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. 2008 Mar;15(3):225-30.
doi: 10.1111/j.1553-2712.2008.00066.x.

Systematic bias introduced by the informed consent process in a diagnostic research study

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Free article

Systematic bias introduced by the informed consent process in a diagnostic research study

Alice M Mitchell et al. Acad Emerg Med. 2008 Mar.
Free article

Abstract

Objectives: To determine population characteristics, outcomes, and reasons for unsuccessful enrollment among potential study subjects approached for written, informed consent in a minimal-risk emergency department (ED) study. The authors hypothesized that the prevalence of venous thromboembolism (VTE) would be lower among study participants and that medical acuity and refusal to provide a blood sample would be the most common reasons for nonparticipation.

Methods: The authors requested prospective, written, informed consent for a blood sample and follow-up from consecutive ED patients undergoing evaluation for pulmonary embolism (PE) and recorded spontaneously stated reasons for refusal. VTE was diagnosed or excluded using a combination of D-dimer testing and selective computed tomography (CT) angiography of the chest with venography of the lower extremities. The primary outcome was defined by the number of CT scans positive for VTE among ED patients evaluated for PE.

Results: Over 16 weeks, 260 of 287 (91%, 95% confidence interval [CI] = 87 to 94%) eligible patients were approached and consent was obtained from 183 patients (64%, 95% CI = 58% to 69%). The prevalence of VTE was 6% among participants and 13% among nonparticipants (95% CI [of the difference] = 1% to 15%). The proportions of African Americans, uninsured, and Medicaid patients were significantly higher among nonparticipants. No significant differences were found in the proportions of nonparticipants who disliked or distrusted research or desired financial reimbursement, compared to those not enrolled due to medical acuity or refused a blood sample.

Conclusions: These data implicate the written, informed consent process as a significant source of bias on estimated disease prevalence.

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