Suppr超能文献

一项真实世界的精准医学计划,包括 KidneyIntelX 测试,可有效改变早期糖尿病肾病患者的管理决策和结局。

A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease.

机构信息

Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Renalytix AI, Inc., New York, NY, USA.

出版信息

J Prim Care Community Health. 2024 Jan-Dec;15:21501319231223437. doi: 10.1177/21501319231223437.

Abstract

INTRODUCTION/OBJECTIVE: The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient's risk for a progressive decline in kidney function over 5 years. We report the 1-year pre- and post-test clinical impact on care management, eGFR slope, and A1C along with engagement of population health clinical pharmacists and patient coordinators to promote a program of sustainable kidney, metabolic, and cardiac health.

METHODS

The KidneyIntelX in vitro prognostic test was previously validated for patients with type 2 diabetes and diabetic kidney disease (DKD) to predict kidney function decline within 5 years was introduced into the RWE study (NCT04802395) across the Health System as part of a population health chronic disease management program from [November 2020 to April 2023]. Pre- and post-test patients with a minimum of 12 months of follow-up post KidneyIntelX were assessed across all aspects of the program.

RESULTS

A total of 5348 patients with DKD had a KidneyIntelX assay. The median age was 68 years old, 52% were female, 27% self-identified as Black, and 89% had hypertension. The median baseline eGFR was 62 ml/min/1.73 m, urine albumin-creatinine ratio was 54 mg/g, and A1C was 7.3%. The KidneyIntelX risk level was low in 49%, intermediate in 40%, and high in 11% of cases. New prescriptions for SGLT2i, GLP-1 RA, or referral to a specialist were noted in 19%, 33%, and 43% among low-, intermediate-, and high-risk patients, respectively. The median A1C decreased from 8.2% pre-test to 7.5% post-test in the high-risk group ( < .001). UACR levels in the intermediate-risk patients with albuminuria were reduced by 20%, and in a subgroup treated with new scripts for SGLT2i, UACR levels were lowered by approximately 50%. The median eGFR slope improved from -7.08 ml/min/1.73 m/year to -4.27 ml/min/1.73 m/year in high-risk patients ( = .0003), -2.65 to -1.04 in intermediate risk, and -3.26 ml/min/1.73 m/year to +0.45 ml/min/1.73 m/year in patients with low-risk ( < .001).

CONCLUSIONS

Deployment and risk stratification by KidneyIntelX was associated with an escalation in action taken to optimize cardio-kidney-metabolic health including medications and specialist referrals. Glycemic control and kidney function trajectories improved post-KidneyIntelX testing, with the greatest improvements observed in those scored as high-risk.

摘要

介绍/目的:KidneyIntelX 是一种多重、生物预后、免疫测定,由 3 种血浆生物标志物和临床变量组成,利用机器学习预测患者在 5 年内肾功能进行性下降的风险。我们报告了 1 年的预测试和后测试对护理管理、eGFR 斜率和 A1C 的临床影响,以及参与人口健康临床药剂师和患者协调员,以促进可持续的肾脏、代谢和心脏健康计划。

方法

KidneyIntelX 体外预后试验之前已经在 2 型糖尿病和糖尿病肾病(DKD)患者中进行了验证,以预测 5 年内的肾功能下降,该试验被引入到 RWE 研究(NCT04802395)中,在整个医疗系统中作为人群健康慢性疾病管理计划的一部分,从[2020 年 11 月至 2023 年 4 月]。对至少有 12 个月随访后进行了 KidneyIntelX 检测的预测试和后测试患者进行了全面评估。

结果

共有 5348 例 DKD 患者进行了 KidneyIntelX 检测。中位年龄为 68 岁,52%为女性,27%自我认定为黑人,89%患有高血压。中位基线 eGFR 为 62 ml/min/1.73 m,尿白蛋白-肌酐比值为 54 mg/g,A1C 为 7.3%。KidneyIntelX 风险水平低的占 49%,中风险的占 40%,高风险的占 11%。低、中、高风险患者的新处方 SGLT2i、GLP-1 RA 或转介给专科医生的比例分别为 19%、33%和 43%。高危组的 A1C 从检测前的 8.2%降至检测后的 7.5%(<0.001)。中间风险组的白蛋白尿患者的 UACR 水平降低了 20%,在接受 SGLT2i 新处方治疗的亚组中,UACR 水平降低了约 50%。高危患者的中位 eGFR 斜率从-7.08 ml/min/1.73 m/年改善至-4.27 ml/min/1.73 m/年(=0.0003),中间风险患者从-2.65 降至-1.04,低风险患者从-3.26 ml/min/1.73 m/年改善至+0.45 ml/min/1.73 m/年(<0.001)。

结论

KidneyIntelX 的部署和风险分层与优化心脏-肾脏-代谢健康相关的行动升级有关,包括药物和专家转诊。KidneyIntelX 检测后血糖控制和肾功能轨迹改善,高危患者的改善最为显著。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b66/10773280/d6f264046a21/10.1177_21501319231223437-fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验