MétaCan
Menu
Back to cohort
Record W4310603353 · doi:10.1097/md.0000000000031748

Factors affecting pain and physical functions in patients with knee osteoarthritis: An observational study

2022· article· en· W4310603353 on OpenAlexaboutno aff
Ahmad H. Alghadir, Masood Khan

Bibliographic record

VenueMedicine · 2022
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisBody mass indexObservational studyKnee painPhysical therapyCross-sectional studyVisual analogue scaleInternal medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

Knee osteoarthritis (KOA) is more common as people age and have a higher body mass index (BMI). We must know the role of various factors in pain and physical functions in patients with KOA. Therefore, the present study sought to examine the factors associated with pain and physical functions in individuals with KOA. This cross-sectional observational study included patients with KOA (n = 125; 57 men, 68 women; mean age 52.9 years). Using the visual analogue scale and a reduced version of the Western Ontario McMaster Universities Osteoarthritis Index, pain severity and physical functions were assessed. Demographic factors such as age, BMI, sex, and Kellgren-Lawrence (K/L) radiographic grade of KOA were analyzed. Age (R = 0.263, P < .001), BMI (R = 0.379, P < .001), and K/L grade (R = 0.844, P < .001) were significantly associated with knee pain. Similarly, age (R = 0.310, P < .001), BMI (R = 0.374, P < .001), and K/L grade (R = 0.862, P < .001) were associated with physical functions. No significant association of sex with pain (R = 0.071, P = .440) and physical functions (R = 0.055, P = .545) was observed. Age, BMI, and K/L grade explained 71% and 74% of knee pain and physical functions, respectively. Age, BMI, and radiographic (K/L) grades were associated with pain and physical functions in patients with KOA. K/L grade was the most significant predictor of pain and physical functions in KOA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.279
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMedicineSame topicOsteoarthritis Treatment and MechanismsFrench-language works237,207