Dataset Information

Determinants of maximal oxygen uptake in patients with heart failure.

ABSTRACT:

Aims

Maximum oxygen uptake (VO_2max ) is an essential parameter to assess functional capacity of patients with heart failure (HF). We aimed to identify clinical factors that determine its value, as they have not been well characterized yet.

Methods

We conducted a retrospective, observational, single-centre study of 362 consecutive patients with HF who underwent cardiopulmonary exercise testing (CPET) as part of standard clinical assessment since 2009-2019. CPET was performed on treadmill, according to Bruce's protocol (n = 360) or Naughton's protocol (n = 2). We performed multivariable linear regression analyses in order to identify independent clinical predictors associated with peak VO_2max .

Results

Mean age of study patients was 57.3 ± 10.9 years, mean left ventricular ejection fraction was 32.8 ± 14.2%, and mean VO_2max was 19.8 ± 5.2 mL/kg/min. Eighty-nine (24.6%) patients were women, and 114 (31.5%) had ischaemic heart disease. Multivariable linear regression analysis identified six independent clinical predictors of VO_2max , including NYHA class (B coefficient = -2.585; P < 0.001), age (B coefficient per 1 year = -0.104; P < 0.001), tricuspid annulus plane systolic excursion (B coefficient per 1 mm = +0.209; P < 0.001), body mass index (B coefficient per 1 kg/m² = -0.172; P = 0.002), haemoglobin (B coefficient per 1 g/dL = +0.418; P = 0.007) and NT-proBNP (B coefficient per 1000 pg/mL = -0.142; P = 0.019).

Conclusions

The severity of HF (NYHA class, NT-proBNP) as well as age, body composition and haemoglobin levels influence significantly exercise capacity. In patients with HF, the right ventricular systolic function is of greater importance for the physical capacity than the left ventricular systolic function.

SUBMITTER: Roibal Pravio J

PROVIDER: S-EPMC8120347 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:We analysed the importance of systemic and peripheral arteriovenous O2 difference ( a-v¯O2 difference and a-vf O2 difference, respectively) and O2 extraction fraction for maximal oxygen uptake ( V˙O2max ). Fick law of diffusion and the Piiper and Scheid model were applied to investigate whether diffusion versus perfusion limitations vary with V˙O2max . Articles (n = 17) publishing individual data (n = 154) on V˙O2max , maximal cardiac output ( Q˙max ; indicator-dilution or the Fick method), a-v¯O2 difference (catheters or the Fick equation) and systemic O2 extraction fraction were identified. For the peripheral responses, group-mean data (articles: n = 27; subjects: n = 234) on leg blood flow (LBF; thermodilution), a-vf O2 difference and O2 extraction fraction (arterial and femoral venous catheters) were obtained. Q˙max and two-LBF increased linearly by 4.9-6.0 L · min-1 per 1 L · min-1 increase in V˙O2max (R2 = .73 and R2 = .67, respectively; both P < .001). The a-v¯O2 difference increased from 118-168 mL · L-1 from a V˙O2max of 2-4.5 L · min-1 followed by a reduction (second-order polynomial: R2 = .27). After accounting for a hypoxemia-induced decrease in arterial O2 content with increasing V˙O2max (R2 = .17; P < .001), systemic O2 extraction fraction increased up to ~90% ( V˙O2max : 4.5 L · min-1 ) with no further change (exponential decay model: R2 = .42). Likewise, leg O2 extraction fraction increased with V˙O2max to approach a maximal value of ~90-95% (R2 = .83). Muscle O2 diffusing capacity and the equilibration index Y increased linearly with V˙O2max (R2 = .77 and R2 = .31, respectively; both P < .01), reflecting decreasing O2 diffusional limitations and accentuating O2 delivery limitations. In conclusion, although O2 delivery is the main limiting factor to V˙O2max , enhanced O2 extraction fraction (≥90%) contributes to the remarkably high V˙O2max in endurance-trained individuals.

Project description:BackgroundTo estimate oxygen uptake (VO2) from cardiopulmonary exercise testing (CPX) using simultaneously recorded seismocardiogram (SCG) and electrocardiogram (ECG) signals captured with a small wearable patch. CPX is an important risk stratification tool for patients with heart failure (HF) owing to the prognostic value of the features derived from the gas exchange variables such as VO2. However, CPX requires specialized equipment, as well as trained professionals to conduct the study.Methods and resultsWe have conducted a total of 68 CPX tests on 59 patients with HF with reduced ejection fraction (31% women, mean age 55 ± 13 years, ejection fraction 0.27 ± 0.11, 79% stage C). The patients were fitted with a wearable sensing patch and underwent treadmill CPX. We divided the dataset into a training-testing set (n = 44) and a separate validation set (n = 24). We developed globalized (population) regression models to estimate VO2 from the SCG and ECG signals measured continuously with the patch. We further classified the patients as stage D or C using the SCG and ECG features to assess the ability to detect clinical state from the wearable patch measurements alone. We developed the regression and classification model with cross-validation on the training-testing set and validated the models on the validation set. The regression model to estimate VO2 from the wearable features yielded a moderate correlation (R2 of 0.64) with a root mean square error of 2.51 ± 1.12 mL · kg-1 · min-1 on the training-testing set, whereas R2 and root mean square error on the validation set were 0.76 and 2.28 ± 0.93 mL · kg-1 · min-1, respectively. Furthermore, the classification of clinical state yielded accuracy, sensitivity, specificity, and an area under the receiver operating characteristic curve values of 0.84, 0.91, 0.64, and 0.74, respectively, for the training-testing set, and 0.83, 0.86, 0.67, and 0.92, respectively, for the validation set.ConclusionsWearable SCG and ECG can assess CPX VO2 and thereby classify clinical status for patients with HF. These methods may provide value in the risk stratification of patients with HF by tracking cardiopulmonary parameters and clinical status outside of specialized settings, potentially allowing for more frequent assessments to be performed during longitudinal monitoring and treatment.