Clinical Outcomes and Healthcare Utilization in Patients Receiving Maintenance Dialysis After the Onset of the COVID-19 Pandemic in Ontario, Canada
Notice bibliographique
Résumé
Background: The impact of the COVID-19 pandemic on clinical outcomes and healthcare utilization in patients receiving maintenance dialysis is unclear. Objective: To compare the rates of clinical outcomes and healthcare utilization in patients receiving maintenance dialysis (in-center and home modalities) before and during the COVID-19 pandemic. Design: Population-based, repeated cross-sectional study. Setting: Linked administrative healthcare databases from Ontario, Canada. Patients: Adults receiving maintenance dialysis from March 15, 2017, to March 14, 2020 (pre-COVID-19 pandemic period) and from March 15, 2020, to March 14, 2023 (COVID-19 pandemic period). Measurements: Our primary outcome was all-cause mortality. Our secondary outcomes included non-COVID-19-related mortality, all-cause hospitalizations (excluding elective surgeries), emergency room visits, intensive care unit admissions, and hospital admissions with mechanical ventilation. We also examined cardiovascular-related hospitalizations, kidney-related outcomes, and ambulatory visits. Methods: We used Poisson generalized estimating equations to model pre-COVID outcome trends and used these to predict post-COVID outcomes and to estimate the relative change (i.e., the ratio of the observed to the expected rate). Results: In 31 900 individuals receiving maintenance dialysis during the study period, the crude incidence rate (per 1000 person-years) of all-cause mortality was 165.0 in the pre-COVID-19 period, compared to 173.2 during the first year of the pandemic and 171.7 during the first 36 months of the pandemic. After adjustment, there was a statistically significant increase in all-cause mortality in 14 out of the 36 months of the COVID-19 period compared to the pre-COVID-19 period, with 494 recorded COVID-19-related deaths. However, when examining the overall all-cause mortality across the months, the adjusted relative rate (aRR) comparing the observed to expected all-cause mortality rate was not statistically significant in the first year of the pandemic (1.08, 95% CI: 1.00, 1.16) and the first 36 months of the pandemic (1.08, 95% CI: 0.99, 1.18) compared to the pre-pandemic period. The crude incidence rate of non-COVID-19-related mortality was 165.0 in the pre-COVID-19 period, compared to 163.3 during the first year of the pandemic and 157.7 during the first 36 months. After adjustment, there was no substantial change in the rate of non-COVID-19-related deaths in the first year of the pandemic (aRR 1.01, 95% CI: 0.94, 1.09), but there was a substantial decrease in all-cause hospitalization, with an aRR of 0.92 (95% CI: 0.88, 0.97), and a substantial decrease in emergency room visits and intensive care unit admissions; findings were consistent 36 months into the pandemic. Limitations: External generalizability to other jurisdictions may be limited, with each region experiencing different COVID-19 rates and implementing different mitigation strategies. Conclusions: In the maintenance dialysis population, all-cause mortality was significantly higher during several months of the pandemic; however, the overall rate of all-cause mortality was not substantially higher than expected in the first 36 months of the COVID-19 pandemic. There was no substantial increase in non-COVID-19-related mortality despite a substantial decrease in acute healthcare utilization. Ongoing monitoring of the dialysis population will offer further insights into the long-term effects of the pandemic.
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 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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».