PO-05-156 software automation for delivery of pill-in-pocket anticoagulation (PIPOAC): experience from Oxford, UK
PO-05-156 software automation for delivery of pill-in-pocket anticoagulation (PIPOAC): experience from Oxford, UK
Background: PIPOAC is an emerging approach for suitable AF patients (infrequent AF episodes, short episode duration, lower CHA2DS2-VASC).
PIPOAC is taken during AF and temporarily after. Time from AF onset to starting PIPOAC must be minimised to allow prompt anticoagulation.
Continuous monitoring for AF onset is achieved using implantable cardiac monitors (ICM). ICM transmission surveillance and patient communication must currently be performed by healthcare staff.
A continuous automated process would reduce clinical workload and ensure PIPOAC is commenced promptly.
Objective: design software to continuously screen Medtronic Carelink platform to view transmissions from patient LINQ II devices. Program must trigger SMS alert to patients for AF episodes over 60 minutes (as per our PIPOAC criteria).
Methods: program code written using .NET open-source application between 2021-24 in four phases. Code improvements made over time to deal with minor bugs, unexpected scenarios, upgrades to .NET, and changes to Carelink website.
Program decision tree for new transmissions shown (Image 1).
Results: software test over 35 days between Oct and Dec 2024 including 32 patients monitored by LINQ II.
Phase one: AF episodes in seven patients. 91.7% of alerts delivered (Table 1). Three AF episodes missed in one patient who triggered transmissions using symptom activator. The program didn't recognize “AF (Symptom)” episodes. Code updated to recognize this category for phase two.
Phase two: AF episodes in five patients. 100% of alerts delivered, none missed.
Median time from AF episode onset to SMS 04:11 hours.
Conclusion: an automated system can effectively and quickly deliver patient alerts for AF. This approach could facilitate wider use of PIPOAC.
S535-S536
Varini, Richard
1c4158e9-951b-4efc-9155-f5b0bd63db75
Briosa e Gala, Andre
409c30a8-0696-4426-9f9b-2539af465dbd
Sharp, Alexander J.
1b75e163-d071-48d8-ad86-0c5ce163a0f4
Simpkins, Mark
fee30c68-9043-4c55-a7ed-71b7cd3349c5
Betts, Timothy R.
a9d90073-a54a-478c-81f0-39ecc5234047
24 April 2025
Varini, Richard
1c4158e9-951b-4efc-9155-f5b0bd63db75
Briosa e Gala, Andre
409c30a8-0696-4426-9f9b-2539af465dbd
Sharp, Alexander J.
1b75e163-d071-48d8-ad86-0c5ce163a0f4
Simpkins, Mark
fee30c68-9043-4c55-a7ed-71b7cd3349c5
Betts, Timothy R.
a9d90073-a54a-478c-81f0-39ecc5234047
Varini, Richard, Briosa e Gala, Andre, Sharp, Alexander J., Simpkins, Mark and Betts, Timothy R.
(2025)
PO-05-156 software automation for delivery of pill-in-pocket anticoagulation (PIPOAC): experience from Oxford, UK.
Heart Rhythm, 22 (4), .
(doi:10.1016/j.hrthm.2025.03.1340).
Record type:
Meeting abstract
Abstract
Background: PIPOAC is an emerging approach for suitable AF patients (infrequent AF episodes, short episode duration, lower CHA2DS2-VASC).
PIPOAC is taken during AF and temporarily after. Time from AF onset to starting PIPOAC must be minimised to allow prompt anticoagulation.
Continuous monitoring for AF onset is achieved using implantable cardiac monitors (ICM). ICM transmission surveillance and patient communication must currently be performed by healthcare staff.
A continuous automated process would reduce clinical workload and ensure PIPOAC is commenced promptly.
Objective: design software to continuously screen Medtronic Carelink platform to view transmissions from patient LINQ II devices. Program must trigger SMS alert to patients for AF episodes over 60 minutes (as per our PIPOAC criteria).
Methods: program code written using .NET open-source application between 2021-24 in four phases. Code improvements made over time to deal with minor bugs, unexpected scenarios, upgrades to .NET, and changes to Carelink website.
Program decision tree for new transmissions shown (Image 1).
Results: software test over 35 days between Oct and Dec 2024 including 32 patients monitored by LINQ II.
Phase one: AF episodes in seven patients. 91.7% of alerts delivered (Table 1). Three AF episodes missed in one patient who triggered transmissions using symptom activator. The program didn't recognize “AF (Symptom)” episodes. Code updated to recognize this category for phase two.
Phase two: AF episodes in five patients. 100% of alerts delivered, none missed.
Median time from AF episode onset to SMS 04:11 hours.
Conclusion: an automated system can effectively and quickly deliver patient alerts for AF. This approach could facilitate wider use of PIPOAC.
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e-pub ahead of print date: 24 April 2025
Published date: 24 April 2025
Identifiers
Local EPrints ID: 505883
URI: http://eprints.soton.ac.uk/id/eprint/505883
ISSN: 1547-5271
PURE UUID: 80d88df5-f783-443f-a6c3-c9b118469717
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Date deposited: 22 Oct 2025 16:42
Last modified: 23 Oct 2025 02:05
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Contributors
Author:
Richard Varini
Author:
Andre Briosa e Gala
Author:
Alexander J. Sharp
Author:
Mark Simpkins
Author:
Timothy R. Betts
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