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Developing strategies for predicting hyperkalemia in potassium-increasing drug-drug interactions


Eschmann, Emmanuel; Beeler, Patrick Emanuel; Schneemann, Markus; Blaser, Jürg (2017). Developing strategies for predicting hyperkalemia in potassium-increasing drug-drug interactions. Journal of the American Medical Informatics Association (JAMIA), 24(1):60-66.

Abstract

OBJECTIVE: To compare different strategies predicting hyperkalemia (serum potassium level ≥5.5 mEq/l) in hospitalized patients for whom medications triggering potassium-increasing drug-drug interactions (DDIs) were ordered.
MATERIALS AND METHODS: We investigated 5 strategies that combined prediction triggered at onset of DDI versus continuous monitoring and taking into account an increasing number of patient parameters. The considered patient parameters were identified using generalized additive models, and the thresholds of the prediction strategies were calculated by applying Youden's J statistic to receiver operation characteristic curves. Half of the data served as the calibration set, half as the validation set.
RESULTS: We identified 132 incidences of hyperkalemia induced by 8413 potentially severe potassium-increasing DDIs among 76 467 patients. The positive predictive value (PPV) of those strategies predicting hyperkalemia at the onset of DDI ranged from 1.79% (undifferentiated anticipation of hyperkalemia due to the DDI) to 3.02% (additionally considering the baseline serum potassium) and 3.10% (including further patient parameters). Continuous monitoring significantly increased the PPV to 8.25% (considering the current serum potassium) and 9.34% (additional patient parameters).
CONCLUSION: Continuous monitoring of the risk for hyperkalemia based on current potassium level shows a better predictive power than predictions triggered at the onset of DDI. This contrasts with efforts to improve DDI alerts by taking into account more patient parameters at the time of ordering.

Abstract

OBJECTIVE: To compare different strategies predicting hyperkalemia (serum potassium level ≥5.5 mEq/l) in hospitalized patients for whom medications triggering potassium-increasing drug-drug interactions (DDIs) were ordered.
MATERIALS AND METHODS: We investigated 5 strategies that combined prediction triggered at onset of DDI versus continuous monitoring and taking into account an increasing number of patient parameters. The considered patient parameters were identified using generalized additive models, and the thresholds of the prediction strategies were calculated by applying Youden's J statistic to receiver operation characteristic curves. Half of the data served as the calibration set, half as the validation set.
RESULTS: We identified 132 incidences of hyperkalemia induced by 8413 potentially severe potassium-increasing DDIs among 76 467 patients. The positive predictive value (PPV) of those strategies predicting hyperkalemia at the onset of DDI ranged from 1.79% (undifferentiated anticipation of hyperkalemia due to the DDI) to 3.02% (additionally considering the baseline serum potassium) and 3.10% (including further patient parameters). Continuous monitoring significantly increased the PPV to 8.25% (considering the current serum potassium) and 9.34% (additional patient parameters).
CONCLUSION: Continuous monitoring of the risk for hyperkalemia based on current potassium level shows a better predictive power than predictions triggered at the onset of DDI. This contrasts with efforts to improve DDI alerts by taking into account more patient parameters at the time of ordering.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic and Policlinic for Internal Medicine
04 Faculty of Medicine > University Hospital Zurich > Clinic for Geriatric Medicine
04 Faculty of Medicine > Institute for Regenerative Medicine (IREM)
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:2017
Deposited On:23 May 2016 15:55
Last Modified:22 Nov 2017 09:52
Publisher:BMJ Publishing Group
ISSN:1067-5027
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/jamia/ocw050
PubMed ID:27174894

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