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Record W4415439268 · doi:10.1302/1358-992x.2025.10.093

HIP ARTHROPLASTY ALTERS THE FUNCTIONAL CONNECTIONS OF THE BRAIN'S PAIN PROCESSING REGIONS

2025· article· en· W4415439268 on OpenAlexaff
B. Goodyear, Pam Railton, Ada Delaney, John R. Matyas, S Lama, Garnette R. Sutherland, Jason Powell

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsAlberta Bible College
Fundersnot available
KeywordsSecondary somatosensory cortexInsulaSomatosensory systemHip surgeryChronic painArthroplastyOsteoarthritisThalamus

Abstract

fetched live from OpenAlex

Hip osteoarthritis (OA) is characterized by chronic pain, which is seldom matched by radiological findings. Using brain MRI, we recently demonstrated that functional connections of the brain's pain processing regions [e.g., secondary somatosensory cortex (S2), posterior insula] are altered in hip OA patients, and the connections of several regions [e.g., thalamus, periaqueductal grey matter (PAG)] are modulated by pain-eliciting activity. In other chronic pain conditions, pain processing in the brain remains altered even when pain is alleviated. Although hip replacement surgery has a high success rate, it is unknown if the brain's pain processing networks are normalized, which could have implications for the clinical management of recurring pain. Resting-state fMRI was performed on 14 hip OA patients (43–72 years of age; 9 males), before and after (>18 months) hip replacement surgery. Patients underwent two fMRI scans per session, before and after stair climbing to elicit acute pain. Pain was assessed using a 10-pt visual analog scale. Data were analyzed using a region-of-interest (ROI) approach, whereby the average temporal signal from S2, PAG, thalamus and posterior insula were determined for each patient, and Pearson's temporal cross-correlation coefficient (r) was considered as the strength of functional connection (i.e., connectivity) between each possible pair of ROIs. A repeated-measures analysis of covariance was performed on the Fisher-transformed r values, with SURGERY (pre, post), STAIRS (before, after) and the interaction between SURGERY and STAIRS (i.e., if surgery impacted the change in functional connectivity evoked by stair climbing) as within-subject factors, SEX (male, female) as a between-subjects factor, and presurgical pain score as a covariate. The median presurgical pain score was 4.5, with a median increase of 2 after stair climbing. The median postsurgical pain score was 0, with a median increase of 1 after stair climbing. SURGERY significantly increased connectivity between S2 and posterior insula [F(1,11) = 5.95; p = 0.033], and higher presurgical pain scores were associated with a greater connectivity increase [F(1,11) = 5.48; p = 0.039]. The interaction between SURGERY and STAIRS was significant for connectivity between a) S2 and PAG [F(1,11) = 5.09; p = 0.045] (STAIRS decreased connectivity presurgically, but increased connectivity postsurgically); b) S2 and thalamus [F(1,11) = 14.10; p = 0.003] (STAIRS decreased connectivity presurgically, but did not alter connectivity postsurgically); and c) posterior insula and thalamus [F(1,11) = 15.41; p = 0.002] (STAIRS did not alter connectivity presurgically, but increased connectivity postsurgically). Hip replacement surgery significantly changes the functional connections between brain regions that process pain and how they respond to pain provoking stimuli. Further studies are planned to include healthy control participants, to determine if hip replacement normalizes pain processing in the brain. A chronically altered pain processing network could have clinical implications for postsurgical pain management.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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