Evidence map›Paper›PMID 39882390›Full record

ArticleInterventional pain medicine2025

Evaluating the effectiveness of genicular radiofrequency ablation for chronic knee pain using the patient-reported outcomes measurement information system (PROMIS) global health-physical health domain: Results of a cross-sectional cohort study.

Todd K Brown, Marc A Caragea, Margaret Beckwith, Amelia Ni, Ling Chen, Tyler Woodworth, Michael Blatt, Cole Cheney, Daniel Carson, Keith Kuo and 9 more

Erratum issuedAbstract read
In one paragraph

Article in Interventional pain medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Todd K BrownSchool of Medicine, University of Utah, Salt Lake City, UT, USA.
Marc A CarageaDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Margaret BeckwithDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Amelia NiDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Ling ChenDivision of Biostatistics, Washington University School of Medicine, St Louis, MO, USA.
Tyler WoodworthDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Michael BlattSchool of Medicine, University of Utah, Salt Lake City, UT, USA.
Cole CheneyMayo Clinic Health System, Mankato, MN, USA.
Daniel CarsonDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Keith KuoSchool of Medicine, University of Utah, Salt Lake City, UT, USA.
Dustin RandallSchool of Medicine, University of Utah, Salt Lake City, UT, USA.
Emily Y HuangJohns Hopkins University School of Medicine, Baltimore, MD, USA.
Andrea CarefootDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Megan MillsDepartment of Radiology, University of Utah School of Medicine, Salt Lake City, UT, USA.
Amanda N CooperDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Allison Glinka PrzybyszDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Taylor BurnhamDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Aaron M CongerDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Zachary L McCormickDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Evaluate the effectiveness of genicular nerve radiofrequency ablation (GNRFA) for chronic knee pain using the Patient-Reported Outcomes Measurement Information System Global Health, Physical Health score (PROMIS-GH-PH). Methods: Patients who underwent GNRFA at a tertiary academic center were identified by CPT code query and contacted for consent. Demographic, clinical, and procedural characteristics were collected from the electronic medical record of participants with baseline PROMIS-GH-PH scores. Outcome data were collected by standardized telephone survey. Treatment success was defined as a ≥2.3-point improvement in PROMIS-GH-PH score (the minimal clinically important difference [MCID]). Predictor variables of PROMIS score change were evaluated using univariate and multivariate linear regression analyses. Results: 32 patients (65.6 % female; 63.7 ± 10.7 years of age) met eligibility criteria and consented to be included in the study. In this cohort, 56.3 % (18/32; 95 % CI: 37.7-73.6) of patients reported improvement ≥ MCID on PROMIS-GH-PH at a mean follow-up time of 21.5 ± 10.6 months. Linear regression analysis demonstrated that patients who never smoked and those with a Kellgren-Lawrence (KL) osteoarthritis grade of 4 had significantly greater PROMIS-GH-PH score improvements at follow-up compared to current or former smokers and patients with KL grades of 0-3, respectively. Conclusion: In this real-world cross-sectional cohort study, over 56 % of participants experienced improvment ≥ MCID on PROMIS-GH-PH after undergoing GFRNA for chronic knee pain. Non-smoking status and radiographically severe osteoarthritis were associated with greater PROMIS-GH-PH score improvements from baseline.

Indexed as

Genicular nerveKnee osteoarthritisKnee painRadiofrequency ablation

Identifiers

PMID39882390
PMCPMC11774768

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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.