Irrigation and debridement for knee osteoarthritis patients with suspected infection by intra-articular injection before total knee arthroplasty: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Patients suffer from knee osteoarthritis (KOA) pain may seek for intra-articular injections before total knee arthroplasty (TKA), which have a possibility of causing the joint sepsis. However, the management and clinical outcomes of these patients following TKA remain uncertain. METHODS: Patients with a history of intra-articular injection, in which a joint sepsis was suspected, were included. The patients received joint irrigation and debridement (I&D) and antibiotic treatment until serum inflammatory indicators returned to normal level before TKA. The information of joint fluid routine and culture, synovium section and culture, and serum inflammatory indicator values were collected. Range of motion, Knee Society Scores (KSS) and Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) were used for functional evaluations. RESULTS: /L, but no positive cultures were found. The culture of synovium detected three positive results: two Staphylococcus epidermidis and one S. aureus. I&D treatment had no obvious effect on the functional outcomes of KOA, but alleviated the joint pain (p < 0.01). Furthermore, we found that I&D pretreatment could increase the operation time with about 10 min longer than the primary TKA (p < 0.01). With respect to TKA outcomes, I&D had a slight influence on the knee flexion (p < 0.01), but no significant difference was identified between the two groups for KSS and WOMAC (all p values > 0.05). In addition, there was no significant difference in complication rates between the two groups in the last follow-up. CONCLUSION: I&D treatment is a valuable procedure for suspected knee infection, which has a higher incidence of detecting microorganisms while does not influence the functional outcomes and complication rates of TKA. However, further larger studies are required to confirm these findings.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".