Patient reported outcomes during the first month following anterior and posterior total hip arthroplasty and hip resurfacing
Bibliographic record
Abstract
BACKGROUND: Surgical treatment for osteoarthritis of the hip includes hip resurfacing (HR) and total hip arthroplasty (THA) via various surgical approaches. The discussion about the benefits and preferability of each procedure is highly controversial. We aimed to quantify the patients' utilization of opioids within the first 30 days following surgery and hypothesized that there are no differences in pain, medication, ability to walk, and function between direct anterior approach THA (DAA-THA), posterior approach THA (PA-THA), and HR. METHODS: This retrospective study evaluated 207 hips in 199 patients (DAA: 126 hips, PA: 59, HR: 21), who underwent surgery for primary osteoarthritis between 2020 and 2022. Patients used an app (SeamlessMD, Toronto, Canada) to report pain, utilization of opioids, additional pain medication, walking distance, swelling, and wound drainage for 30 days and HOOS-JR and satisfaction at one month after surgery. Results were compared between the groups after adjusting for age and BMI and patient satisfaction was correlated with pain and function. RESULTS: Opioid cessation was 99% 20 days after surgery. HOOS-JR improvement from pre- to postoperative was 23 points on average (-29-82, SD 15) and was significant in all groups (p < 0.001). No differences in pain, the dosage of opioids and complications were found between DAA-THA, PA-THA and HR. CONCLUSION: The current data showed a high rate of opioid cessation (99%) within 3 weeks following hip reconstructive surgery. DAA-THA, PA-THA, and HR provided comparable opioid usage, function, and a low early complication rate within the first month after surgery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".