Dataset Information

Improving the Identification of Out-of-Hospital Sudden Cardiac Deaths in a General Practice Research Database.

ABSTRACT:

Background

The ascertainment of sudden cardiac death (SCD) in electronic health databases is challenging.

Objectives

Our objective was to evaluate the applicability of the validated computer definition of SCD developed by Chung et al. in a retrospective study of SCD and domperidone exposure in the Clinical Practice Research Datalink (CPRD).

Methods

We assessed out-of-hospital SCD by applying the validated computer definition and linking data with Hospital Episode Statistics and death certificates. We developed a separate algorithm to identify end-of-life care in noninstitutionalized patients and excluded associated deaths from the analysis to address their misclassification as SCD.

Results

Of the 681,104 patients in the study cohort, 3444 were initially classified as out-of-hospital SCD. Next, 163 deaths were identified as expected deaths by our algorithm for end-of-life home care. After review of patient profiles, 162 were classified as expected deaths because of evidence that the patient received palliative or end-of-life care, but one was a false negative. The exclusion of such cases appreciably changed the odds ratio for current exposure to domperidone compared with non-use of study medications from 2.09 (95 % confidence interval [CI] 1.16-3.74) to 1.71 (95 % CI 0.92-3.18). A similar effect on the odds ratio was observed for current exposure to metoclopramide but not to proton pump inhibitors.

Conclusions

Our algorithm to identify end-of-life care at home in the CPRD performed well, with only one false negative. The exclusion of misclassified cases of SCD reduced the magnitude of the odds ratios for SCD associated with domperidone and metoclopramide exposure by controlling protopathic bias.

SUBMITTER: Varas-Lorenzo C

PROVIDER: S-EPMC5042942 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Publications

Improving the Identification of Out-of-Hospital Sudden Cardiac Deaths in a General Practice Research Database.

Varas-Lorenzo Cristina C Arana Alejandro A Johannes Catherine B CB McQuay Lisa J LJ Rothman Kenneth J KJ Fife Daniel D

Drugs - real world outcomes 20160901 3

<h4>Background</h4>The ascertainment of sudden cardiac death (SCD) in electronic health databases is challenging.<h4>Objectives</h4>Our objective was to evaluate the applicability of the validated computer definition of SCD developed by Chung et al. in a retrospective study of SCD and domperidone exposure in the Clinical Practice Research Datalink (CPRD).<h4>Methods</h4>We assessed out-of-hospital SCD by applying the validated computer definition and linking data with Hospital Episode Statistics ...[more]

PMID: 27747831

Similar Datasets

Project description:BackgroundConventional definitions of sudden cardiac death (SCD) presume cardiac cause. We studied the World Health Organization-defined SCDs autopsied in the POST SCD study (Postmortem Systematic Investigation of SCD) to determine whether premortem characteristics could identify autopsy-defined sudden arrhythmic death (SAD) among presumed SCDs.MethodsBetween January 2, 2011, and January 4, 2016, we prospectively identified all 615 World Health Organization-defined SCDs (144 witnessed) 18 to 90 years in San Francisco County for medical record review and autopsy via medical examiner surveillance. Autopsy-defined SADs had no extracardiac or acute heart failure cause of death. We used 2 nested sets of premortem predictors-an emergency medical system set and a comprehensive set adding medical record data-to develop Least Absolute Selection and Shrinkage Operator models of SAD among witnessed and unwitnessed cohorts.ResultsOf 615 presumed SCDs, 348 (57%) were autopsy-defined SAD. For witnessed cases, the emergency medical system model (area under the receiver operator curve 0.75 [0.67-0.82]) included presenting rhythm of ventricular tachycardia/fibrillation and pulseless electrical activity, while the comprehensive (area under the receiver operator curve 0.78 [0.70-0.84]) added depression. If only ventricular tachycardia/fibrillation witnessed cases (n=48) were classified as SAD, sensitivity was 0.46 (0.36-0.57), and specificity was 0.90 (0.79-0.97). For unwitnessed cases, the emergency medical system model (area under the receiver operator curve 0.68 [0.64-0.73]) included black race, male sex, age, and time since last seen normal, while the comprehensive (area under the receiver operator curve 0.75 [0.71-0.79]) added use of β-blockers, antidepressants, QT-prolonging drugs, opiates, illicit drugs, and dyslipidemia. If only unwitnessed cases <1 hour (n=59) were classified as SAD, sensitivity was 0.18 (0.13-0.22) and specificity was 0.95 (0.90-0.97).ConclusionsOur models identify premortem characteristics that can better specify autopsy-defined SAD among presumed SCDs and suggest the World Health Organization definition can be improved by restricting witnessed SCDs to ventricular tachycardia/fibrillation or nonpulseless electrical activity rhythms and unwitnessed cases to <1 hour since last normal, at the cost of sensitivity.

Dataset Information

Improving the Identification of Out-of-Hospital Sudden Cardiac Deaths in a General Practice Research Database.

Background

Objectives

Methods

Results

Conclusions

Publications

Improving the Identification of Out-of-Hospital Sudden Cardiac Deaths in a General Practice Research Database.

Similar Datasets

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