Evidence map›Paper›PMID 35112180›Full record

SynthesisKnee surgery, sports traumatology, arthroscopy : official journal of the ESSKA2022

Defining and predicting radiographic knee osteoarthritis progression: a systematic review of findings from the osteoarthritis initiative.

Peter Y Joo, Alireza Borjali, Antonia F Chen, Orhun K Muratoglu, Kartik M Varadarajan

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

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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

5 authors.

Peter Y JooDepartment of Orthopaedic Surgery, University of Rochester Medical Center, Rochester, NY, USA.
Alireza BorjaliHarris Orthopaedics Laboratory, Department of Orthopaedic Surgery, Massachusetts General Hospital, 55 Fruit Street, GRJ-12-1223, Boston, MA, 02214, USA.
Antonia F ChenDepartment of Orthopaedic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0003-2040-8188
Orhun K MuratogluHarris Orthopaedics Laboratory, Department of Orthopaedic Surgery, Massachusetts General Hospital, 55 Fruit Street, GRJ-12-1223, Boston, MA, 02214, USA.
Kartik M VaradarajanHarris Orthopaedics Laboratory, Department of Orthopaedic Surgery, Massachusetts General Hospital, 55 Fruit Street, GRJ-12-1223, Boston, MA, 02214, USA. kmangudivaradarajan@mgh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purposes of this systematic review were to (1) identify the commonly used definitions of radiographic KOA progression, (2) summarize the important associative risk factors for disease progression based on findings from the OAI study and (3) summarize findings from radiographic KOA progression prediction modeling studies regarding the characterization of progression and outcomes.

methodsA systematic review was performed by conducting a literature search of definitions, risk factors and predictive models for radiographic KOA progression that utilized data from the OAI database. Radiographic progression was further characterized into "accelerated KOA" and "typical progression," as defined by included studies.

resultsOf 314 studies identified, 41 studies were included in the present review. Twenty-eight (28) studies analyzed risk factors associated with KOA progression, and 13 studies created or validated prediction models or risk calculators for progression. Kellgren-Lawrence (KL) grade based on radiographs was most commonly used to characterize KOA progression (50%), followed by joint space width (JSW) narrowing (32%) generally over 48 months. Risk factors with the highest odds ratios (OR) for progression included periarticular bone mineral density (OR 10.40), any knee injury within 1 year (OR 9.22) and baseline bone mineral lesions (OR 7.92). Nine prediction modeling studies utilized both clinical and structural risk factors to inform their models, and combined models outperformed purely clinical or structural models.

conclusionThe cumulative evidence suggests that combinations of structural and clinical risk factors may be able to predict radiographic KOA progression, particularly in patients with accelerated progression. Clinically relevant and feasible prediction models and risk calculators may provide valuable decision-making support when caring for patients at risk of KOA progression, although standardization in modeling and variable identification does not yet exist.

Indexed as

Knee InjuriesOsteoarthritis, KneeDisease ProgressionHumansKnee JointRadiographyRisk FactorsKneeModelOsteoarthritisOsteoarthritis initiativePredictionRadiographic progression

Identifiers

What Socratic 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 Socratic graph.