Acetabular blood flow during total hip arthroplasty.
Bibliographic record
Abstract
OBJECTIVE: To determine the immediate effect of reaming and insertion of the acetabular component with and without cement on peri-acetabular blood flow during primary total hip arthroplasty (THA). DESIGN: A clinical experimental study. SETTING: A tertiary referral and teaching hospital in Toronto. PATIENTS: Sixteen patients (9 men, 7 women) ranging in age from 30 to 78 years and suffering from arthritis. INTERVENTION: Elective primary THA with a cemented (8 patients) and non-cemented (8 patients) acetabular component. All procedures were done by a single surgeon who used a posterior approach. MAIN OUTCOME MEASURE: Acetabular bone blood-flow measurements made with a laser Doppler flowmeter before reaming, after reaming and after insertion of the acetabular prosthesis. RESULTS: Acetabular blood flow after prosthesis insertion was decreased by 52% in the non-cemented group (p < 0.001) and 59% in the cemented group (p < 0.001) compared with baseline (pre-reaming) values. CONCLUSION: The significance of these changes in peri-acetabular bone blood flow during THA may relate to the extent of bony ingrowth, peri-prosthetic remodelling and ultimately the incidence of implant failure because of aseptic loosening.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".