Extracapsular femoral neck fractures treated with total hip arthroplasty: identification of a population with better outcomes
Bibliographic record
Abstract
Background: Femoral neck fractures (FNF) are associated to patient's disability, reduced quality of life and mortality. None of the fixation devices commonly used for extracapsular (EC) FNF (i.e., dynamic hip screws (DHS) and intramedullary nails (IN)) is clearly superior to the other, especially in case of unstable fractures (31.A2 and 31.A3 according to AO/OTA classification). The aim of our study was to identify a sub-population of patients with EC fractures in which better outcomes could be obtainable using total hip arthroplasty (THA). Methods: All patients with EC unstable fractures treated with THA were included in the present study. Demographic data, American Society of Anesthesiologists (ASA) score, hospitalization length, transfusion rate, implant-related complications and mortality rate were collected. Clinical outcomes were evaluated using the Oxford Hip Score (OHS), while patients' general health status through the 12 Item Short Form questionnaires (SF-12). Results: 30 patients (7 male; 23 female) with a mean age of 78.8 years were included. The 1-year mortality rate was 13.3%. The mean OHS was 27.5, while the mean SF-12 were 45.84 for the mental item and 41.6 for the physical one. Age was the only factor associated with the OHS and patients older than 75 years presented a 12- fold higher risk of developing bad outcomes. Conclusions: THA seems to be a viable option for unstable EC fractures, with good clinical outcomes, especially in patients younger than 75 years of age. The mortality rate associated with THA in EC fractures is low and anyway comparable with IN.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".