Bibliographic record
Abstract
Context: Injection with homologously-used umbilical cord tissue allograft has not been adequately studied in patients suffering from knee pain. Objectives: The goal of this study is to determine if knee pain subjects who received cryopreserved umbilical cord tissue (UCT) injected into knee joints experience less knee pain, better function, decreased physical limitations, and reduction of medications (e.g., opiates, NSAIDs, and acetaminophen) over a 6-month period. Methods: Prior to initiation of this study, Institutional Review Board (IRB) approval was obtained. Visual Analog Scale (VAS), Western Ontario and McMaster Universities Osteoarthritic Index (WOMAC), and medication usage data were recorded for thirty (30) consenting knee pain subjects receiving UCT at a single site in the United States. Subject profile information was also gathered and utilized to gain further insight into any effects of age, gender, and BMI on pain improvement over time. Results: Mean resting VAS scores improved from 1.95 to 0.83 over 6 months (p<0.001), while mean VAS scores with activity improved from 6.28 to 2.87 (p<0.001) for the same period. There was no strong evidence of correlation found between gender and VAS scores (resting or with activity). However, there were statistically significant correlations found for both BMI vs. Pre-injection VAS with activity scores (r=0.402, p=.028) and Age vs. Pre-injection VAS with activity scores (r=0.434, p=.017). Mean WOMAC daily activity function scores improved from 44.7 to 18.5 over the same 6 months (p<.001). Overall, of the patients who used medications at the beginning of the study (18), 77.8% of them reduced or eliminated medication use. Conclusion: Analysis demonstrates that injection with UCT decreases pain, improves physical function, and allows for less medication use for at least 6 months.
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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 | 0.001 |
| 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) | 0.002 | 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".