Role of Platelets Rich Plasma Intra-Articular Injections in the Treatment of Knee Osteoarthritis among Elderly
Bibliographic record
Abstract
Background: Knee OA is a major publ ic heal th problem among elderly. I t is a debi l i tating condi tion associatedwi th increased morbidi ty and disabi l i ty . Thus, the development of therapeutic interventions could enhance thequal i ty of l i fe for the elderlyAim: To evaluate the cl inical effi cacy of platelets rich plasma int ra articular injections in t reatment of KneeOsteoarthri tis among Elderly.Methods: one arm cl inical t rial on 44 elderly par ticipants al l of them received a single session of intraarticularPRP injection, they were subjected to physical function and mobi l i ty assessment using Western Ontario andMcMaster Universi ties Ar thri tis Index (WOMAC) questionnai re and pain assessment by the numeric pain ratingscale (NRS-11) at 6 and 12 months post injection.Results: study reported a statistical ly signi ficant improvement in al l functional WOMAC assessment scores andNRS after 6 months and 12 months post injection fol low up wi th the tendency for gradual decl ine of cl inicalimprovement ti l l the end of fol low up after 1 y ear.Conclusions: Intraar ticular PRP injections are safe, effective and rel iable t reatment option providing functionalimprovement and pain cont rol for elderly patients wi th knee OA
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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 | 0.000 | 0.000 |
| 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".