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Updated: Aug 17, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Relationship between a risk score for QT interval prolongation and mortality across rural and urban inpatient
Malinda S Tan1, C William Heise2, Tyler Gallo3
1Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, UT, USA.
Objectives:
To evaluate the relationship between a modified Tisdale QTc-risk score (QTc-RS) and inpatient mortality and length of stay in a broad inpatient population with an order for a medication with a known risk of torsades de pointes (TdP).
Background:
Managing the risk of TdP is challenging due to the number of medications with known risk of TdP and the complexity of precipitating factors. A model to predict risk of mortality may be useful to guide treatment decisions.
Methods:
This was a retrospective observational study using inpatient data from 28 healthcare facilities in the western United States. This risk score ranges from zero to 23 with weights applied to each risk factor based on a previous validation study. Logistic regression and a generalized linear model were performed to assess the relationship between QTc-RS and mortality and length of stay.
Results:
Between April and December 2020, a QTc-RS was calculated for 92,383 hospitalized patients. Common risk factors were female (55.0%); age > 67 years (32.1%); and receiving a medication with known risk of TdP (24.5%). A total of 2770 (3%) patients died during their hospitalization. Relative to patients with QTc-RS < 7, the odds ratio for mortality was 4.80 (95%CI:4.42-5.21) for patients with QTc-RS = 7-10 and 11.51 (95%CI:10.23-12.94) for those with QTc-RS ≥ 11. Length of hospital stay increased by 0.7 day for every unit increase in the risk score (p < 0.0001).
Conclusion:
There is a strong relationship between increased mortality as well as longer duration of hospitalization with an increasing QTc-RS.
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