Quantifying Patient Preferences for Leadless Pacemaker Devices
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Cardiac Rhythm Disorder
- Sponsor
- Abbott Medical Devices
- Enrollment
- 117
- Locations
- 11
- Primary Endpoint
- Mean Rankings for Pacemaker Device Features
- Status
- Completed
- Last Updated
- last year
Overview
Brief Summary
Prospective, non-randomized, multi-center study designed to quantify patient preferences pertaining to risks and features of conventional transvenous pacemakers and leadless pacemakers
Detailed Description
The purpose of this study is to quantify patient preferences pertaining to risks and features of conventional transvenous pacemakers and leadless pacemakers. The preference study is designed to elicit patient preferences for risks and features that vary between a dual chamber leadless pacemaker system and a dual chamber transvenous pacemaker system, to quantify their relative importance.
Investigators
Eligibility Criteria
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
- Not provided
Outcomes
Primary Outcomes
Mean Rankings for Pacemaker Device Features
Time Frame: Baseline
Ranking of six pacemaker device features from most concerning (1) to least concerning (6)
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.
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.
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.
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.
Probability of Choosing Specified Pacemakers - All 3 Profiles
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, 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.
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.
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.
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.
Secondary Outcomes
- Constrained 2-class Latent-class Model Preference Weights(Baseline)
- Number of Discrete Choice Experiment Questions Answered(Baseline)
- Association of Patient Characteristics With Membership in the Transvenous Class Versus the Leadless Class(Baseline)