#720 SMART stone MDT and patient care recommendations: the nephrologist's role in optimizing the adult high-risk kidney stone patient pathway
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".