Emotional processes and stress in children affected by hereditary angioedema with C1-inhibitor deficiency: a multicenter, prospective study
Bibliographic record
Abstract
BACKGROUND: Hereditary angioedema with C1-inhibitor deficiency (C1-INH-HAE) is characterized by recurrent edema of unpredictable frequency and severity. Stress, anxiety, and low mood are among the triggering factors most frequently reported. Impaired regulation and processing of emotions, also known as alexithymia, may influence outcomes. The aim of this study was to confirm the presence of alexithymia and stress in children with C1-INH-HAE, to determine whether they are also present in children affected by other chronic diseases, and to investigate their relationship with C1-INH-HAE severity. Data from children with C1-INH-HAE (n = 28) from four reference centers in Italy were compared with data from children with type 1 diabetes (T1D; n = 23) and rheumatoid arthritis (RA; n = 25). Alexithymia was assessed using the Alexithymia Questionnaire for Children scale; perceived stress was assessed using the Coddington Life Event Scale for Children (CLES-C). RESULTS: Mean age (standard deviation [SD]) in the C1-INH-HAE, T1D, and RA groups was 11.8 (3.3), 11.7 (2.9), and 11.1 (2.6) years, respectively. Mean C1-INH-HAE severity score was 5.9 (2.1), indicating moderate disease. Alexithymia scores were similar among disease groups and suggestive of difficulties in identifying and describing emotions; CLES-C scores tended to be worse in C1-INH-HAE children. C1-INH-HAE severity was found to correlate significantly and positively with alexithymia (p = 0.046), but not with perceived stress. Alexithymia correlated positively with perceived stress. CONCLUSIONS: Alexithymia is common in children with chronic diseases. In C1-INH-HAE, it may result in increased perceived stress and act as a trigger of edema attacks. Comprehensive management of C1-INH-HAE children should consider psychological factors.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".