Gastric dysfunction in patients with chronic nausea and vomiting syndromes defined by a novel non-invasive gastric mapping device
Notice bibliographique
Résumé
Abstract Importance Chronic nausea and vomiting syndromes (NVS) are prevalent and debilitating disorders. Putative mechanisms include gastric neuromuscular disease and dysregulation of brain-gut interaction, but clinical tests for objectively defining gastric motor function are lacking. Objective A novel medical device enabling non-invasive body surface gastric mapping (BSGM) was developed and applied to evaluate NVS pathophysiology. Design A case-control study where BSGM was performed in NVS patients and matched controls using Gastric Alimetry (Alimetry, New Zealand), comprising a conformable high-resolution array (8×8 electrodes; 20 mm inter-electrode spacing), wearable Reader, and validated symptom logging App. Continuous measurement encompassed a fasting baseline (30 min), 482 kCal meal (10 min), and 4-hr post-prandial recording. Setting Multicenter study in Auckland, New Zealand and Calgary, Canada. Participants 43 NVS patients (gastroparesis and Rome IV chronic NVS) and 43 matched controls. Main outcomes and measures Symptom severity and quality of life were measured using Patient Assessment of Upper Gastrointestinal Disorders-Symptom Severity Index (PAGI-SYM), Gastroparesis Cardinal Symptom Index (GCSI), and Patient Assessment of Upper Gastrointestinal Disorders-Quality of Life (PAGI-QOL) instruments. Health psychology metrics included the State Trait Anxiety Inventory Short Form (STAI-SF) and Patient Health Questionnaire-2 (PHQ-2) questionnaires. Spectral analyses including frequency, amplitude, and fed-fasting power ratio. Spatial biomarker analyses included spatial frequency stability and average spatial covariance. Results Meal responses were impaired in NVS, with reduced amplitudes compared to controls (median 23.3 vs 38.0 µV, p<0.001), impaired fed-fasting power-ratios (1.1 vs 1.6, p=0.02), and disorganized slow-waves (spatial frequency stability 13.6 vs 49.5; p<0.001). However, two distinct NVS subgroups were evident with indistinguishable symptoms (all p>0.05). A majority (62%) had normal BSGM studies (all biomarkers non-significant vs controls) with increased psychological comorbidities (43.5% vs 7.7%; p=0.03) and anxiety scores (median 16.5 vs 13.0; p=0.035). A smaller subgroup (31%) had markedly abnormal BSGM, with test biomarkers correlating with symptoms (nausea, pain, excessive fullness, early satiety, bloating; all r>0.35, p<0.05). Conclusions and Relevance NVS patients share overlapping symptoms, but comprise distinct underlying phenotypes as revealed by a novel BSGM device. These phenotypes correlate with symptoms, which should inform clinical management and allocations into therapeutic trials. Key Points Question How does body surface gastric mapping, a novel non-invasive medical device for evaluating gastric motility, aid assessment of patients with chronic nausea and vomiting. Findings Two subgroups were revealed in chronic nausea and vomiting syndromes, which could not be differentiated by symptoms alone. Where body surface gastric mapping was normal, symptoms correlated with psychological comorbidities, and where body surface gastric mapping was abnormal, symptoms correlated with gastric electrophysiology metrics. Meaning Distinct phenotypes revealed by body surface gastric mapping correlate with symptoms, which should inform targeted clinical management and allocations into therapeutic trials.
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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 | 0,001 |
| 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 | 0,001 |
| 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 ».