Serious Infection Rates Among Children With Systemic Lupus Erythematosus Enrolled in Medicaid
Bibliographic record
Abstract
OBJECTIVE: To investigate the nationwide prevalence and incidence of serious infections among children with systemic lupus erythematosus (SLE) enrolled in Medicaid, the US health insurance program for low-income patients. METHODS: From Medicaid claims (2000-2006) we identified children ages 5 to <18 years with SLE (≥3 International Classification of Diseases, Ninth Revision [ICD-9] codes of 710.0, each >30 days apart) and lupus nephritis (LN; ≥2 ICD-9 codes for kidney disease on/after SLE codes). From hospital discharge diagnoses, we identified infection subtypes (bacterial, fungal, and viral). We calculated incidence rates (IRs) per 100 person-years, mortality rates, and hazard ratios adjusted for sociodemographic factors, medications, and preventive care. RESULTS: Among 3,500 children with identified SLE, 1,053 serious infections occurred over 10,108 person-years; the IR was 10.42 per 100 person-years (95% confidence interval [95% CI] 9.80-11.07) among all those with SLE and 17.65 per 100 person-years (95% CI 16.29-19.09) among those with LN. Bacterial infections were most common (87%, of which 39% were bacterial pneumonias). In adjusted models, African Americans and American Indians had higher rates of infections compared with white children, and those with comorbidities or receiving corticosteroids had higher infection rates than those without. Males had lower rates of serious infections compared to females. The 30-day postdischarge mortality rate was 4.4%. CONCLUSION: Overall, hospitalized infections were very common in children with SLE, with bacterial pneumonia being the most common infection. Highest infection risks were among African American and American Indian children, those with LN, comorbidities, and those taking corticosteroids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".