Pre-Operative Status and Quality of Life Following Total Joint Replacement in a Developing Country: A Prospective Pilot Study
Bibliographic record
Abstract
BACKGROUND: An increasing number of medical relief organizations have launched programs to perform total joint replacements in the developing world. There is a paucity of data on the clinical outcomes of these procedures. We documented pre- and post-operative pain and functional status in a group of low income Dominicans who underwent total hip or knee replacement performed by an American relief organization. METHODS: In March 2009 and 2010, we surveyed patients participating in Operation Walk Boston, a medical relief organization that provides total joint replacements to patients in the Dominican Republic. Questionnaires included the Western Ontario and McMaster University Osteoarthritis (WOMAC) Index scales and the Short-Form 36 (SF-36) scales for physical activity and mental health. Scores were transformed to a 0 - 100 point scale (100 is best). RESULTS: 81 individuals (mean age 61 years, 60% female) completed the pre-operative questionnaires. Twenty eight of the 35 who completed preoperative forms in 2009 also completed follow up forms in 2010 (follow-up rate 80%). Patients reported poor pre-operative WOMAC function (mean = 33.6, sd = 22.0) and WOMAC pain (mean = 38.4, sd = 22.9) scores preoperatively. Mean post-operative WOMAC pain and function scores were 86.4 (sd = 13.1) and 88.1 (sd = 11.4) respectively. Improvement in pain and function was similar for patients undergoing hip (n=11) and knee (n=17) replacements. CONCLUSION: Total joint replacement was effective in relieving pain and restoring function in this program. These results are useful for comparison to outcomes in developed countries and for establishing benchmarks for future programs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".