Evidence map›Paper›PMID 30229234›Full record

ArticleJB & JS open access2018

A New, Easy, Fast, and Reliable Method to Correctly Classify Acetabular Fractures According to the Letournel System.

Guillaume Riouallon, Amer Sebaaly, Peter Upex, Mourad Zaraa, Pomme Jouffroy

Open access · goldAbstract read
In one paragraph

Article in JB & JS open access, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 19 citations in OpenAlex.

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  4. Algorithms in acetabular fracture classifications.Archives of orthopaedic and trauma surgery · 2024
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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

5 authors at 2 institutions in 2 countries.

Guillaume RiouallonDepartment of Orthopaedic Surgery, Groupe Hospitalier Paris Saint Joseph, Paris, France.
Amer SebaalyDepartment of Orthopaedic Surgery, Groupe Hospitalier Paris Saint Joseph, Paris, France.
Peter UpexDepartment of Orthopaedic Surgery, Groupe Hospitalier Paris Saint Joseph, Paris, France.
Mourad ZaraaDepartment of Orthopaedic Surgery, Groupe Hospitalier Paris Saint Joseph, Paris, France.
Pomme JouffroyDepartment of Orthopaedic Surgery, Groupe Hospitalier Paris Saint Joseph, Paris, France.
Hôpital Paris Saint-Joseph · FRSaint Joseph University · LB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate classification of acetabular fractures remains difficult. To aid in the classification of acetabular fractures and to aid in teaching, our department developed a diagnostic algorithm that involves the use of 1 standardized 3-dimensional reconstruction of a computed tomography (CT) scan (an exopelvic view without the femoral head) with 8 anatomical landmarks. The algorithm was integrated into a smartphone application (app). The main objective of this study was to test the efficacy of this algorithm and smartphone app.

methodsFourteen reviewers (3 experts, 3 fellows, 3 residents, and 5 novice reviewers) evaluated a set of 35 CT scans of acetabular fractures in 2 phases. During the first phase, the scans (including axial 2-dimensional views and 3-dimensional (3D) multiplanar reconstruction views) were assessed by each reviewer twice, with an interval of 4 weeks between the readings to decrease recall bias. During that phase, the reviewers were provided with a diagram of the Letournel classification system with no guidelines for interpretation. During the second phase, performed 4 weeks after the first phase, 1 standardized 3D reconstruction (an exopelvic view without the femoral head) was reviewed twice, with an interval of 4 weeks between the readings. During that phase, the reviewers used the smartphone app. The primary outcome was the accuracy of classification. Interobserver reliability, reading time, and time needed for accurate classification were noted.

resultsThe accuracy of fracture classification was 64.5% when the standard method of analysis was used and 83.4% when the app was used (p < 0.001). Improvement was noted in all groups, with the expert group showing the least improvement (88.6% to 97.2%, p = 0.04) and the novice group showing the most improvement (42.0% to 75.5%, p < 0.001). Furthermore, use of the app greatly increased the accuracy of classification of complex fractures. The average reading time was 71.8 minutes when the standard method was used and 37.4 minutes when the app was used. The interobserver reliability improved in all groups to an excellent reliability (interclass correlation coefficient [ICC] > 0.79).

conclusionsThe Letournel classification system is difficult to understand and to learn but remains the only system guiding the surgical strategy for acetabular fractures. The impact of diagnostic algorithms is debatable. The most important finding of the present study is the high accuracy for inexperienced groups when the app was used. Another important finding is the high reliability of this method for the diagnosis of complex acetabular fractures.

Identifiers

PMID30229234
PMCPMC6132906
OpenAlexW2789510531

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.