Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned HospitalisationCitation formats

  • External authors:
  • Joanne K Taylor
  • Manish Motwani
  • Catherine M Leonard
  • Fozia Zahir Ahmed

Standard

Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation. / Sammut-Powell, Camilla; Taylor, Joanne K; Motwani, Manish; Leonard, Catherine M; Martin, Glen P.; Ahmed, Fozia Zahir.

In: Journal of the American Heart Association, 13.04.2022.

Research output: Contribution to journalArticlepeer-review

Harvard

Sammut-Powell, C, Taylor, JK, Motwani, M, Leonard, CM, Martin, GP & Ahmed, FZ 2022, 'Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation', Journal of the American Heart Association.

APA

Sammut-Powell, C., Taylor, J. K., Motwani, M., Leonard, C. M., Martin, G. P., & Ahmed, F. Z. (Accepted/In press). Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation. Journal of the American Heart Association.

Vancouver

Sammut-Powell C, Taylor JK, Motwani M, Leonard CM, Martin GP, Ahmed FZ. Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation. Journal of the American Heart Association. 2022 Apr 13.

Author

Sammut-Powell, Camilla ; Taylor, Joanne K ; Motwani, Manish ; Leonard, Catherine M ; Martin, Glen P. ; Ahmed, Fozia Zahir. / Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation. In: Journal of the American Heart Association. 2022.

Bibtex

@article{8af81aa99c134c62b86fb8f8abe99663,
title = "Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation",
abstract = "BackgroundUnplanned hospitalisations are common in patients with cardiovascular disease. The {\textquoteleft}Triage Heart Failure Risk Status{\textquoteright} (Triage-HFRS) algorithm in patients with cardiac implantable electronic devices (CIEDs) uses data from up to 9 device-derived physiological parameters to stratify patients as low/medium/high-risk of 30-day heart failure-hospitalisation (HFH); but its use to predict all-cause hospitalisation in the has not been explored. We examined the association between Triage-HFRS and risk of all-cause-, cardiovascular-, or HF-hospitalisation (ACH, CVH, HFH).MethodsA prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage-HFRS enabled CIED (cardiac resynchronisation therapy {\textquoteleft}CRT{\textquoteright} device, implantable cardioverter-defibrillator {\textquoteleft}ICD{\textquoteright} or pacemaker). Cox proportional hazards models explored association between Triage-HFRS and time-to-hospitalisation; a frailty term at the patient-level accounted for repeated measures. Results274/435 patients (63.0%) transmitted >1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. 153 (32.9%) patients had >1 unplanned hospitalisation during the study period totalling 356 non-elective hospitalisations. A high HFRS conferred a 37.3% sensitivity and 86.2% specificity for 30-day all-cause hospitalisation, and for heart failure hospitalisations, 62.5% and 85.6% respectively. Compared to a low Triage-HFRS, a high HFRS conferred a 4.2 relative risk of 30-day ACH (8.5% v 2.0%), 5.0 relative risk of 30-day CVH (3.6% v 0.7%), and 7.7 relative risk of 30-day HFH (2.0% v 0.3%). ConclusionIn patients with CIEDs , remotely monitored Triage-HFRS data discriminated between patients at high and low risk of all-cause hospitalisation (cardiovascular or non-cardiovascular) in real-time.",
author = "Camilla Sammut-Powell and Taylor, {Joanne K} and Manish Motwani and Leonard, {Catherine M} and Martin, {Glen P.} and Ahmed, {Fozia Zahir}",
year = "2022",
month = apr,
day = "13",
language = "English",
journal = "American Heart Association. Journal. Cardiovascular and Cerebrovascular Disease",
issn = "2047-9980",
publisher = "John Wiley & Sons Ltd",

}

RIS

TY - JOUR

T1 - Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation

AU - Sammut-Powell, Camilla

AU - Taylor, Joanne K

AU - Motwani, Manish

AU - Leonard, Catherine M

AU - Martin, Glen P.

AU - Ahmed, Fozia Zahir

PY - 2022/4/13

Y1 - 2022/4/13

N2 - BackgroundUnplanned hospitalisations are common in patients with cardiovascular disease. The ‘Triage Heart Failure Risk Status’ (Triage-HFRS) algorithm in patients with cardiac implantable electronic devices (CIEDs) uses data from up to 9 device-derived physiological parameters to stratify patients as low/medium/high-risk of 30-day heart failure-hospitalisation (HFH); but its use to predict all-cause hospitalisation in the has not been explored. We examined the association between Triage-HFRS and risk of all-cause-, cardiovascular-, or HF-hospitalisation (ACH, CVH, HFH).MethodsA prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage-HFRS enabled CIED (cardiac resynchronisation therapy ‘CRT’ device, implantable cardioverter-defibrillator ‘ICD’ or pacemaker). Cox proportional hazards models explored association between Triage-HFRS and time-to-hospitalisation; a frailty term at the patient-level accounted for repeated measures. Results274/435 patients (63.0%) transmitted >1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. 153 (32.9%) patients had >1 unplanned hospitalisation during the study period totalling 356 non-elective hospitalisations. A high HFRS conferred a 37.3% sensitivity and 86.2% specificity for 30-day all-cause hospitalisation, and for heart failure hospitalisations, 62.5% and 85.6% respectively. Compared to a low Triage-HFRS, a high HFRS conferred a 4.2 relative risk of 30-day ACH (8.5% v 2.0%), 5.0 relative risk of 30-day CVH (3.6% v 0.7%), and 7.7 relative risk of 30-day HFH (2.0% v 0.3%). ConclusionIn patients with CIEDs , remotely monitored Triage-HFRS data discriminated between patients at high and low risk of all-cause hospitalisation (cardiovascular or non-cardiovascular) in real-time.

AB - BackgroundUnplanned hospitalisations are common in patients with cardiovascular disease. The ‘Triage Heart Failure Risk Status’ (Triage-HFRS) algorithm in patients with cardiac implantable electronic devices (CIEDs) uses data from up to 9 device-derived physiological parameters to stratify patients as low/medium/high-risk of 30-day heart failure-hospitalisation (HFH); but its use to predict all-cause hospitalisation in the has not been explored. We examined the association between Triage-HFRS and risk of all-cause-, cardiovascular-, or HF-hospitalisation (ACH, CVH, HFH).MethodsA prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage-HFRS enabled CIED (cardiac resynchronisation therapy ‘CRT’ device, implantable cardioverter-defibrillator ‘ICD’ or pacemaker). Cox proportional hazards models explored association between Triage-HFRS and time-to-hospitalisation; a frailty term at the patient-level accounted for repeated measures. Results274/435 patients (63.0%) transmitted >1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. 153 (32.9%) patients had >1 unplanned hospitalisation during the study period totalling 356 non-elective hospitalisations. A high HFRS conferred a 37.3% sensitivity and 86.2% specificity for 30-day all-cause hospitalisation, and for heart failure hospitalisations, 62.5% and 85.6% respectively. Compared to a low Triage-HFRS, a high HFRS conferred a 4.2 relative risk of 30-day ACH (8.5% v 2.0%), 5.0 relative risk of 30-day CVH (3.6% v 0.7%), and 7.7 relative risk of 30-day HFH (2.0% v 0.3%). ConclusionIn patients with CIEDs , remotely monitored Triage-HFRS data discriminated between patients at high and low risk of all-cause hospitalisation (cardiovascular or non-cardiovascular) in real-time.

M3 - Article

JO - American Heart Association. Journal. Cardiovascular and Cerebrovascular Disease

JF - American Heart Association. Journal. Cardiovascular and Cerebrovascular Disease

SN - 2047-9980

ER -