RATIONALE: Current methods assessing clinical risk because of exercise intolerance in patients with cardiopulmonary disease rely on a small subset of traditional variables. Alternative strategies incorporating the spectrum of factors underlying prognosis in at-risk patients may be useful clinically, but are lacking. OBJECTIVE: Use unbiased analyses to identify variables that correspond to clinical risk in patients with exercise intolerance. METHODS AND RESULTS: Data from 738 consecutive patients referred for invasive cardiopulmonary exercise testing at a single center (2011-2015) were analyzed retrospectively (derivation cohort). A correlation network of invasive cardiopulmonary exercise testing parameters was assembled using |r| > 0.5. From an exercise network of 39 variables (ie, nodes) and 98 correlations (ie, edges) corresponding to P < 9.5e^-46 for each correlation, we focused on a subnetwork containing peak volume of oxygen consumption (pVO₂) and 9 linked nodes. K-mean clustering based on these 10 variables identified 4 novel patient clusters characterized by significant differences in 44 of 45 exercise measurements (P < 0.01). Compared with a probabilistic model, including 23 independent predictors of pVO₂ and pVO₂ itself, the network model was less redundant and identified clusters that were more distinct. Cluster assignment from the network model was predictive of subsequent clinical events. For example, a 4.3-fold (P < 0.0001; 95% CI, 2.2-8.1) and 2.8-fold (P = 0.0018; 95% CI, 1.5-5.2) increase in hazard for age- and pVO₂-adjusted all-cause 3-year hospitalization, respectively, were observed between the highest versus lowest risk clusters. Using these data, we developed the first risk-stratification calculator for patients with exercise intolerance. When applying the risk calculator to patients in 2 independent invasive cardiopulmonary exercise testing cohorts (Boston and Graz, Austria), we observed a clinical risk profile that paralleled the derivation cohort. CONCLUSIONS: Network analyses were used to identify novel exercise groups and develop a point-of-care risk calculator. These data expand the range of useful clinical variables beyond pVO₂ that predict hospitalization in patients with exercise intolerance.

To determine whether low ventricular filling pressures are a clinically relevant etiology of unexplained dyspnea on exertion, a database of 619 consecutive, clinically indicated invasive cardiopulmonary exercise tests (iCPETs) was reviewed to identify patients with low maximum aerobic capacity (VO₂max) due to inadequate peak cardiac output (Q_tmax) with normal biventricular ejection fractions and without pulmonary hypertension (impaired: n = 49, VO₂max = 53% predicted [interquartile range (IQR): 47%-64%], Q_tmax = 72% predicted [62%-76%]). These were compared to patients with a normal exercise response (normal: n = 28, VO₂max = 86% predicted [84%-97%], Q_tmax = 108% predicted [97%-115%]). Before exercise, all patients received up to 2 L of intravenous normal saline to target an upright pulmonary capillary wedge pressure (PCWP) of $>$/=5 mmHg. Despite this treatment, biventricular filling pressures at peak exercise were lower in the impaired group than in the normal group (right atrial pressure [RAP]: 6 [IQR: 5-8] vs. 9 [7-10] mmHg, P = 0.004; PCWP: 12 [10-16] vs. 17 [14-19] mmHg, P $<$ 0.001), associated with decreased stroke volume (SV) augmentation with exercise (+13 ± 10 [standard deviation (SD)] vs. +18 ± 10 mL/m(2), P = 0.014). A review of hemodynamic data from 23 patients with low RAP on an initial iCPET who underwent a second iCPET after saline infusion (2.0 ± 0.5 L) demonstrated that 16 of 23 patients responded with increases in Q_tmax ([+24% predicted [IQR: 14%-34%]), VO₂max (+10% predicted [7%-12%]), and maximum SV (+26% ± 17% [SD]). These data suggest that inadequate ventricular filling related to low venous pressure is a clinically relevant cause of exercise intolerance.

Metabolic adaptation to hypoxia is critical for survival in metazoan species for which reason they have developed cellular mechanisms for mitigating its adverse consequences. Here, we have identified L-2-hydroxyglutarate (L2HG) as a universal adaptive determinant of the hypoxia response. L2HG is a metabolite of unknown function produced by the reduction of mitochondrial 2-oxoglutarate by malate dehydrogenase. L2HG accumulates in response to increases in 2-oxoglutarate, which occur as a result of tricarboxylic acid cycle dysfunction and increased mitochondrial reducing potential. These changes are closely coupled to cellular redox homeostasis, as increased cellular L2HG inhibits electron transport and glycolysis to offset the adverse consequences of mitochondrial reductive stress induced by hypoxia. Thus, L2HG couples mitochondrial and cytoplasmic energy metabolism in a model of cellular redox regulation.