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Enregistrement W4316086010 · doi:10.14309/01.ajg.0000860348.78120.4d

S927 The Impact of the COVID-19 Pandemic on Patients With Ulcerative Colitis: Results From a Global Ulcerative Colitis Patient Survey

2022· article· en· W4316086010 sur OpenAlexaffabout
Laurent Peyrin‐Biroulet, Karoliina Ylänne, Allyson Sipes, Michelle Segovia, Sean Gardiner, Joseph C. Cappelleri, Amy Mulvey, Remo Panaccione

Notice bibliographique

RevueThe American Journal of Gastroenterology · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueCOVID-19 and healthcare impacts
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésMedicineUlcerative colitisPandemicMedical prescriptionTelehealthFamily medicineQuality of life (healthcare)AnxietyHealth careCoronavirus disease 2019 (COVID-19)DiseaseTelemedicineInternal medicineNursingPsychiatryInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

Introduction: The COVID-19 pandemic presented challenges around disease management, lifestyle changes, and provision of care for patients (pts) with ulcerative colitis (UC). Methods: This UC Narrative global survey (United States, Canada, Japan, France, and Finland) was conducted by The Harris Poll between 25 August and 13 December 2021, among 584 pts with UC (confirmed by endoscopy) aged ≥ 18 years who had attended a gastroenterologist or internist’s office in the past 3 years, had not had a colectomy, and had ever taken prescription medication for UC. The survey aimed to understand how the COVID-19 pandemic impacted pts with UC and assessed overall disease management, telehealth use, healthcare experience, perceived quality of care, emotional well-being, reliance on alternative support systems, and preferences for virtual/in-person interactions with doctors. Data were from pts who consented and completed the survey; analyzed using descriptive statistics. Results: Overall, 25% of pts experienced more UC flares during the pandemic than in 2019. Most pts taking prescription medication (88%) were very/somewhat satisfied with their current treatment plan but overall, 53% strongly/somewhat agreed that they were hesitant to change their treatment plan during the pandemic. Factors that pts agreed helped to control UC symptoms included having fewer social outings (37%), working from home (29%), and having less busy schedules (28%). Factors that pts agreed made controlling UC symptoms more difficult included having more anxiety/stress (43%), hesitancy to visit a hospital or office (34%), and being unable to get an appointment with their doctor (23%). Virtual appointments were more common during the pandemic than before, and more pts relied on alternative support systems for management of UC (Table). Overall, 79% were very/somewhat satisfied with their ability to access needed healthcare during the pandemic, and pts who used each appointment type were equally very satisfied/satisfied with the overall quality of care at in-person (81%) and virtual (81%) appointments. However, in-person appointments were preferred by 68% of pts when meeting a new doctor, 55% when experiencing a flare, 52% for regular check-ups, and 21% for UC prescription refills. Conclusion: During the pandemic, most pts with UC were satisfied with their current treatment plan and ability to access healthcare, and more pts relied on alternative support for management of UC, but many were negatively impacted by anxiety/stress. Table 1. - Disease management before, during, and after the COVID-19 pandemic: reliance on alternative support systems for management of ulcerative colitis Prior to the pandemic During the pandemic Plan to do after the pandemic Have never done or plan to do Talked openly with their doctor about how their disease impacts their life 54% 54% 44% 17% Set goals with their doctor for managing their disease 48% 46% 40% 25% Communicated with a nurse at their doctor’s office between appointments 45% 40% 34% 32% Used an online patient portal to contact their doctor’s office or see lab results 31% 47% 33% 32% Used social media to connect with other patients or learn about ulcerative colitis 24% 39% 27% 46% Used symptom tracking or disease management apps 23% 31% 29% 48% Relied on information from patient advocacy groups 19% 27% 22% 54% Relied on patient support groups 15% 22% 22% 59% Had virtual appointments with their doctor 13% 55% 32% 31%

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,026

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,040
Tête enseignante GPT0,351
Écart entre enseignants0,311 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission2
Résumé présentoui

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