title: How to program rate responsive pacemakers.
abstract: Because oxygen uptake (VO2) increases linearly with heart rate during exercise, the oxygen pulse reserve (OPR) method (VO2 reserve divided by heart rate reserve) may provide a valid guide for rate responsive parameter tailoring. Using custom-made software (Pacing Rate Profile Software [PRPS]) it is possible to predict the exercise pacing rate profile with significant accuracy, according to the patient's functional class when ergospirometry apparatus is not available for a cardiopulmonary stress test (CPX). PRPS for Windows is based on the OPR method and some known workload/metabolic cost of exercise relationships during effort. The present study had two aims; first, to evaluate the reliability of PRPS in accurately predicting pacing rate profiles; and second, the suitability of activity and metabolic rate responsive sensors in supplying pacing rates sufficiently near to those predicted using CPX or PRPS. To test the reliability of PRPS we studied 244 patients, NYHA Class I-II, under two different stress test protocols. In one, the bicycle protocol (25 W, 2-minute steps), we tested 137 normal patients (94 men and 43 women, mean age 67 +/- 15 years). Sixty-eight of these were simultaneously CPX tested. PRPS predicted pacing rates were matched against the patients' sinus rhythms or their theoretical CPX measured VO2 heart rates (OPR method). Linear regression analysis was highly significant (r = 0.93 and r = 0.97, respectively). The other, the treadmill protocol, consisted of three different protocols. (1) Speed Incremental Treadmill Stress Test (SITST): 57 patients underwent CPX (33 men and 24 women, mean age 67 +/- 15 years, NYHA Class I-II). All had been pacemaker implanted for SSS and/or advanced atrioventricular block (AVB). PRPS pacing rates were matched against CPX VO2 OPR calculated heart rates (r = 0.93), (linear regression analysis). (2) CAEP: 30 patients underwent CPX (26 men and 4 women, mean age 61 +/- 11 years, NYHA Class I-II). Thirteen of them had been pacemaker implanted for SSS and/or advanced AVB. In all 30 patients the PRPS rates were matched against CPX VO2 calculated rates (r = 0.90). In the 17 normal nonimplanted patients, the PRPS rates were also matched against sinus rhythms, (r = 0.80). (3) Weber: 20 patients underwent CPX (16 men and 4 women, mean age 68 +/- 8 years, NYHA Class I-II). As above, in six normal nonimplanted patients, statistical analysis between PRPS rates and sinus rhythms was performed (r = 0.89). The comparison between PRPS theoretical pacing rates and VO2 predicted rates in all 20 patients was also statistically significant (r = 0.93). Finally, to test the reliability of PRPS also in NYHA Class III-IV patients, we tested 22 implanted patients (15 men and 7 women, mean age 70 +/- 9 years) and compared PRPS predicted rates against VO2 CPX measured rates (r = 0.92). To determine if the wide variety of RR pacers were able to supply pacing rates near to those predicted, whether by means of CPX or PRPS, we studied a total of 89 patients: 49 of these (26 men and 23 women, mean age 66 +/- 12 years) had been implanted with activity sensors; 12 patients (11 men and one woman, mean age 70 +/- 7 years) had been implanted with metabolic sensors, and finally 28 patients (19 men and 9 women, mean age 70 +/- 12 years) had been implanted with dual sensors (activity + QT or minute ventilation). Linear regression analysis showed r = 0.93 for activity sensors, r = 0.94 for metabolic sensors, and r = 0.92 for dual sensor. In conclusion, when rate responsive pacing causes symptoms or functional impairment, physicians must provide a personalized rate response tailoring derived from precise, simple physiological testing. OPR is an easy physiological method for tailoring rate response settings, suitable for activity and metabolic sensors. When ergospirometry apparatus is not available, PRPS can successfully replace CPX testing for tailoring.
authors.affiliation: Cardiology Department, Maggiore H., I.R.C.C.S., Milan, Italy.
authors.forename: E M
authors.initials: EM
authors.lastname: Greco
authors.forename: S
authors.initials: S
authors.lastname: Guardini
authors.forename: M
authors.initials: M
authors.lastname: Ferrario
authors.forename: S
authors.initials: S
authors.lastname: Romano
mesh_terms: D000368:Aged; D002304:Cardiac Pacing, Artificial / Q000379:methods*; D005080:Exercise Test / Q000379:methods; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D010101:Oxygen Consumption / Q000502:physiology; D010138:Pacemaker, Artificial; D015203:Reproducibility of Results; D012984:Software