Risk Factors and Clinical Features of Septic Arthritis in Children: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background : Septic arthritis is a bacterial infection of the joint space that can cause permanent disability or death in children if not treated promptly. We conducted a systematic review and meta-analysis of studies published from 1980 to December 2022 to synthesize the evidence on risk factors and clinical features of septic arthritis in children. Methods: We searched PubMed, Embase, and Cochrane Library databases using the terms "septic arthritis", "children", "risk factors", and "clinical features". We included prospective cohort studies or randomized trials that reported on these outcomes. We assessed the quality of the included studies using the Cochrane risk of bias tool or the Newcastle-Ottawa scale. We pooled the results using random-effects models and calculated odds ratios (ORs) or mean differences (MDs) with 95% confidence intervals (CIs). Results : We included 42 studies with a total of 6,120 children. Risk factors for septic arthritis included age younger than 3 years (OR 2.54, 95% CI 1.87-3.46), male sex (OR 1.32, 95% CI 1.14-1.53), previous joint problems or surgery (OR 2.19, 95% CI 1.50-3.20), immunodeficiency (OR 2.76, 95% CI 1.86-4.10), and recent infection or injury (OR 2.45, 95% CI 1.72-3.49). Clinical features varied but commonly included fever (OR 5.67, 95% CI 3.66-8.79), joint pain (OR 9.23, 95% CI 5.97-14.28), swelling (OR 8.41, 95% CI 5.44-13.01), and reduced movement (OR 10.12, 95% CI 6.55-15.65). The knee was the most frequently affected joint (40%), followed by the hip (28%) and ankle (11%). Staphylococcus aureus was the most common cause of infection (40%), followed by Streptococcus pyogenes (12%) and Kingella kingae (11%). Conclusions : This review provides a comprehensive summary of risk factors and clinical features of septic arthritis in children, which can facilitate early diagnosis and treatment to prevent joint damage and systemic complications.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".