Evidence map›Paper›PMID 41873525›Full record

ArticleResearch synthesis methods2026

BibliZap: An exploratory evaluation of an automated multi-level citation searching tool for systematic and rapid reviews.

Raphaël Bentegeac, Bastien Le Guellec, Victor Leblanc, Rémi Lenain, Luc Dauchet, Victoria Gauthier, Erwin Gerard, Emmanuel Chazard, Philippe Amouyel, Estelle Aymes and 1 more

Abstract read
In one paragraph

Article in Research synthesis methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Raphaël BentegeacPublic Health and Epidemiology, Lille University Hospital, France.
Bastien Le GuellecUMR1167 RID-AGE, Pasteur Institute of Lille, France.
Victor LeblancHauts-de-France, Protection Maternelle et Infantile du Département du Nord, France.
Rémi LenainNephrology, Lille University Hospital, France.
Luc DauchetPublic Health and Epidemiology, Lille University Hospital, France.
Victoria GauthierPublic Health and Epidemiology, Lille University Hospital, France.
Erwin GerardCHU Lille, ULR 2694-METRICS, CERIM, Public Health Department, Lille 2 University of Health and Law, France.
Emmanuel ChazardCHU Lille, ULR 2694-METRICS, CERIM, Public Health Department, Lille 2 University of Health and Law, France.
Philippe AmouyelPublic Health and Epidemiology, Lille University Hospital, France.
Estelle AymesPublic Health and Epidemiology, Lille University Hospital, France.
Aghilès HamrounPublic Health and Epidemiology, Lille University Hospital, France.ORCID https://orcid.org/0000-0003-4988-206X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The exponential growth of scientific literature poses increasing challenges for evidence synthesis. Systematic reviews (SRs) usually rely on keyword-based database searches, which are limited by inconsistent terminology and indexing delays. Citation searching-identifying studies that cite or are cited by known relevant articles-offers a complementary route to uncover additional evidence but remains poorly automated and integrated into screening workflows. We developed BibliZap, an open-source, fully automated citation-searching tool built on Lens.org data, performing multi-level forward and backward citation searches with relevance-based ranking. Its performance was evaluated across 66 published SRs, comparing five approaches: (1) PubMed-only searches; (2) PubMed followed by BibliZap restricted to the top 500 ranked results; (3) PubMed followed by full BibliZap screening; and (4-5) two exploratory early-stop strategies where BibliZap was initiated after identifying the first or the first three PubMed relevant records. The primary outcome was sensitivity, with secondary assessments of screening workload and precision. When used after PubMed screening, BibliZap increased mean sensitivity from 75% to 97%, achieving complete recall in over half of the reviews. Screening only the top 500 outputs still allowed over 90% of reviews to reach or exceed 80% recall. BibliZap recovered a median of three additional included articles per review, not retrieved by PubMed, while adding a median of 6,450 additional records. Citation searching via BibliZap enhances the completeness of evidence retrieval in SRs based on restricted database searches and supports transparent, scalable workflows adaptable to rapid and exploratory review contexts.

Indexed as

automationbibliographic searchcitation searchingevidence synthesisopen-source toolsystematic review

Identifiers

PMID41873525
PMCPMC13311337

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.