Prospective, non-randomized, multi-center study designed to quantify patient preferences pertaining to risks and features of conventional transvenous pacemakers and leadless pacemakers
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.
Study Type
OBSERVATIONAL
Enrollment
117
Patient preference survey on implantable cardiac pacemaker systems
Honor Health
Scottsdale, Arizona, United States
Arrhythmia Research Group
Jonesboro, Arkansas, United States
Arkansas Heart Hospital
Little Rock, Arkansas, United States
Mean Rankings for Pacemaker Device Features
Ranking of six pacemaker device features from most concerning (1) to least concerning (6)
Time frame: Baseline
Results From RPL Model of Discrete Choice Experiment Choice Questions - Preference Weights (Effect-coded Parameters)
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.
Time frame: Baseline
Results From RPL Model of Discrete Choice Experiment Choice Questions- Standard Deviations
The standard deviations representing the degree of variation in preference weights, with larger estimates representing preference heterogeneity.
Time frame: Baseline
Maximum-acceptable Risks of a Complication
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.
Time frame: Baseline
Maximum-acceptable Risks of an Infection
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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Pacific Heart Institute
Santa Monica, California, United States
Baptist Medical Center
Jacksonville, Florida, United States
Rush University Medical Center
Chicago, Illinois, United States
Prairie Education & Research Cooperative
Springfield, Illinois, United States
Charlton Memorial Hospital
Fall River, Massachusetts, United States
New York Presbyterian Hospital/Cornell University
New York, New York, United States
Hightower Clinical
Oklahoma City, Oklahoma, United States
...and 1 more locations
Time frame: Baseline
Probability of Choosing Specified Pacemakers - All 3 Profiles
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.
Time frame: Baseline
Probability of Choosing Specified Pacemakers - Leadless Pacemaker Removable vs. Leadless Pacemaker Non-removable
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.
Time frame: Baseline
Probability of Choosing Specified Pacemakers - Leadless Pacemaker Removable vs. Pacemaker With Leads
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.
Time frame: Baseline
Probability of Choosing Specified Pacemakers - Leadless Pacemaker Non-removable vs. Pacemaker With Leads
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.
Time frame: Baseline
Constrained 2-class Latent-class Model Preference Weights
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.
Time frame: Baseline
Number of Discrete Choice Experiment Questions Answered
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.
Time frame: Baseline
Association of Patient Characteristics With Membership in the Transvenous Class Versus the Leadless Class
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.
Time frame: Baseline