The influence of total hip arthroplasty on patients` disability
Bibliographic record
Abstract
Abstract Introduction Hip osteoarthritis manifests itself with pain, limitation of the range of motion, weaker muscles and pathological gait pattern. Total hip arthroplasty is a treatment of choice which leads to pain relief and improvement in patients’ functioning. The aim of the work was to assess the influence of total hip arthroplasty on the reduction in patients’ disability. Material and methods The study group included 30 patients aged 62.53 ± 12.79. Mean body height was 168.03 ± 8.83 cm, while mean body mass was 78.47 ± 12.86 kg. Patients were examined twice, i.e. before the surgery and three months post surgery. In order to assess disability levels, two scales were applied, i.e. Western Ontario and McMaster Universities Arthritis Index (WOMAC) and modified Harris Hip Score (HHS). Results Total hip arthroplasty significantly reduced the patients’ disability. Prior to the surgery, the mean results of HHS were at the level of 37.07 ± 14.47 points. After the surgery, the patients scored 74.93 ± 24.12 points. In WOMAC, the study participants scored an average of 61.7 ± 20.82 points before the surgery and 19.78 ± 26.31 points after the surgery. No correlations of the respondents’ BMI and the duration of pain with the level of improvement resulting from the surgical treatment were noted either in HHS or in WOMAC. A positive correlation was found between the age of the respondents and the level of improvement in HHS. Conclusions Total hip arthroplasty significantly reduced the patients’ disability three months after the surgery. No correlations of the respondents’ BMI and the duration of pain with the level of improvement in their physical fitness were noted.
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 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".