A multivariable index for grading exercise gas exchange severity in patients with pulmonary arterial hypertension and heart failure

Psychophysiological Models to Identify and Monitor Elderly with a Cardiovascular Condition: The Added Value of Psychosocial Parameters to Routinely Applied Physiological Assessments

The steadily growing elderly population calls for efficient, reliable and preferably ambulant health supervision. Since cardiovascular risk factors interact with psychosocial strain (e.g., depression), we investigated the potential contribution of psychosocial factors in discriminating generally healthy elderly from those with a cardiovascular condition, on and above routinely applied physiological assessments. Fifteen elderly (aged 60 to 88) with a cardiovascular diagnosis were compared to fifteen age and gender matched healthy peers. Six sequential standardized lab assessments were conducted (one every two weeks), including an autonomic test battery, a 6-min step test and questionnaires covering perceived psychological state and experiences over the previous two weeks. Specific combinations of physiological and psychological factors (most prominently symptoms of depression) effectively predicted (clinical) cardiovascular markers. Additionally, a highly significant prognostic model was found, including depressive symptoms, recently experienced negative events and social isolation. It appeared slightly superior in identifying elderly with or without a cardiovascular condition compared to a model that only included physiological parameters. Adding psychosocial parameters to cardiovascular assessments in elderly may consequently provide protocols that are significantly more efficient, relatively comfortable and technologically feasible in ambulant settings, without necessarily compromising prognostic accuracy.

The effect of remote ischemic pre-conditioning on pulmonary vascular pressure and gas exchange in healthy humans during hypoxia

This study investigated whether rIPC alters the typical changes in pulmonary arterial pressure, pulmonary gas exchange associated with exercise in hypoxia.

METHODS

16 healthy adults were randomized to either rIPC treatment (n = 8) or control (n = 8). Afterward, subjects performed supine ergometry at constant load (30 W, 40˜50 rpm) for 25 min during hypoxia (12.5% O₂). Following a 90˜120 min rest, either rIPC or sham treatment was performed, which was then followed by post-assessment exercise. Throughout exercise, pulmonary arterial systolic pressure (PASP) and mean pulmonary arterial pressure (mPAP) were measured via echocardiography, while pulmonary gas exchange was being assessed.

RESULTS

The rICP group demonstrated improved PASP and mPAP (p < 0.05), whereas the control group did not. Additionally, breathing efficiency (V_E/V_CO2) and end-tidal CO₂ (PET_CO2) were improved in rIPC group (p < 0.05), but not in controls.

CONCLUSION

These data suggest that rIPC contributes to reduced pulmonary arterial pressure, and improved pulmonary gas exchange during hypoxic exercise. However, follow-up studies are needed to apply these findings to patient care settings.

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.

Pulmonary Hypertension and Cardiopulmonary Exercise in Heart Failure

In heart failure (HF), pulmonary hypertension (PH) is initially associated with a rise in the left ventricular filling pressure. PH is defined by pulmonary hemodynamic measurements including pulmonary capillary wedge pressure, mean pulmonary arterial pressure and pulmonary vascular resistance. Eventually, PH in HF may become more of a reactive process. Although the mechanism of the reactive PH development is not clearly understood, vascular dysfunction induced by remodeling, vasoactive substances and genetic variation appear to contribute significantly to this form of PH. Noninvasive cardiopulmonary exercise testing has been extensively utilized to assess disease severity in HF patients. It provides integrated information that is dependent on cardiopulmonary hemodynamics, lung mechanics, breathing pattern and strategy. In this review, we will discuss the mechanisms of PH development in HF and how noninvasive gas exchange measures obtained with submaximal exercise are influenced by PH in this population.

Ventilatory gas exchange and early response to cardiac resynchronization therapy

BACKGROUND

Cardiac resynchronization therapy (CRT) is an accepted intervention for chronic heart failure (HF), although approximately 30% of patients are non-responders. The purpose of this study was to determine whether exercise respiratory gas exchange obtained before CRT implantation predicts early response to CRT.

METHODS

Before CRT implantation, patients were assigned to either a mild-moderate group (Mod G, n = 33, age 67 ± 10 years) or a moderate-severe group (Sev G, n = 31, age 67 ± 10 years), based on abnormalities in exercise gas exchange. Severity of impaired gas exchange was based on a score from the measures of VE/VCO(2) slope, resting PETCO(2) and change of PETCO(2) from resting to peak. All measurements were performed before and 3 to 4 months after CRT implantation.

RESULTS

Although Mod G did not have improved gas exchange (p > 0.05), Sev G improved significantly (p < 0.05) post-CRT. In addition, Mod G did not show improved right ventricular systolic pressure (RSVP; pre vs post: 37 ± 14 vs 36 ± 11 mm Hg, p > 0.05), yet Sev G showed significantly improved RVSP, by 23% (50 ± 14 vs 42 ± 12 mm Hg, p < 0.05). Both groups had improved left ventricular ejection fraction (p < 0.05), New York Heart Association class (p < 0.05) and quality of life (p < 0.05), but no significant differences were observed between groups (p > 0.05). No significant changes were observed in brain natriuretic peptide in either group post-CRT.

CONCLUSION

Based on pre-CRT implantation ventilatory gas exchange, subjects with the most impaired values appeared to have more improvement post-CRT, possibly associated with a decrease in RVSP.