Biomedical subjects
Publications and source records attributed to Heikki Huikuri.
The power spectra of the heart rate variability frequency bands, analyzed from 24-hour ECG recordings, did not change 12 months after bilateral subthalamic nucleus operation in 14 patients with Parkinson's disease.
BACKGROUND: Decreased vagal activity after myocardial infarction results in reduced heart-rate variability and increased risk of death. To distinguish between vagal and sympathetic factors that affect heart-rate variability, we used a signal-processing algorithm to separately characterise deceleration and acceleration of heart rate. We postulated that diminished deceleration-related modulation of heart rate is an important prognostic marker. Our prospective hypotheses were that deceleration capacity is a better predictor of risk than left-ventricular ejection fraction (LVEF) and standard deviation of normal-to-normal intervals (SDNN). METHODS: We quantified heart rate deceleration capacity by assessing 24-h Holter recordings from a post-infarction cohort in Munich (n=1455). We blindly validated the prognostic power of deceleration capacity in post-infarction populations in London, UK (n=656), and Oulu, Finland (n=600). We tested our hypotheses by assessment of the area under the receiver-operator characteristics curve (AUC). FINDINGS: During a median follow-up of 24 months, 70 people died in the Munich cohort and 66 in the London cohort. The Oulu cohort was followed-up for 38 months and 77 people died. In the London cohort, mean AUC of deceleration capacity was 0.80 (SD 0.03) compared with 0.67 (0.04) for LVEF and 0.69 (0.04) for SDNN. In the Oulu cohort, mean AUC of deceleration capacity was 0.74 (0.03) compared with 0.60 (0.04) for LVEF and 0.64 (0.03) for SDNN (p<0.0001 for all comparisons). Stratification by dichotomised deceleration capacity was especially powerful in patients with preserved LVEF (p<0.0001 in all cohorts). INTERPRETATION: Impaired heart rate deceleration capacity is a powerful predictor of mortality after myocardial infarction and is more accurate than LVEF and the conventional measures of heart-rate variability.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Prediction of the onset of Torsade de Pointes (TdP) is a challenge for clinicians, because the list of drugs affecting myocardial repolarisation is continuously increasing. Alterations in the activity of autonomic nervous system and abnormalities in ventricular repolarisation are key features both as triggers and as markers for vulnerability to TdP. Recent molecular genetic studies have shown that autonomic nervous system has channel and gene specific influences on vulnerability to TdP. New analysis techniques in quantifying the dispersion of repolarisation have also been developed. QT interval dispersion, defined as a difference between the maximum and minimum QT interval measured from the standard 12-lead electrocardiogram (ECG), is one such method. In preliminary studies, QT dispersion has provided more accurate information on the risk for TdP than the measurement of the length of QT interval from a single ECG lead. Unfortunately, QT dispersion is entailed with some conceptual and methodological problems, which impairs its widespread clinical utility in risk stratification. Despite advances in the understanding of the role of autonomic nervous system as a trigger of TdP in specific gene mutations and improved clinical methods in detecting repolarisation abnormalities, accurate and reliable prediction of the onset of TdP still remains an unresolved clinical problem in individual cases.