Vetter, Victoria L.

Abstract Aims To assess the potential for artificial intelligence-enabled electrocardiogram (AI-ECG) to serve as a long-term cardiac surveillance tool and predict left ventricular systolic dysfunction in childhood cancer patients. Methods and results We assessed performance of our previously established AI-ECG model to predict left ventricular ejection fraction (LVEF) ≤50% and ≤40% in patients with childhood cancer during internal testing (Boston Children’s Hospital) and external validation (Children’s Hospital of Philadelphia). The internal test cohort comprised 447 patients [57% male; age at cancer diagnosis 11.2 (5.4–15.7) years; 1553 ECG–echo pairs at median age 13.5 (IQR 7.7–17.9) years; 6.4% with LVEF ≤50%; 1.3% with LVEF ≤40%], 28% with leukaemia, 16% with lymphoma, 8% with neuroblastoma, 8% with sarcoma, 2% with gastrointestinal cancers, 3% with genitourinary cancers, 6% with central nervous system cancers, 11% with other/unspecified cancers, and 18% with missing/unknown cancer labels. Treatment strategies included anthracyclines (35%), bone marrow transplant (7%), and radiation (1%). The external test cohort comprised 2964 patients [55.4% male; 7054 ECG–echo pairs at median age 11.6 (IQR 6.8–15.1) years; 2.5% with LVEF ≤50%; 0.9% with LVEF ≤40%]. Similar AUROCs (0.80–0.85), sensitivities (0.75–0.82), NPVs (0.986–0.996), and percent predicted negative (51–65%) were obtained across institutions to predict LVEF ≤50%, outperforming a biomarker-based model benchmark. Patients with high AI-ECG risk scores for LVEF ≤50% had higher rates of mortality [hazard ratio 3.1 (95% CI 1.8–5.3), P < 0.001] compared to patients with low AI-ECG risk scores. Conclusion AI-ECG shows promise as a digital biomarker for cardiac surveillance in the vulnerable childhood cancer survivor population.

There are multiple conditions that can make children prone to having a sudden cardiac arrest (SCA) or sudden cardiac death (SCD). Efforts have been made by multiple organizations to screen children for cardiac conditions, but the emphasis has been on screening before athletic competition. This article is an update of the previous American Academy of Pediatrics policy statement of 2012 that addresses prevention of SCA and SCD. This update includes a comprehensive review of conditions that should prompt more attention and cardiology evaluation. The role of the primary care provider is of paramount importance in the evaluation of children, particularly as they enter middle school or junior high. There is discussion about whether screening should find any cardiac condition or just those that are associated with SCA and SCD. This update reviews the 4 main screening questions that are recommended, not just for athletes, but for all children. There is also discussion about how to handle post-SCA and SCD situations as well as discussion about genetic testing. It is the goal of this policy statement update to provide the primary care provider more assistance in how to screen for life-threatening conditions, regardless of athletic status.

Cardiac channelopathies are potentially lethal inherited arrhythmia syndromes and an important cause of sudden cardiac death (SCD) in young athletes. Other cardiac rhythm and conduction disturbances also may indicate the presence of an underlying cardiac disorder. The 12-lead ECG is utilised as both a screening and a diagnostic tool for detecting conditions associated with SCD. Fundamental to the appropriate evaluation of athletes undergoing ECG is an understanding of the ECG findings that may indicate the presence of a pathological cardiac disease. This article describes ECG findings present in primary electrical diseases afflicting young athletes and outlines appropriate steps for further evaluation of these ECG abnormalities. The ECG findings defined as abnormal in athletes were established by an international consensus panel of experts in sports cardiology and sports medicine.