Andrew Brennan is a categorical pediatrics resident. He graduated from Rutgers Robert Wood Johnson Medical School in 2019 and previously attended Northeastern University where he received his B.S. in Health Science. Primary interests include pediatric cardiology.

Professional Education

  • M.D., Rutgers Robert Wood Johnson Medical School (2019)
  • B.S., Northeastern University, Health Science (2013)

All Publications

  • Anti-NMDAR Encephalitis: A Multidisciplinary Approach to Identification of the Disorder and Management of Psychiatric Symptoms. Psychosomatics Forrester, A., Latorre, S., O'Dea, P. K., Robinson, C., Goldwaser, E. L., Trenton, A., Tobia, A., Aziz, R., Dhawan, S., Brennan, A., Kurukumbi, M., Dong, Y., Benavides, D. R., Offurum, A. I. 2020; 61 (5): 456-466


    The novelty of anti-NMDA receptor encephalitis, for which somatic treatments have only recently been developed, has led to a lack of information on assessment and treatment of its variable behavioral manifestations.In this article, we discuss 4 challenging cases of anti-NMDAR encephalitis, focusing on the importance of a multidisciplinary approach to identification and management of the disorder and the necessity of close collaboration in the acute hospital setting for management of the behavioral symptoms.The cases we discuss highlight some of the medication and nonpharmacologic treatment strategies that may facilitate management of psychiatric symptoms, both while the medical workup is ongoing and after the diagnosis has been confirmed.

    View details for DOI 10.1016/j.psym.2020.04.017

    View details for PubMedID 32507506

  • A Method to Account for Variation in Congenital Heart Surgery Length of Stay. Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Brennan, A., Gauvreau, K., Connor, J., Almodovar, M., DiNardo, J., Banka, P., Nathan, M., Mathieu, D., Kaza, A., Mayer, J. E., Bergersen, L. 2017; 18 (6): 550-560


    We sought to develop a risk-adjustment methodology for length of stay in congenital heart surgery, as none exist.Prospective cohort analysis combined with previously obtained retrospective cohort analysis of a Department of Cardiovascular Surgery clinical database.Patients discharged from Boston Children's Hospital between October 1, 2006, and May 31, 2014, that underwent a congenital heart surgery procedure(s) linked to one of 103 surgical procedure types.Six thousand two hundred nine discharges during the reporting period at Boston Children's Hospital comprised the cohort. Seven Surgical Length Categories were developed to group surgical procedure types. A multivariable model for outcome length of stay was built using a derivation cohort consisting of a 75% random sample, starting with Surgical Length Categories and considering additional a priori factors. Postoperative factors were then added to improve predictive performance. The remaining 25% of the cohort was used to validate the multivariable models. The coefficient of determination (R) was used to estimate the variability in length of stay explained by each factor. The Surgical Length Categories yielded an R of 42%. Model performance increased when the a priori factors preoperative status, noncardiac abnormality, genetic anomaly, preoperative catheterization during episode of care, weight less than 3 kg, and preoperative vasoactive support medication were introduced to the model (R = 60.8%). Model performance further improved when postoperative ventilation greater than 7 days, operating room time, postoperative catheterization during episode of care, postoperative reintubation, number of postoperative vasoactive support medications, postoperative ICU infection, and greater than or equal to one secondary surgical procedure were added (R = 76.7%). The validation cohort yielded an R of 76.5%.We developed a statistically valid procedure-based categorical variable and multivariable model for length of stay of congenital heart surgeries. The Surgical Length Categories and important a priori and postoperative factors may be used to pursue a predictive tool for length of stay to inform scheduling and bed management practices.

    View details for DOI 10.1097/PCC.0000000000001168

    View details for PubMedID 28437365

  • A method to account for variation in congenital heart surgery charges. The Annals of thoracic surgery Bergersen, L., Brennan, A., Gauvreau, K., Connor, J., Almodovar, M., DiNardo, J., David, S., Triedman, J., Banka, P., Emani, S., Mayer, J. E. 2015; 99 (3): 939-46


    In response to societal pressure to reduce expenditures and increase quality, we sought to develop a methodology to predict hospital charges related to congenital heart surgery.Patients undergoing congenital heart surgery at Boston Children's Hospital in fiscal years 2007 to 2009 comprised the derivation cohort. Clinical data, including Current Procedural Terminology coding of the primary surgical intervention, were collected prospectively and linked to total hospital charges for an episode of care. Surgical charge categories were developed to group surgical procedure types using empiric data and expert consensus. A multivariable model was built using surgical charge categories and additional patient and procedural characteristics to predict the outcome, total hospital charges. A contemporary cohort for fiscal years 2010 to 2012 was used to validate surgical charge categories and the multivariable model.In the derivation cohort, 2,105 cases met inclusion criteria. One hundred three surgical procedure types were categorized into seven surgical charge categories, yielding a grouper variable with an R(2) explanatory value of 47.3%. Explanatory value increased with consideration of patient age, admission status, and preoperative ventilator dependence (R(2) = 59.4%), as well as weight category, noncardiac abnormality, and genetic syndrome other than trisomy 21 (R(2) = 61.5%). Additional variability in charge was explained when extracorporeal membrane oxygenation utilization and greater than one operating room visit during the episode of care were added (R(2) = 74.3%). The contemporary cohort yielded an R(2) explanatory value of 67.7%.The combination of clinical data with resource utilization information resulted in a statistically valid predictive model for total hospital charges in congenital heart surgery.

    View details for DOI 10.1016/j.athoracsur.2014.10.066

    View details for PubMedID 25620593

  • Development of a charge adjustment model for cardiac catheterization. Pediatric cardiology Brennan, A., Gauvreau, K., Connor, J., O'Connell, C., David, S., Almodovar, M., DiNardo, J., Banka, P., Mayer, J. E., Marshall, A. C., Bergersen, L. 2015; 36 (2): 264-73


    A methodology that would allow for comparison of charges across institutions has not been developed for catheterization in congenital heart disease. A single institution catheterization database with prospectively collected case characteristics was linked to hospital charges related and limited to an episode of care in the catheterization laboratory for fiscal years 2008-2010. Catheterization charge categories (CCC) were developed to group types of catheterization procedures using a combination of empiric data and expert consensus. A multivariable model with outcome charges was created using CCC and additional patient and procedural characteristics. In 3 fiscal years, 3,839 cases were available for analysis. Forty catheterization procedure types were categorized into 7 CCC yielding a grouper variable with an R (2) explanatory value of 72.6%. In the final CCC, the largest proportion of cases was in CCC 2 (34%), which included diagnostic cases without intervention. Biopsy cases were isolated in CCC 1 (12%), and percutaneous pulmonary valve placement alone made up CCC 7 (2%). The final model included CCC, number of interventions, and cardiac diagnosis (R (2) = 74.2%). Additionally, current financial metrics such as APR-DRG severity of illness and case mix index demonstrated a lack of correlation with CCC. We have developed a catheterization procedure type financial grouper that accounts for the diverse case population encountered in catheterization for congenital heart disease. CCC and our multivariable model could be used to understand financial characteristics of a population at a single point in time, longitudinally, and to compare populations.

    View details for DOI 10.1007/s00246-014-0994-3

    View details for PubMedID 25113520

    View details for PubMedCentralID PMC4303716