Evidence map›Paper›PMID 33511051›Full record

ReviewJournal of translational internal medicine2020

Shengxuening

Qin Zeng, Xin-Hui Wang, Li-Ping Yang, Rui Lang, Ying Liang, Ren-Huan Yu

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of translational internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
0.4field-weighted citation impact, top 34% 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. 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 at 4 institutions in 1 country.

Qin ZengGraduate School of Beijing University of Chinese Medicine, Beijing 100029, China.
Xin-Hui WangDepartment of Nephrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing 100029, China.
Li-Ping YangDepartment of Nephrology, Guanganmen Hospital of China Academy of Chinese Medical Sciences, Beijing 100053, China.
Rui LangDepartment of Nephrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing 100029, China.
Ying LiangDepartment of Nephrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing 100029, China.
Ren-Huan YuDepartment of Nephrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing 100029, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNXiyuan Hospital · CNBeijing University of Chinese Medicine · CNGuang’anmen Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Shengxuening (SXN), as an effective supplement to heme-like iron, has been widely used in China to treat renal anemia. However, proof of its use for improving inflammation is scarce in the past decades. This work aimed to evaluate the effectiveness of SXN with inflammatory factors as primary endpoints. By searching PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Biology Medicine disc (CBM), VIP Information/ China Science and Technology Journal Database, and WANFANG Database, we identified previous studies that met the inclusion criteria and included them in the systematic review. Analyses were performed using STATA. Nine randomized controlled trials were included in this systematic review. The results revealed that, when compared with oral iron supplementation, SXN can reduce the level of inflammatory factors, including hs-CRP (WMD -1.93 mg/L; 95% CI -2.14 to -1.72), IL-6 (

Indexed as

inflammationoral iron supplementationrenal anemiaShengxueningsystematic review

Identifiers

PMID33511051
PMCPMC7805283
OpenAlexW3118828044

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.