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David Kao, MD

Please provide a summary of your research and the project overview.


Heart failure (HF) is a major cause of morbidity, mortality, and resource utilization throughout the world, and its importance is likely to increase with the aging population. Patients are heterogenous with respect to etiology, prognosis, and response to therapy, and our ability to identify high-risk patients versus those likely to improve with medical therapy remains limited. Approximately 50% of all HF patients have a preserved ejection fraction (HFpEF).  Most HFpEF patients are women, and there are currently no known effective therapies for HFpEF. In comparison, HF with reduced ejection fraction (HFrEF), which predominately affects men, has many established therapies. Characterization of HF subgroups may provide insight into mechanisms of disease, gender differences, and facilitate personalized prediction of outcomes and treatment response. I use emerging bioinformatics technologies including large-scale database systems and cluster-based analysis applied to clinical and molecular data to identify and characterize subgroups of HF. The central hypothesis of my work is that systematic characterization of HF patients will improve HF outcomes by supporting precision HF management. I propose using these results to develop personalized treatment plans for HF patients to maximize likelihood of clinical improvement and minimize unnecessary interventions.


What are the implications for your research? Why is your work important both short term and long term?


I plan to use the results of my research to develop personalized treatment plans for HF patients to maximize likelihood of clinical improvement and minimize unnecessary interventions. In the short term, the results of my research may provide valuable insight into mechanisms of HF and identify potential strategies for personalizing HF management based on patient characteristics. My long-term goal is to develop technologies that combine electronic health data with molecular profiling data to identify important HF subgroups and demonstrate efficacy of personalized HF care. The product of my research will be a patient-centered, reusable infrastructure to study gender differences in HF, test established predictive models, and discover novel HF subgroups that can be shared with providers via an electronic medical record through real-time decision support.


Please take the above two questions and answer them as if you are explaining them to a sixth grader.


HF is common health problem that affects many people, particularly the elderly, and frequently results in death within a few years of diagnosis.  Although some HF patients can be treated with medicines, about half of patients have a type of HF (HFpEF) that has no proven treatments.  Most of the patients with this kind of HF are women. I believe that we may be able to use computer-based methods similar to the ones used by Amazon, iTunes, and Pandora to identify groups of patients that may respond better to certain medicines. To do this, I combine electronic data stored by patients’ doctors with genetic testing in order find special patient groups.  I then look to see if any of these groups of HF patients do better than others with specific medicines.  If I am successful, I hope that this information can be built into the computers at doctors’ offices so that doctors can use it to customize treatment of their HF patients.


What is the proposed timeframe for your project? Where would you like to see your findings published?


This work has been ongoing for approximately 3 years, resulting in 3 publications on this specific project (PLOS One, the Journal of the American College of Cardiology-Heart Failure, American Journal of Cardiology) in addition to several others in the areas of drug safety. The manuscript describing the initial HFpEF analysis is currently in revision with the European Journal of Heart Failure, and we are about to submit a manuscript to Circulation describing the Effect of β-Blocker On Remodeling and Gene Expression Trial (BORG), which combines clinical characteristics and molecular profiling to elucidate mechanisms of response to β-blockers in HF.  Dr. Lindenfeld and I are about to submit a paper of efficacy of telemonitoring to the Journal of Cardiac Failure, and we have another manuscript on association of timing of hospital admission with outcomes in HF that we hope to submit within the next 6 months, possibly to JACC-HF or the European Journal of HF.  Ultimately, I would also like to write a methods paper detailing the analytic pipeline for publication in either the Journal of Bioinformatics or the Journal of the American Medical Informatics Association.

Who is your mentor?


My primary mentor is JoAnn Lindenfeld, and my secondary UC mentor is Mike Bristow. 

If you are able to, please share any recent progress or findings to date.


We have identified subtypes of both HFpEF and HFrEF that have quite different prognosis (survival time) and response to therapies.  This includes one group of HFpEF patients (patients with diabetes mellitus, hypertension, high cholesterol, and kidney problems) who may respond to the drug irbesartan.  We now plan to look at additional variables that may be useful in identifying patient subgroups and validate the results in independent clinical trials, most notably the CHARM trial.


We also published finding expanding the number of possible risk factors for peripartum cardiomyopathy (PPCM) by looking at a very large number of hospital records.  We were also able to demonstrate the risk of adverse neonatal events was also higher when PPCM was present.  In the course of this work, we proposed a risk score for estimating the likelihood that a patient will develop PPCM.


A similar analysis looking at many hospitalized heart failure patients over 14 years in the state of New York also revealed strong associations between survival in HF hospitalization and season (winter is worst), day of the week (Friday/Saturday is worst), and time of the day (afternoon/evening is worst).  This work has only been presented in abstract form, but got a substantial amount of press at the 2013 European Society of Cardiology HF Congress (Lisbon, Portugal).


In the BORG analysis, we have greatly expanded the number of myocardial genes whose expression appears to be associated with improvement in heart function.  We have also identified a number of possible predictors of response to β-blockers, including some which perform markedly better in women than in men.  This study will produce a series of papers, the first of which is nearly complete.


In collaboration with Bosch Healthcare, we analyzed results from a demonstration study of a telemonitoring device called the Health Buddy in Medicare patients.  The primary finding was that availability of the Health Buddy was associated with a significantly improved survival rate, which was primarily seen in those who actually used the device.  This manuscript is essentially complete and will be submitted after approval by the Centers for Medicare and Medicaid Services.


With the support of UCH, we have constructed a real-time decision support system.  The pilot application is calculation of a complex risk score for hospital readmission in patients hospitalized for HF.  We plan to expand this functionality to permit use of other risk scores and patient subgroup definitions that are identified in the course of my other work.


What are some of your recent publications?


Kao DP, Kreso E, Dale RA, Gonarow GC, Krantz MJ. Characteristics and outcomes among heart failure patients with anemia and renal insufficiency with and without blood transfusions (Public Discharge Data from California 2000-2006). Am J Card. 2011; 107:69-73. PMCID: PMC3835688.

Kao DP, Wagner BD, Robertson AD, Bristow MR, Lowes BD. A personalized BEST: Characterization of latent clinical classes of nonischemic heart failure that predict outcomes and response to bucindolol. PLOS One. 2012; 7:e48184. PMCID: PMC3492337.
Kao DP, Davis G, Aleong R, O’Connor CM, Fiuzat M, Carson PE, Anand IS, Plehn JF, Gottlieb SS, Silver MA, Lindenfeld JA, Miller AB, White M, Murphy GA, Sauer W, Bristow MR. Effect of bucindolol on heart failure outcomes and heart rate response in patients with reduced ejection fraction heart failure and atrial fibrillation. Eur J Heart Fail. 2013; 15324-33. PMCID: PMC3576901.
Kao DP, Bucher Bartleson B, Khatri V, Dart R, Mehler PS, Katz D, Krantz MJ. Trends in reporting of methadone-associated cardiac arrhythmia, 1997-2011: an analysis of registry data. Ann Int Med. 2013; 158:735-740. PMCID: PMC3793842.
ao DP, Hsich E, Lindenfeld J. Characteristics, adverse events, and racial differences among delivering mothers with peripartum cardiomyopathy. JCHF 2013; 1:409-416. PMCID: PMC3806506.


Please list some of the recent conferences where you have presented your research or attended. (limited to those while funded by the CWHR, starting 2012)


National/International Conference Oral Presentations

Epperson LE, Kao DP, Minobe W, Gilbert EM, Lowes BD, Bristow MR. Gene Expression Changes Associated with β-blocker reverse remodeling in the failing human heart constitute a β1-adrenergic receptor gene regulatory network. Scientific Sessions of American Heart Association, Nov 16-20, 2013.

Krantz MJ, Traut C, Kao DP. Opioid Agonists & Cardiac Safety: Pharmacovigilance & ECG Implementation. American Association for the Treatment of Opioid Dependence National Conference, Nov. 11, 2013.


Hinterberg M, Kao DP, Karimpour-Fard A, Sucharov K, Hunter LE, Port JD, Bristow MR. Myocardial expression of the microRNA dre-mir-133a-5p is associated with improvement in left ventricular ejection fraction in patients with idiopathic dilated cardiomyopathy treated with β-blockers. Annual Scientific Session & Expo of Am Coll Cardiol, March 10, 2013.

ao DP, Varosy P, Aleong R. Impact of payor status on presentation, therapies, and outcomes in 31,614 patients hospitalized with Wolff-Parkinson-White Syndrome. American Heart Association Annual Scientific Sessions, Nov 5, 2012. Circulation. 2012:126:A14800.

Kao DP, Epperson LE, Karimpour-Fard, Gilbert EM, Lowes BD, Hunter LE, Bristow MR. Transcription of Select Homeobox Genes Increases in Patients with Heart Failure-Reduced Ejection Fraction Who Have Improvements in Left Ventricular Ejection Fraction on β-blocker Therapy. American Heart Association Annual Scientific Sessions, Nov 5, 2012. Circulation. 2012:126:A14777.



National/International Conference Posters



Kao DP, Varosy P, Nguyen DT, Tzou W, Katz D, Shculler J, Sung R, Steckman D, Sauer WH, Aleong R. Predictors of adverse events in 24,890 patients undergoing lead extraction. Scientific Sessions, American Heart Association, Nov 16-20,2013.



Kao DP, Varosy P, Nguyen DT, Tzou W, Katz D, Shculler J, Sung R, Steckman D, Sauer WH, Aleong R. Temporal trends in mortality and adverse events in 24,890 patients undergoing lead extraction over a decade. Scientific Sessions, American Heart Association, Nov. 16-20, 2013.

Kao DP, Epperson LE, Meyer L, Ferguson D, Zolty R, Weller JD, Gilbert EM, Lowes BD, Bristow MR. Serial gene expression changes associated with reverse remodeling in dilated cardiomyopathies: results of the effects of beta-blockers on remodeling and gene expression in the failing human heart (BORG) Trial. Scientific Sessions, American Heart Association, Nov 16-20, 2013.

Kao DP, Epperson LE, Karimpour-Fard A, Gilbert EM, Lowes BD, Hunter LE, Bristow MR. Expression levels of select mRNA triads are predictive of response to beta-blocker therapy in patients with reduced ejection fraction heart failure. European Society of Cardiology Heart Failure Congress 2013.



Kao DP, McIlvennan CK, Page RL, Lindenfeld J. Impact of day, month, and hour of admission on inpatient outcomes in 949,907 hospitalizations for congestive heart failure. European Society of Cardiology Heart Failure Congress 2013.



When and how did you become interested in research?


I have been involved in biomedical research almost continuously since 1996.  I worked in 2 primary labs during my undergraduate education and received a Bachelor of Science in Biomedical Engineering.  Since then, I have participated in basic science/molecular genetics, behavioral science, clinical intervention, clinical imaging, phenotyping and now applied informatics research.   I have always enjoyed the process of discovery, but it was not until I had the opportunity to complete a post-doctoral fellowship in Biomedical Informatics Research at Stanford University that I found a research strategy that really suited by experience and ability.  I find the diversity of studies that the informatics skill set allows me to conduct to be extremely powerful, and through my work, I hope to contribute to unlocking the potential of electronic clinical data to improve health.


Who has/have been the most influential mentor(s) in your career? Why



Roy Ziegelstein, MD (Johns Hopkins) – He is thoughtful and honest, and was the first mentor I had where I was sure that his primary interest was my success.  I aspire to be like Roy when I am in the mentor role



Norman Rizk, MD (Stanford Hospital) – He is transparent, honest, and supportive.  He gave excellent advice, even when it was hard to hear.  Again, I was sure that his priority was my well-being and su




JoAnn Lindenfeld, MD (University of Colorado) – She is fearless, and selfless in her advocacy.  She is also excited by new and challenging ideas, and she is willing pursue them, even in the face of skepticism. She is also one of the best clinical cardiologists I’ve worked with.

Michael Bristow, MD PhD (University of Colorado) – He is tenacious and determined in the pursuit of new knowledge.  From him, I have learned to do the next best experiment, even if it won’t change the world and look out for the surprising findings because they are often the true discoveries.


What other grants/funding opportunities are you currently pursuing? 


NHLBI R21 – Secondary Dataset Analyses in Heart, Lung, and Blood Disease and Sleep Disorders, PI: Kao (submitted, Nov. 2013)


NHLBI K08 – Mentored Clinical Scientist Development Award, PI: Kao (due February, 2014)


Butcher Seed Grant – Co-investigator: Carsten Görg, (due January, 2014)


Fogarty R25 – Global Health Research and Research Training eCapacity Initiative; PI: James Hakim, University of Zimbabwe (due May, 2014)


 Kao poster award.JPG

Colleen McIlvennan  and David Kao, 2014 American College of Cardiology national conference, best Cardiovascular Team Poster!