Reduction in Mortality following Elective Major Hip and Knee Surgery: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Systematic reviews reporting time trends in mortality following major orthopaedic surgery are few and have limitations. They reported on only a fraction (< 15%) of the available data and did not investigate potential causes of the reduction in mortality. METHODS: We searched PubMed for randomized trials and observational studies, published between 1950 and 2016, reporting on mortality within 3 months of elective total hip and knee replacement (THR/TKR). Mortality risks were estimated for each 5-year interval using a Poisson regression model and presented by study design and mode of prophylaxis. To estimate the mortality reduction unrelated to anti-thrombotic use, we performed a pooled analysis of four thromboprophylaxis strategies for which data spanned five decades. RESULTS: We identified 255 eligible studies, which documented 31,604 deaths among 6,293,954 patients, and found a consistent decline in mortality irrespective of study design and mode of prophylaxis. Mortality declined from 1.15% pre-1980 to 0.24% post-2000, a 78.7% relative risk reduction (95% confidence interval [CI]: 74.7-82.1%) in randomized and cohort studies. Furthermore, our data showed a 74.4% (95% CI: 68.7-79.0%) relative reduction in mortality independent of the methods of prophylaxis, thereby indicating that improvements in peri-operative care unrelated to anti-thrombotic prophylaxis played a major role in such reduction. CONCLUSION: Mortality following elective THR/TKR has markedly declined over the past 50 years and is now low irrespective of which prophylactic agent is being used. Although anti-thrombotic prophylaxis may have contributed, other improvements in peri-operative care played a major role in the mortality reduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".