Exploring Attention-Deficit/Hyperactivity Disorder Symptoms in Patients With Atopic Dermatitis by Disease Severity: Cross-Sectional Analysis
Notice bibliographique
Résumé
Background: Atopic dermatitis (AD) is a chronic inflammatory skin condition affecting a significant percentage of the global population. Emerging research suggests a potential link between AD and neurodevelopmental disorders like attention-deficit/hyperactivity disorder (ADHD). However, there is a lack of comprehensive studies within the Saudi Arabian population examining this association. Objective: This study aims to determine the prevalence of ADHD among patients with AD in Saudi Arabia and to explore potential associations with demographic and clinical factors. Methods: In this cross-sectional, multicenter study conducted between May and November 2024, 419 patients with AD were recruited from various hospitals in Saudi Arabia. Children were screened for ADHD symptoms using the ADHD Rating Scale-5, while adults were assessed with the Adult Self-Report Scale. Logistic regression was used to evaluate the influence of AD severity, age, gender, nationality, and BMI on the likelihood of ADHD symptoms. Results: A total of 419 patients with AD were included, of whom 234 (55.8%) were children and 185 (44.2%) were adults; 239 (57%) were female and 360 (85.9%) were Saudi nationals. ADHD symptoms were identified in 84 (20%) patients, with a slightly higher prevalence among children (49/234, 20.9%) compared to adults (35/185, 18.9%; P=.61). No significant associations were found between ADHD symptoms and gender, nationality, BMI, or AD severity in either age group. Moderate to severe AD was more common among adults (48/185, 25.9%) than children (42/234, 17.9%; P=.048). Conclusions: This study found that 20% of patients with AD screened positive for ADHD symptoms, with slightly higher rates in children than adults. No significant associations were observed between ADHD symptoms and gender, nationality, BMI, or AD severity. Although no significant clinical predictors were identified, the findings emphasize the need for ADHD screening in patients with AD, particularly in regions with high AD prevalence. Future longitudinal studies should explore underlying mechanisms and assess how managing one condition may influence the other.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».