Chronic Postsurgical Pain after Primary Total Hip Arthroplasty for Osteoarthritis: A Nationwide Cross-Sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Total hip arthroplasty (THA) is frequently performed in patients who have osteoarthritis to relieve pain and improve quality of life. However, there is limited contemporary data on satisfaction and risk of persistent postsurgical pain, even though it is essential for informed decision-making. The objective of our study was to investigate the incidence of chronic postsurgical pain, pain characteristics, use of analgesics, patient satisfaction, and willingness to undergo surgery again one year after THA for osteoarthritis. METHODS: We conducted a nationwide cross-sectional online survey of unselected patients who underwent primary, unilateral THA for primary osteoarthritis. At one year after surgery, we invited 2,533 patients identified from two national registers to participate in the survey. The primary outcome was moderate to severe chronic postsurgical pain, defined as a numerical rating scale score ≥ 4. The secondary outcomes included frequency of pain, pain interference with everyday life, the Western Ontario and McMaster Universities Osteoarthritis Index pain domain, the Doleur Neuropatique 4 interview, use of analgesics, satisfaction, and willingness to undergo surgery again. RESULTS: Of 1,880 (74.2%) respondents, 244 (13.0%) had moderate or severe chronic postsurgical pain (numerical rating scale ≥ 4), 1,715 (91.2%) patients were either satisfied or very satisfied with the result of surgery, and 1,752 (93.2%) would still have undergone surgery if they could go back in time. CONCLUSIONS: At one year after primary THA, at least 13% of Danish patients experienced moderate to severe postsurgical pain. However, up to 91% of patients reported being satisfied or very satisfied with the outcome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".