The Determinants of Eosinophilia in Patients With Severe Asthma
Notice bibliographique
Résumé
Background: Asthma is defined by the Global Initiative for Asthma (GINA) as a heterogeneous disease characterized by chronic airway inflammation. The pathogenesis of the disease is better understood with the comprehension of immunological pathways. These pathways differ by the type of recruited cells and released interleukin (IL). Thus, asthma can be classified into subtypes based on the underlying immune mechanism: eosinophilic asthma (EA) and non-eosinophilic asthma (NEA). Patients with EA tend to respond better to inhaled corticosteroid as compared to those with NEA. The distinction of EA is very important in the light of emergent type 2 inflammation targeted therapies. Methods: We performed a 1-year (2018) retrospective cohort analysis of the Nationwide Inpatient Database (NIS). We included all adult patients presenting with severe asthma. Patients were stratified into two groups: eosinophilic severe asthma and non-eosinophilic severe asthma. The primary outcomes measures were the prevalence of chronic steroid use, status asthmaticus, family history of asthma, food, drug and environmental allergies, presence of nasal polyps, allergic rhinitis, allergic dermatitis, need for mechanical ventilation, need for oxygen supplementation, gastroesophageal reflux disease, in-hospital mortality, and length of stay. We performed descriptive statistics. Continuous parametric variables were reported using a mean and standard deviation. Continuous nonparametric variables were reported using a median and interquartile range. To compare the characteristics of the two groups, we used the independent t -test for continuous parametric variables and the Mann-Whitney U test for continuous nonparametric variables. The Chi-square test was used to assess differences in categorical variables. Results: A total of 2,646 patients were included, out of which 882 belonged to the eosinophilic group and 1,764 were in the non-eosinophilic group. Comparing EA versus NEA, we have found that eosinophilic group was characterized by higher percentage of steroid use (18.3% vs. 9.5%, P < 0.001). This group also had higher rates of status asthmaticus and positive family history (P = 0.009 and 0.004, respectively). The presence of allergies, allergic rhinitis, nasal polyps, and allergic dermatitis was higher among patients with eosinophilia. The need for mechanical ventilation and supplemental oxygen was also higher among this group (P < 0.001 for both); however, there was no significant difference in mortality rate (P = 0.347) and the length of hospital stay was similar in both groups (P < 0.001). Conclusion: We showed herein that the eosinophilic subtype of asthma differs widely from the non-eosinophilic phenotype. Clinically, patients with eosinophilia might exhibit different symptomatology, more atopy, and concomitant comorbidities. However, this group might have better response to steroid therapy and might benefit from the new emergent T2 immune targeted therapy. The identification of EA is crucial for better disease control. J Clin Med Res. 2024;16(4):133-137 doi: https://doi.org/10.14740/jocmr5162
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».