Bibliographic record
Abstract
UNLABELLED: The incidence rate of periprosthetic fractures has increased in the past decade. Osteolysis, age and preoperative function are factors that influence morbidity. Treatment options include conservative and surgical treatment. OBJECTIVES: To conduct a study analyzing the functional results of the surgical treatment of periprosthetic hip fractures at the ABC Medical Center considering preoperative and postoperative variables. MATERIAL AND METHODS: Cross-sectional retrospective study of patients with a diagnosis of periprosthetic hip fracture between January 2000 and December 2011, classified using the Vancouver system. The Oxford Hip Score was used pre- and postoperatively as a functional measure. The variables to evaluate included age, sex, surgical technique, and the time elapsed between primary surgery and the periprosthetic fracture. RESULTS: Twenty-five patients were analyzed; frequency was 3.3 cases per year. 80% of periprosthetic fractures were postoperative; 72% were total hip arthroplasties. The time elapsed between primary surgery and the traumatic event was 2 to 4 years (68%), with a mean of 4.5 years for hemiarthroplasties and 3.9 years for total arthroplasties. Patients who according to the Oxford Hip Score had good function maintained their results; 75% of those with moderate function maintained their score. Patients with poor function improved. CONCLUSIONS: At the ABC Medical Center, the outcomes of the treatment of periprosthetic hip fractures are considered as good according to the Oxford Hip Score.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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".