ARTIFICIAL INTELLIGENCE APPROACH IN OPTIMISATION OF HEPARIN DOSING IN POST COVID-19 PATIENTS DURING HEMODIALYSIS

ARTIFICIAL INTELLIGENCE APPROACH IN OPTIMISATION OF HEPARIN DOSING IN POST COVID-19 PATIENTS DURING HEMODIALYSIS

Registration ID: IJNRD_219822

Published ID: IJNRD2404765

DOI: Click Here to Get

Dr SIVAKUMAR V , Dr SATHISH KUMAR A , Dr MONICA F , Dr PRIYADHARSHINI K

Hemodialysis,Machine learning,Hypercoagulation,Heparin

ABSTRACT: INTRODUCTION: Hemodialysis patients have a higher risk of thrombo-embolic events and hence they require anti-coagulation therapy throughout the dialysis procedure. Post COVID patients undergoing hemodialysis experience an increased risk for dialysis circuit clotting compared to others. This study aims to optimize heparin dosing for post COVID-19 pateints during hemodialysis using machine learning (ML). METHODS: A prospective observational study, conducted at Dialysis unit, PSG hospitals, Coimbatore for a duration of 6 months. 136 samples were collected and the data included age, gender, BMI, DM-2, hypothyroidism, ionized calcium, serum creatinine, serum albumin, clotting history, COVID-19 infected and vaccine doses which was fed into Machine Learning to optimize heparin dosing. We used decision tree algorithm for ML model. RESULTS: In this study, a prototype model of Machine Learning was developed and optimization of heparin dose during hypercoagulation was done. A sample data was validated in the model which gave a promising performance with a sensitivity score of 0.86. Other factors such as serum albumin, ionized calcium, anemia, body mass index and hypothyroidism were found to influence the clotting risk in hemodialysis patients. CONCLUSION: Heparin dose optimization was carried out using the prototype model. A variation of 24.39% is observed for heparin dose given based on the protocol and the model predicted dose. This model has to be fine tuned to improve sensitivity score and model accuracy, to analyze further other influencing factors for clotting and to predict heparin dosing for more complex data.

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"ARTIFICIAL INTELLIGENCE APPROACH IN OPTIMISATION OF HEPARIN DOSING IN POST COVID-19 PATIENTS DURING HEMODIALYSIS", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.h623-h629, April-2024, Available :https://ijnrd.org/papers/IJNRD2404765.pdf

Volume 9 Issue 4, April-2024

Pages : h623-h629

Paper Reg. ID: IJNRD_219822

Published Paper Id: IJNRD2404765

Downloads: 000121151

Research Area: Pharmacy

Country: kallakurichi, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404765.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404765

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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