Nishimura, Rick A.

Background Optimal management of patients with severe mitral stenosis ( MS ) and low transmitral gradient is incompletely understood. Methods and Results We examined 101 consecutive patients with severe rheumatic MS (mitral valve area ≤1.5 cm 2 ) who underwent balloon valvuloplasty. Low gradient was defined as mean transmitral gradient <10 mm Hg and low flow as stroke volume index ≤35 mL/m 2 by echocardiography. Symptoms and mortality data were collected. Systolic, diastolic, and arterial function were characterized by measuring left ventricular (LV) end‐systolic elastance, LV stiffness constant (β), diastolic capacitance (predicted LV end‐diastolic volume at a common LV filling pressure of 30 mm Hg), and effective arterial elastance. Low gradient (<10 mm Hg) was present in 55 patients, including low flow/low gradient in 11 and normal flow/low gradient in 44 patients, and high gradient was present in 46 patients. Participants with low‐flow/low‐gradient (LG) MS were older with higher rates of atrial fibrillation (64%) and subvalvular thickening, higher afterload, and decreased LV compliance with lower ejection fraction (57±10% versus 65±4% versus 63±6%, P =0.002) but similar end‐systolic elastance compared with patients with normal‐flow/ LG and high‐gradient MS . The normal‐flow/ LG group had larger mitral valve area and lower left atrial pressure by catheterization, as well as favorable long‐term outcomes compared with the low‐flow/ LG and high‐gradient MS group. A total of 40% of patients with LG MS had no symptomatic benefit from valvuloplasty compared with 18% of patients with high‐gradient MS ( P =0.02). Conclusions Presence of low gradient in patients with severe MS was associated with lesser symptomatic benefit from valvuloplasty. In the subset with low stroke volume index, this may be related to independent ventricular‐vascular uncoupling, decreased LV compliance, and high prevalence of atrial fibrillation in addition to intrinsic MS .

Background Automated individualized risk prediction tools linked to electronic health records ( EHR s) are not available for management of patients with peripheral arterial disease. The goal of this study was to create a prognostic tool for patients with peripheral arterial disease using data elements automatically extracted from an EHR to enable real‐time and individualized risk prediction at the point of care. Methods and Results A previously validated phenotyping algorithm was deployed to an EHR linked to the Rochester Epidemiology Project to identify peripheral arterial disease cases from Olmsted County, MN, for the years 1998 to 2011. The study cohort was composed of 1676 patients: 593 patients died over 5‐year follow‐up. The c‐statistic for survival in the overall data set was 0.76 (95% confidence interval [CI], 0.74–0.78), and the c‐statistic across 10 cross‐validation data sets was 0.75 (95% CI, 0.73–0.77). Stratification of cases demonstrated increasing mortality risk by subgroup (low: hazard ratio, 0.35 [95% CI, 0.21–0.58]; intermediate‐high: hazard ratio, 2.98 [95% CI, 2.37–3.74]; high: hazard ratio, 8.44 [95% CI, 6.66–10.70], all P <0.0001 versus the reference subgroup). An equation for risk calculation was derived from Cox model parameters and β estimates. Big data infrastructure enabled deployment of the real‐time risk calculator to the point of care via the EHR . Conclusions This study demonstrates that electronic tools can be deployed to EHR s to create automated real‐time risk calculators to predict survival of patients with peripheral arterial disease. Moreover, the prognostic model developed may be translated to patient care as an automated and individualized real‐time risk calculator deployed at the point of care.