Estimated VO2 Max Research Articles

Evaluating Seismocardiography as a Non-Exercise Method for Estimating Maximal Oxygen Uptake

Background: The value of maximal oxygen uptake (VO2MAX) is a key health indicator. Usually, VO2MAX is determined with cardiopulmonary exercise testing (CPET), which is cumbersome and time-consuming, making it impractical in many testing scenarios. The aim of this study is to validate a novel seismocardiography sensor (Seismofit®, VentriJect DK, Hellerup, Denmark) for non-exercise estimation of VO2MAX. Methods: A cohort of 94 healthy subjects (52% females, 48.2 (8.7) years old) were included in this study. All subjects performed an ergometer CPET. Seismofit® measurements were obtained 10 and 5 min before CPET in resting condition and 5 min after exhaustion. Results: The CPET VO2MAX was 37.2 (8.6) mL/min/kg, which was not different from the two first Seismofit® estimates at 37.5 (8.1) mL/min/kg (p = 0.28) and 37.3 (7.8) mL/min/kg (p = 0.66). Post-exercise Seismofit® was 33.8 (7.1) mL/min/kg (p < 0.001). The correlation between the CPET and the Seismofit® was r = 0.834 and r = 0.832 for the two first estimates, and the mean average percentage error was 11.4% and 11.2%. Intraclass correlation coefficients between the first and second Seismofit® measurement was 0.993, indicating excellent test-retest reliability. Conclusion: The novel Seismofit® VO2MAX estimate correlates well with CPET VO2MAX, and the accuracy is acceptable for general health assessment. The repeatability of Seismofit® estimates obtained at rest was very high.

EP146 - Feasibility Study: SmartWatch and Rockport Walk Test safely measures estimated VO2 Max

Abstract Aims To assess feasibility and safety of estimating VO2 max using a SmartWatch and the Rockport Walk Test, and to assess robustness of the protocol for a pilot study on oesophageal adenocarcinoma patients. Methods This prospective feasibility study included ASA grade 1 adults with a SmartWatch. Participants walked 1 mile on the flat, and end heart rate and time taken were recorded both via SmartWatch and manually. Pre- and post-exercise questionnaires provided. Estimated VO2 calculated using the Rockport formula. Results Ten participants (five female), mean age 32.8 (25-37). Mean heart rate via SmartWatch 107.25bpm (80-133) and manually 104.6bpm (84-120). Mean time to complete 1 mile 15:17 minutes (13:08 – 16:48). Average estimated VO2 max 43.6 (41.57- 50.03). Pre-activity 100% of participants found instructions clear and easy-to-follow, and were confident to undertake the activity and complete it safely. Although pre-activity 20% of participants were not confident in finding a suitable flat location and 10% not confident with the technology, in the post-activity survey 100% of participants found it easy to find a suitable location and easy to measure, record and upload their results. One user highlighted difficulty with manually measuring heart rate, and another noted challenges with road crossings disrupting their walk. Conclusions It is feasible to measure estimated VO2 max remotely using wearable technology and a validated test such as Rockport Walk Test in healthy adults. This study highlighted several areas of protocol improvement to deploy the study in oesophageal cancer patients to minimise potential risks and optimise safety and usability.

Assessing the Accuracy of Smartwatch-Based Estimation of Maximum Oxygen Uptake Using the Apple Watch Series 7: Validation Study.

Determining maximum oxygen uptake (VO2max) is essential for evaluating cardiorespiratory fitness. While laboratory-based testing is considered the gold standard, sports watches or fitness trackers offer a convenient alternative. However, despite the high number of wrist-worn devices, there is a lack of scientific validation for VO2max estimation outside the laboratory setting. This study aims to compare the Apple Watch Series 7's performance against the gold standard in VO2max estimation and Apple's validation findings. A total of 19 participants (7 female and 12 male), aged 18 to 63 (mean 28.42, SD 11.43) years were included in the validation study. VO2max for all participants was determined in a controlled laboratory environment using a metabolic gas analyzer. Thereby, they completed a graded exercise test on a cycle ergometer until reaching subjective exhaustion. This value was then compared with the estimated VO2max value from the Apple Watch, which was calculated after wearing the watch for at least 2 consecutive days and measured directly after an outdoor running test. The measured VO2max (mean 45.88, SD 9.42 mL/kg/minute) in the laboratory setting was significantly higher than the predicted VO2max (mean 41.37, SD 6.5 mL/kg/minute) from the Apple Watch (t18=2.51; P=.01) with a medium effect size (Hedges g=0.53). The Bland-Altman analysis revealed a good overall agreement between both measurements. However, the intraclass correlation coefficient ICC(2,1)=0.47 (95% CI 0.06-0.75) indicated poor reliability. The mean absolute percentage error between the predicted and the actual VO2max was 15.79%, while the root mean square error was 8.85 mL/kg/minute. The analysis further revealed higher accuracy when focusing on participants with good fitness levels (mean absolute percentage error=14.59%; root-mean-square error=7.22 ml/kg/minute; ICC(2,1)=0.60 95% CI 0.09-0.87). Similar to other smartwatches, the Apple Watch also overestimates or underestimates the VO2max in individuals with poor or excellent fitness levels, respectively. Assessing the accuracy and reliability of the Apple Watch's VO2max estimation is crucial for determining its suitability as an alternative to laboratory testing. The findings of this study will apprise researchers, physical training professionals, and end users of wearable technology, thereby enhancing the knowledge base and practical application of such devices in assessing cardiorespiratory fitness parameters.

Cardiorespiratory Fitness Decreases High-Sensitivity C-Reactive Protein and Improves Parameters of Metabolic Syndrome.

To evaluate the relationship between cardiorespiratory fitness (CRF), expressed as maximal oxygen uptake (ml.kg-1.min-1), metabolic syndrome (MetS), and high-sensitivity C-reactive protein (hs-CRP), a marker of systemic inflammation. The relationship between CRF, MetS, and hs-CRP was examined in a cohort of 173 men and women. CRF was evaluated using a Bruce protocol treadmill test and measured as estimated maximal oxygen uptake (VO2 max). Participants' physical activity status was self-reported. Plasma hs-CRP levels were measured using a standardized immunoassay, and the diagnostic criteria for MetS were based on guidelines established by the International Diabetes Federation (IDF). An inverse association was observed between hs-CRP levels and estimated VO2 max (p<0.01). Additionally, hs-CRP increased linearly with the number of MetS criteria present (p<0.01), while the estimated VO2 max decreased as the number of MetS criteria increased (p<0.01). Moreover, higher estimated VO2 max correlated with increased self-reported physical activity levels (p<0.01). Notably, participants engaging in two to three hours of exercise per week had hs-CRP levels ≤2.5 mg/L (p=0.018), considered a low-to-moderate risk range. Higher CRF, reflected by an estimated VO2 max, ≥45 ml/kg/min, is associated with lower hs-CRP levels and fewer MetS criteria. Additionally, regular physical activity, corresponding to higher VO2 max, appears to reduce systemic inflammation and ameliorate MetS risk factors. These findings support the mechanisms by which improved CRF and exercise may lower the risk of cardiovascular diseases (CVD) and type 2 diabetes (T2DM).

Assessing Maximal Oxygen Uptake: Influence of Leg Length in the Harvard Step Test and Queen’s College Step Test

Maximal oxygen uptake (VO2max) indicates cardiovascular endurance in evaluating overall health and physical performance. The CPX method is accurate, but accessibility is lower due to issues related to cost and complexity. For this reason, the Harvard Step Test and Queen's College Step Test are drawing interest. Step-based tests are influenced by factors such as leg length, requiring an investigation into the correlation between leg length and VO₂max estimation using these methods. This study investigates the influence of leg length on predicted VO₂max (pVO2max) determined through both the Harvard Step Test and the Queen's College Step Test. The assessment of VO2max was carried out using CPX on a treadmill. Measurements were obtained through the Harvard Step Test and Queen's College Step Test on steps. The participants were informed about the experimental procedure, and the experiment was conducted 24 hours later. The experiment maintained controlled conditions, and each measurement was conducted as a single trial, repeated three times for accuracy. The study found a significant positive correlation (r = 0.595, P &lt; 0.05) between CPX VO2max and lower leg length. Lower leg length was found to significantly influence exercise intensity as determined by both the Harvard Step Test pVO2max (explaining 35.4% of the variance, P &lt; 0.05) and the Queen's College Step Test pVO2max (explaining 30% of the variance, P &lt; 0.05). It is recommended to adjust the step height to the individual's body size when estimating exercise difficulty or pVO2max using step-based exercises.

Responsiveness of respiratory function in Parkinson's Disease to an integrative exercise programme: A prospective cohort study.

Respiratory disorders are the most common cause of death in Parkinson's Disease (PD). Conflicting data exist on the aetiology of respiratory dysfunction in PD and few studies examine the effects of exercise-based interventions on respiratory measures. This study was conducted to better understand respiratory dysfunction in PD and to identify measures of dysfunction responsive to an integrative exercise programme. The objectives were to compare baseline respiratory measures with matched, published population norms and to examine immediate and longer-term effects of a 12-week integrated exercise programme on these measures. Twenty-three people with mild PD (median Hoehn & Yahr = 2) self-selected to participate in this exploratory prospective cohort study. Evaluation of participants occurred at three time points: at baseline; following the 12-week exercise programme and at 4-month follow-up. Outcome measures included: Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 second (FEV1), FEV1/FVC ratio, Peak Expiratory Flow (PEF), Inspiratory Muscle Strength (MIP), Expiratory Muscle Strength (MEP), Peak Cough Flow (PCF), and Cardiovascular Fitness measures of estimated VO2 max and 6-Minute Walk Test (6MWT). Compared to published norms, participants had impaired cough, reduced respiratory muscle strength, FEV, FVC, PEF and cardiovascular fitness. Post exercise intervention, statistically significant improvements were noted in MEP, cardiovascular fitness, and PEF. However only gains in PEF were maintained at 4-month follow-up. Significant respiratory dysfunction exists, even in the early stages of PD. Metrics of respiratory muscle strength, peak expiratory flow and cardiovascular fitness appear responsive to an integrative exercise programme.

StepTest4all: Improving the Prediction of Cardiovascular Capacity Assessment in Young Adults.

Cardiovascular capacity, expressed as maximal oxygen uptake (VO2max), is a strong predictor of health and fitness and is considered a key measure of physiological function in the healthy adult population. The aim of this study was to investigate the influence of the physical activity levels (PAlevel) of participants in the StepTest4all (validated protocol for the estimation of VO2max in adults). The sample consisted of 69 participants, including 27 women (age 21.7 ± 3.6 years; body mass = 63.5 ± 14.8 kg; height = 1.64 ± 0.06 m; body mass index = 23.7 ± 5.3 kg/m2) and 42 men (aged 21.7 ± 3.4 years; body mass = 72.0 ± 7.3 kg; height = 1.77 ± 0.07 m; body mass index = 23.1 ± 2.1 kg/m2). The participants were assigned to one of the two groups: (i) the VO2max prediction group and (ii) the prediction model validation group. In the multiple linear regression, the following predictors of VO2max remained significant: sex (p < 0.001), physical activity level (p = 0.014), and HRR60 (p = 0.020). The prediction equation (R2 = 74.0%, SEE = 4.78) showed a close and strong relationship between the measurements and can be expressed as follows: VO2max = 17.105 + 0.260·(HRR60) + 8.563·(sex) + 4.097·(PAlevel), in which HRR60 is the magnitude of the HR decrease (bpm) in one minute immediately after stopping the step, and sex: men = 1, women = 0, and PAlevel is level 1 (low), level 2 (moderate), and level 3 (high). The StepTest4all was shown to be a suitable method for estimating cardiovascular capacity, expressed as VO2max, in young adults. Retaining PAlevel as a significant predictor allows us to better individualize the participants' VO2max.

Identifying the optimal workload combination for maximizing oxygen consumption estimation in submaximal tests

For decades, indirect submaximal tests using heart rate (HR) to estimate maximal oxygen consumption (VO2max) have been used for assessing cardiorespiratory fitness without pushing individuals to their limits. However, the optimal combination of submaximal workloads to use for maximizing estimation performance remains unclear. The study reprocessed data from 18 adolescent athletes undergoing a cycle ergometer incremental test with step-wise increments of 15 Watt/min until volitional exhaustion, sourced from a publicly available dataset. Multiple HR-derived metrics were computed over six distinct combinations of increasing workloads (50, 65, 80, 95, 110, 125 Watt). Principal component analysis was employed for dimensionality reduction. The top-performing regression model was chosen after training and validating various regression models, including machine learning-based ones. The HR data recorded at a single workload of 50 Watt was already adequate for estimating group VO2max, exhibiting similar scores (p = 0.80) to actual group values. Utilizing three consecutive workloads (50, 65, and 80 Watt) provided the most accurate individual VO2max prediction, revealing the highest correlation coefficient (0.71) along with the smallest bias (0.019 L/O2) and standard deviation (0.39 L/O2) across all six combinations. The project identifies optimal workloads for constructing new submaximal VO2max estimation tests. Additionally, it introduces new models for estimating VO2max for adolescents, each with varying performance based on the number of workloads utilized.

FEASIBILITY OF AEROBIC FITNESS TESTING IN AMNESTIC MILD COGNITIVE IMPAIRMENT FROM THE ACT TRIAL

Abstract Aerobic fitness has been postulated as a physiological mechanism of action for aerobic exercise to modify Alzheimer’s disease, but it has not been adequately studied in older adults with (MCI). The purpose of this study is to evaluate the feasibility of a gold-standard, laboratory-based, symptom-limited cycle-ergometer exercise testing (GXT) in older adults with amnestic mild cognitive impairment (aMCI) to assess peak oxygen consumption (VO2max [ml/kg/min]) using baseline data from the ACT Trial. The test was categorized as a submax, near-max, and max test based on if 0, 1, and ≥2 of the American College of Sports Medicine criteria was met: &amp;gt;90% of age-predicted maximum heart rate, plateau in VO2Peak, respiratory exchange ratio &amp;gt;1.10, and rating of perceived exertion &amp;gt;17. VO2max was predicted as 3.5*maximal metabolic equivalents (METs). Among 146 enrolled participants (73.8±5.7 years old with 16.9±2.9 years of education, 51.4% men, and 91.8% Caucasian), 145 completed GXTs. Sixteen GXTs (11.0%) were submax (VO2Peak 13.5±4.4), 53 (36.6%) were near-max (VO2Peak 16.5±4.1), and 76 (52.4%) were max (VO2Peak 18.4±5.1). Predicted VO2max were 21.6±6.8, 28.7±26.3, and 30.0±20.5 from submax, near-max, and max tests, respectively. Among max GXTs, VO2max was 19.5±4.9 in men (n=37) and 17.4±5.1 in women (n=39). In conclusion, GXTs was feasible for ~52% of the participants. METs-based prediction overly inflates VO2max estimates, in comparison to VO2max obtained from max GXTs. VO2max levels are substantially lower in older adults with aMCI than peers (23.1±6.3 in men and 21.1±3.4 in women), suggesting aerobic exercise as an important intervention for this population.

The informative power of heart rate along with machine learning regression models to predict maximal oxygen consumption and maximal workload capacity

Prediction of maximal oxygen consumption (VO2max) and maximal workload capacity (MWC) through submaximal exercise tests is an important topic for sports sciences. Numerous studies highlighted the predictive power of submaximal heart rate (HR) and oxygen consumption (VO2) in predicting VO2max and MWC. The challenge is achieving the best possible precision and accuracy by identifying the best predictors and regression models. This project assessed the performance of different indexes along with machine learning regression models to estimate VO2max and MWC. Predictors consisted of biodata (age, weight, and height) along with different combinations of change-scores of HR and VO2 between 0–50 Watts, 50–65 Watts, and 65–80 Watts (Δ0–50, Δ50–65, and Δ65–80, respectively). The use of biodata + HR Δ50–65 + HR Δ65-80 via a Squared Exponential Gaussian Process Regression model resulted in the best performance in predicting VO2max, while the use of biodata + HR Δ0–50 via a Robust Linear Regression model resulted in the best performance in predicting MWC. These results suggest that information provided by HR only during submaximal exercise offers the best predictive mean for estimating VO2max and MWC, while the use of VO2 changes or its addition along with HR changes does not improve predictions. Moreover, different predictors need to be selected for the best estimation of VO2max and MWC. Change-scores refer to absolute value changes, providing information to develop athlete assessment protocols through standardized workloads. These results show practical applicability for sports assessments to be performed indirectly, rapidly, sub-maximally, and through the simple measurement of HR.

Association between maximal oxygen consumption and physical performance tests among older adults with cognitive frailty

IntroductionCardiorespiratory fitness has an inverse relationship with cognitive impairment and frailty in older adults. Direct assessment of maximal oxygen consumption (VO2 max) is the gold standard to assess cardiorespiratory fitness. However, it is costly and requires a laboratory setting. Therefore, VO2 max estimation among older adults with cognitive frailty (CF) will allow the assessment of aerobic capacity, which is commonly overlooked due to the complexity of the test. AimThis study aims to determine the use of one of three physical performance tests (2-minute step, 2-minute walk, and 1-minute sit to stand) to effectively estimate cardiorespiratory fitness among older adults with CF. MethodsIn this cross-sectional study, community-dwelling individuals aged 60 years old and above in Klang Valley were screened for CF. The participants performed three physical performance tests (2-minute walk, 2-minute step, and 1-minute sit to stand) followed by treadmill-based maximal exercise testing on another day. ResultsA total of 32 older adults with cognitive frailty (mean age; SD: 67.1;4.7 years) participated in this study. Nearly half of them had hypertension (43.5 %), hypercholesterolemia (43.5 %), and multimorbidity (47.8 %). Among the endurance tests performed, only the 2-minute walk test independently predicted VO2 max by sex-specific with men (R2 = 0.58, p = 0.03) and women (R2 = 0.34, p = 0.01). The 2-minute walk test had good agreement with VO2 max (ICC = 0.77, 95 % CI: −3.1–2.4). ConclusionThe 2-minute walk test is a valid tool for estimating cardiorespiratory fitness among older adults with CF. However, it should be further tested across a larger population.

Mean power output for muscular endurance exercises and maximal oxygen uptake in military young adults.

The American Heart Association recommends a cardiopulmonary exercise test (CPET) and some alternative exercise tests to evaluate maximal oxygen uptake (VO2 max) of youth. Power output has shown a high correlation with VO2 max on a CPET. However, the correlations between mean power output (MPO) for muscular endurance exercises and VO2 max measured from a CPET are not established in young adults. Forty-five volunteers, with an average age of 29.93 ± 7.05 years, from a sample of 1120 military personnel in Taiwan who attended a 2-minute pushup test and a 2-minute sit-up test were included in the current study. These volunteers subsequently underwent a CPET using the Bruce protocol to assess VO2 max. According to the physics rule, MPO (watts) for the muscular endurance test was defined as a product of moving distance and force: [1/5 × body height (m) × numbers performed × body mass (kg) × gravity (9.8 m/s2)]. Pearson correlation analyses were performed. For the 2-min pushups, the correlations (r) between pushup numbers and VO2 max with and without body mass adjustment were 0.541 (P < .01) and 0.188 (P = .21), respectively, while the correlation (r) between MPO and VO2 max with and without body mass adjustment were 0.410 and 0.557 (both P < .01), respectively. For the 2-minute sit-ups, the correlations (r) between sit-up numbers and VO2 max with and without body mass adjustment were 0.529 (P < .01) and 0.291 (P = .052), respectively, while the correlations (r) between MPO and VO2 max with and without body mass adjustment were 0.318 (P = .03) and 0.705 (P < .01), respectively. In military young adults, MPO for both the 2-minute sit-up and the 2-minute pushup tests could be used as alternative field-based methods to estimate VO2 max.

Associations between soil-transmitted helminth infections and physical activity, physical fitness, and cardiovascular disease risk in primary schoolchildren from Gqeberha, South Africa.

School-aged children in low- and middle-income countries carry the highest burden of intestinal helminth infections, such as soil-transmitted helminths (STH). STH infections have been associated with negative consequences for child physical and cognitive development and wellbeing. With the epidemiological transition and rise in cardiovascular disease (CVD), studies have shown that helminth infections may influence glucose metabolism by preventing obesity. Thus, the aim of this study was to determine the association of STH infections in schoolchildren from Gqeberha, focusing on physical activity, physical fitness, and clustered CVD risk score. This cross-sectional study involved 680 schoolchildren (356 girls and 324 boys; mean age 8.19 years, SD±1.4) from disadvantaged communities in Gqeberha (formerly, Port Elizabeth), South Africa. Stool samples were collected and examined for STH infections using the Kato-Katz method. Physical activity (accelerometer) and physical fitness (grip strength, 20 m shuttle run) were measured using standard procedures. Furthermore, anthropometry, blood pressure, as well as glycated haemoglobin and lipid profile from capillary blood samples were assessed. We employed one-way ANOVAs to identify the associations of STH infections in terms of species and infection intensity with physical activity, physical fitness, and clustered CVD risk score. We found a low STH infection prevalence (7.2%) in our study, with participants infected with at least one intestinal helminth species. In comparison to their non-infected peers, children infected with STH had lower mean grip strength scores, but higher mean VO2max estimation and higher levels of MVPA (p < .001). When considering type and intensity of infection, a positive association of A. lumbricoides infection and MVPA was found. In contrast, light T. trichiura-infected children had significantly lower grip strength scores compared to non and heavily-infected children. VO2max and MVPA were positively associated with light T. trichiura infection. No significant association between the clustered CVD risk score and infection with any STH species was evident. STH-infected children had lower grip strength scores than their non-infected peers, yet, achieved higher VO2max and MVPA scores. Our study highlights that the type and intensity of STH infection is relevant in understanding the disease burden of STH infections on children's health. The findings of our study must be interpreted cautiously due to the low infection rate, and more research is needed in samples with higher prevalence rates or case-control designs.

Including supramaximal verification reduced uncertainty in VO2peak response rate.

Many reports describe using a supramaximal verification phase-exercising at a power output higher than the highest power output recorded during an incremental cardiopulmonary test-to validate VO2max. The impact of verification phases on estimating the proportion of individuals who increased VO2peak in response to high-intensity interval training (HIIT) remains an underexplored area in the individual response literature. This analysis investigated the influence of same-day and separate-day verification phases during repeated measurements (incremental tests-INCR1 and INCR2; incremental tests+supramaximal verification phases-INCR1+and INCR2+) of VO2peak on typical error (TE) and the proportion of individuals classified as responders (i.e., the response rate) following 4 weeks of HIIT (n=25) or a no-exercise control period (n=9). Incorporation of supramaximal verification consistently reduced the standard deviation of individual response, TE, and confidence interval (CI) widths. However, variances were statistically similar across all groups (p>0.05). Response rates increased when incorporating either one (INCR1 to INCR1+; 24%-48%, p=0.07) or two (INCR2 to INCR2+; 28%-48%, p=0.063) supramaximal verification phases. However, response rates remained unchanged when either zero-based thresholds or smallest worthwhile difference response thresholds were used (50% and 90% CIs, all p>0.05). Supramaximal verification phases reduced random variability in VO2peak response to HIIT. Compared with separate-day testing (INCR2 and INCR2+), the incorporation of a same-day verification (INCR1+) reduced CI widths the most. Researchers should consider using a same-day verification phase to reduce uncertainty and better estimate VO2peak response rate to HIIT.

Effects of aerobic, resistance, and combined training on thyroid function and quality of life in hypothyroidism. A randomized controlled trial

PurposeThis study aimed to compare the effects of aerobic, resistance, and combined exercises on thyroid function, lipid profile, exercise capacity, and quality of life (QoL) in hypothyroid women. MethodsSixty women aged 35 to 45 with clinical hypothyroidism were randomized to four equal groups: aerobic training (AT), resistance training (RT), combined AT/RT, and control groups. All exercises were performed at low to moderate intensity, three days per week, and for 12 weeks. Patients in all groups were on levothyroxine therapy. Outcome measures were free thyroxin (T4), thyroid stimulating hormone (TSH), lipid profile, estimated maximal oxygen consumption (VO2 max) and QoL assessed by the 12-item Short Form (SF-12) Health Survey. ResultsAll exercise groups showed significant improvements in all outcome measures compared to the baseline and the controls (p < 0.05). The combined AT/RT group showed more significant improvements in TSH and the mental component summary score of the SF-12 compared to the AT and RT groups (p < 0.05). The AT group showed the most significant improvement in estimated VO2 max, followed by the combined AT/RT and then the RT group. Non-significant differences were found between exercise groups in T4, blood lipids, and the physical component summary score of the SF-12 (p > 0.05). ConclusionIn women with hypothyroidism on levothyroxine treatment, all AT, RT, and combined AT/RT could equally improve T4 levels, lipid profile, and physical health-related QoL. However, the combined AT/RT could induce the greatest improvements in TSH and mental health-related QoL, while the AT could have the greatest impact on exercise capacity in these patients. Trial registrationPan African Clinical Trial Registry (PACTR), retrospective, PACTR202305810673587.

Maximal oxygen uptake prediction from submaximal bicycle ergometry using a differential model

The maximal oxygen uptake (VO2max) estimation has been a subject of research for many years. Cardiorespiratory measurements during incremental tests until exhaustion are considered the golden yard stick to assess VO2max. However, precise VO2max determination based on submaximal tests is attractive for athlete as well for clinical populations. Here, we propose and verify such a method based on experimental data. Using a recently developed model of heart rate (HR) and VO2 kinetics in graded exercise tests, we applied a protocol, which is terminated at 80% of the estimated maximal HR during ergometer cycling. In our approach, initially, formula for maximal HR is selected by retrospective study of a reference population (17 males, 23.5 ± 2.0 years, BMI: 23.9 ± 3.2 kg/m2). Next, the subjects for experimental group were invited (nine subjects of both sexes: 25.1 ± 2.1 years, BMI 23.2 ± 2.2 kg/m2). After calculation of maximal HR using cardiorespiratory recordings from the submaximal test, VO2max is predicted. Finally, we compared the prediction with the values from the maximal exercise test. The differences were quantified by relative errors, which vary from 1.2% up to 13.4%. Some future improvements for the procedure of VO2max prediction are discussed. The experimental protocol may be useful for application in rehabilitation assessment and in certain training monitoring settings, since physical exertion is not a prerequisite and the approach provides an acceptable VO2max estimation accuracy.

Validation of Aerobic Capacity (VO2max) and Lactate Threshold in Wearable Technology for Athletic Populations

As wearable technology (WT) has evolved, devices have developed the ability to track a range of physiological variables. These include maximal aerobic capacity (VO2max) and lactate threshold (LT). With WT quickly growing in popularity, independent evaluation of these devices is important to determine the appropriate use-cases for the devices. Therefore, the purpose of this study was to determine the validity of WT in producing estimates of VO2max and LT in athletic populations. METHODS: 21 participants completed laboratory LT and VO2max testing, as well as an outdoor testing session guided by the WT being tested (Garmin fēnix 6® watch and accompanying heart rate monitor). Statistical analysis was completed, using hypothesis testing (ANOVA, t-test), correlation analysis (Pearson’s r, Lin’s Concordance Correlation [CCC]), error analysis (mean absolute percentage error [MAPE]), equivalence testing (TOST test), and bias assessment (Bland–Altman analysis). RESULTS: The Garmin watch was found to have acceptable agreement for VO2max when compared to the 1 min averaged values (MAPE = 6.85%, CCC = 0.7) and for LT and the onset of blood lactate accumulation (OBLA), (MAPE = 7.52%, CCC = 0.79; MAPE = 8.20%, CCC = 0.74, respectively). Therefore, the Garmin fēnix 6® produces accurate measurements of VO2max and LT in athletic populations and can be used to make training decisions among athletes.

VO2max prediction based on submaximal cardiorespiratory relationships and body composition in male runners and cyclists: a population study.

Oxygen uptake (VO2) is one of the most important measures of fitness and critical vital sign. Cardiopulmonary exercise testing (CPET) is a valuable method of assessing fitness in sport and clinical settings. There is a lack of large studies on athletic populations to predict VO2max using somatic or submaximal CPET variables. Thus, this study aimed to: (1) derive prediction models for maximal VO2 (VO2max) based on submaximal exercise variables at anaerobic threshold (AT) or respiratory compensation point (RCP) or only somatic and (2) internally validate provided equations. Four thousand four hundred twenty-four male endurance athletes (EA) underwent maximal symptom-limited CPET on a treadmill (n=3330) or cycle ergometer (n=1094). The cohort was randomly divided between: variables selection (nrunners = 1998; ncyclist = 656), model building (nrunners = 666; ncyclist = 219), and validation (nrunners = 666; ncyclist = 219). Random forest was used to select the most significant variables. Models were derived and internally validated with multiple linear regression. Runners were 36.24±8.45 years; BMI = 23.94 ± 2.43 kg·m-2; VO2max=53.81±6.67 mL·min-1·kg-1. Cyclists were 37.33±9.13 years; BMI = 24.34 ± 2.63 kg·m-2; VO2max=51.74±7.99 mL·min-1·kg-1. VO2 at AT and RCP were the most contributing variables to exercise equations. Body mass and body fat had the highest impact on the somatic equation. Model performance for VO2max based on variables at AT was R2=0.81, at RCP was R2=0.91, at AT and RCP was R2=0.91 and for somatic-only was R2=0.43. Derived prediction models were highly accurate and fairly replicable. Formulae allow for precise estimation of VO2max based on submaximal exercise performance or somatic variables. Presented models are applicable for sport and clinical settling. They are a valuable supplementary method for fitness practitioners to adjust individualised training recommendations. No external funding was received for this work.

Nonexercise machine learning models for maximal oxygen uptake prediction in national population surveys.

Nonexercise algorithms are cost-effective methods to estimate cardiorespiratory fitness (CRF), but the existing models have limitations in generalizability and predictive power. This study aims to improve the nonexercise algorithms using machine learning (ML) methods and data from US national population surveys. We used the 1999-2004 data from the National Health and Nutrition Examination Survey (NHANES). Maximal oxygen uptake (VO2 max), measured through a submaximal exercise test, served as the gold standard measure for CRF in this study. We applied multiple ML algorithms to build 2 models: a parsimonious model using commonly available interview and examination data, and an extended model additionally incorporating variables from Dual-Energy X-ray Absorptiometry (DEXA) and standard laboratory tests in clinical practice. Key predictors were identified using Shapley additive explanation (SHAP). Among the 5668 NHANES participants in the study population, 49.9% were women and the mean (SD) age was 32.5years (10.0). The light gradient boosting machine (LightGBM) had the best performance across multiple types of supervised ML algorithms. Compared with the best existing nonexercise algorithms that could be applied to the NHANES, the parsimonious LightGBM model (RMSE: 8.51 ml/kg/min [95% CI: 7.73-9.33]) and the extended LightGBM model (RMSE: 8.26 ml/kg/min [95% CI: 7.44-9.09]) significantly reduced the error by 15% and 12% (P < .001 for both), respectively. The integration of ML and national data source presents a novel approach for estimating cardiovascular fitness. This method provides valuable insights for cardiovascular disease risk classification and clinical decision-making, ultimately leading to improved health outcomes. Our nonexercise models provide improved accuracy in estimating VO2 max within NHANES data as compared to existing nonexercise algorithms.

Abstract P444: Estimated Power Output for a Distance Run and Maximal Oxygen Uptake in Young Adults

Background: Both cardiopulmonary exercise testing (CPET) and run field test are recommended by the American Heart Association for assessing maximal oxygen uptake (VO 2 max) of youth. Power output was highly correlated with VO 2 max in a CPET. However, it is unclear the correlations of time and estimated power output (EPO) for a run field test with VO 2 max obtained from a CPET in young adults. Methods: This study included 45 participants, aged 20-40 years, from a sample of 1,120 military personnel who completed a 3000-m run field test in Taiwan in 2020. The participants subsequently received a CPET with the Bruce protocol to assess VO 2 max in the same year. According to the physics rule, EPO (watts) for the run field test was defined as a product of half body mass (kg) and [distance (3000-m)/time (s) for a run field test] 2 . Pearson product-moment correlation analyses were performed. Results: The Pearson correlation coefficient (r) of time against EPO for the run field test was estimated 0.708 (p &lt;0.001). The correlation coefficient between time for the run field test and VO 2 max (L/min) in a CPET was estimated 0.462 (p =0.001). By contrast, the correlation coefficient between time for the run field test and VO 2 max scaled to body mass in a CPET was estimated 0.729 (p &lt;0.001). The correlation coefficient of EPO for the run field test against VO 2 max in a CPET was estimated 0.813 (p &lt;0.001). Conclusion: In young adults, although time for a run field test was a reliable estimate of VO 2 max scaled to body mass, EPO proportionally to the mean velocity squared was found as a superior estimate of VO 2 max.