Evidence map›Paper›PMID 42541393›Full record

SynthesisClinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis

Diagnostic Validation of PERC and Resource Utilization in Suspected Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis.

Xueyan Liu, Hua Fan, Yangyang Hai, Jun Wang, Xinbo Yu, Zhaohui Lv, Sirui Gu

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

7 authors.

Xueyan LiuEmergency Department, China-Japan Friendship Hospital, Beijing, China.ORCID 0009-0009-8006-164X
Hua FanEmergency Department, China-Japan Friendship Hospital, Beijing, China.ORCID 0009-0000-2609-9748
Yangyang HaiPediatric Department, China-Japan Friendship Hospital, Beijing, China.
Jun WangPediatric Department, China-Japan Friendship Hospital, Beijing, China.
Xinbo YuSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Zhaohui LvThe First Clinical Medical College, Shandong University of Chinese Medicine, Jinan, China.
Sirui GuPediatric Department, China-Japan Friendship Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and AimsPulmonary embolism (PE) is a frequent and potentially fatal diagnosis in the emergency department (ED). The Pulmonary Embolism Rule-out Criteria (PERC), an eight-item clinical decision rule used to identify patients at very low risk of pulmonary embolism, is widely applied to exclude PE in low-risk patients; however, its real-world diagnostic performance and impact on imaging utilization remain incompletely defined. This systematic review aimed to evaluate the diagnostic accuracy of PERC and its effect on reducing computed tomography pulmonary angiography (CTPA) use.Materials and MethodsThis review followed the Joanna Briggs Institute (JBI) methodology for diagnostic test accuracy studies. Eligible studies enrolled ED patients with suspected PE who were classified as low risk according to the original study-specific approaches, including clinician gestalt, Wells score, revised Geneva score, or YEARS-based assessment. PubMed, Web of Science Core Collection, the Cochrane Library, and ClinicalTrials.gov were searched for eligible studies published between 2004 and 2025.ResultsTen studies involving 13,672 patients were included. The pooled PE prevalence was 7%. The pooled sensitivity, specificity, and negative predictive value of PERC were 95% (95% CI: 89%-98%), 26% (95% CI: 16%-40%), and 98.2% (95% CI: 97.8%-99.0%), respectively. PERC application was associated with a significant reduction in imaging utilization (RR = 0.85, 95% CI: 0.80-0.91).ConclusionsPERC provides a highly sensitive and safe strategy for ruling out PE in low-risk ED patients and significantly reduces unnecessary use of advanced imaging without compromising diagnostic safety.

Indexed as

Pulmonary EmbolismAcute DiseaseEmergency Service, HospitalHumansemergency departmentmeta-analysisPERC rulepulmonary embolismsystematic review

Identifiers

PMID42541393
PMCPMC13428846

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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.