Evidence map›Paper›PMID 27653367›Full record

ArticleScientific reports2016

Associations between metabolic syndrome and clinical benign prostatic hyperplasia in a northern urban Han Chinese population: A prospective cohort study.

Si-Cong Zhao, Ming Xia, Jian-Chun Tang, Yong Yan

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
1.8field-weighted citation impact, top 15% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 25 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Si-Cong ZhaoDepartment of Urology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Ming XiaDepartment of Urology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Jian-Chun TangDepartment of Cardiology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Yong YanDepartment of Urology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Capital Medical University · CNBeijing Shijitan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biologic rationales exist for the associations between metabolic syndrome (MetS) and benign prostatic hyperplasia (BPH). However, epidemiologic studies have yield inconsistent results. The aim of the present study was to prospectively evaluate the associations of MetS with the risk of BPH. The presence of MetS, the number of MetS components, and the individual MetS components were evaluated. After adjusting for potential confounders, MetS was associated with increased risk of BPH (HR: 1.29; 95% CI, 1.08-1.50; p < 0.001). Compared with subjects without any MetS components, the HRs were 0.88 (95% CI, 0.67-1.09; p = 0.86), 1.18 (95% CI, 0.89-1.47; p = 0.29) and 1.37 (95% CI, 1.08-1.66; p = 0.014) for subjects with 1, 2, or ≥3 MetS components, and there was a biologic gradient between the number of MetS components and the risk of BPH (p-trend < 0.001). Central obesity and low high-density lipoprotein cholesterol were the two main divers of the associations between these two conditions, with HRs of 1.93 (95% CI, 1.14-2.72; p = 0.001) for central obesity, and 1.56 (95% CI, 1.08-2.04; p = 0.012) for low HDL-C. Our findings support the notion that MetS may be an important target for BPH prevention and intervention.

Identifiers

PMID27653367
PMCPMC5032014
OpenAlexW2521217181

What OpenQuestion 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 OpenQuestion graph.