Evidence map›Paper›PMID 35207428›Full record

ReviewLife (Basel, Switzerland)2022

Can The 'Speed Bump Sign' Be a Diagnostic Tool for Acute Appendicitis? Evidence-Based Appraisal by Meta-Analysis and GRADE.

Ling Wang, Ching-Hsien Ling, Pei-Chun Lai, Yen-Ta Huang

Open access · goldAbstract readReview
In one paragraph

Review in Life (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Clinical Evidence and Potential Mechanisms of Complementary Treatment ofEvidence-based complementary and alternative medicine : eCAM · 2022
    Review
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.

Ling WangDepartment of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.
Ching-Hsien LingDepartment of Surgery, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970, Taiwan.
Pei-Chun LaiEducational Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.ORCID 0000-0001-9143-7395
Yen-Ta HuangDepartment of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan.
National Cheng Kung University Hospital · TWTzu Chi Foundation · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe 'speed bump sign' is a clinical symptom characterised by aggravated abdominal pain while driving over speed bumps. This study aimed to perform a diagnostic meta-analysis, rate the certainty of evidence (CoE) and analyse the applicability of the speed bump sign in the diagnosis of acute appendicitis. MATERIALS AND

methodsFour databanks and websites were systemically searched, and the Quality Assessment of Diagnostic Accuracy Studies 2 was used to evaluate the risk of bias. Meta-analysis was assessed by MIDAS commands in Stata 15. Grading of Recommendations, Assessment, Development and Evaluation methodology was applied to examine the CoE.

resultsFour studies with 343 participants were included. The pooled sensitivity and specificity were 0.94 (95% CI (confidence interval) = 0.83-0.98; I

conclusionCurrent evidence shows that the speed bump sign is a useful 'rule-out' test for diagnosing acute appendicitis. With good accessibility, the speed bump sign may be added as a routine part of taking the history of patients with abdominal pain.

Indexed as

acute appendicitisdiagnosismeta-analysisspeed bump sign

Identifiers

PMID35207428
PMCPMC8875208
OpenAlexW4205827466

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.