Evidence map›Paper›PMID 33913381›Full record

SynthesisRenal failure2021

Risk factors for mortality in patients undergoing peritoneal dialysis: a systematic review and meta-analysis.

Jialing Zhang, Xiangxue Lu, Han Li, Shixiang Wang

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Renal failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
6.6field-weighted citation impact, top 2% 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

35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 64 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Observational
  9. Article
  10. Visit-to-visit blood pressure variability and clinical outcomes in peritoneal dialysis - based on machine learning algorithms.Hypertension research : official journal of the Japanese Society of Hypertension · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Observational
  18. Article
  19. Serum Lipoprotein(a) Levels as a Predictor of Aortic Stiffness in Patients on Long-Term Peritoneal Dialysis.Medical science monitor : international medical journal of experimental and clinical research · 2024
    Article
  20. Observational
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.

Jialing ZhangDepartment of Blood Purification, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Xiangxue LuDepartment of Blood Purification, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Han LiDepartment of Blood Purification, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Shixiang WangDepartment of Blood Purification, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Beijing Chao-Yang Hospital · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimInconsistent investigations of the risk factors for all-cause mortality in patients undergoing peritoneal dialysis (PD) were reported. The present meta-analysis aimed to assess the impact of some clinical characteristics on the risk of mortality in PD patients.

Indexed as

Alkaline PhosphataseCardiovascular DiseasesCause of DeathHumansKidney Failure, ChronicMortalityPeritoneal DialysisRisk AssessmentRisk FactorsAlkaline PhosphataseCardiovascular mortalitymeta-analysismortalityperitoneal dialysisrisk factor

Identifiers

PMID33913381
PMCPMC8901278
OpenAlexW3158510841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.