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    CKD Prediction in HIV+ Patients

    Determines probability of HIV patients developing CKD in the next 5 years, if they take tenofivir or not.
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    When to Use
    Pearls/Pitfalls
    Why Use
    • Patients who are expected to be low-risk for the development of CKD, to confirm this
    • Patients who are expected to be high-risk for the development of CKD, to make sure alternatives to tenofovir are used
    • It is well-known that tenofovir is associated with a higher risk of developing chronic kidney disease (CKD).
    • This risk is substantially higher in patients with traditional CKD risk factors.
    • This risk calculator helps determine risk of developing CKD, and may help practitioners choose patients who would be good or poor candidates for tenofovir depending on their overall CKD risks.
    • This score was developed in a US VA patient population, and only males were included in this study.
    • This population was also overall “healthier” than the general VA population in other cardiovascular and renal disease states, with relatively low rates of hyperglycemia or hypertension.

    Low risk patients may be good candidates for tenofovir, and high risk patients should avoid tenofovir when determining appropriate anti-retroviral therapies.

    Past or present tenofivir use can change the predicted outcome of the patient

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    Next Steps
    Evidence
    Creator Insights

    Critical Actions

    • Patients with low scores may be good candidates for tenofovir.
    • Patients with high scores should avoid tenofovir in their treatment regimen, given their significantly higher risk of developing CKD within 5 years.

    Formula

    Addition of selected points.

    Facts & Figures

    Category Point Total 5 - year event rate (95 % CI)
    TDF users 0 1.4 (0.9, 2.2)
    1 2.2 (1.4, 3.3)
    2 3.6 (2.9, 4.4)
    3 5.3 (4.4, 6.5)
    4 7.6 (6.6, 8.8)
    5 8.6 (7.4, 10.1)
    6 10.9 (9.4, 12.6)
    7 13.1 (11.1, 15.4)
    8 19.4 (16.3, 23.2)
    ≥9 21.4 (18.1, 25.2)
    TDF non-users 0 0.5 (0.3, 0.9)
    1 0.3 (0.1, 0.8)
    2 1.5 (1.2, 2.0)
    3 1.9 (1.4, 2.4)
    4 2.7 (2.2, 3.3)
    5 4.1 (3.4, 4.9)
    6 5.1 (4.3, 6.1)
    7 8.7 (7.4, 10.2)
    8 11.0 (9.2, 13.2)
    ≥9 16.4 (14.1, 19.2)
    Dr. Rebecca Scherzer

    About the Creator

    Rebecca Scherzer, PhD, is an academic administrator at UCSF School of Medicine. She is a research statistician for the Fat Redistribution and Metabolic Change in HIV Infection study and for UCSF's Kidney Health Research Collaborative. Dr. Scherzer research and publications span topics including body composition, metabolic changes, kidney disease and HIV infection-related cardiovascular risk.

    To view Dr. Rebecca Scherzer's publications, visit PubMed