Evidence map›Paper›PMID 36697472›Full record

ArticleScientific reports2023

A novel bi-planar calibration method for digital templating in total hip arthroplasty.

Christian Ries, Tim Rolvien, Frank Timo Beil, Henriette S Boese, Christoph Kolja Boese

Abstract read
In one paragraph

Article in Scientific reports, 2023. 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

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

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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

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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

5 authors.

Christian RiesDivision of Orthopaedics, Department of Trauma and Orthopaedic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Tim RolvienDivision of Orthopaedics, Department of Trauma and Orthopaedic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Frank Timo BeilDivision of Orthopaedics, Department of Trauma and Orthopaedic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Henriette S BoeseClinic for Anesthesiology and Operative Intensive Care, Albertinen Hospital, Martinistr. 52, 20246, Hamburg, Germany.
Christoph Kolja BoeseDivision of Orthopaedics, Department of Trauma and Orthopaedic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. christoph.boese@googlemail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In total hip arthroplasty and reconstructive orthopedic surgery, pre-operative digital templating is essential for surgical treatment optimization, risk management, and quality control. Calibration is performed before templating to address magnification effects. Conventional methods including fixed calibration factors, individual marker-based calibration and dual-scale marker methods are not reliable. A novel bi-planar calibration method is described aiming to reduce the error below clinical significance. The bi-planar calibration method requires two conventional orthogonal radiographs and a standard radiopaque marker ball. An algorithm computes the hip plane height parallel to the detector in the antero-posterior radiograph. Foreseeable errors (i.e., patient rotation and misplaced markers or lateral offset) are considered in a correction algorithm. Potential effects of errors are quantified in a standard model. Influence of rotation in lateral radiographs and lateral offset of marker on the calibration factor are quantified. Without correction, patient rotation in the lateral radiograph of 30° results in absolute calibration error of 2.2% with 0 mm offset and 6.5% with 60 mm lateral offset. The error is below the threshold of 1.5% for rotation less than 26° with 0 mm offset and 10° with 60 mm offset. The method is supposed to be reliable in precisely predicting the hip plane and thereby the calibration factor. It may be superior to other methods available. In theory, the method allows correction of clinically relevant rotation of at least 30° and marker displacement without impacting the computed calibration factor.

Indexed as

Arthroplasty, Replacement, HipHip ProsthesisCalibrationHip JointHumansReproducibility of Results

Identifiers

PMID36697472
PMCPMC9876910

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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.