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Enregistrement W4415426725 · doi:10.1093/ndt/gfaf116.0366

#720 SMART stone MDT and patient care recommendations: the nephrologist's role in optimizing the adult high-risk kidney stone patient pathway

2025· article· en· W4415426725 sur OpenAlexaboutno aff
Pietro Manuel Ferraro, Esteban Emiliani, Thomas Knoll, Giorgia Mandrile, Gill Rumsby, Bhaskar Somani

Notice bibliographique

RevueNephrology Dialysis Transplantation · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueKidney Stones and Urolithiasis Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésReferralKidney stone diseaseKidney stonesKidney diseaseMultidisciplinary teamPatient referralIntervention (counseling)Patient careMultidisciplinary approach

Résumé

récupéré en direct d'OpenAlex

Abstract Background and Aims Kidney stone formers are at risk of loss of kidney function over time and have substantial morbidity as well as reduced quality of life (QoL) [1,2]. There is a need for earlier diagnosis, alongside metabolic investigation, to determine suspicion of secondary stone disease to enable earlier intervention and prevent progressive kidney damage [2]. Currently, there is a lack of best practice recommendations for forming a multidisciplinary team (MDT) to aid patient management of high-risk adult recurrent kidney stone formers. We propose a ‘SMART’ Stone MDT that aims to provide guidance on the role of an MDT, including Nephrologists, in the early identification, referral and assessment of adult high-risk kidney stone formers to advance patient care. Method Recommendations were developed by the expert Steering Committee (SC, 1 Nephrologist, 3 Urologists and 2 Biochemists/Geneticists) from the UK, Spain, Germany and Italy. These recommendations were voted on by invited specialists to determine their level of agreement, from ‘strongly agree’ to ‘strongly disagree’, via an online survey. With an agreement threshold set at 70%, the SC reviewed the survey results, additional comments and any areas of disagreement, before finalising the recommendations. Results A total of 44 recommendations were developed by the SC, designed to support the structure of an ideal MDT including team composition, patient identification and referral, planning and coordination, patient assessment, decision-making, communication, onward referral and care integration. Thirteen core recommendations were chosen as being the highest priority for the activities of an MDT. Of the 48 additional invited specialists, 29 voted on the core recommendations (5 Nephrologists, 22 Urologists and 2 Biochemists/Geneticists) from 19 countries across Europe, Canada, East Asia, South/Southeast Asia, and the Middle East. All 13 core recommendations reached the 70% agreement threshold.The remaining 31 recommendations were voted on by those specialists who opted-in to partake in an extended questionnaire (n = 15/21; 3 Nephrologists, 10 Urologists and 2 Biochemists/Geneticists). All 31 extended recommendations reached the 70% agreement threshold. 93% (n = 27/29) of responders agreed or strongly agreed that an MDT is required to improve the patient journey and provide the best outcomes for patients with complex stones. 100% (n = 29/29) of responders agreed or strongly agreed that the Nephrologist should be included in the MDT as a core team member. The main recommended roles and responsibilities of the Nephrologist from the perspective of an ideal MDT reached an agreement level of 80% (n = 12/15, extended questionnaire). Roles and responsibilities include but are not limited to, leading cases relating to patients on a medical pathway, metabolic assessment and interpretation of laboratory tests to establish a diagnosis and/or suspicion of secondary stone disease, medical management and follow-up and kidney function monitoring, and management of reduced kidney function. While the recommendations focus on the ideal situation, location-specific nuances, including healthcare setting, infrastructure and resource availability, should be taken into consideration. Conclusion An ideal MDT process can achieve comprehensive, high-quality, and coordinated patient care, which is especially useful for patients with complex stone diseases. The role of the Nephrologist is important in the formation of an ideal MDT, to establish a correct diagnosis and/or suspicion of secondary stone disease, as well as medical management and follow-up to name a few. A high level of agreement was reached on core and extended recommendations relating to the implementation of an ideal MDT in identifying and managing high-risk stone formers.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,045
score de la tête « metaresearch » (Gemma)0,133
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,045
Score d'incertitude au seuil0,237

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0450,133
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,002
Communication savante0,0040,003
Science ouverte0,0030,005
Intégrité de la recherche0,0050,005
Charge utile insuffisante (le modèle a refusé de juger)0,0120,006

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.

Tête enseignante Opus0,006
Tête enseignante GPT0,238
Écart entre enseignants0,232 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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