Remote multidisciplinary diagnostic discussion and spirometry for ILD patients in rural Virginia
Notice bibliographique
Résumé
INTRODUCTION: Patients with interstitial lung disease (ILD) in rural areas face significant barriers to care and management of their disease. This study assessed the feasibility of remote ILD care using virtual multidisciplinary discussions (MDD) for accurate diagnosis and home-based spirometry for ILD management in rural Virginia. METHODS: A prospective feasibility study was conducted involving patients with suspected ILD living in rural Virginia. Participants were enrolled through their community pulmonary provider for discussion in the remote Virginia Commonwealth University (VCU) MDD. Following MDD recommendations were provided by the group and distributed back to their community physicians. These recommendations included additional diagnostic work-up as well as suggestions in adjustment in management. Additionally, subjects were also screened for home spirometry testing. The subjects were trained on the NuvoAir home spirometry system and followed for 6 months Results were then compared to in clinic spirometry at 3 and 6 months. RESULTS: Remote MDD discussions led to a change in diagnosis of 65% of subjects had a consensus diagnosis following MDD, including 47% of subjects with a change in preMDD diagnosis. For the 35% of subjects with determined “Unclassifiable ILD” referring physicians were provided additional diagnostic recommendations. Home spirometry was found to have excellent agreement with FVC measurement as compared to in clinic spirometry. Additionally, patient experience with home testing was strongly positive. CONCLUSION: The multimodal model of remote MDD and spirometric monitoring with home devices was determined to be acceptable and feasible for rural Virginian patients and their community pulmonary physicians. The benefit of this combination suggests an increase in diagnostic accuracy while providing support for rural providers on additional diagnostic testing and management for these patients as well as decreasing the patient burden of continued monitoring of these progressive diseases. However, additional exploration into the reasons for low referrals needs to be explored before this program could be further implemented.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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 ».