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Articles by J. A House
Total Records ( 2 ) for J. A House
  S. K Mehta , A. D Frutkin , J. B Lindsey , J. A House , J. A Spertus , S. V Rao , F. S Ou , M. T Roe , E. D Peterson , S. P Marso and on Behalf of the National Cardiovascular Data Registry
 

Background— Bleeding in patients undergoing percutaneous coronary intervention (PCI) is associated with increased morbidity, mortality, length of hospitalization, and cost. We identified baseline clinical characteristics associated with bleeding complications after PCI and developed a simplified, clinically useful algorithm to predict patient risk.

Methods and Results— Data were analyzed from 302 152 PCI procedures performed at 440 US centers participating in the National Cardiovascular Data Registry. As defined by the National Cardiovascular Data Registry, bleeding required transfusion, prolonged hospital stay, and/or a drop in hemoglobin >3.0 g/dL from any location, including percutaneous entry site, retroperitoneal, gastrointestinal, genitourinary, and other/unknown location. Bleeding complications occurred in 2.4% of patients. From the best-fitting model consisting of 15 clinical elements associated with post-PCI bleeding in a random 80% training cohort, we developed a parsimonious risk algorithm. Predictors of bleeding included age, gender, previous heart failure, glomerular filtration rate, peripheral vascular disease, no previous PCI, New York Heart Association/Canadian Cardiovascular Society Functional Classification class IV heart failure, ST-elevation myocardial infarction, non–ST-elevation myocardial infarction, and cardiogenic shock. The parsimonious model was validated in the remaining 20% of the population (c-statistic, 0.72) and in clinically relevant subgroups of patients. This simplified model was used to derive a clinical risk algorithm, with larger numbers corresponding with greater risk. In 3 categories, bleeding rates were greater in patients with higher estimates (≤7, 0.7%; 8 to 17, 1.8%; ≥18, 5.1%).

Conclusions— This report identifies baseline clinical factors associated with bleeding and proposes a clinically useful algorithm to estimate bleeding risk. This model is potentially actionable in altering therapeutic decision making and improving outcomes in patients undergoing PCI.

  J. B Lindsey , J. A House , K. F Kennedy and S. P. Marso
 

Background— Coronary plaque classified as thin-cap fibroatheroma (TCFA) is believed to be associated with plaque rupture and coronary heart disease–related events. Although an association between duration of diabetes and increased coronary heart disease risk has been demonstrated, the relationship between TCFA and diabetes duration is unknown.

Methods and Results— Prospective registry of diabetic patients undergoing diagnostic coronary angiography and intravascular ultrasound (IVUS) enrolled in a diabetic gene and biomarker banking registry. Plaque composition in the most diseased 10-mm segment of a single coronary artery was assessed using IVUS virtual histology and was classified by phenotype as IVUS-defined adaptive intimal thickening, pathological intimal thickening, TCFA, fibroatheroma, or fibrocalcific. Patients (n=54) were stratified by duration of diabetes (<10 or ≥10 years). Patients with diabetes ≥10 years were older, less likely to have a history of tobacco use, had higher total cholesterol levels, and were more likely to be treated with insulin compared with patients with diabetes <10 years. Longer duration of diabetes was associated with greater plaque burden in the most diseased 10-mm segment (60.4% [53.4% to 66.8%] versus 50.2% [47.7% to 58.4%], P=0.008). The proportion of IVUS-defined TCFA in the ≥10-year group was greater than the <10-year group (54.4% [11.6% to 77.5%] versus 10.8% [0.0% to 26.1%], P=0.009). This association persisted after adjustment for multiple comparisons, clinical characteristics, and diabetes treatment.

Conclusions— In this cohort, longer duration of diabetes was associated with IVUS-defined TCFA, a plaque phenotype associated with risk of rupture and coronary heart disease events.

Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00428961.

 
 
 
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