Evidence map›Paper›PMID 36446908›Full record

ArticleKnee surgery, sports traumatology, arthroscopy : official journal of the ESSKA2023

Patient-reported impairment following TKA is reduced when a computationally simulated predicted ideal alignment is achieved.

Joshua Twiggs, Brad Miles, David Parker, David Liu, Andrew Shimmin, Brett Fritsch, Justin Roe, Jonathan Baré, Michael Solomon, David Dickison and 3 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

13 authors at 9 institutions in 3 countries.

Joshua Twiggs360MedCare, Suite 3, Building 1/20 Bridge St, Pymble, Sydney, NSW, 2073, Australia. joshua@360med.care.ORCID http://orcid.org/0000-0003-0063-0435
Brad Miles360MedCare, Suite 3, Building 1/20 Bridge St, Pymble, Sydney, NSW, 2073, Australia.
David ParkerSydney Orthopaedic Research Institute, Sydney, 2067, Australia.
David LiuGold Coast Centre for Bone and Joint Surgery, Gold Coast, 4221, Australia.
Andrew ShimminMelbourne Orthopaedic Group, Melbourne, 3181, Australia.
Brett FritschSydney Orthopaedic Research Institute, Sydney, 2067, Australia.
Justin RoeNorth Sydney Orthopaedic and Sports Medicine Centre, The Mater Hospital, Sydney, 2060, Australia.
Jonathan BaréMelbourne Orthopaedic Group, Melbourne, 3181, Australia.
Michael SolomonSydney Orthopaedic Specialists, Sydney, 2031, Australia.
David DickisonPeninsula Orthopaedics, Sydney, 2099, Australia.
Stephen McMahonMalabar Orthopaedic Clinic, Melbourne, 3181, Australia.
Richard BoyleBoyle Orthopaedics, Sydney, 2042, Australia.
Len Walter360MedCare, Suite 3, Building 1/20 Bridge St, Pymble, Sydney, NSW, 2073, Australia.
ResMed (Australia) · AUMelbourne Health · AUSydney Orthopaedic Research Institute · AUEnel (Italy) · ITGold Coast Hospital · AUMater Misericordiae Hospital · AUMelbourne Clinic · AUNorthwest Orthopaedic Specialists · USPeninsula Health · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeJoint dynamics following Total Knee Arthroplasty (TKA) may influence patient-reported outcome. Simulations allow many knee alignment approaches to a single patient to be considered prior to surgery. The simulated kinematics can be matched to patient-reported outcome to predict kinematic patterns most likely to give the best outcome. This study aims to validate one such previously developed algorithm based on a simulated deep knee bend (the Dynamic Knee Score, DKS).

methods1074 TKA patients with pre- and post-operative Computerised Tomography (CT) scans and 12-month post-operative Knee Injury and Osteoarthritis Outcomes (KOOS) Scores were identified from the 360 Med Care Joint Registry. Landmarking and registration of implant position was performed on all CT scans, and each of the achieved TKAs was computationally simulated and received a predictive outcome score from the DKS. In addition, a set of potential alternative surgical plans which might have been followed were simulated. Comparison of patient-reported issues and DKS score was evaluated in a counter-factual study design.

resultsPatient-reported impairment with the knee catching and squatting was shown to be 30% lower (p = 0.005) and 22% lower (p = 0.026) in patients where the best possible DKS result was the one surgically achieved. Similar findings were found relating attainment of the best tibial slope and posterior femoral resection DKS plans to patient-reported difficulty straightening the knee (40% less likely, p < 0.001) and descending stairs (35% less likely, p = 0.006).

conclusionThe DKS has been shown to correlate with presence of patient-reported impairments post-TKA and the resultant algorithm can be applied in a pre-operative planning setting. Outcome optimization in the future may come from patient-specific selection of an alignment strategy and simulations may be a technological enabler of this trend. LEVEL OF EVIDENCE: III (Retrospective Cohort Study).

Indexed as

Arthroplasty, Replacement, KneeKnee ProsthesisOsteoarthritis, KneeBiomechanical PhenomenaHumansKnee JointPatient Reported Outcome MeasuresRetrospective StudiesComputational simulationJoint dynamicsKinematicsMachine learningOutcomePROMSTotal knee arthroplasty (TKA)

Identifiers

PMID36446908
PMCPMC9957835
OpenAlexW4310459951

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.