Evidence map›Paper›PMID 25155472›Full record

ArticleArthritis care & research2015

Pain phenotype in patients with knee osteoarthritis: classification and measurement properties of painDETECT and self-report Leeds assessment of neuropathic symptoms and signs scale in a cross-sectional study.

Bryan J Moreton, Victoria Tew, Roshan das Nair, Maggie Wheeler, David A Walsh, Nadina B Lincoln

Open access · hybridAbstract read
In one paragraph

Article in Arthritis care & research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 4 pooled it
7.8field-weighted citation impact, top 2% 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

60 citing papers in PubMed, 4 syntheses or guidelines pooled it, 115 citations in OpenAlex.

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  18. Assessment of Pain in Osteoarthritis of the Knee.Journal of personalized medicine · 2023
    Review
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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

6 authors at 1 institution in 1 country.

Bryan J MoretonUniversity of Nottingham, Nottingham, UK.
Victoria Tew
Roshan das Nair
Maggie Wheeler
David A Walsh
Nadina B Lincoln
University of Nottingham · GB

Funding

Arthritis Research UK 18769
6 · The paper itself

Abstract

objectiveMultiple mechanisms are involved in pain associated with osteoarthritis (OA). The painDETECT and Self-Report Leeds Assessment of Neuropathic Symptoms and Signs (S-LANSS) questionnaires screen for neuropathic pain and may also identify individuals with musculoskeletal pain who exhibit abnormal central pain processing. The aim of this cross-sectional study was to evaluate painDETECT and S-LANSS for classification agreement and fit to the Rasch model, and to explore their relationship to pain severity and pain mechanisms in OA.

methodsA total of 192 patients with knee OA completed questionnaires covering different aspects of pain. Another group of 77 patients with knee OA completed questionnaires and underwent quantitative sensory testing for pressure-pain thresholds (PPTs). Agreement between painDETECT and S-LANSS was evaluated using kappa coefficients and receiver operator characteristic (ROC) curves. Rasch analysis of both questionnaires was conducted. Relationships between screening questionnaires and measures of pain severity or PPTs were calculated using correlations.

resultsPainDETECT and S-LANSS shared a stronger correlation with each other than with measures of pain severity. ROC curves identified optimal cutoff scores for painDETECT and S-LANSS to maximize agreement, but the kappa coefficient was low (κ = 0.33-0.46). Rasch analysis supported the measurement properties of painDETECT but not those of S-LANSS. Higher painDETECT scores were associated with widespread reductions in PPTs.

conclusionThe data suggest that painDETECT assesses pain quality associated with augmented central pain processing in patients with OA. Although developed as a screening questionnaire, painDETECT may also function as a measure of characteristics that indicate augmented central pain processing. Agreement between painDETECT and S-LANSS for pain classification was low, and it is currently unknown which tool may best predict treatment outcome.

Indexed as

PhenotypeAgedCross-Sectional StudiesFemaleHealth SurveysHumansMaleMiddle AgedNeuralgiaOsteoarthritis, KneePain MeasurementSelf Report

Identifiers

PMID25155472
PMCPMC4407932
OpenAlexW1548981124

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.