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| Name | Class |
|---|---|
| University College, London | OTHER |
| Wellcome Trust | OTHER |
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The ANSeR Clinical Investigation is a multi-centre, randomised, controlled, clinical investigation of a standalone decision support Algorithm for Neonatal Seizure Recognition, the ANSER Software system.
This will be an open, two arm, parallel group, randomised, controlled investigation of the ANSeR Software System as a stand-alone neonatal seizure recognition decision support tool. Term neonates requiring EEG monitoring will be stratified by recruiting site and then randomised to receive either EEG monitoring with the ANSeR Software System or EEG monitoring without the ANSeR Software System.
It is proposed that the rate of true detections (sensitivity) of investigation personnel using the ANSeR Software System in clinical practice will be at least 25% higher than that of investigation personnel not using the ANSeR Software System in routine clinical practice. In addition we expect the specificity of investigation personnel using the ANSeR Software System to be no worse than 10% less than that of investigation personnel not using the ANSeR Software System. This should result in more appropriate and timely use of antiepileptic drugs (AED).
Randomisation Immediately following enrolment in the investigation, each participant will be randomly assigned to receive either EEG monitoring with the ANSeR Software System or without the ANSeR Software System. Randomisation will be stratified by recruiting site with a 1:1 allocation ratio to each group. Block randomisation with varying block sizes will be used and the randomisation and allocation will be performed centrally using a web-based electronic system.
Blinding As this is an investigation of a medical device (software), the investigation personnel will be aware of which group the participant is assigned to. The expert panel who are the diagnostic reference standard will be blinded to group allocation. The biostatistician will also be blinded to group allocation during the analysis of the data.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| non ANSeR Software System | No Intervention | Routine clinical EEG monitoring | |
| ANSeR Software System | Experimental | The intended use of the ANSeR Software System is to provide a real time decision support tool to assist in the diagnosis of seizures in neonates (between 36 weeks and 44 weeks corrected age) and to provide a review tool for EEG and seizure analysis. ANSeR is intended to provide a reliable, effective, objective and intuitive means of identifying seizures |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ANSeR Software System | Device | ANSeR Software System a stand alone, software medical device for Neonatal seizure decision support tool |
|
| Measure | Description | Time Frame |
|---|---|---|
| The Seizure Detection Rate for all Neonates enrolled in the investigation arm compared to Seizure Detection Rate for all Neonates in the control arm. | The rate of true seizure detection (sensitivity), as recorded on a Seizure Record form, 25% superior in the investigation arm compared to the control group (usual clinical practice). The Expert Committee will be used as the diagnostic reference standard. | 12-18 months |
| The False Detections per hour (sensitivity) for all Neonates enrolled in the investigation arm compared to the False Detection Rate for all Neonates in the control arm. | The False Detections per hour (specificity), as recorded on a Seizure Record form, 10% superior in the investigation arm compared to the control group (usual clinical practice). The Expert Committee will be used as the diagnostic reference standard. | 12-18 months |
| Measure | Description | Time Frame |
|---|---|---|
| Seizure burden (min) for all Neonates enrolled in the investigation arm compared to Seizure burden (min) for all Neonates in the control arm. | To quantify seizure burden (min) in the investigation arm and control arm. | 12-18 months |
| Number of Neonates administered Anti-epileptic drug (AED) in the investigation arm compared to Number of Neonates administered Anti-epileptic drug (AED) in the control arm. |
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Inclusion Criteria:
Neonates 36 weeks - 44 weeks corrected gestational age in whom EEG monitoring is indicated because they are deemed to be
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Janet Rennie, Doctor | University College London Hospitals | Principal Investigator |
| Geraldine Boylan, PhD | University College Cork, Cork, Ireland | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Cork University Maternity Hospital | Wilton | Cork | Ireland | |||
| Rotunda Maternity Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32861271 | Result | Pavel AM, Rennie JM, de Vries LS, Blennow M, Foran A, Shah DK, Pressler RM, Kapellou O, Dempsey EM, Mathieson SR, Pavlidis E, van Huffelen AC, Livingstone V, Toet MC, Weeke LC, Finder M, Mitra S, Murray DM, Marnane WP, Boylan GB. A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial. Lancet Child Adolesc Health. 2020 Oct;4(10):740-749. doi: 10.1016/S2352-4642(20)30239-X. Epub 2020 Aug 27. | |
| 36398397 |
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| 12-18 months |
| Dublin |
| Ireland |
| University Medical Centre Utrecht, Wilhelmina Children's Hospital | Utrecht | KE 04.123.1, Po Box 85090 | Netherlands |
| Karolinska Institutet and University Hospital | Huddinge | Stockholm County | K78 141 86 | Sweden |
| Barts and the London NHS Trust, | London | E1 1BB | United Kingdom |
| The London and Homerton Hospital | London | E9 6SR. | United Kingdom |
| University College London Hospitals NHS Foundation Trust | London | NW1 2BU | United Kingdom |
| Great Ormond Street Hospital | London | WC1N3JH | United Kingdom |
| Result |
| Pavel AM, O'Toole JM, Proietti J, Livingstone V, Mitra S, Marnane WP, Finder M, Dempsey EM, Murray DM, Boylan GB; ANSeR Consortium. Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic-ischemic encephalopathy. Epilepsia. 2023 Feb;64(2):456-468. doi: 10.1111/epi.17468. Epub 2022 Dec 20. |
| 36683815 | Result | Pavel AM, Mathieson SR, Livingstone V, O'Toole JM, Pressler RM, de Vries LS, Rennie JM, Mitra S, Dempsey EM, Murray DM, Marnane WP, Boylan GB; ANSeR Consortium. Heart rate variability analysis for the prediction of EEG grade in infants with hypoxic ischaemic encephalopathy within the first 12 h of birth. Front Pediatr. 2023 Jan 4;10:1016211. doi: 10.3389/fped.2022.1016211. eCollection 2022. |
| 34626667 | Result | Pavel AM, Rennie JM, de Vries LS, Blennow M, Foran A, Shah DK, Pressler RM, Kapellou O, Dempsey EM, Mathieson SR, Pavlidis E, Weeke LC, Livingstone V, Murray DM, Marnane WP, Boylan GB. Neonatal Seizure Management: Is the Timing of Treatment Critical? J Pediatr. 2022 Apr;243:61-68.e2. doi: 10.1016/j.jpeds.2021.09.058. Epub 2021 Oct 7. |
| ID | Term |
|---|---|
| D012640 | Seizures |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D004827 | Epilepsy |
| D009422 | Nervous System Diseases |
| D009461 | Neurologic Manifestations |
| ID | Term |
|---|---|
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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