Lower Risk of Home Hemodialysis Attrition in Patients Using Nx2me Connected Health Technology
Notice bibliographique
Résumé
Background: Home hemodialysis is a growing treatment modality for end-stage renal disease. Home hemodialysis facilitates increased treatment frequency, which may reduce intradialytic symptoms, decrease risk of cardiovascular morbidity, and improve quality of life. However, patients may elect to discontinue home hemodialysis for medical or psychosocial reasons and to convert to in-center hemodialysis. Tools that improve communication and coordination between patients and providers and reduce therapy burden on patients may reduce risk of attrition. Nx2me Connected Health (NxStage Medical, Inc, Lawrence, MA) is a telehealth platform that collects NxStage System One cycler data and patient factors (eg, blood pressure, weight), transmits data to providers after each dialysis session, and enables providers to review data in the Nx2me Clinician Portal regularly; in contrast, usual care involves monthly review of patient-completed session records on paper. Objective: To assess whether use of Nx2me Connected Health was associated with reduced risk of home hemodialysis attrition in patients on the System One cycler. Methods: We collected data from home hemodialysis patients that initiated use of Nx2me Connected Health. At first use of Nx2me, we identified cumulative time with the System One cycler and treatment setting (in-center training or home). From NxStage records, we identified 3 matched controls for each Nx2me user. Specifically, for a Nx2me user who had accumulated t days with the System One cycler at first use of Nx2me, we identified potential controls who had also accumulated at least t days with the System One cycler (without use of Nx2me) and retained those in the same treatment setting as the Nx2me user at t days after first use of the System One cycler. We randomly selected 3 matched controls from this subset. We followed Nx2me users and matched controls until home hemodialysis attrition and classified the cause of attrition as non-controllable (due to transplant or death) or controllable (due to health issues, therapy burden, or other reasons). We used Fine-Gray competing-risks regression to model incidence of attrition, with stratification by matched cluster and adjustment for race, vascular access modality, and number of dialysis sessions per week. Results: We identified 401 Nx2me users (cumulative follow-up years, 356) and 1203 matched controls (1111). Crude attrition rates in Nx2me users and matched controls were 39.6 and 50.6 stops per 100 patient-years, respectively. For Nx2me users versus matched controls, adjusted hazard ratios of attrition due to controllable causes were 0.64 (95% CI 0.49-0.83) overall and 0.52 (95% CI 0.36-0.76) in the subset of patients with <3 months on the System One cycler at first use of Nx2me (and their respective matched controls). In contrast, adjusted hazard ratios of attrition due to non-controllable causes were 1.09 (95% CI 0.79-1.51) overall and 1.01 (95% CI 0.55-1.84) in the aforementioned subset. Conclusions: Use of Nx2me Connected Health reduced risk of home hemodialysis attrition due to health issues, therapy burden, and other reasons that ordinarily lead to conversion to in-center hemodialysis. The magnitude of risk reduction was larger in patients who initiated use of Nx2me shortly after first treatment with the NxStage System One cycler.
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 | 0,000 |
| 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 | 0,000 | 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 ».