Weathering the storm
Bibliographic record
Abstract
Aims: It is not unusual for patients, prior to their total hip arthroplasty (THA), to indicate that their symptoms worsen with certain meteorological conditions. However, the prevalence and evolution of weather-related pain (WRP) following THA remain poorly understood. The aim of this study was to investigate the prevalence of WRP both before and after primary THA, assess the impact of THA on pre-existing WRP, explore the development of de novo WRP postoperatively, and identify potential risk factors associated with WRP. Methods: An in-person survey was conducted on 331 consecutive patients (442 primary THAs) at the time of their postoperative follow-up visit. Each patient was assessed using a questionnaire specifically designed to address weather-related joint pain before and after their THA. The clinical evaluation included patient-reported outcome measures (PROMs). Results: Preoperatively, WRP was present in 18% (61/331) of the patients, with 69% (42/61) achieving complete resolution postoperatively (p < 0.001). In patients with WRP in multiple joints preoperatively, the THA failed to alleviate the WRP in 34% (16/47) of cases. In addition, 9% (30/331) of the THA patients developed de novo WRP after surgery. Although the overall prevalence of WRP in patients post THA was 12% (51/442), the prevalence was 31% (19/61) in patients with WRP preoperatively. Patients with a preoperative diagnosis of rheumatoid arthritis, ankylosing spondylitis, or osteonecrosis, as well as older patients and those with a higher BMI, were more likely to have WRP postoperatively. Conclusion: WRP is not uncommon prior to and after THA. Although THA can effectively alleviate WRP in specific patient populations, it does not universally eliminate preoperative WRP or prevent the emergence of new WRP after surgery. The impact of THA on WRP should be discussed with patients preoperatively to facilitate informed decision-making and clarify postoperative expectations.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".