A novel method for patient-specific QTc--modeling QT-RR hysteresis.
BACKGROUND
Cardiac repolarization adaptation to cycle length change is patient dependent and results in complex QT-RR hysteresis. We hypothesize that accurate patient-specific QT-RR curves and rate corrected QT values (QTc) can be derived through patient-specific modeling of hysteresis.


RESULTS
Model development was supported by QT-RR observations from 1959 treadmill tests, allowing extensive exploration of the influences of autonomic function on QT adaptation to rate changes. The methodology quantifies and then removes patient-specific repolarization adaptation rates. The estimated average 95% QT confidence limit was approximately 1 msec for the studied population. The model was validated by comparing QT-RR curves derived from a submaximal exercise protocol with rapid exercise and recovery phases, characterized by high hysteresis, with QT-RR values derived from an incremental stepped protocol that held heart rate constant for 5 minutes at each stage of exercise and recovery.


CONCLUSIONS
The underlying physiologic changes affecting QT dynamics during the transitions from rest to exercise to recovery are quite complex. Nevertheless, a simple patient-specific model, comprising only three parameters and based solely on the preceding history of RR intervals and trend, is sufficient to accurately model QT hysteresis over an entire exercise test for a diverse population. A brief recording of a resting ECG, combined with a short period of submaximal exercise and recovery, provides sufficient information to derive an accurate patient-specific QT-RR curve, eliminating QTc bias inherent in population-based correction formulas.
VA Palo Alto Health Care System, Palo Alto, CA, USA. dave_hadley@comcast.net
David M
DM
Hadley
Victor F
VF
Froelicher
Paul J
PJ
Wang
D000222:Adaptation, Physiological / Q000502:physiology; D005080:Exercise Test; D006329:Heart Conduction System / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008955:Models, Cardiovascular
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