Education & Certifications

  • BA, Johns Hopkins University

All Publications

  • Challenges With Relying on Body Fat and Weight Values for Obesity-Reply. JAMA internal medicine Narayan, A., Agarwal, A. A., Stanford, F. C. 2024

    View details for DOI 10.1001/jamainternmed.2024.2376

    View details for PubMedID 38884971

  • Body Composition in Anti-Obesity Medication Trials-Beyond Scales. JAMA internal medicine Agarwal, A. A., Narayan, A., Stanford, F. C. 2024

    View details for DOI 10.1001/jamainternmed.2023.7733

    View details for PubMedID 38372971

  • Opioid usage in lumbar disc herniation patients with nonsurgical, early, and late surgical treatments. World neurosurgery Zhou, Z., Jin, M. C., Jensen, M. R., Barros Guinle, M. I., Ren, A., Agarwal, A. A., Leaston, J., Ratliff, J. K. 2023


    Assess opioid usage in surgical and non-surgical patients with lumbar disc herniation receiving different treatment approaches and timing.Individuals with newly diagnosed lumbar intervertebral disc without myelopathy were queried from Optum Clinformatics DataMart. Patients were categorized into 3 cohorts: nonsurgical, early surgery, and late surgery. Early surgery cohort patients had surgery within 30-days post-diagnosis; late surgery cohort patients had surgery after 30 days but before 1-year post-diagnosis. The index date was defined as the diagnosis date for nonsurgical patients, and the initial surgery date for surgical patients. The primary outcome was the average daily opioid morphine milligram equivalent (MME) prescribed. Additional outcomes included the percentage of opioid-using patients and cumulative opioid burden.A total of 573,082 patients met inclusion criteria: 533,226 patients received nonsurgical treatments, 22,312 patients received early surgery, and 17,544 patients received late surgery. Both surgical cohorts experienced a "post-surgical hump" of opioid usage, which then sharply declined and gradually plateaued, with daily opioid MME consistently lower in the early as opposed to late surgery cohort. The early surgery cohort also consistently had a lower prevalence of opioid-using patients than the late surgery cohort. Patients receiving nonsurgical demonstrated the highest one-year post-index cumulative opioid burden, and the early surgery cohort consistently had lower cumulative opioid MME than the late surgery cohort.Early surgery in lumbar disc herniation patients is associated with lower long-term average daily MME, incidence of opioid use, and one-year cumulative MME burden compared to nonsurgical and late surgery treatment approaches.

    View details for DOI 10.1016/j.wneu.2023.02.029

    View details for PubMedID 36775237

  • Predictive Value of Clinical Complete Response after Chemoradiation for Rectal Cancer Liu, C., Boncompagni, A. A., Perrone, K., Agarwal, A., Hur, D. G., Lopez, I., Sheth, V., Morris, A. M. LIPPINCOTT WILLIAMS & WILKINS. 2022: S51-S52
  • Using Ethereum Smart Contracts to Store and Share COVID-19 Patient Data CUREUS JOURNAL OF MEDICAL SCIENCE Batchu, S., Patel, K., Henry, O. S., Mohamed, A., Agarwal, A. A., Hundal, H., Joshi, A., Thoota, S., Patel, U. K. 2022; 14 (1): e21378


    Introduction The emergence and rapid spread of the coronavirus disease 2019 (COVID-19) pandemic have revealed the limitations in current healthcare systems to handle patient records securely and transparently, and novel protocols are required to address these shortcomings. An attractive option is the use of Ethereum smart contracts to secure the storage of medical records and concomitant data logs. Ethereum is an open-source platform that can be used to construct smart contracts, which are collections of code that allow transactions under certain parameters and are self-executable. Methods The present study developed a proof-of-concept smart contract that stores COVID-19 patient data such as the patient identifier (ID), variant, chest CT grade, and significant comorbidities. A sample, fictitious patient data for the purpose of testing was configured to a private network. A smart contract was created in the Ethereum state and tested by measuring the time to insert and query patient data. Results Testing with a private, Proof of Authority (PoA) network required only 191 milliseconds and 890 MB of memory per insertion to insert 50 records while inserting 350 records required 674 milliseconds and similar memory per insertion, as memory per insertion was nearly constant with the increasing number of records inserted. Retrieving required 912 MB for a query involving all three fields and no wildcards in a 350-record database. Only 883 MB was needed to procure a similar observation from a 50-record database. Conclusion This study exemplifies the use of smart contracts for efficient retrieval/insertion of COVID-19 patient data and provides a case use of secure and efficient data logging for sensitive COVID-19 data.

    View details for DOI 10.7759/cureus.21378

    View details for Web of Science ID 000750679500027

    View details for PubMedID 35198290

    View details for PubMedCentralID PMC8853077