• James E Tisdale, Heather A Jaynes, Joanna R Kingery, Noha A Mourad, Tate N Trujillo, Brian R Overholser, and Richard J Kovacs.
• Department of Pharmacy Practice, College of Pharmacy, Purdue University, Indianapolis, IN 46202, USA. jtisdale@purdue.edu
• Circ Cardiovasc Qual. 2013 Jul 1;6(4):479-87.

BackgroundIdentifying hospitalized patients at risk for QT interval prolongation could lead to interventions to reduce the risk of torsades de pointes. Our objective was to develop and validate a risk score for QT prolongation in hospitalized patients.Methods And ResultsIn this study, in a single tertiary care institution, consecutive patients (n=900) admitted to cardiac care units comprised the risk score development group. The score was then applied to 300 additional patients in a validation group. Corrected QT (QTc) interval prolongation (defined as QTc>500 ms or an increase of >60 ms from baseline) occurred in 274 (30.4%) and 90 (30.0%) patients in the development group and validation group, respectively. Independent predictors of QTc prolongation included the following: female (odds ratio, 1.5; 95% confidence interval, 1.1-2.0), diagnosis of myocardial infarction (2.4 [1.6-3.9]), septic shock (2.7 [1.5-4.8]), left ventricular dysfunction (2.7 [1.6-5.0]), administration of a QT-prolonging drug (2.8 [2.0-4.0]), ≥2 QT-prolonging drugs (2.6 [1.9-5.6]), or loop diuretic (1.4 [1.0-2.0]), age >68 years (1.3 [1.0-1.9]), serum K⁺ <3.5 mEq/L (2.1 [1.5-2.9]), and admitting QTc >450 ms (2.3; confidence interval [1.6-3.2]). Risk scores were developed by assigning points based on log odds ratios. Low-, moderate-, and high-risk ranges of 0 to 6, 7 to 10, and 11 to 21 points, respectively, best predicted QTc prolongation (C statistic=0.823). A high-risk score ≥11 was associated with sensitivity=0.74, specificity=0.77, positive predictive value=0.79, and negative predictive value=0.76. In the validation group, the incidences of QTc prolongation were 15% (low risk); 37% (moderate risk); and 73% (high risk).ConclusionsA risk score using easily obtainable clinical variables predicts patients at highest risk for QTc interval prolongation and may be useful in guiding monitoring and treatment decisions.

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