ArticleEuropean journal of orthopaedic surgery & traumatology : orthopedie traumatologie2023
Computed tomography micromotion analysis in the follow-up of patients with surgically treated pelvic fractures: a prospective clinical study.
Article in European journal of orthopaedic surgery & traumatology : orthopedie traumatologie, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Precision of photon-counting detector CT compared to conventional CT for total wrist arthroplasty migration: a cadaveric and clinical study.Skeletal radiology · 2026Article
- CT-based micromotion analysis for tracking fracture displacement and fragment movement in trochanteric hip fractures: an agreement study.Acta orthopaedica · 2026Article
- CT Motion-Analysis of Implant Loosening in Total Wrist Arthroplasty: A Pilot Study.Journal of wrist surgery · 2026Article
- Inducible displacement CT for implant loosening detection: a scoping review on methods, validation, and challenges.Acta orthopaedica · 2026Article
- CT-Based Micromotion Analysis After Locking Plate Fixation of AO Type C Distal Radius Fractures.Indian journal of orthopaedics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeHigh-energy pelvic fractures are complex injuries often requiring surgical treatment. Different radiological methods exist to evaluate the reduction and healing process postoperatively but with certain limitations. The aim of this study was to evaluate Computed Tomography Micromotion Analysis (CTMA) in a clinical setting for follow-up of surgically treated pelvic fracture patients.
methods10 patients surgically treated for a pelvic fracture were included and prospectively followed with Computed Tomography (CT) at 0, 6, 12 and 52 weeks postoperatively. CTMA was used to measure postoperative translation and rotation of the pelvic fracture during the 52 weeks follow-up. Clinical outcomes were collected through the questionnaires EQ-5D index score and Majeed score.
results10 patients were included with mean age (± SD, min-max) 52 (16, 31-80) years and 70% (n = 7) were males. The median (IQR, min-max) global translation from 0 to 52 weeks was 6.0 (4.6, 1.4-12.6) millimeters and median global rotation was 2.6 (2.4, 0.7-4.7) degrees. The general trend was a larger translation between 0 and 6 weeks postoperatively compared to 6-12 and 12-52 weeks. For the clinical outcomes, the general trend was that all patients started from high scores which decreased in the first postoperative follow-up and recovered to different extent during the study period.
conclusionCTMA was successfully used in the follow-up of surgically treated pelvic fracture patients. Movement in the pelvic fractures after surgical fixation was largest between 0 and 6 weeks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.