Evidence map›Paper›PMID 35514749›Full record

ArticleFrontiers in medicine2022

Physical Activity and Mortality in Patients With Chronic Kidney Disease: A Protocol for Systematic Review and Dose-Response Meta-Analysis.

Fan Zhang, Hui Wang, Liuyan Huang, Yan Bai

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 2 institutions in 1 country.

Fan ZhangDepartment of Nephrology, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Hui WangDepartment of Anorectology, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Liuyan HuangDepartment of Nephrology, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yan BaiDepartment of Cardiology, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Shanghai University of Traditional Chinese Medicine · CNLonghua Hospital Shanghai University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine the dose-response associations between total physical activity, different intensity of physical activity, and all-cause mortality in patients with chronic kidney disease (CKD). Methods and Analysis: PubMed, Embase, Web of Science, and the Cochrane library will be searched from inception to June 2022. Only cohort studies assessing physical activity associations with all-cause mortality among CKD patients will be considered for inclusion. The quality of included cohort studies will be evaluated according to the Newcastle-Ottawa Scale (NOS). The robust error meta-regression (REMR) model will be used to establish dose-response relationships between physical activity and mortality. Additional statistical analysis including Egger's test, subgroup analysis, sensitivity analysis. The strengths of evidence will be evaluated with the Grading of Recommendation, Assessment, Development, and Evaluation approach. Ethics and Dissemination: Ethics approval is not required as no private information from individuals is collected. PROSPERO Registration Number: CRD 42021283630.

Indexed as

chronic kidney diseasedose-responsemeta-analysismortalityphysical activity

Identifiers

PMID35514749
PMCPMC9063632
OpenAlexW4223561836

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.