The Feasibility of a Transitional Care Unit for Patients Newly Started on In-Center Hemodialysis: A Research Letter
Notice bibliographique
Résumé
Background: Patients with end-stage kidney disease face high mortality and morbidity after dialysis initiation. Transitional care units (TCUs) are typically 4- to 8-week structured multidisciplinary programs targeted toward patients starting hemodialysis during this high-risk time in their care. The goals of such programs are to provide psychosocial support, provide dialysis modality education, and reduce risks of complications. Despite apparent benefits, the TCU model may be challenging to implement, and the effect on patient outcomes is unclear. Objective: To assess a newly created multidisciplinary TCUs' feasibility for patients newly started on hemodialysis. Design: Before-and-after study. Setting: Kingston Health Sciences Centre hemodialysis unit in Ontario, Canada. Patients: We considered all adult patients (age 18+) who initiated in-center maintenance hemodialysis eligible for the TCU program, although patients on infection control precautions and evening shifts were not able to receive TCU care due to staffing limitations. Measurements: We defined feasibility as eligible patients completing the TCU program in a timely fashion without additional need for space, no signal of harm, and without explicit concerns from TCU staff or patients at weekly meetings. Key outcomes at 6 months included mortality, proportion hospitalized, dialysis modality, vascular access, initiation of transplant workup, and code status. Methods: The TCU care consisted of 1:1 nursing and education until predefined clinical stability and dialysis decisions were satisfied. We compared outcomes among the pre-TCU cohort who initiated hemodialysis between June 2017 and May 2018, and TCU patients who initiated dialysis between June 2018 and March 2019. We summarized outcomes descriptively, along with unadjusted odds ratios (ORs) and 95% confidence intervals (CIs). Results: We included 115 pre-TCU patients and 109 post-TCU patients, of whom 49/109 (45%) entered and completed the TCU. The most common reasons for not participating in the TCU included evening hemodialysis shifts (18/60, 30%) or contact precautions (18/60, 30%). The TCU patients completed the program in a median of 35 (25-47) days. We observed no differences in mortality (9% vs 8%; OR = 0.93, 95% CI = 0.28-3.13) or proportion hospitalized (38% vs 39%; OR = 1.02, 95% CI = 0.51-2.03) between the pre-TCU cohort and TCU patients. There was also no difference in use of home dialysis (16% vs 10%; OR = 1.67, 95% CI = 0.64-4.39), non-catheter access (32% vs 25%; OR = 1.44, 95% CI = 0.69-2.98), initiation of transplant workup (14% vs 12%; OR 1.67; 95% CI = 0.64-4.39), and choosing "do not resuscitate" (DNR) orders (22% vs 19%; OR = 1.22, 95% CI = 0.54-2.77). There was no negative patient or staff feedback on the program. Limitations: Small sample size and potential for selection bias given inability to provide TCU care for patients on infection control precautions or evening shifts. Conclusions: The TCU accommodated a large number of patients, who completed the program in a timely fashion. The TCU model was determined to be feasible at our center. There was no difference in outcomes due to the small sample size. Future work at our center is required to expand the number of TCU dialysis chairs to evening shifts and evaluate the TCU model in prospective, controlled studies.
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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 | 0,007 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».