ASN Highlights vs KAK

This ASN Highlights 2020, Event App provides you all the information you need about the ASN Highlights 2020 program. You can access • Program Information • Browse, faculty profile & talks summaries • Browse program schedule • Ask a question to the faculty • Post your program feedback • Access faculty slides

Quick risk-calculator for contrast-induced nephropathy based on validated clinical model KAK-CIN Score is a clinical decision-support tool designed to help healthcare professionals estimate the probability of Contrast-Induced Nephropathy (CIN) in patients who will receive intravascular contrast medium. The algorithm is based on the peer-reviewed study by Kulkarni et al (Indian Journal of Nephrology, 2023) which derived and validated a simplified risk score system. Key features: Input four key patient variables: Estimated Glomerular Filtration Rate (eGFR) Contrast volume (mL) Route of contrast administration (arterial vs intravenous) Presence or absence of Diabetes Mellitus Instantly calculates a risk-percentage for CIN and provides a risk category (e.g., low, moderate, high) and provides the CIN Score. Published Journal: https://indianjnephrol.org/?view-pdf=1&embedded=true&article=af81b65b1e790875fb17d4a368ca9457Aplh7GbponE%3D Why use KAK-CIN Score? The original study included 1,300 patients (derivation 1,000 + validation 300) with an observed incidence of CIN of 3.8 %. The model showed high sensitivity (90.4 %) and specificity (98.8 %) in the validation cohort. Unlike many prior CIN risk models that were limited to cardiac catheterisation, this score covers both intra-arterial and intravenous contrast exposure. Important disclaimer This app is for educational and decision-support purposes only. It does not replace clinical judgement, institutional protocols or specialist consultation. Use results in conjunction with the full clinical context. The authors are not responsible for any clinical outcomes resulting from use of this tool. Always follow local guidelines. Privacy & Security No patient-identifiable data is stored beyond your device.