Bibliographic record
Abstract
Due to the increasing prevalence of coxarthrosis, total hip arthroplasty has become one of the most frequently performed orthopedic operations. This surgery eliminates the symptoms that limit the patient's quality of life. Postoperative quality of life after total hip arthroplasty is assessed by the PROM (Patient reported outcome measures) questionnaires. There are generic PROM questionnaires for assessing general health and disease-specific questionnaires. The most frequently used generic questionnaires are Short Form Health Survey (SF) with 36, 20, 12 or 8 questions and European Quality of Life-5 Dimensions (EQ-5D). Most frequently used disease-specific questionnaires are Harris Hip Score (HHS), Western Ontario and McMaster Universities Osteoarthritis index (WOMAC), Hip disability and Osteoarthritis Outcome Score (HOOS), Oxford Hip Score (OHS), Larson's questionnaire, modified Merle d'Aubigne and Postel Score (MDA), Charnley Hip Score, Lower Extremity Functional Scale (LEFS) American Academy of Orthopaedic Surgeons' Hip and Knee Score (AAOSHKS) and Lequesne Index of Severity for Osteoarthritis of the Hip (LISOH). The aim of this graduate thesis is to present the PROMs questionnaires that are most frequently used in the self-assessment of the total hip endoprosthesis outcomes. PROMs questionnaires serve as appropriate instrument to evaluate the outcome of the treatment as patient's personal satisfaction with postoperative quality of life is the most important indicator of the success of the treatment. OHS proved to be the highest quality disease-specific questionnaire.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.065 | 0.020 |
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".