Paediatric acute lymphadenitis: Emergency department management and clinical course
Bibliographic record
Abstract
OBJECTIVES: To describe clinical characteristics and management of acute lymphadenitis and to identify risk factors for complications. METHODS: Health record review of children ≤17 years with acute lymphadenitis (≤2 weeks) in a tertiary paediatric emergency department (2009-2014); 10% of charts were reviewed by a blinded second reviewer. Multivariate logistic regression identified factors associated with intravenous antibiotic treatment, unplanned return visits warranting intervention, and surgical drainage. RESULTS: Of 1,023 health records, 567 participants with acute lymphadenitis were analyzed. The median age = 4 years (interquartile range [IQR]: 2 to 8 years), and median duration of symptoms = 1.0 day (IQR: 0.5 to 3.0 days). Cervical lymphadenitis was most common. Antibiotics were prescribed in 73.5% of initial visits; 86.9% of participants were discharged home. 29.0% received intravenous antibiotics, 19.3% had unplanned emergency department return visits, and 7.4% underwent surgical drainage. On multivariate analysis, factors associated with intravenous antibiotic use included history of fever (odds ratio [OR]=2.07, 95% confidence interval [CI]: 1.11 to 3.92), size (OR=1.74 per cm, 95% CI: 1.44 to 2.14), age (OR=0.84 per year, 95% CI: 0.76 to 0.92), and prior antibiotic use (OR=4.45, 95% CI: 2.03 to 9.88). The factors associated with unplanned return visit warranting intervention was size (OR=1.30 per cm, 95% CI: 1.06 to 1.59) and age (OR=0.89, 95% CI: 0.80 to 0.97). Factors associated with surgical drainage were age (OR=0.68 per year, 95% CI: 0.53 to 0.83) and size (OR=1.80 per cm, 95% CI: 1.41 to 2.36). CONCLUSIONS: The vast majority of children with acute lymphadenitis were managed with outpatient oral antibiotics and did not require return emergency department visits or surgical drainage. Larger lymph node size and younger age were associated with increased intravenous antibiotic initiation, unplanned return visits warranting intervention and surgical drainage.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".