A Photoplethysmography-Based Machine Learning Algorithm for Early Atrial Fibrillation Detection: A Prospective Validation Study (HeartCore AF)
Prospective Validation of a Machine-Learning Algorithm Using Photoplethysmography Signals for Early Detection of Atrial Fibrillation During Remote Telemonitoring
調査の概要
詳細な説明
Atrial fibrillation (AF) and heart failure (HF) frequently coexist and share a bidirectional causal relationship; their concurrence is associated with worse clinical outcomes. Early detection of AF may enable timely intervention and improve outcomes. This study is prospectively validating a machine-learning algorithm for AF detection from PPG signals, intended for integration into the Seerlinq remote monitoring platform. This algorithm builds on the same core PPG signal-processing technology as Seerlinq's HeartCore device (a CE-certified, Class IIb device under the EU MDR that monitors left ventricular filling pressures in heart failure patients). It is a stand-alone algorithm designed specifically to detect clinically relevant (≥ 30s) atrial fibrillation.
Validation of the algorithm will proceed in three stages: (1) internal cross-validation; (2) external validation against an independent cohort with paired PPG-ECG recordings, to confirm generalizability; and (3) validation in a cohort of patients with paroxysmal atrial fibrillation and frequent sinus-AF transitions, to assess performance during clinically challenging rhythm changes.
The study is enrolling toward an estimated 1,000 unique PPG recordings. A 12-lead ECG is used to confirm cardiac rhythm classification (gold standard) as the reference for evaluating algorithm performance.
研究の種類
入学 (推定)
連絡先と場所
研究連絡先
- 名前：Marta Kollárová, MSc., PhD.
- 電話番号：+421 950 896 026
- メール：marta.kollarova@premedix.org
研究場所
-
-
-
Bratislava、スロバキア
- 募集
- PreMedix
-
コンタクト：
- Allan Bohm, M.D., MSc. PhD.
- 電話番号：+421 907 411 499
- メール：allan.bohm@premedix.org
-
主任研究者：
- Allan Bohm, M.D., MSc., PhD.
-
-
参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
サンプリング方法
調査対象母集団
説明
Inclusion Criteria:
- Adults ≥18 years with a diagnosis of heart failure (HFrEF, HFmrEF, or HFpEF)
- 12-lead ECG performed to confirm cardiac rhythm classification (AF vs. non-AF)
Exclusion Criteria:
- Missing a valid PPG recording
研究計画
研究はどのように設計されていますか？
デザインの詳細
コホートと介入
グループ/コホート |
介入・治療 |
|---|---|
|
Documented AF
HF patients with a history of permanent/paroxysmal AF and AF documented on 12-lead ECG at enrollment
|
The PPG-based atrial fibrillation detection algorithm is a non-invasive signal processing approach that analyzes photoplethysmographic waveforms obtained during remote monitoring.
The algorithm evaluates pulse-to-pulse variability, waveform characteristics, and signal quality parameters to identify irregular rhythm patterns associated with atrial fibrillation and provide early detection of potential arrhythmic events.
|
|
Non-AF
HF patients in sinus rhythm on the index 12-lead ECG with no prior documented AF episodes
|
The PPG-based atrial fibrillation detection algorithm is a non-invasive signal processing approach that analyzes photoplethysmographic waveforms obtained during remote monitoring.
The algorithm evaluates pulse-to-pulse variability, waveform characteristics, and signal quality parameters to identify irregular rhythm patterns associated with atrial fibrillation and provide early detection of potential arrhythmic events.
|
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
時間枠 |
|---|---|
|
Diagnostic accuracy (area under the ROC curve) of the PPG-based machine-learning algorithm for detecting clinically relevant AF (≥ 30s), compared with gold-standard 12-lead ECG
時間枠：Through study completion (estimated November 2026)
|
Through study completion (estimated November 2026)
|
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Sensitivity and specificity of the algorithm at the Youden-optimal threshold
時間枠：Through study completion (estimated November 2026)
|
Through study completion (estimated November 2026)
|
|
|
Positive predictive value and negative predictive value
時間枠：Through study completion (estimated November 2026)
|
Through study completion (estimated November 2026)
|
|
|
Average precision
時間枠：Through study completion (estimated November 2026)
|
area under the precision-recall curve
|
Through study completion (estimated November 2026)
|
|
Model calibration
時間枠：Through study completion (estimated November 2026)
|
e.g., calibration curve / Brier score
|
Through study completion (estimated November 2026)
|
|
Matthews correlation coefficient
時間枠：Through study completion (estimated November 2026)
|
Through study completion (estimated November 2026)
|
|
|
Overall classification accuracy
時間枠：Through study completion (estimated November 2026)
|
Through study completion (estimated November 2026)
|
|
|
Specificity and false-positive rate in the subgroup with frequent atrial/ventricular extrasystoles
時間枠：Through study completion (estimated November 2026)
|
Through study completion (estimated November 2026)
|
|
|
Accuracy of AF detection during sinus-AF transitions at the individual patient level
時間枠：Through study completion (estimated November 2026)
|
Through study completion (estimated November 2026)
|
協力者と研究者
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- HeartCoreAF01
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
IPD プランの説明
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。