Patient Preferences for Leadless Pacemakers
Quantifying Patient Preferences for Leadless Pacemaker Devices
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Grant Kim
- Phone Number: 818-493-3147
- Email: grant.kim1@abbott.com
Study Locations
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Arizona
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Scottsdale, Arizona, United States, 85258
- Honor Health
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Arkansas
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Jonesboro, Arkansas, United States, 72401
- Arrhythmia Research Group
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Little Rock, Arkansas, United States, 72211
- Arkansas Heart Hospital
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California
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Santa Monica, California, United States, 90404
- Pacific Heart Institute
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Florida
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Jacksonville, Florida, United States, 32207
- Baptist Medical Center
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Illinois
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Chicago, Illinois, United States, 60612
- Rush University Medical Center
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Springfield, Illinois, United States, 62769
- Prairie Education & Research Cooperative
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Massachusetts
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Fall River, Massachusetts, United States, 02720
- Charlton Memorial Hospital
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New York
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New York, New York, United States, 10021
- New York Presbyterian Hospital/Cornell University
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Oklahoma
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Oklahoma City, Oklahoma, United States, 73102
- Hightower Clinical
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Utah
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Salt Lake City, Utah, United States, 84132
- University of Utah Hospital
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Able to read and speak English to consent to participate in the survey
- Willing and able to use a tablet or computer to complete the survey
- Scheduled to undergo evaluation for a de novo cardiac pacemaker at the study site (patient may or may not have a known indication for a pacemaker at the time)
Exclusion Criteria:
- None
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Mean Rankings for Pacemaker Device Features
Time Frame: Baseline
|
Ranking of six pacemaker device features from most concerning (1) to least concerning (6)
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Baseline
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Results From RPL Model of Discrete Choice Experiment Choice Questions - Preference Weights (Effect-coded Parameters)
Time Frame: Baseline
|
The preference weights for the RPL model.
Effect-coded parameters generate log-odds preference weights representing the relative strength of preference for each attribute level versus the mean effect across levels normalized at zero.
A higher weight indicates a more preferred level while a lower weight indicates a less preferred level.
|
Baseline
|
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Results From RPL Model of Discrete Choice Experiment Choice Questions- Standard Deviations
Time Frame: Baseline
|
The standard deviations representing the degree of variation in preference weights, with larger estimates representing preference heterogeneity.
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Baseline
|
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Maximum-acceptable Risks of a Complication
Time Frame: Baseline
|
Maximum-acceptable risk (MAR) of a complication was calculated for patients based off latent-class analysis with two groups-leadless class and transvenous class (see secondary outcome Constrained 2-class Latent-class model preference weights).
The MAR represents risk level patients would be willing to accept to obtain their preferred pacemaker type, no discomfort, a device with longer battery life, and a device with more time since regulatory approval.
|
Baseline
|
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Maximum-acceptable Risks of an Infection
Time Frame: Baseline
|
Maximum-acceptable risk (MAR) of an infection was calculated for patients based off latent-class analysis with two groups-leadless class and transvenous class (see secondary outcome Constrained 2-class Latent-class model preference weights).
The MAR represent the risk that patients would be willing to accept to obtain their preferred pacemaker type, no discomfort, a device with longer battery life, and a device with more time since regulatory approval.
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Baseline
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Probability of Choosing Specified Pacemakers - All 3 Profiles
Time Frame: Baseline
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Preference weight estimates were used to calculate the predicted probabilities that patients would choose a hypothetical pacemaker profile out of three different pacemaker types- leadless pacemaker removable, leadless pacemaker non-removable, or pacemaker with leads.
Attributes for each pacemaker profile were defined using historical or published values.
Preference weights from the latent class model were used to compute the probability that respondents within each class preference would choose a pacemaker profile over another.
|
Baseline
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Probability of Choosing Specified Pacemakers - Leadless Pacemaker Removable vs. Leadless Pacemaker Non-removable
Time Frame: Baseline
|
Preference weight estimates were used to calculate the predicted probabilities that patients would choose a hypothetical pacemaker profile out of three different pacemaker types- leadless pacemaker removable or leadless pacemaker non-removable.
Attributes for each pacemaker profile were defined using historical or published values.
Preference weights from the latent class model were used to compute the probability that respondents within each class preference would choose a pacemaker profile over another.
|
Baseline
|
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Probability of Choosing Specified Pacemakers - Leadless Pacemaker Removable vs. Pacemaker With Leads
Time Frame: Baseline
|
Preference weight estimates were used to calculate the predicted probabilities that patients would choose a hypothetical pacemaker profile out of three different pacemaker types- leadless pacemaker removable or pacemaker with leads.
Attributes for each pacemaker profile were defined using historical or published values.
Preference weights from the latent class model were used to compute the probability that respondents within each class preference would choose a pacemaker profile over another.
|
Baseline
|
|
Probability of Choosing Specified Pacemakers - Leadless Pacemaker Non-removable vs. Pacemaker With Leads
Time Frame: Baseline
|
Preference weight estimates were used to calculate the predicted probabilities that patients would choose a hypothetical pacemaker profile out of three different pacemaker types- leadless pacemaker non-removable or pacemaker with leads.
Attributes for each pacemaker profile were defined using historical or published values.
Preference weights from the latent class model were used to compute the probability that respondents within each class preference would choose a pacemaker profile over another.
|
Baseline
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Constrained 2-class Latent-class Model Preference Weights
Time Frame: Baseline
|
Latent-class (LC) analysis was used to identify systematically different preference patterns across respondents.
LC analysis provides a unique set of estimates of preference weights for a prespecified number of preference classes.
Respondents are probabilistically assigned to classes based on the similarity of their responses to the overall preference pattern identified in each class.
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Baseline
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Number of Discrete Choice Experiment Questions Answered
Time Frame: Baseline
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Number of Discrete choice experiment (DCE) questions answered by 117 respondents who answered at least the first 8 DCE questions.
After respondents answered 8 DCE questions, they were asked if they would like to complete 4 additional questions.
|
Baseline
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Association of Patient Characteristics With Membership in the Transvenous Class Versus the Leadless Class
Time Frame: Baseline
|
Respondent characteristics can be associated with class membership probabilities to "profile" the classes.
These results show if respondents with certain characteristics are more likely to be in one class versus the other.
The odds ratios of being in the transvenous class versus the leadless class for patient characteristics.
Odds ratios greater than 1 indicate a higher likelihood of being in the class preferring transvenous pacemakers and pacemakers with longer time since government approval.
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Baseline
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Shelby Reed, PhD, Duke Clinical Research Institute
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- ABT-CIP-10435
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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