Recent trends in cardiac electrophysiology and catheter ablation in New Zealand

Understanding PITX2-Dependent Atrial Fibrillation Mechanisms through Computational Models

Atrial fibrillation (AF) is a common arrhythmia. Better prevention and treatment of AF are needed to reduce AF-associated morbidity and mortality. Several major mechanisms cause AF in patients, including genetic predispositions to AF development. Genome-wide association studies have identified a number of genetic variants in association with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene for the homeobox transcription PITX2. Because of the inherent complexity of the human heart, experimental and basic research is insufficient for understanding the functional impacts of PITX2 variants on AF. Linking PITX2 properties to ion channels, cells, tissues, atriums and the whole heart, computational models provide a supplementary tool for achieving a quantitative understanding of the functional role of PITX2 in remodelling atrial structure and function to predispose to AF. It is hoped that computational approaches incorporating all we know about PITX2-related structural and electrical remodelling would provide better understanding into its proarrhythmic effects leading to development of improved anti-AF therapies. In the present review, we discuss advances in atrial modelling and focus on the mechanistic links between PITX2 and AF. Challenges in applying models for improving patient health are described, as well as a summary of future perspectives.

Regional variation in cardiac implantable electronic device implants trends in New Zealand over the past decade (ANZACS-QI 54)

BACKGROUND

Permanent pacemaker (PPM) and implantable cardioverter defibrillator (ICD) implant rates have increased in New Zealand over the past decade. This study aims to provide a contemporary analysis of regional variation in implant rates.

METHOD

New PPM and ICD implants in patients ≥15 years were identified for ten years (2009 to 2018) using procedure coding in the National Minimum Datasets, which collects all New Zealand public hospital admissions. Age-standardised new implant rates per million adult population were calculated for each of the four regions (Northern, Midland, Central and Southern) and the 20 district health boards (DHBs) across those regions. Trend analysis was performed using joinpoint regression.

RESULTS

New PPM implant rates increased nationally by 3.4%/year (p < 0.001). The Northern region had the highest new PPM implant rate, increasing by 4.5%/year (p < 0.001). Excluding DHBs with <50 000 people, the new PPM implant rate for 2017/2018 was highest in Counties Manukau DHB (854.3/million, 95% CI: 774.9-933.6/million) and lowest in Canterbury DHB (488.6/million, 95% CI: 438.1-539.0/million). New ICD implant rates increased nationally by 3.0%/year (p = 0.002). The Midland region had the highest new ICD implant rate, increasing by 3.8%/year (p = 0.013). Excluding DHBs with <50 000 people, the new ICD implant rate for 2017/2018 was highest in Bay of Plenty DHB (228.5/million, 95% CI: 180.4-276.6/million) and lowest in Canterbury DHB (90.2/million, 95% CI: 69.9-110.4/million).

CONCLUSION

There was significant variation in PPM and ICD implant rates across regions and DHBs, suggesting potential inequity in patient access across New Zealand. This article is protected by copyright. All rights reserved.