Fractured neck of femur: a review of three seminal papers and their implications to clinical management
Bibliographic record
Abstract
It is unusual, if not unique, for three major research papers concerned with the management of the fractured neck of femur (FNOF) to be published in a short period of time, each describing large prospective randomized clinical trials. These studies were conducted in up to 17 countries worldwide, involving up to 80 surgical centers and include large numbers of patients (up to 2,900) with FNOF. Each article investigated common clinical dilemmas; the first paper comparing total hip arthroplasty versus hemiarthroplasty for FNOF, the second as to whether ‘fast track’ care offers improved clinical outcomes and the third, compares sliding hip with multiple cancellous hip screws. Each paper has been deemed of sufficient quality and importance to warrant publication in The Lancet or the New England Journal of Medicine. Although ‘premier’ journals, they only occationally contain orthopaedic studies and thus may not be routinely read by the busy orthopaedic/surgical clinician of any grade. It is therefore our intention with this present article to accurately summarize and combine the results of all three papers, presenting, in our opinion, the most important clinically relevant facts. Cite this article: Bone Joint Open 2020;1-6:198–202.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".