Evidence map›Paper›PMID 22917701›Full record

ArticleClinical journal of the American Society of Nephrology : CJASN2012

Dialysis search filters for PubMed, Ovid MEDLINE, and Embase databases.

Arthur V Iansavichus, R Brian Haynes, Christopher W C Lee, Nancy L Wilczynski, Ann McKibbon, Salimah Z Shariff, Peter G Blake, Robert M Lindsay, Amit X Garg

Abstract read
In one paragraph

Article in Clinical journal of the American Society of Nephrology : CJASN, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  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

9 authors.

Arthur V IansavichusDivision of Nephrology and Department of Epidemiology and Biostatistics, Western University, London, Ontario, Canada.
R Brian Haynes
Christopher W C Lee
Nancy L Wilczynski
Ann McKibbon
Salimah Z Shariff
Peter G Blake
Robert M Lindsay
Amit X Garg

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

BACKGROUND AND

objectivesPhysicians frequently search bibliographic databases, such as MEDLINE via PubMed, for best evidence for patient care. The objective of this study was to develop and test search filters to help physicians efficiently retrieve literature related to dialysis (hemodialysis or peritoneal dialysis) from all other articles indexed in PubMed, Ovid MEDLINE, and Embase. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A diagnostic test assessment framework was used to develop and test robust dialysis filters. The reference standard was a manual review of the full texts of 22,992 articles from 39 journals to determine whether each article contained dialysis information. Next, 1,623,728 unique search filters were developed, and their ability to retrieve relevant articles was evaluated.

resultsThe high-performance dialysis filters consisted of up to 65 search terms in combination. These terms included the words "dialy" (truncated), "uremic," "catheters," and "renal transplant wait list." These filters reached peak sensitivities of 98.6% and specificities of 98.5%. The filters' performance remained robust in an independent validation subset of articles.

conclusionsThese empirically derived and validated high-performance search filters should enable physicians to effectively retrieve dialysis information from PubMed, Ovid MEDLINE, and Embase.

Indexed as

BibliometricsMEDLINEPubMedRenal DialysisTerminology as TopicVocabulary, ControlledData MiningEvidence-Based MedicineHumansReproducibility of Results

Identifiers

PMID22917701
PMCPMC3463205

What Socratic holds

Textmetadata
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 Socratic graph.