Impact of closed loop stimulation on prognostic cardiopulmonary variables in patients with chronic heart failure and severe chronotropic incompetence: a pilot, randomized, crossover study.

AIMS: Clinical effects of rate-adaptive pacing in heart failure patients with chronotropic incompetence (CI) undergoing cardiac resynchronization therapy (CRT) remain unclear. Closed loop stimulation (CLS) is a new rate-adaptive sensor in CRT devices. We evaluated the effectiveness of CLS in CRT patients with severe CI, focusing primarily on key prognostic variables assessed by cardiopulmonary exercise (CPX) testing. METHODS AND RESULTS: In the randomized, crossover, multicentre BIO|CREATE study, 20 CRT patients with severe CI and NYHA Class II/III (60%/40%) were randomized 1:1 to the sequence DDD-40 mode to DDD-CLS mode, or the sequence DDD-CLS mode to DDD-40 mode (1 month in each mode). Patients underwent symptom-limited treadmill-based CPX test in each mode. An improvement (decrease) of the ventilatory efficiency (VE) slope of ≥5% during CLS was regarded as positive response to CLS. Seventeen patients with full data sets had a mean intra-individual VE slope change of -1.8 ± 3.0 (-4.1%) with CLS (P = 0.23). Eight patients (47%) were CLS responders, with a -6.1 ± 2.7 (-16.4%) slope change (P = 0.029). Compared to non-responders, CLS responders had a higher left ventricular (LV) ejection fraction (46 ± 3 vs. 36 ± 9%; P = 0.0070), smaller end-diastolic LV volume (121 ± 34 vs. 181 ± 41 mL; P = 0.0085), smaller end-systolic LV volume (65 ± 23 vs. 114 ± 39 mL; P = 0.0076), and were predominantly in NYHA Class II (P = 0.0498). CONCLUSION: The data of the present pilot study are compatible with the notion that CLS activation may improve VE slope in CRT patients with severe CI and less advanced heart failure. Further research is needed to determine the long-term clinical outcomes of CLS.

Streamlining cardiopulmonary exercise testing for use as a screening and tracking tool in primary care.

Cardiopulmonary exercise testing (CPET) using a spectrum of different approaches demonstrates usefulness for objectively assessing patient disease severity in clinical and research settings. Still, an absence of trained specialists and/or improper data interpretation techniques can pose major limitations to the effective use of CPET for the clinical classification of patients. This study aimed to test an automated disease likelihood scoring algorithm system based on cardiopulmonary responses during a simplified step-test protocol. For patients with heart failure (HF), pulmonary hypertension (PAH), obstructive lung disease (OLD), or restrictive lung disease (RLD), we compared patient scores stratified into one of four "silos" generated from our novel algorithm system against patient evaluations provided by expert clinicians. Patients with HF (n = 12), PAH (n = 9), OLD (n = 16), or RLD (n = 10) performed baseline pulmonary function testing followed by submaximal step-testing. Breath-by-breath measures of ventilation and gas exchange, in addition to oxygen saturation and heart rate were collected continuously throughout testing. The algorithm demonstrated close alignment with patient assessments provided by clinical specialists: HF (r = 0.89, P < 0.01); PAH (r = 0.88, P < 0.01); OLD (r = 0.70, P < 0.01); and RLD (r = 0.88, P < 0.01). Furthermore, the algorithm was capable of differentiating major disease from other disease pathologies. Thus, in a clinically relevant manner, these data suggest this simplified automated disease algorithm scoring system used during step-testing to identify the likelihood that patients have HF, PAH, OLD, or RLD closely correlates with patient assessments conducted by trained clinicians.

Algorithm for Predicting Disease Likelihood From a Submaximal Exercise Test.

We developed a simplified automated algorithm to interpret noninvasive gas exchange in healthy subjects and patients with heart failure (HF, n = 12), pulmonary arterial hypertension (PAH, n = 11), chronic obstructive lung disease (OLD, n = 16), and restrictive lung disease (RLD, n = 12). They underwent spirometry and thereafter an incremental 3-minute step test where heart rate and SpO2 respiratory gas exchange were obtained. A custom-developed algorithm for each disease pathology was used to interpret outcomes. Each algorithm for HF, PAH, OLD, and RLD was capable of differentiating disease groups (P < .05) as well as healthy cohorts (n = 19, P < .05). In addition, this algorithm identified referral pathology and coexisting disease. Our primary finding was that the ranking algorithm worked well to identify the primary referral pathology; however, coexisting disease in many of these pathologies in some cases equally contributed to the cardiorespiratory abnormalities. Automated algorithms will help guide decision making and simplify a traditionally complex and often time-consuming process.

Effects of atrioventricular and interventricular delays on gas exchange during exercise in patients with heart failure.

BACKGROUND: Cardiac resynchronization therapy (CRT) has been an important treatment for heart failure. However, it is controversial as to whether an individualized approach to altering AV and VV timing intervals would improve outcomes. Changes in respiratory patterns and gas exchange are dynamic and may be influenced by timing delays. Light exercise enhances the heart and lung interactions. Thus, in this study we investigated changes in non-invasive gas exchange by altering AV and VV timing intervals during light exercise. METHODS: Patients (n = 20, age 66 ± 9 years) performed two walking tests post-implantation. The protocol evaluated AV delays (100, 120, 140, 160 and 180 milliseconds), followed by VV delays (0, -20 and -40 milliseconds) while gas exchange was assessed. RESULTS: There was no consistent group pattern of change in gas exchange variables across AV and VV delays (p > 0.05). However, there were modest changes in these variables on an individual basis with variations in VE/VCO2 averaging 10%; O2 pulse 11% and PETCO2 5% across AV delays, and 4%, 8% and 2%, respectively, across VV delays. Delays that resulted in the most improved gas exchange differed from nominal in 17 of 20 subjects. CONCLUSION: Gas exchange measures can be improved by optimization of AV and VV delays and thus could be used to individualize the approach to CRT optimization.