Tracking Atrial Fibrillation After Intensive Care Admission

Overview

Atrial fibrillation (AF) is a heart problem that causes an irregular heartbeat. It can cause the heart to beat more rapidly and reduce the heart's ability to pump blood around the body efficiently, causing heart failure. It also increases the risk of blood clots forming inside the heart. These clots may then be pumped out of the heart, through the blood vessels, to other parts of the body. This can cause strokes if the clots spread to the brain. AF is a common problem outside an Intensive Care Unit (ICU), where treatment is based on good, evidence-based guidelines designed to reduce the risk of problems like heart failure or strokes. Around 10% of patients treated in ICU develop atrial fibrillation as a complication of their underlying illness. Some patients will recover their normal heart rhythm before leaving the ICU, often with the help of some medical treatments. It is not known whether these patients will get AF again after leaving the ICU, or when this is likely to happen. It is also unknown whether patients who avoid AF whilst on the ICU may still be at high risk of developing it after they leave. This study will identify patients on the ICU who have no previous record of atrial fibrillation. These patients will be monitored whilst on the ICU to identify those who develop AF. Those patients who develop new onset AF will be monitored on the ward after leaving the ICU to see which patients have AF at this point. The heart monitoring will be repeated once the patients leave hospital, again to identify whether they have atrial fibrillation. Some studies suggest that AF during critical illness causes a long-term risk of recurrent AF and AF associated complications such as heart failure, stroke, and death. To understand how to minimise these risks in intensive care patients, we need to know how which patients who develop atrial fibrillation whilst in an ICU go on to have recurrent atrial fibrillation in hospital and in the community. These patients may benefit from interventions to reduce long term adverse events such as anticoagulation to reduce stroke risk.

The study aims to determine whether it is feasible to screen patients to detect atrial fibrillation after treatment on an intensive care unit. Patients who develop new onset AF in ICU who have no history of atrial fibrillation prior to ICU admission will be included. These patients will be monitored for atrial fibrillation on the ward post ICU discharge (for 14 days or until hospital discharge), and then again at 3 months post hospital discharge (for 7 days), when they attend the routine post ICU follow up clinic. In the ICU, this study cohort of patients will be monitored continuously to detect atrial fibrillation. If atrial fibrillation is suspected, this will be confirmed by independent review of a 12-lead ECG. On the ward, post ICU discharge patients will be given a chest patch for continuous cardiac rhythm monitoring designed to detect arrhythmia, which they will wear for 7 days, before a second patch is used for a further 7 days or until hospital discharge, whichever is shortest in duration. Data relating to past medical history, history of illness requiring ICU admission, subsequent events post ICU discharge and complications post-hospital discharge including hospital readmissions will be collected via hospital records and by patient interview at the follow up clinic. Patients will attend the ICU follow up clinic at 3 months post hospital discharge. At this time, they will be provided with a new chest patch from the same manufacturer, which they will wear for 7 days. The primary aim will be to demonstrate the feasibility of monitoring patients for AF occurrence post ICU discharge using a wearable patch device. Secondary aims will be to identify the proportion of patients who develop NOAF (New onset atrial fibrillation) in ICU who go on to have AF post discharge, as well as documenting the stroke risk, mortality and length of hospital stay in this patient group. This study will guide the design of a larger study investigating AF occurrence and stroke risk in patients post ICU discharge. Exploratory objectives include to validate a newly designed AF detection algorithm. Objective 1: Validation of a new state-of-the-art machine learning algorithm against the manufactured-approved AF detection algorithm and three best-in-class algorithms. Objective 2: Identify subgroups of patients that are at increased risk of adverse outcomes of new onset atrial fibrillation in ICU compared to those who are not.