Evidence map›Paper›PMID 33163600›Full record

ArticleArthroplasty today2020

Patient Demographics and Anthropometric Measurements Predict Tibial and Femoral Component Sizing in Total Knee Arthroplasty.

Dominic Marino, Jay Patel, John M Popovich, Jason Cochran

Abstract read
In one paragraph

Article in Arthroplasty today, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Article
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

4 authors.

Dominic MarinoDepartment of Orthopedic Surgery, McLaren-Greater Lansing Hospital, Lansing, MI, USA.
Jay PatelDepartment of Orthopedic Surgery, McLaren-Greater Lansing Hospital, Lansing, MI, USA.
John M PopovichDepartment of Orthopedic Surgery, Sparrow Hospital, Lansing, MI, USA.
Jason CochranDepartment of Orthopedic Surgery, McLaren-Greater Lansing Hospital, Lansing, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate sizing is critical for the overall success of a total knee arthroplasty (TKA). This study's primary purpose was to investigate the ability to predict the tibial and femoral component size in a single implant system from patient demographics and anthropometric data. A secondary goal was to compare the predicted tibial and femoral component sizes from our statistical model with a previously validated electronic application used to predict the implant size.

methodsA consecutive series of 484 patients undergoing a primary TKA at a single institution was reviewed. Data on height, weight, body mass index, sex, age, and component size were collected. A proportional odds model was developed to predict tibial and femoral component sizes. The relationship between the proportional odds model predictions was also compared with the component sizes determined by the Arthroplasty Size Predictor electronic application.

resultsWeight, height, and sex predicted the implanted component size with an accuracy of 54.0% (n = 247/484) for the tibia and 51.1% (n = 231/484) for the femur. The accuracy improved to 94.4% (n = 457/484) for the tibia and 93.4% (n = 452/484) for the femur within ±1 component size. Our data are highly correlated to the Arthroplasty Size Predictor for the predicted tibial component size (ρ = 0.91,

conclusionsOur novel templating model may improve operative efficiency for a single TKA system. Our findings have a high concordance with a widely available electronic application used to predict implant sizes for a variety of TKA systems.

Indexed as

AnthropometricArthritisFrame sizeKneeTemplatingTotal knee arthroplasty

Identifiers

PMID33163600
PMCPMC7606840

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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.