Risk-based referral model to nephrologist-specialist care in Stockholm.

IF 5.6
Aurora Caldinelli, Anne-Laure Faucon, Arvid Sjölander, Roosa Lankinen, Antoine Creon, Edouard L Fu, Marie Evans, Juan Jesus Carrero
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引用次数: 0

Abstract

Background and hypothesis: For most patients, clinical management of early stages of CKD is performed in primary care settings. KDIGO 2024 guidelines recommended using a 5-year kidney failure risk equation (KFRE) of 3-5% to guide nephrologist referrals. Here, we aimed to assess the impact of adopting a risk-based referral model compared to traditional referral criteria.

Methods: Observational retrospective study of adults with eGFR < 60 mL/min/1.73m² (Lund-Malmö equation) from the SCREAM project, a healthcare utilization cohort from Stockholm, Sweden. We evaluated the performance of the Non-North American 4-variable KFRE and recalibrated it to better fit our setting. KFRE thresholds were compared with traditional models: the clinical Swedish criteria and the classic KDIGO 2012 criteria, both of which are mainly based on age, eGFR and albuminuria thresholds. Sensitivity, specificity, positive, negative predictive values, reclassification matrices, net reclassification improvement, and decision curve analyses were used to assess performance and clinical utility.

Results: The study included 887 388 observations from 192 964 individuals. At inclusion, 49% were men, median age was 76 years and median eGFR 54 mL/min/1.73m2. During follow-up, 2 624(1.4%) progressed to KRT. KFRE demonstrated a good prediction performance, further improved after recalibration. Both Non-North American and SCREAM recalibrated KFRE provided higher sensitivity and specificity than Swedish and classical KDIGO criteria. KFRE-based referral models yielded better net reclassification improvement, demonstrating superior performance in decision curve analyses. Higher thresholds (15% for the Non-North American KFRE, 9% for the SCREAM recalibrated KFRE) than the KDIGO recommended ones provided the best combined sensitivity and specificity. Compared with traditional referral models, implementation of a risk-based referral would decrease the number of unnecessary referrals by 23% and 25%, respectively.

Conclusion: In a large north-European healthcare system, transitioning to a risk-based referral model would result in an important reduction of unnecessary referrals while maintaining a low rate of missed cases, optimizing resource utilization.

风险为基础的转诊模式肾内科专家护理在斯德哥尔摩。
背景和假设:对于大多数患者,早期CKD的临床管理是在初级保健机构进行的。KDIGO 2024指南建议使用3-5%的5年肾衰竭风险方程(KFRE)来指导肾病专家转诊。在这里,我们旨在评估采用基于风险的转诊模型与传统转诊标准的影响。方法:对成人eGFR患者进行观察性回顾性研究结果:该研究包括来自192964人的887388例观察结果。纳入时,49%为男性,中位年龄为76岁,中位eGFR为54 mL/min/1.73m2。随访期间,2 624例(1.4%)进展为KRT。KFRE显示出良好的预测性能,重新校准后进一步提高。与瑞典和经典的KDIGO标准相比,非北美和SCREAM重新校准的KFRE具有更高的灵敏度和特异性。基于kfr的推荐模型产生了更好的净重分类改进,在决策曲线分析中表现出优越的性能。与KDIGO推荐的阈值相比,更高的阈值(非北美KFRE为15%,SCREAM重新校准的KFRE为9%)提供了最佳的综合灵敏度和特异性。与传统转诊模式相比,实施基于风险的转诊将使不必要的转诊数量分别减少23%和25%。结论:在北欧大型医疗保健系统中,过渡到基于风险的转诊模式将大大减少不必要的转诊,同时保持低漏诊率,优化资源利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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