguang Huang, Chun Huang, Taotao Liu, Yue Qiu

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 3 pooled it
–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

7 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Clinical and Genetic Characteristics ofJournal of diabetes research · 2021
    Pooled it
  3. Pooled it
  4. Review
  5. Article
  6. Article
  7. Article
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.

Hongliang ZhangPharmacy Department, The First Affiliated Hospital of Guangxi Medical University, 530021, Nanning, China.
Xiaobin ZhongGuangxi Key Laboratory of Regenerative Medicine, The First Affiliated Hospital of Guangxi Medical University, 530021, Nanning, China.
Zhenguang HuangPharmacy Department, The First Affiliated Hospital of Guangxi Medical University, 530021, Nanning, China.
Chun HuangPharmacy Department, The First Affiliated Hospital of Guangxi Medical University, 530021, Nanning, China.
Taotao LiuPharmacy Department, The First Affiliated Hospital of Guangxi Medical University, 530021, Nanning, China.
Yue QiuPharmacy Department, The First Affiliated Hospital of Guangxi Medical University, 530021, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effect of sulfonylurea for the treatment of neonatal diabetes (NDM) is remain uncertain. We conducted this systematic review and meta-analysis to investigate the effect of sulfonylurea for NDM and to provide the latest and most convincing evidence for developing clinical practice guidelines of NDM. A literature review was performed to identify all published studies reporting the sulfonylurea on the treatment of neonatal diabetes. The search included the following databases: PUBMED, EMBASE and the Cochrane Library. The primary outcome was the success rates of treatment, change of glycosylated hemoglobin (HbA1c) and C-peptide. Data results were pooled by using MetaAnalyst with a random-effects model. Ten studies (6 cohort studies and 4 cross-sectional studies) involving 285 participants were included in the analysis. The pooled estimated success rate by the random-effects model was 90.1%(95% CI: 85.1%-93.5%). HbA1c had a significantly lower compared with before treatment. The pooled estimate of MD was -2.289, and the 95% CI was -2.790 to -1.789 (

Indexed as

meta-analysisneonatal diabetessulfonylureasystematic review

Identifiers

PMID29296240
PMCPMC5746142

What OpenQuestion holds

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LicenceCC BY
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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.