Patient Benefits And Cost Savings Predicted For Mineralocorticoid-Receptor Antagonist Treatment Of Early And Advanced Diabetic Kidney Disease

Blankenburg, Michael; Pelkey, Ryan; Folse, H.

doi:10.1016/j.jval.2015.09.1458

Cited by 2 publications

(1 citation statement)

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“…Despite their proven efficacy, these medications are often underutilized due to elevated costs or clinical inertia [39][40][41] . An accurate prediction of CKD progression to late stages not only refines risk stratification, but also provides evidences for clinicians to initiate high-risk patients on these medications earlier, given the anticipated greater benefit 42 . Such predictions may motivate patients at a high risk of CKD progression to persist with these new medications, despite potential regimen complexities, side effects, and higher co-pays 43 .…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Zhu,

Bi,

Saunders

et al. 2023

Sci Rep

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Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Zhu,

Bi,

Saunders

et al. 2023

Sci Rep

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Pharmacotherapy considerations with finerenone in the treatment of chronic kidney disease associated with type 2 diabetes

Ashjian,

Clarke,

Pogue

2023

American Journal of Health-System Pharmacy

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Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose This review provides an overview of the management of chronic kidney disease (CKD) associated with type 2 diabetes (T2D), how the novel treatment class of nonsteroidal mineralocorticoid receptor antagonists (MRAs) fits within the treatment landscape, and how pharmacists can contribute to the multidisciplinary care of patients with CKD associated with T2D. Summary Optimizing pharmacotherapy for patients with CKD associated with T2D is critical to prevent or slow progression to end-stage kidney disease and reduce the incidence of cardiovascular events. However, many patients with CKD receive suboptimal treatment, in part because of the high complexity of care required, a lack of disease recognition among providers and patients, and a failure to utilize new kidney-protective therapies. Finerenone is the first nonsteroidal, selective MRA to be approved by the US Food and Drug Administration and the European Medicines Agency for the treatment of adult patients with CKD associated with T2D. Clinical trials have demonstrated that finerenone significantly reduces the risk of cardiorenal disease progression vs placebo and has a reduced risk of hyperkalemia compared to traditional steroidal MRAs. Initiation of finerenone should follow evaluation of baseline estimated glomerular filtration rate and serum potassium levels. Consideration of potential drug-drug interactions, follow-up monitoring of potassium levels, and coordination of changes in pharmacotherapy across the patient care team are also important. Conclusion Finerenone is a valuable addition to the treatment landscape for CKD associated with T2D. Through their expertise in medication management, transitions of care, and patient education, clinical pharmacists are well positioned to ensure patients receive safe and effective treatment.

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Patient Benefits And Cost Savings Predicted For Mineralocorticoid-Receptor Antagonist Treatment Of Early And Advanced Diabetic Kidney Disease

Cited by 2 publications

References 0 publications

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Pharmacotherapy considerations with finerenone in the treatment of chronic kidney disease associated with type 2 diabetes

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