Weight-Bearing Status After Peri-Prosthetic Proximal Femur Fracture Open Reduction and Internal Fixation (ORIF) or Revision Arthroplasty: A Clinical Audit
Bibliographic record
Abstract
Background Peri-prosthetic proximal femur fractures (PPFFs) are becoming increasingly common due to the rising number of total hip arthroplasties (THAs) in ageing populations. These complex fractures often require either open reduction and internal fixation (ORIF) or revision arthroplasty. Postoperative weight-bearing (WB) status plays a critical role in recovery, yet there is considerable variability in clinical practice. Objectives This audit aimed to evaluate the documentation and implementation of postoperative WB protocols following ORIF or revision arthroplasty for PPFFs. It assessed adherence to British Hip Society best practice guidelines, reasons for deviations, and rates of fixation failure. Methods A retrospective single-cycle audit was conducted at a UK District General Hospital between January 2023 and June 2024. Data was collected from the Hip Fracture Registry. Inclusion criteria were patients with closed PPFFs around THA or hemiarthroplasty; exclusions included fractures involving intra-medullary devices or knee prostheses. Patients were classified using the Vancouver classification (types A-C). Data points included fracture type, treatment modality, postoperative WB status, rationale for WB decision, and fixation outcomes. Results Thirty-eight patients met the inclusion criteria: four (10.5%) had type A fractures, 28 (73.7%) type B, and six (15.8%) type C. Twenty-eight (73.7%) patients underwent surgical intervention (19 ORIF; nine revision arthroplasty), while 10 (26.3%) were managed conservatively. Of the surgical group, 22 (78.6%) were mobilised as full weight-bearing (FWB), four (14.3%) were limited weight-bearing (LWB), and two (7.2%) were non-weight-bearing (NWB). LWB was most often attributed to the intraoperative identification of poor bone stock; NWB was associated with medial calcar instability or metastatic involvement. Only one (3.5%) patient experienced fixation failure, with conservative management adopted due to comorbidities. A notable finding was the lack of detailed documentation for WB restrictions in LWB and NWB groups, which posed challenges for postoperative rehabilitation. Conclusions This audit demonstrates that while the majority of PPFF patients were managed in accordance with national guidance promoting early FWB, a significant proportion received restricted WB without adequate justification. The low rate of fixation failure supports the feasibility of immediate FWB in appropriately selected patients. However, the absence of clear functional instructions in many cases highlights a need for improved communication and standardised documentation. Further multi-centre studies are required to establish robust, evidence-based postoperative protocols for this growing patient population.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".