Literature DB >> 23541006

Institution-wide QT alert system identifies patients with a high risk of mortality.

Kristina H Haugaa1, J Martijn Bos, Robert F Tarrell, Bruce W Morlan, Pedro J Caraballo, Michael J Ackerman.   

Abstract

OBJECTIVES: To determine the phenotype and outcome of patients with QTc of at least 500 ms and to create a pro-QTc risk score for mortality. PATIENTS AND METHODS: An institution-wide computer-based QT alert system was developed and implemented at Mayo Clinic in Rochester, Minnesota. This system screens all electrocardiograms (ECGs) performed and alerts the physician if the QTc is 500 ms or greater. Between November 10, 2010, and June 30, 2011, 86,107 ECGs were performed in 52,579 patients. Clinical diagnoses, laboratory abnormalities, and medications known to influence the QT interval were collected from the medical records and summarized in a new pro-QTc score. Survival was compared with that of the 51,434 Mayo Clinic patients with a QTc less than 500 ms during the same period.
RESULTS: QT alerts were sent for 1145 patients (2%); of these, 470 (41%) had no other identifiable ECG reason for QT prolongation (eg, pacing). All-cause mortality during a mean ± SD of 224 ± 174 days of follow-up was 19% in those with QTc of 500 ms or greater compared with 5% in patients with QTc less than 500 ms (log-rank P<.001). The pro-QTc score was an age-independent predictor of mortality (pro-QTc score: hazard ratio, 1.18; 95% CI, 1.05-1.32; P=.006; age: hazard ratio, 1.02; 95% CI, 1.01-1.03; P=.004.). QT-prolonging medications accounted for 37% of the pro-QTc score.
CONCLUSION: This novel institution-wide QT alert system identified patients with a high risk of mortality. The pro-QTc score, reflecting patients' multimorbidity and multipharmacy, was an independent predictor of mortality. The QT alert system may increase a physician's awareness of a high-risk patient. Potentially lifesaving interventions can be facilitated by reducing the modifiable factors of the pro-QTc score.
Copyright © 2013 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2013        PMID: 23541006     DOI: 10.1016/j.mayocp.2013.01.013

Source DB:  PubMed          Journal:  Mayo Clin Proc        ISSN: 0025-6196            Impact factor:   7.616


  55 in total

1.  Phenotype of Children with QT Prolongation Identified Using an Institution-Wide QT Alert System.

Authors:  Heather N Anderson; J Martijn Bos; Kristina H Haugaa; Bruce W Morlan; Robert F Tarrell; Pedro J Caraballo; Michael J Ackerman
Journal:  Pediatr Cardiol       Date:  2015-04-07       Impact factor: 1.655

2.  Impact of clinical decision support preventing the use of QT-prolonging medications for patients at risk for torsade de pointes.

Authors:  Atsushi Sorita; J Martijn Bos; Bruce W Morlan; Robert F Tarrell; Michael J Ackerman; Pedro J Caraballo
Journal:  J Am Med Inform Assoc       Date:  2014-10-16       Impact factor: 4.497

Review 3.  Adverse Drug Event Causality Analysis (ADECA): A Process for Evaluating Evidence and Assigning Drugs to Risk Categories for Sudden Death.

Authors:  Raymond L Woosley; Klaus Romero; Craig W Heise; Tyler Gallo; Jared Tate; Raymond David Woosley; Sophie Ward
Journal:  Drug Saf       Date:  2017-06       Impact factor: 5.606

4.  Development of a risk score for QTc-prolongation: the RISQ-PATH study.

Authors:  Eline Vandael; Bert Vandenberk; Joris Vandenberghe; Isabel Spriet; Rik Willems; Veerle Foulon
Journal:  Int J Clin Pharm       Date:  2017-03-09

5.  Development of a risk model for predicting QTc interval prolongation in patients using QTc-prolonging drugs.

Authors:  Anita N Bindraban; José Rolvink; Florine A Berger; Patricia M L A van den Bemt; Aaf F M Kuijper; Ruud T M van der Hoeven; Aukje K Mantel-Teeuwisse; Matthijs L Becker
Journal:  Int J Clin Pharm       Date:  2018-07-26

6.  Automated T-wave analysis can differentiate acquired QT prolongation from congenital long QT syndrome.

Authors:  Alan Sugrue; Peter A Noseworthy; Vaclav Kremen; J Martijn Bos; Bo Qiang; Ram K Rohatgi; Yehu Sapir; Zachi I Attia; Peter Brady; Pedro J Caraballo; Samuel J Asirvatham; Paul A Friedman; Michael J Ackerman
Journal:  Ann Noninvasive Electrocardiol       Date:  2017-04-21       Impact factor: 1.468

7.  A smart algorithm for the prevention and risk management of QTc prolongation based on the optimized RISQ-PATH model.

Authors:  Eline Vandael; Bert Vandenberk; Joris Vandenberghe; Bart Van den Bosch; Rik Willems; Veerle Foulon
Journal:  Br J Clin Pharmacol       Date:  2018-10-06       Impact factor: 4.335

8.  QT interval prolongation in hospitalized patients on cardiology wards: a prospective observational study.

Authors:  Qasim Khan; Mohammad Ismail; Iqbal Haider; Inam Ul Haq; Sidra Noor
Journal:  Eur J Clin Pharmacol       Date:  2017-08-12       Impact factor: 2.953

9.  Effectiveness of a clinical decision support system for reducing the risk of QT interval prolongation in hospitalized patients.

Authors:  James E Tisdale; Heather A Jaynes; Joanna R Kingery; Brian R Overholser; Noha A Mourad; Tate N Trujillo; Richard J Kovacs
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2014-05-06

10.  Risk management of QTc-prolongation in patients receiving haloperidol: an epidemiological study in a University hospital in Belgium.

Authors:  Eline Vandael; Bert Vandenberk; Joris Vandenberghe; Isabel Spriet; Rik Willems; Veerle Foulon
Journal:  Int J Clin Pharm       Date:  2016-01-09
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.