Frequency, Severity, and Associations of Gastrointestinal Symptoms in Adults and Children with Type 1 Diabetes
Notice bibliographique
Résumé
Background: Significant variability is reported as to the presence and quality of gastrointestinal (GI) symptoms in patients with type 1 diabetes (T1D). Objective: To assess reported GI symptoms and associated comorbidities in adults and children with T1D. Methods: The Gastrointestinal Symptom Scale (GISS) and a Visual Analog Scale (VAS) were used to assess GI symptom type and severity in 2,370 patients with T1D aged 8-45 years as part the screening phase of the Celiac Disease and Diabetes Dietary Intervention and Evaluation Trial (CD-DIET). Co-morbidities, including diabetes-related complications, were extracted from clinical records. The presence and severity of GI symptoms and relationships with demographic, clinical and other diabetes-related factors were evaluated. Results: Overall, 1368 adults (57.7%) aged 19-45 years and 1002 (42.3%) pediatric patients aged 8-18 years were studied. At least one GI symptom was reported in 34.1% of adults as compared with 21.7% of children (p<0.0001). Common symptoms in children included upper abdominal pain, lower abdominal pain and nausea while adults more frequently reported lower GI symptoms with females describing more severe symptoms. Overall, patients with ≥1 GI symptom were more likely to have diabetes complications when adjusted for age and sex (OR=1.41; 95% CI=1.1-1.7; p=0.002). Conversely, patients who reported diabetes complications such as nephropathy, retinopathy and/or cardiovascular disease were 1.94 (95% CI=1.49-2.52) times more likely to report GI symptoms. No association was observed between autoimmune conditions (including screen-detected celiac disease and reported thyroid disease) and GI symptoms. Conclusions: In this large screening study in a contemporary T1D cohort, significant differences were found between age groups with more frequent GI symptoms in adults. Significant associations were observed between GI symptoms and diabetes complications along with diabetes duration. Disclosure F.H. Mahmud: None. E. Nunes de Melo: None. A.B. Clarke: None. E. Assor: None. A. Parikh: None. A. Advani: Research Support; Self; AstraZeneca, Boehringer Ingelheim GmbH. Other Relationship; Self; Boehringer Ingelheim GmbH. B.A. Perkins: Advisory Panel; Self; Boehringer Ingelheim GmbH. Research Support; Self; Boehringer Ingelheim GmbH, Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Abbott. Speaker's Bureau; Self; Abbott, Janssen Pharmaceuticals, Inc.. Advisory Panel; Self; Insulet Corporation. Speaker's Bureau; Self; Insulet Corporation, Dexcom, Inc.. B.R. Shah: None. C.S. Zuijdwijk: None. C. McDonald: None. D. Mack: None. D. Koltin: None. E. Hsieh: None. E.M. Szentgyorgyi: None. F. Saibil: None. G. Mukerji: None. H.A. Lochnan: Research Support; Self; Amylin Pharmaceuticals, Boston Therapeutics, Inc., Sanofi. J. Gilbert: Other Relationship; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Janssen Pharmaceuticals, Inc., Sanofi. K. Bax: None. M.L. Lawson: None. M.D. Beaton: Advisory Panel; Self; Takeda Canada Inc., Janssen Pharmaceuticals, Inc., AbbVie Inc.. N.A. Saloojee: None. O. Lou: None. P.H. Gallego: None. R.L. Houlden: Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., AstraZeneca, Eli Lilly and Company. R. Aronson: Other Relationship; Self; Novo Nordisk Inc., Janssen Pharmaceuticals, Inc., Sanofi, AstraZeneca. Research Support; Self; Eli Lilly and Company, Becton, Dickinson and Company, Merck & Co., Inc., Senseonics, Boehringer Ingelheim Pharmaceuticals, Inc.. S.E. Kirsch: None. W.G. Paterson: None. Z. Punthakee: Research Support; Self; Amgen, Astra Zeneca/Bristol Myers Squibb, Lexicon, Merck, NovoNordisk, Sanofi. Speaker's Bureau; Self; Abbott, Astra Zeneca/Bristol Myers Squibb, Boehringer Ingelheim/Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Sanofi. Advisory Panel; Self; Astra Zeneca/Bristol Myers Squibb, Boehringer Ingelheim/Eli Lilly, Dexcom, Janssen, Medtronic, NovoNordisk, Pfizer, Sanofi. M.A. Marcon: None.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| 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 ».