ADVERSE CHILDHOOD EXPERIENCES: PREVALENCE AND RELATIONSHIP TO DISEASE OUTCOMES IN CHILDHOOD-ONSET SYSTEMIC LUPUS ERYTHEMATOSUS (CSLE)
Bibliographic record
Abstract
O069 / #96 Topic:AS18 - Pediatric SLE ABSTRACT CONCURRENT SESSION 12: PEDIATRIC SLE – ADVANCES IN DISEASE OUTCOMES AND MENTAL HEALTH 24-05-2025 10:40 AM - 11:40 AM Background/Purpose Childhood-onset systemic lupus erythematosus (cSLE) is an autoimmune disease characterized by multiorgan inflammation, alongside high frequencies of mood disorders and cognitive impairment. Adverse Childhood Experiences (ACEs) quantify traumatic childhood events, which have been linked to altered immune response and increased chronic disease risk. Prior studies indicate that those with ≥ 4 ACEs, including adults with SLE, face higher risk of worse health outcomes. Limited research exists on ACEs in cSLE. We aimed to describe the prevalence of ACEs among cSLE patients and investigate associations with i) disease activity, ii) patient-reported outcome measures, and iii) self-reported executive function. Methods This cross-sectional study analyzed prospective data from cSLE patients aged 13-19 years at the time of assessment. The Pediatric ACEs and Related Life Events Screener (PEARLS) measured self-reported ACEs. Disease activity over the time since diagnosis was measured by the adjusted mean Systemic Lupus Erythematosus Disease Activity Index (SLEDAI-2K). The Patient Reported Outcomes Information System (PROMIS) Pediatric-37 Profile assessed patient-reported anxiety, depression, and fatigue. The Behavior Rating Inventory of Executive Function (BRIEF-2) Global Executive Composite score measured executive function. The frequency of ACEs types was tabulated, and patients were classified into high-risk (≥ 4 ACEs) and low-risk (≤ 3 ACEs) groups. Associations between ACEs risk group and the outcomes were examined using regression analyses with generalized linear models, adjusted for age. Results Of 48 cSLE patients (mean age 15.23 ± 1.87 years, 85% female), 73% reported at least 1 ACE, and 30% reported ≥ 4 ACEs (Table 1). The most common ACEs were caregiver verbal abuse, emotional neglect, and separation, as well as community violence (Figure 1). Being in the high-risk ACEs group compared to low risk, was significantly associated with worse scores for PROMIS anxiety (p<0.001), depression (p<0.001), and fatigue (p=0.001), alongside poorer executive function scores (p<0.001) (Figure 2). No significant associations were observed for disease activity (p=0.987). Table 1. Patient Demographics, Disease Characteristics, and Outcome Measures Figure 1. Self-Reported Adverse Childhood Experiences (ACEs) in Patients with cSLE: Frequency and Types Note. Figure 1 illustrates the distribution of 19 reported adverse childhood experiences (ACEs) types within our cSLE cohort (n=48). Among the total ACEs (n=134) self-reported on the patient PEARLS questionnaire, the most commonly reported ACEs were caregiver verbal abuse (n=18), community violence (n=14), emotional neglect (n=14), and caregiver separation/divorce (n=14). Figure 2. Relationship between ACEs and Self-Reported cSLE Outcomes Note. Figure 2 contains 4 sets of boxplots depicting differences in mean outcome scores between the high-risk and low-risk ACEs groups. Associations show beta coefficients, confidence intervals, and p-values from regression analyses. Regression analyses showed significant associations for worse PROMIS anxiety (p<0.001), depression (p<0.001), and fatigue (p=0.001) scores alongside poorer executive function (p<0.001) within the high-risk group. The p-value threshold used for significance was p<0.05. Acknowledgments: Lupus Research Alliance, U.S. Department of Defense Conclusions Within our cSLE cohort, ACEs were substantially prevalent, with almost a third of patients having experienced ≥ 4 ACEs. The high-risk group (≥ 4 ACEs) had significantly worse patient-reported outcomes across anxiety, depression, fatigue, and executive function. These results underscore the impact of ACEs on patient well-being, emphasizing the need for integrated medical and mental health care approaches. Future research should examine these associations within larger cohorts.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".