Evidence map›Paper›PMID 34806345›Full record

ArticleArthritis care & research2023

Identifying Long-Term Trajectories of Foot Pain Severity and Potential Prognostic Factors: A Population-Based Cohort Study.

Michelle Marshall, Milica Blagojevic-Bucknall, Trishna Rathod-Mistry, Martin J Thomas, John J Edwards, George Peat, Hylton B Menz, Edward Roddy

Open access · hybridAbstract read
In one paragraph

Article in Arthritis care & research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. [Nomographic Model for Predicting Severe Foot Pain in Nurses from Tertiary Hospitals in China].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023
    Article
  4. Article
  5. Review
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

8 authors at 3 institutions in 2 countries.

Michelle MarshallPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK.ORCID 0000-0001-8163-6948
Milica Blagojevic-BucknallPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK.
Trishna Rathod-MistryPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK.
Martin J ThomasPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK, and Haywood Academic Rheumatology Centre, Midlands Partnership NHS Foundation Trust, Haywood Hospital, Burslem, Staffordshire, UK.ORCID 0000-0002-4951-9925
John J EdwardsPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK.
George PeatPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK.
Hylton B MenzPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK, and School of Allied Health, Human Services and Sport, College of Science, Health and Engineering, La Trobe University, Melbourne, Victoria, Australia.ORCID 0000-0002-2045-3846
Edward RoddyPrimary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK, and Haywood Academic Rheumatology Centre, Midlands Partnership NHS Foundation Trust, Haywood Hospital, Burslem, Staffordshire, UK.ORCID 0000-0002-8954-7082
Arthritis UK · GBMidlands Partnership NHS Foundation Trust · GBLa Trobe University · AU

Funding

Arthritis Research UK 18174Department of Health 396Department of Health CL-201610003Department of Health ICA-CL-2016-02-014Department of Health NIHR 300818Medical Research Council G0501798
6 · The paper itself

Abstract

objectivesTo identify distinct foot pain trajectories over 7 years and examine their associations with potential prognostic factors.

methodsAdults ages ≥50 years and registered with 4 general practices in North Staffordshire, UK were mailed a baseline health survey. Those reporting current or recent foot pain were invited to attend a research assessment clinic. Follow-up was by repeated postal surveys at 18, 36, 54, and 84 months. Distinct trajectories of foot pain were explored using latent class growth analysis (LCGA). Subsequently, identified trajectories were combined into most and least progressive groups, and covariate-adjusted associations with a range of prognostic factors were examined.

resultsOf 560 adults with foot pain attending baseline research clinics, 425 (76%) provided data at baseline and 2 or more follow-up time points. LCGA for foot pain severity (0-10 numerical rating scale) identified a 4-trajectory model: "mild, improving" (37%); "moderate, improving" (33%); "moderate-severe, persistent" (24%); and "severe, persistent" (6%). Compared with individuals in more favorable (improving) pain trajectories, those in less favorable (persistent) pain trajectories were more likely to be obese, have routine/manual and intermediate occupations, have poorer physical and mental health, have catastrophizing beliefs, have greater foot-specific functional limitation, and have self-assessed hallux valgus at baseline.

conclusionsFour distinct trajectories of foot pain were identified over a 7-year period, with one-third of individuals classified as having pain that is persistently moderate-severe and severe in intensity. The effect of intervening to target modifiable prognostic factors such as obesity and hallux valgus on long-term outcomes in people with foot pain requires investigation.

Indexed as

Hallux ValgusAdultCohort StudiesHumansMiddle AgedObesityPainPain MeasurementPrognosis

Identifiers

PMID34806345
PMCPMC10952181
OpenAlexW3216876677

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.