Peritoneal Dialysis Use and Practice Patterns: An International Survey Study
Notice bibliographique
Résumé
Rationale & Objective Approximately 11% of people with kidney failure worldwide are treated with peritoneal dialysis (PD). This study examined PD use and practice patterns across the globe. Study Design A cross-sectional survey. Setting & Participants Stakeholders including clinicians, policy makers, and patient representatives in 182 countries convened by the International Society of Nephrology between July and September 2018. Outcomes PD use, availability, accessibility, affordability, delivery, and reporting of quality outcome measures. Analytical Approach Descriptive statistics. Results Responses were received from 88% (n = 160) of countries and there were 313 participants (257 nephrologists [82%], 22 non-nephrologist physicians [7%], 6 other health professionals [2%], 17 administrators/policy makers/civil servants [5%], and 11 others [4%]). 85% (n = 156) of countries responded to questions about PD. Median PD use was 38.1 per million population. PD was not available in 30 of the 156 (19%) countries responding to PD-related questions, particularly in countries in Africa (20/41) and low-income countries (15/22). In 69% of countries, PD was the initial dialysis modality for ≤10% of patients with newly diagnosed kidney failure. Patients receiving PD were expected to pay 1% to 25% of treatment costs, and higher (>75%) copayments (out-of-pocket expenses incurred by patients) were more common in South Asia and low-income countries. Average exchange volumes were adequate (defined as 3-4 exchanges per day or the equivalent for automated PD) in 72% of countries. PD quality outcome monitoring and reporting were variable. Most countries did not measure patient-reported PD outcomes. Limitations Low responses from policy makers; limited ability to provide more in-depth explanations underpinning outcomes from each country due to lack of granular data; lack of objective data. Conclusions Large inter- and intraregional disparities exist in PD availability, accessibility, affordability, delivery, and reporting of quality outcome measures around the world, with the greatest gaps observed in Africa and South Asia. Approximately 11% of people with kidney failure worldwide are treated with peritoneal dialysis (PD). This study examined PD use and practice patterns across the globe. A cross-sectional survey. Stakeholders including clinicians, policy makers, and patient representatives in 182 countries convened by the International Society of Nephrology between July and September 2018. PD use, availability, accessibility, affordability, delivery, and reporting of quality outcome measures. Descriptive statistics. Responses were received from 88% (n = 160) of countries and there were 313 participants (257 nephrologists [82%], 22 non-nephrologist physicians [7%], 6 other health professionals [2%], 17 administrators/policy makers/civil servants [5%], and 11 others [4%]). 85% (n = 156) of countries responded to questions about PD. Median PD use was 38.1 per million population. PD was not available in 30 of the 156 (19%) countries responding to PD-related questions, particularly in countries in Africa (20/41) and low-income countries (15/22). In 69% of countries, PD was the initial dialysis modality for ≤10% of patients with newly diagnosed kidney failure. Patients receiving PD were expected to pay 1% to 25% of treatment costs, and higher (>75%) copayments (out-of-pocket expenses incurred by patients) were more common in South Asia and low-income countries. Average exchange volumes were adequate (defined as 3-4 exchanges per day or the equivalent for automated PD) in 72% of countries. PD quality outcome monitoring and reporting were variable. Most countries did not measure patient-reported PD outcomes. Low responses from policy makers; limited ability to provide more in-depth explanations underpinning outcomes from each country due to lack of granular data; lack of objective data. Large inter- and intraregional disparities exist in PD availability, accessibility, affordability, delivery, and reporting of quality outcome measures around the world, with the greatest gaps observed in Africa and South Asia.
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 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 ».