Patient Preferences for Leadless Pacemakers
Quantifying Patient Preferences for Leadless Pacemaker Devices
1 other identifier
observational
117
1 country
11
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
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for all trials
Started Mar 2022
11 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
March 28, 2022
CompletedFirst Submitted
Initial submission to the registry
April 4, 2022
CompletedFirst Posted
Study publicly available on registry
April 14, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 13, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
June 13, 2023
CompletedResults Posted
Study results publicly available
February 20, 2025
CompletedFebruary 20, 2025
January 1, 2025
1.2 years
April 4, 2022
July 11, 2024
January 30, 2025
Conditions
Outcome Measures
Primary Outcomes (9)
Mean Rankings for Pacemaker Device Features
Ranking of six pacemaker device features from most concerning (1) to least concerning (6)
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.
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.
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.
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.
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.
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.
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.
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.
Baseline
Secondary Outcomes (3)
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
Interventions
Patient preference survey on implantable cardiac pacemaker systems
Eligibility Criteria
300 patients
You may qualify if:
- 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)
You may not qualify if:
- None
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (11)
Honor Health
Scottsdale, Arizona, 85258, United States
Arrhythmia Research Group
Jonesboro, Arkansas, 72401, United States
Arkansas Heart Hospital
Little Rock, Arkansas, 72211, United States
Pacific Heart Institute
Santa Monica, California, 90404, United States
Baptist Medical Center
Jacksonville, Florida, 32207, United States
Rush University Medical Center
Chicago, Illinois, 60612, United States
Prairie Education & Research Cooperative
Springfield, Illinois, 62769, United States
Charlton Memorial Hospital
Fall River, Massachusetts, 02720, United States
New York Presbyterian Hospital/Cornell University
New York, New York, 10021, United States
Hightower Clinical
Oklahoma City, Oklahoma, 73102, United States
University of Utah Hospital
Salt Lake City, Utah, 84132, United States
Related Publications (1)
Reed SD, Yang JC, Wallace MJ, Sutphin J, Johnson FR, Ozdemir S, Delgado SM, Goates S, Harbert N, Lo M, Rajagopalan B, Ip JE, Al-Khatib SM. Patient Preferences for Features Associated With Leadless Versus Conventional Transvenous Cardiac Pacemakers. Circ Cardiovasc Qual Outcomes. 2024 Dec;17(12):e011168. doi: 10.1161/CIRCOUTCOMES.124.011168. Epub 2024 Nov 21.
PMID: 39569505DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Results Point of Contact
- Title
- Stephanie Delgado
- Organization
- Abbott Medical Devices
Study Officials
- PRINCIPAL INVESTIGATOR
Shelby Reed, PhD
Duke Clinical Research Institute
Publication Agreements
- PI is Sponsor Employee
- No
- Restrictive Agreement
- No
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Target Duration
- 1 Day
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
April 4, 2022
First Posted
April 14, 2022
Study Start
March 28, 2022
Primary Completion
June 13, 2023
Study Completion
June 13, 2023
Last Updated
February 20, 2025
Results First Posted
February 20, 2025
Record last verified: 2025-01