Patient Risk Interpretation of Symptoms Model (PRISM): How Patients Assess Cardiac Risk.
Kreatsoulas C, Taheri C, Pattathil N, Panchal P, Kakkar T.
J Gen Intern Med. 2021 08. 36(8):2205-2211. PMID: 34100233
Links
Bibliography
Definition of successful outcomes after surgery for each type of strabismus: a Delphi study.
Serafino M, Granet DB, Kushner BJ, Dagi LR, Kekunnaya R, Nucci P, Kreatsoulas C.
J AAPOS. 2021 02. 25(1):3.e1-3.e5. PMID: 33607273
Young Adults and Adverse Childhood Events: A Potent Measure of Cardiovascular Risk.
Kreatsoulas C, Fleegler EW, Kubzansky LD, McGorrian CM, Subramanian SV.
Am J Med. 2019 05. 132(5):605-613. PMID: 30639555
A review of menopausal hormone therapy: recalibrating the balance of benefit and risk.
Rajan S, Kreatsoulas C.
Pol Arch Intern Med. 2019 04 30. 129(4):276-280. PMID: 30608056
Machine learning in social epidemiology: Learning from experience.
Kreatsoulas C, Subramanian SV.
SSM Popul Health. 2018 Apr. 4:347-349. PMID: 29854919
Avoiding S3 Valve Over-Sizing by Deployment Balloon Over-Filling: Impact on Rates of Permanent Pacemaker and Other Procedural Complications During TAVR.
Sheth T, Natarajan MK, Kreatsoulas C, Whitlock R, Parry D, Chu V, Smith A, Velianou JL.
J Invasive Cardiol. 2018 01. 30(1):23-27. PMID: 29289947
Design of the Magnetic Resonance Imaging Evaluation of Mineralocorticoid Receptor Antagonism in Diabetic Atherosclerosis (MAGMA) Trial.
Rajagopalan S, Alaiti MA, Broadwater K, Goud A, Gaztanaga J, Connelly K, Fares A, Shirazian S, Kreatsoulas C, Farkouh M, Dobre M, Fink JC, Weir MR.
Clin Cardiol. 2017 Sep. 40(9):633-640. PMID: 28555959
Food Insecurity Screening in Pediatric Primary Care: Can Offering Referrals Help Identify Families in Need?
Bottino CJ, Rhodes ET, Kreatsoulas C, Cox JE, Fleegler EW.
Acad Pediatr. 2017 07. 17(5):497-503. PMID: 28302365
Interpreting angina: symptoms along a gender continuum.
Kreatsoulas C, Crea-Arsenio M, Shannon HS, Velianou JL, Giacomini M.
Open Heart. 2016. 3(1):e000376. PMID: 27158523
Commentary: The salience of socioeconomic status in assessing cardiovascular disease and risk in low- and middle-income countries.
Kreatsoulas C, Corsi DJ, Subramanian SV.
Int J Epidemiol. 2015 Oct. 44(5):1636-47. PMID: 26493737
News
Can artificial intelligence help predict the likelihood of a heart attack?
It may be someday be possible to use artificial intelligence (AI) algorithms to gauge a person’s risk of cardiovascular disease (CVD). That’s according to research being done by Catherine Kreatsoulas, research fellow in the Department of Social and…
Women dismiss heart disease warning signs more than men
Women are more likely than men to dismiss chest pain that signals heart problems and to delay seeking medical help, even though heart disease is a leading cause of death for both women and men, according to a…
Women generally have same heart disease symptoms as men
Contrary to popular belief, women generally experience the same coronary artery disease (CAD, or cardiovascular disease) symptoms — including chest pain, pressure, and/or tightness — as men, [[Catherine Kreatsoulas]], research fellow in the Department of Social and Behavioral…