Smith–Petersen Versus Watson–Jones Approach Does Not Affect Quality of Open Reduction of Femoral Neck Fracture
Bibliographic record
Abstract
OBJECTIVE: To compare immediate quality of open reduction of femoral neck fractures by alternative surgical approaches. DESIGN: Retrospective cohort study. SETTING: Twelve Level 1 North American trauma centers. PATIENTS: Eighty adults 18-65 years of age with isolated, displaced, OTA/AO type 31-B2 or -B3 femoral neck fractures treated with internal fixation. INTERVENTION: Thirty-two modified Smith-Petersen anterior approaches versus 48 Watson-Jones anterolateral approaches for open reduction performed by fellowship-trained orthopaedic trauma surgeons. MAIN OUTCOME: Reduction quality as assessed by 3 senior orthopaedic traumatologists as "acceptable" or "unacceptable" on AP and lateral postoperative radiographs. RESULTS: No difference was observed in the rate of acceptable reduction by modified Smith-Petersen (81%) versus Watson-Jones (81%) approach (risk difference null, 95% confidence interval -17.4% to 17.4%, P = 1.00) with 90.4% panel agreement (Fleiss' weighted κ = 0.63, P < 0.01). Stratified analyses did not identify a significant difference in the rate of acceptable reduction between approaches when stratified by Pauwels angle, basicervical or transcervical fracture location, or posterior comminution. The Smith-Petersen approach afforded a better reduction when preoperative skeletal traction was not applied (RR = 1.67 [95% CI 1.10-2.52] vs. RR = 0.87 [95% CI 0.70-1.08], P = 0.006). CONCLUSIONS: No difference was observed in the quality of open reduction of displaced femoral neck fractures in young adults when a Watson-Jones anterolateral approach versus a modified Smith-Petersen anterior approach was performed by orthopaedic trauma surgeons. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".