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Amyloidosis Incidence in High-Risk Cardiac Device Patients

Histopathological Incidence of Amyloidosis in High-Risk Patients Undergoing Cardiac Device Implantation

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06186167
Enrollment
100
Registered
2023-12-29
Start date
2024-01-29
Completion date
2024-12-31
Last updated
2024-02-20

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

AL Amyloidosis, Amyloid, Amyloidosis Cardiac, ATTR Amyloidosis Wild Type, Cardiac Amyloidosis, Infiltrative Cardiomyopathy, Amyloid, Systemic Amyloidosis

Keywords

Cardiac Devices, Chest Wall Fat Pad Biopsy, Cardiac Implantable Electronic Devices

Brief summary

This single-practice prospective cohort study aims to enhance the diagnosis of cardiac amyloidosis in high-risk patients undergoing standard cardiac device implantation. By analyzing chest wall fat tissue, which is usually discarded, we aim to determine the diagnostic yield of such biopsies for amyloidosis and to develop a predictive screening model based on clinical, lab, and imaging data. The study, running from December 2023 to December 2024, expects to enroll 100 patients and may provide a new, non-invasive diagnostic avenue for this condition.

Detailed description

The study targets a key gap in cardiac amyloidosis diagnosis by systematically evaluating the histopathological incidence of the disease using chest wall fat pad biopsies-tissue that is typically discarded during the implantation of cardiac devices like pacemakers, ICDs, and CRT-D/Ps. Standard surgical procedures are adhered to, ensuring minimal additional risk to patients. The collected tissue samples are analyzed by the HCA pathology laboratory to detect amyloid deposits, thereby potentially identifying amyloidosis in a non-invasive manner. In addition to the primary endpoint of histopathological diagnosis, the study retrospectively aims to validate a predictive model that incorporates a wide range of data to streamline the identification of patients at high risk for cardiac amyloidosis. Strict measures are in place to protect patient confidentiality and data security. By potentially improving diagnostic efficiency, this research could contribute to earlier detection and treatment strategies, thus improving patient outcomes for those at high risk of this life-threatening condition.

Interventions

PROCEDUREChest Wall Fat Tissue Collection

As part of routine cardiac device implantation, chest wall fat tissue is collected for histopathological analysis. This tissue, which is typically discarded, will be used to identify amyloid deposits in high-risk cardiac patients. No additional surgical intervention is performed beyond the standard procedure for device implantation.

Sponsors

Midwest Heart & Vascular Specialists
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
40 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Patients who are 40 years of age or older * Patients who are able and willing to provide informed consent * Patients who are scheduled for CIED implantation within the study period and with clinical lab and imaging features suggestive of cardiac amyloidosis

Exclusion criteria

* Individuals below the age of 40. * Persons who are unable to consent or who do not consent to participate. * Patients who have already been diagnosed with cardiac amyloidosis prior to the study

Design outcomes

Primary

MeasureTime frameDescription
Diagnostic yield of chest wall fat pad biopsy for cardiac amyloidosisDecember 2023 to December 2024, corresponding to the study duration during which patients will be enrolled and outcomes will be assessedThe primary outcome measure is the histopathologic diagnosis of amyloidosis in chest wall fat tissue removed during cardiac device implantation

Secondary

MeasureTime frameDescription
Development of a predictive screening model for cardiac amyloidosisRetrospective analysis of patient data collected from December 2023 to December 2024Retrospective development and validation of a predictive model using pre-procedural clinical, lab, and imaging data to identify patients at high risk for cardiac amyloidosis

Countries

United States

Contacts

Primary ContactVasvi Singh, MD
vasvi.singh@hcahealthcare.com(913) 253-3000
Backup ContactElizabeth Fulks, MS
elizabeth.fulks@hcahealthcare.com(913) 253-3000

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026