Evidence map›Paper›PMID 36971801›Full record

ArticleArchives of orthopaedic and trauma surgery2023

Identification of the joint line in revision total knee arthroplasty using a multiple linear regression model: a cadaveric study.

Yunfei Hou, Jun Jiang, Han Liu, Ruikang Wang, Jingyu Wu, Yixiong Wang, Jianhao Lin

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Article in Archives of orthopaedic and trauma surgery, 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
0.6field-weighted citation impact, top 32% 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, 2 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

7 authors at 3 institutions in 1 country.

Yunfei Hou *Arthritis Clinic and Research Center, Peking University People's Hospital, Peking University, No. 11, Xizhimen South Street, Xicheng District, Beijing, 100044, People's Republic of China.
Jun Jiang *Arthritis Clinic and Research Center, Peking University People's Hospital, Peking University, No. 11, Xizhimen South Street, Xicheng District, Beijing, 100044, People's Republic of China.
Han LiuDepartment of Orthopedics, Jin Xiang People's Hospital, Jining Medical University, No. 117, Jinfeng East Road, Jinxiang County, 272100, Shandong Province, People's Republic of China.
Ruikang WangArthritis Clinic and Research Center, Peking University People's Hospital, Peking University, No. 11, Xizhimen South Street, Xicheng District, Beijing, 100044, People's Republic of China.
Jingyu WuDepartment of Orthopedics, The Affiliated Zhengzhou Central Hospital of Zhengzhou University, 16 Tongbai North Road, Zhongyuan District, Zhengzhou City, 450000, Henan Province, People's Republic of China.
Yixiong WangDepartment of Orthopedics, Jincheng General Hospital, Chang'an Road, Beishidian Town, Jincheng City, 048000, Shanxi Province, People's Republic of China.
Jianhao LinArthritis Clinic and Research Center, Peking University People's Hospital, Peking University, No. 11, Xizhimen South Street, Xicheng District, Beijing, 100044, People's Republic of China. linjianhao@pkuph.edu.cn.ORCID http://orcid.org/0000-0003-1830-9244
Peking University · CNJining Medical University · CNZhengzhou Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe results of revision total knee arthroplasty (rTKA) may be compromised by excessive joint line (JL) elevation. It is critical but challenging in reestablishing the JL in rTKA. Previous studies have confirmed that, biomechanically and clinically, JL elevation should not exceed 4 mm. Image-based studies described several approaches to locate the JL intraoperatively, however magnification errors could occur. In this cadaveric study, we aim to define an accurate and reliable method to determine the JL. MATERIALS AND

methodsThirteen male and eleven female cadavers were used, with an average age of death being 48.3 years. The transepicondylar width (TEW), the distance from the medial (MEJL) and lateral (LEJL) epicondyle, adductor tubercle (ATJL), fibular head (FHJL) and tibial tubercle (TTJL) to the JL were measured in 48 knees. Intra- and interobserver reliability and validity were tested prior to any additional analysis. Pearson correlation and linear regression analysis were used to examine the correlations between landmark-JL distances (LEJL, MEJL, ATJL, FHJL and TTJL) and the TEW, and to further derive models for intraoperative JL determination. The accuracy of different models, quantified by errors between estimated and measured landmark-JL distances, was compared using the Friedman and post hoc Dunn tests.

resultsThe intra- and inter-observer measurements for TEW, MEJL, LEJL, ATJL, TTJL and FHJL did not differ significantly (p > 0.05). Between genders, significant differences were found on TEW, MEJL, LEJL, ATJL, FHJL and TTJL (p < 0.05). There was no association between TEW and either FHJL or TTJL (p > 0.05), while ATJL, MEJL, and LEJL were found to be correlated with TEW (p < 0.05). Six models were derived: (1) MEJL = 0.37*TEW (r = 0.384), (2) LEJL = 0.28*TEW (r = 0.380), (3) ATJL = 0.47*TEW (r = 0.608), (4) MEJL = 0.413*TEW - 4.197 (R

conclusionCompared to previous image-based measurements, the current cadaveric study most closely resembles a realistic view of intraoperative settings and could circumvents magnification errors. We recommend using Model 6, the JL can be best estimated by referencing the AT and the ATJL can be calculated as ATJL (mm) = 0.455*TEW (mm) + 1.440 (mm).

Indexed as

Arthroplasty, Replacement, KneeCadaverFemaleHumansKnee JointLinear ModelsMaleMiddle AgedReproducibility of ResultsTibiaCadaveric studyJoint lineLinear regressionModel developmentRevision total knee arthroplasty

Identifiers

PMID36971801
OpenAlexW4361010347

What OpenQuestion holds

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Registered trials

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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.