Clinical Focus

  • Pediatrics

Academic Appointments

Professional Education

  • Board Certification: American Board of Pediatrics, Pediatrics (2023)
  • Residency: Stanford University Pediatric Residency at Lucile Packard Children's Hospital (2023) CA
  • Medical Education: University of Texas at Austin Registrar (2020) TX


  • Thomas E. Milner, Austin McElroy, Aydin Zahedivash, Nitesh Katta. "United States Patent 11,779,220 Multi-Channel Orthogonal Convolutional Neural Networks", Research Development Foundation, Oct 10, 2023
  • Livia Schiavinato Eberlin, Thomas Milner, Jialing Zhang, John Lin, John Rector, Nitesh Katta, Aydin Zahedivash. "United States Patent 11,756,778 Collection Probe and Methods for the use Thereof", The University of Texas System Board of Regents, Sep 12, 2023

All Publications

  • Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study. JMIR medical informatics Yoo, R. M., Viggiano, B. T., Pundi, K. N., Fries, J. A., Zahedivash, A., Podchiyska, T., Din, N., Shah, N. H. 2024; 12: e51171


    Background: With the capability to render prediagnoses, consumer wearables have the potential to affect subsequent diagnoses and the level of care in the health care delivery setting. Despite this, postmarket surveillance of consumer wearables has been hindered by the lack of codified terms in electronic health records (EHRs) to capture wearable use.Objective: We sought to develop a weak supervision-based approach to demonstrate the feasibility and efficacy of EHR-based postmarket surveillance on consumer wearables that render atrial fibrillation (AF) prediagnoses.Methods: We applied data programming, where labeling heuristics are expressed as code-based labeling functions, to detect incidents of AF prediagnoses. A labeler model was then derived from the predictions of the labeling functions using the Snorkel framework. The labeler model was applied to clinical notes to probabilistically label them, and the labeled notes were then used as a training set to fine-tune a classifier called Clinical-Longformer. The resulting classifier identified patients with an AF prediagnosis. A retrospective cohort study was conducted, where the baseline characteristics and subsequent care patterns of patients identified by the classifier were compared against those who did not receive a prediagnosis.Results: The labeler model derived from the labeling functions showed high accuracy (0.92; F1-score=0.77) on the training set. The classifier trained on the probabilistically labeled notes accurately identified patients with an AF prediagnosis (0.95; F1-score=0.83). The cohort study conducted using the constructed system carried enough statistical power to verify the key findings of the Apple Heart Study, which enrolled a much larger number of participants, where patients who received a prediagnosis tended to be older, male, and White with higher CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes, stroke, vascular disease, age 65-74 years, sex category) scores (P<.001). We also made a novel discovery that patients with a prediagnosis were more likely to use anticoagulants (525/1037, 50.63% vs 5936/16,560, 35.85%) and have an eventual AF diagnosis (305/1037, 29.41% vs 262/16,560, 1.58%). At the index diagnosis, the existence of a prediagnosis did not distinguish patients based on clinical characteristics, but did correlate with anticoagulant prescription (P=.004 for apixaban and P=.01 for rivaroxaban).Conclusions: Our work establishes the feasibility and efficacy of an EHR-based surveillance system for consumer wearables that render AF prediagnoses. Further work is necessary to generalize these findings for patient populations at other sites.

    View details for DOI 10.2196/51171

    View details for PubMedID 38596848

  • Utility of smart watches for identifying arrhythmias in children. Communications medicine Zahedivash, A., Chubb, H., Giacone, H., Boramanand, N. K., Dubin, A. M., Trela, A., Lencioni, E., Motonaga, K. S., Goodyer, W., Navarre, B., Ravi, V., Schmiedmayer, P., Bikia, V., Aalami, O., Ling, X. B., Perez, M., Ceresnak, S. R. 2023; 3 (1): 167


    Arrhythmia symptoms are frequent complaints in children and often require a pediatric cardiology evaluation. Data regarding the clinical utility of wearable technologies are limited in children. We hypothesize that an Apple Watch can capture arrhythmias in children.We present an analysis of patients ≤18 years-of-age who had signs of an arrhythmia documented by an Apple Watch. We include patients evaluated at our center over a 4-year-period and highlight those receiving a formal arrhythmia diagnosis. We evaluate the role of the Apple Watch in arrhythmia diagnosis, the results of other ambulatory cardiac monitoring studies, and findings of any EP studies.We identify 145 electronic-medical-record identifications of Apple Watch, and find arrhythmias confirmed in 41 patients (28%) [mean age 13.8 ± 3.2 years]. The arrythmias include: 36 SVT (88%), 3 VT (7%), 1 heart block (2.5%) and wide 1 complex tachycardia (2.5%). We show that invasive EP study confirmed diagnosis in 34 of the 36 patients (94%) with SVT (2 non-inducible). We find that the Apple Watch helped prompt a workup resulting in a new arrhythmia diagnosis for 29 patients (71%). We note traditional ambulatory cardiac monitors were worn by 35 patients (85%), which did not detect arrhythmias in 10 patients (29%). In 73 patients who used an Apple Watch for recreational or self-directed heart rate monitoring, 18 (25%) sought care due to device findings without any arrhythmias identified.We demonstrate that the Apple Watch can record arrhythmia events in children, including events not identified on traditionally used ambulatory monitors.

    View details for DOI 10.1038/s43856-023-00392-9

    View details for PubMedID 38092993

    View details for PubMedCentralID 4937287

  • Beyond mortality: early childhood development and COVID's impact. Pediatric research Zahedivash, A., Padrez, R., Chamberlain, L. J. 2023

    View details for DOI 10.1038/s41390-023-02843-4

    View details for PubMedID 37833528

  • UTILITY OF THE APPLE WATCH (R) FOR IDENTIFYING ARRHYTHMIAS IN CHILDREN Zahedivash, A., Chubb, H., Giacone, H., Boramanand, N., Dubin, A., Trela, A., Lencioni, E., Motonaga, K., Goodyer, W., Ceresnak, S. R. ELSEVIER SCIENCE INC. 2023: 1563
  • Implantable Cardioverter Defibrillators in Infants and Toddlers: Indications, Placement, Programming, and Outcomes. Circulation. Arrhythmia and electrophysiology Zahedivash, A., Hanisch, D., Dubin, A. M., Trela, A., Chubb, H., Motonaga, K., Goodyer, W., Maeda, K., Reinhartz, O., Ma, M., Martin, E., Ceresnak, S. 2022: CIRCEP121010557


    Limited data exist regarding implantable cardioverter defibrillator (ICD) usage in infants and toddlers. This study evaluates ICD placement indications, procedural techniques, programming strategies, and outcomes of ICDs in infants and toddlers.This is a single-center retrospective review of all patients ≤3 years old who received an ICD from 2009 to 2021.Fifteen patients received an ICD at an age of 1.2 years (interquartile range [IQR], 0.1-2.4; 12 [80%] women; weight, 8.2 kg [IQR, 4.2-12.6]) and were followed for a median of 4.28 years (IQR, 1.40-5.53) or 64.2 patient-years. ICDs were placed for secondary prevention in 12 patients (80%). Diagnoses included 8 long-QT syndromes (53%), 4 idiopathic ventricular tachycardias/ventricular fibrillations (VFs; 27%), 1 recurrent ventricular tachycardia with cardiomyopathy (7%), 1 VF with left ventricular noncompaction (7%), and 1 catecholaminergic polymorphic ventricular tachycardia (7%). All implants were epicardial, with a coil in the pericardial space. Intraoperative defibrillation safety testing was attempted in 11 patients (73%), with VF induced in 8 (53%). Successful restoration of sinus rhythm was achieved in all tested patients with a median of 9 (IQR, 7.3-11.3) J or 0.90 (IQR, 0.68-1.04) J/kg. Complications consisted of 1 postoperative chylothorax and 3 episodes of feeding intolerance. VF detection was programmed to 250 (IQR, 240-250) ms with first shock delivering 10 (IQR, 5-15) J or 1.1 (IQR, 0.8-1.4) J/kg. Three patients (20%) received appropriate shocks for ventricular tachycardia/VF. No patient received an inappropriate shock. There were 2 (13%) ventricular lead fractures (at 2.6 and 4.2 years post-implant), 1 (7%) pocket-site infection, and 2 (13%) generator exchanges. All patients were alive, and 1 patient (7%) received a heart transplant.ICDs can be safely and effectively placed for sudden death prevention in infants and toddlers with good midterm outcomes.

    View details for DOI 10.1161/CIRCEP.121.010557

    View details for PubMedID 35089800

  • IMPLANTABLE CARDIOVERTER-DEFIBRILLATORS IN INFANTS AND TODDLERS: INDICATIONS, PLACEMENT, PROGRAMMING AND OUTCOMES Zahedivash, A., Hanisch, D., Dubin, A. M., Trela, A. V., Chubb, H., Motonaga, K., Goodyer, W., Maeda, K., Reinhartz, O., Ceresnak, S. ELSEVIER SCIENCE INC. 2021: 470
  • Automated Coronary Plaque Characterization With Intravascular Optical Coherence Tomography and Smart-Algorithm Approach JACC-CARDIOVASCULAR IMAGING Baruah, V., Zahedivash, A., Hoyt, T., McElroy, A., Vela, D., Buja, L., Cabe, A., Oglesby, M., Estrada, A., Antonik, P., Milner, T. E., Feldman, M. D. 2020; 13 (8): 1848-1850

    View details for DOI 10.1016/j.jcmg.2020.02.022

    View details for Web of Science ID 000580915500027

    View details for PubMedID 32305483

  • The bridge ventilator consortium - bringing trainees to the frontlines of innovation MEDICAL EDUCATION ONLINE Hakimi, A. A., Zahedivash, A., Hong, E. M., Chen, L. Y., Heidari, A. E. 2020; 25 (1): 1826887

    View details for DOI 10.1080/10872981.2020.1826887

    View details for Web of Science ID 000573931100001

    View details for PubMedID 32996865

    View details for PubMedCentralID PMC7586724

  • Development of an open-access, web-based interactive tool to learn autonomic nervous system physiology and pharmacology ADVANCES IN PHYSIOLOGY EDUCATION Zahedivash, A., Lee, M. W. 2018; 42 (1): 64-67

    View details for DOI 10.1152/advan.00125.2017

    View details for Web of Science ID 000423465600010

    View details for PubMedID 29341808

  • Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system SCIENCE TRANSLATIONAL MEDICINE Zhang, J., Rector, J., Lin, J. Q., Young, J. H., Sans, M., Katta, N., Giese, N., Yu, W., Nagi, C., Suliburk, J., Liu, J., Bensussan, A., DeHoog, R. J., Garza, K. Y., Ludolph, B., Sorace, A. G., Syed, A., Zahedivash, A., Milner, T. E., Eberlin, L. S. 2017; 9 (406)


    Conventional methods for histopathologic tissue diagnosis are labor- and time-intensive and can delay decision-making during diagnostic and therapeutic procedures. We report the development of an automated and biocompatible handheld mass spectrometry device for rapid and nondestructive diagnosis of human cancer tissues. The device, named MasSpec Pen, enables controlled and automated delivery of a discrete water droplet to a tissue surface for efficient extraction of biomolecules. We used the MasSpec Pen for ex vivo molecular analysis of 20 human cancer thin tissue sections and 253 human patient tissue samples including normal and cancerous tissues from breast, lung, thyroid, and ovary. The mass spectra obtained presented rich molecular profiles characterized by a variety of potential cancer biomarkers identified as metabolites, lipids, and proteins. Statistical classifiers built from the histologically validated molecular database allowed cancer prediction with high sensitivity (96.4%), specificity (96.2%), and overall accuracy (96.3%), as well as prediction of benign and malignant thyroid tumors and different histologic subtypes of lung cancer. Notably, our classifier allowed accurate diagnosis of cancer in marginal tumor regions presenting mixed histologic composition. Last, we demonstrate that the MasSpec Pen is suited for in vivo cancer diagnosis during surgery performed in tumor-bearing mouse models, without causing any observable tissue harm or stress to the animal. Our results provide evidence that the MasSpec Pen could potentially be used as a clinical and intraoperative technology for ex vivo and in vivo cancer diagnosis.

    View details for DOI 10.1126/scitranslmed.aan3968

    View details for Web of Science ID 000409369900003

    View details for PubMedID 28878011

    View details for PubMedCentralID PMC5830136

  • Histology-Validated Neural Networks Enable Accurate Plaque Tissue and Thin-Capped Fibroatheroma Characterization Through Intravascular Optical Coherence Tomography Baruah, V. L., Zahedivash, A., Hoyt, T. B., Vela, D., Buja, L., Milner, T. E., Feldman, M. D. LIPPINCOTT WILLIAMS & WILKINS. 2016
  • Differences in forward angular light scattering distributions between M1 and M2 macrophages JOURNAL OF BIOMEDICAL OPTICS Halaney, D. L., Zahedivash, A., Phipps, J. E., Wang, T., Dwelle, J., Le Saux, C., Asmis, R., Milner, T. E., Feldman, M. D. 2015; 20 (11): 115002


    The ability to distinguish macrophage subtypes noninvasively could have diagnostic potential in cancer, atherosclerosis, and diabetes, where polarized M1 and M2 macrophages play critical and often opposing roles. Current methods to distinguish macrophage subtypes rely on tissue biopsy. Optical imaging techniques based on light scattering are of interest as they can be translated into biopsy-free strategies. Because mitochondria are relatively strong subcellular light scattering centers, and M2 macrophages are known to have enhanced mitochondrial biogenesis compared to M1, we hypothesized that M1 and M2 macrophages may have different angular light scattering profiles. To test this, we developed an in vitro angle-resolved forward light scattering measurement system. We found that M1 and M2 macrophage monolayers scatter relatively unequal amounts of light in the forward direction between 1.6 deg and 3.2 deg with M2 forward scattering significantly more light than M1 at increasing angles. The ratio of forward scattering can be used to identify the polarization state of macrophage populations in culture.

    View details for DOI 10.1117/1.JBO.20.11.115002

    View details for Web of Science ID 000366017500026

    View details for PubMedID 26538329

    View details for PubMedCentralID PMC4881287