| Title: |
Repolarization in bundle branch block, can artificial intelligence offer insights? |
| Authors: |
Salman, M; Kennedy, D; Doggart, P; Mceneany, D |
| Source: |
European Heart Journal - Digital Health ; volume 7, issue Supplement_1 ; ISSN 2634-3916 |
| Publisher Information: |
Oxford University Press (OUP) |
| Publication Year: |
2026 |
| Description: |
Background QT interval interpretation remains challenging in patients with bundle branch block (BBB), where QRS widening prolongs the QT interval due to delayed ventricular depolarization. A validated correction formula, QTm = QTBBB − (50% × QRSBBB), compensates for prolongation of depolarization time due to BBB, , enabling estimation of true repolarization time. However, its clinical impact on automated ECG prioritization systems requires validation. Objective To evaluate the effect of BBB-specific QT correction on automated severity classification and validate algorithm performance in detecting BBB and measuring intervals. Methods We analysed 250 ECGs selected from a proprietary database: 50 BBB cases (25 LBBB, 25 RBBB) and 200 controls (125 with normal conduction, 75 with non-specific QRS widening ≥110 ms). QTBBB and QRSBBB were defined as the longest globally measured QT and QRS intervals on the 12-lead ECG. The PulseAI neural network classified BBB and measured intervals. QT correction (QTm) was applied to BBB cases, followed by Fridericia’s rate adjustment. Severity classifications included: Emergent (≥500 ms), Significant (≥470 ms), Borderline (≥430 ms), and Normal ( |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1093/ehjdh/ztaf143.124 |
| Availability: |
https://doi.org/10.1093/ehjdh/ztaf143.124; https://academic.oup.com/ehjdh/article-pdf/7/Supplement_1/ztaf143.124/66378649/ztaf143.124.pdf |
| Rights: |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Accession Number: |
edsbas.3ED04934 |
| Database: |
BASE |