Evidence map›Paper›PMID 29445357›Full record

ArticleFrontiers in endocrinology2018

Gender Difference in the Association of Early- vs. Late-Onset Type 2 Diabetes with Non-Fatal Microvascular Disease in China: A Cross-sectional Study.

Xiaoxu Huo, Junqing Zhang, Xiaohui Guo, Juming Lu, Jing Li, Wei Zhao, Linong Ji, Xilin Yang

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Role of Natural Killer T (NKT) Cells in Type II Diabetes-Induced Vascular Injuries.Medical science monitor : international medical journal of experimental and clinical research · 2018
    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

8 authors.

Xiaoxu HuoDepartment of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.
Junqing ZhangDepartment of Endocrinology, Peking University First Hospital, Beijing, China.
Xiaohui GuoDepartment of Endocrinology, Peking University First Hospital, Beijing, China.
Juming LuDepartment of Endocrinology, Chinese PLA General Hospital, Beijing, China.
Jing LiDepartment of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.
Wei ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.
Linong JiDepartment of Endocrinology, Peking University People's Hospital, Beijing, China.
Xilin YangDepartment of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to test whether early-onset (defined as <40 years of age) type 2 diabetes mellitus (T2DM) imparted different risks of microvascular disease to Chinese men and women.

methods222,537 Chinese patients with T2DM were recruited in 630 hospitals from 106 cities in 30 provinces of China in 2012 using a cross-sectional design. Logistic regression analysis was performed to obtain odds ratios (ORs) of male vs. female for diabetic retinopathy (DR) and diabetic nephropathy (DN). Additive interaction was used to test whether male gender and early-onset T2DM had interactive effects for DR and DN.

resultsMore men than women with T2DM had DN (4.5 vs. 3.0%,

conclusionEarly-onset T2DM increased more risk of microvascular complications in Chinese men than in women, most of increased risks being attributable to longer diabetes durations.

Indexed as

Chinesediabetic nephropathydiabetic retinopathyearly-onset type 2 diabetes mellitusgender difference

Identifiers

PMID29445357
PMCPMC5797749

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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.