The Influence of VO2max Percentage During Interval Training on Cycling Performance Adaptations

Table of Contents

Overall Summary

Overview

This study explores how the percentage of maximal oxygen uptake (VO2max) achieved during interval training affects performance improvements in well-trained cyclists. Over nine weeks, 22 cyclists participated in an interval training program, with their VO2max continually monitored to determine its relationship to key performance metrics. The study situates itself within broader research on the optimization of high-intensity training and aims to clarify inconsistent findings about the correlation between VO2max levels during training and endurance improvements.

Key Findings

Strengths

Areas for Improvement

Significant Elements

Table

Description: Table 1 provides baseline participant characteristics, crucial for understanding initial conditions and facilitating comparisons between high and low VO2max groups.

Relevance: The table underlines significant baseline differences, such as VO2max levels, which are pivotal for interpreting the study's findings and assessing group comparability.

Figure

Description: Figure 1 displays the average fraction of VO2max achieved during intervals, highlighting differences between high and low VO2max groups.

Relevance: The figure visually reinforces the study's focus on the importance of maintaining high VO2max levels during training for optimal performance gains.

Conclusion

The study confirms that achieving higher percentages of VO2max during interval training is a key determinant of performance improvements in cyclists. This finding suggests a shift towards prioritizing VO2max-based metrics over traditional heart rate measures for assessing training intensity. The research highlights the need for future studies to explore practical methods of integrating VO2max monitoring into diverse training regimens and to investigate the long-term impacts of sustained high-intensity training on various performance metrics. By addressing current limitations such as variability in training volume, subsequent research can further refine the understanding of how VO2max influences endurance adaptations.

Section Analysis

Abstract

Overview

This study investigated the relationship between the percentage of maximal oxygen uptake (VO2max) achieved during interval training and improvements in cycling performance. Twenty-two well-trained cyclists underwent a 9-week interval training intervention. Results showed a positive correlation between the percentage of VO2max during interval sessions and improvements in maximal power output, performance index, and VO2max. Percentage of VO2max was identified as the best indicator of training adaptations compared to other measures like maximal heart rate.

Key Aspects

Strengths

Suggestions for Improvement

Introduction

Overview

This introduction establishes the context for studying the relationship between training intensity, measured by percentage of VO2max, and resulting adaptations in cyclists. It highlights existing research on the importance of high-intensity exercise near VO2max for stressing the oxygen system and its use as a training stimulus. While previous studies have explored time spent at or above 90% of VO2max, the introduction points out inconsistencies in findings regarding its correlation with performance improvements. This study aims to address this ambiguity by investigating the relationship between the average percentage of VO2max during power output-matched interval sessions and changes in endurance performance and physiological determinants in well-trained cyclists.

Key Aspects

Strengths

Suggestions for Improvement

Materials & Methods

Overview

This section details the methodology employed in the study, including the training intervention, exercise testing procedures, and data collection methods. The training intervention involved a 9-week program with varying interval protocols. Exercise testing included VO2max tests, blood lactate measurements, and power output assessments. Data collection involved continuous monitoring of VO2, power output, heart rate, and perceived exertion, with specific calibration and quality control procedures.

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Table 1: Baseline characteristics for all participants, as well as divided into groups eliciting the highest and lowest average fraction of maximal oxygen uptake during interval sessions (HIGH%VO2max and LOW%VO2max, respectively).
First Reference in Text
secondary analyses were performed by dividing participants into two groups based on whether their average % of VO2max during the interval sessions was in the highest or lowest half of the group (HIGH%VO2max and LOW%VO2max, respectively; Table 1).

This table presents the baseline characteristics of the participants in the study. It's organized into three columns: one for all participants combined, and two more for subgroups based on the percentage of VO2max achieved during interval training (HIGH%VO2max and LOW%VO2max). The rows list various physiological and performance metrics, including age, body mass, height, maximal heart rate (HRmax), maximal blood lactate concentration ([La-]max), maximal power output (Wmax), power output at 4 mmol/L blood lactate (PO4mmol), power output during 15-min and 40-min maximal cycling trials (PO15min and PO40min), a performance index, maximal oxygen uptake (VO2max), fractional utilization of VO2max at 4 mmol/L [La-] (% of VO2max@4mmol), gross efficiency (GE175w), peak leg press power, and hemoglobin mass. Means and standard deviations are provided for each metric. Statistical annotations indicate significant differences between the HIGH%VO2max and LOW%VO2max groups. Footnotes clarify the definitions of certain metrics and explain the performance index calculation.

Methodological Critique
  • The division of participants into HIGH%VO2max and LOW%VO2max groups introduces a potential source of bias, as baseline differences between these groups could influence the training response. While the table controls for some baseline values in later analyses, the pre-existing differences are still a concern.
  • The table provides clear definitions for most metrics, but the exact protocols for the performance tests (e.g., warm-up procedures, incremental steps) could be more detailed. More information on the training backgrounds of the participants would also be helpful.
  • The study justifies the use of VO2max as a key training metric, citing relevant literature. However, the rationale for choosing specific performance tests and the construction of the performance index could be further elaborated.
  • The statistical annotations clearly indicate significant differences, but effect sizes are not presented in the table itself, which would enhance the interpretation of the magnitude of these differences.
Presentation Critique
  • The table is generally well-organized and easy to read. However, the abbreviations for some metrics (e.g., PO4mmol, GE175w) might not be immediately clear to all readers and could benefit from more explicit definitions in the table itself, rather than just in the footnotes.
  • The use of standard deviations in parentheses is conventional and clear. The statistical annotations are effectively used to highlight key differences. However, visually separating the two subgroups more distinctly (e.g., with a stronger line or shading) could improve readability.
  • The table is appropriate for a scientific audience familiar with exercise physiology terminology. However, a brief explanation of the performance levels (3-5) mentioned in the related text would improve accessibility for a broader audience.
  • The table adheres to standard conventions for presenting baseline characteristics. Including units for all metrics directly in the table header would further improve clarity.
Key Values
  • VO2max: The overall average VO2max is 67.1 (6.4) mL·min⁻¹·kg⁻¹, indicating a well-trained sample. The HIGH%VO2max group had a slightly lower baseline VO2max (65.1 (5.3) mL·min⁻¹·kg⁻¹) compared to the LOW%VO2max group (69.1 (7.1) mL·min⁻¹·kg⁻¹). This difference, though statistically significant, might be influenced by the small sample size, especially in the HIGH%VO2max group.
  • PO40min: The average PO40min is 3.8 (0.4) W·kg⁻¹, which serves as the baseline for prescribing interval training intensity. The similarity in PO40min between the HIGH%VO2max and LOW%VO2max groups (3.8 (0.5) vs. 3.7 (0.4) W·kg⁻¹) confirms that the interval training was indeed power output-matched.
  • Performance Index: The average performance index is 0.749 (0.086), providing a composite measure of overall endurance performance. The lack of significant difference between groups at baseline suggests similar initial performance abilities.
Key Insights
  • The significant baseline differences in VO2max, HRmax, and GE175w between the HIGH%VO2max and LOW%VO2max groups raise concerns about the potential influence of these pre-existing differences on the training outcomes. This highlights the importance of considering baseline characteristics when interpreting the results.
  • The table effectively communicates the baseline characteristics of the participants and provides context for the subsequent training intervention. However, the lack of effect sizes and more detailed information about the training backgrounds of the participants limits the depth of analysis.
  • The inclusion of a performance index is a valuable attempt to capture overall endurance performance, but its construction and interpretation could be further clarified.
  • The findings underscore the importance of carefully considering baseline differences and providing comprehensive participant information when designing and analyzing training interventions.
Table 2: Average weekly training data during the 9-week training intervention for groups eliciting the highest and lowest average fraction of maximal oxygen uptake during interval sessions (HIGH%VO2max and LOW%VO2max, respectively).
First Reference in Text
During the training intervention, endurance training was reported according to a five-zone intensity scale based on % of PO40min for endurance training performed as cycling and % of average HR during the 40-min cycling trial for other types of endurance training (Table 2; Hunter et al., 2010).

This table displays the average weekly training data during the 9-week intervention, broken down by training intensity zones and other training types. It compares the HIGH%VO2max and LOW%VO2max groups (as defined in Table 1). Training data are presented as hours and minutes per week (h:m) for each training zone (Zones 1-5, based on power output or heart rate), heavy resistance training, core training, and total training. The table also includes data on perceived leg well-being (Feeling legs) on a 1-9 scale. Statistical annotations indicate significant or trending differences between the two groups.

Methodological Critique
  • Using different metrics for prescribing intensity (PO40min for cycling and average HR for other activities) introduces inconsistency and makes direct comparisons between training loads across different activities challenging. This could confound the relationship between training load and adaptation.
  • The table lacks clarity on how "other types of endurance training" were quantified and whether these activities were also controlled for intensity. This omission makes it difficult to assess the overall training load accurately.
  • While the reference to Hunter et al. (2010) provides some justification for the five-zone intensity scale, the specific rationale for using this particular scale and its relevance to the study's objectives could be further elaborated.
  • The table adheres to standard practice of presenting training data, but the lack of information on the distribution of training sessions within each week (e.g., frequency, duration) limits the insights into the training process.
Presentation Critique
  • The table is generally clear, but the abbreviations for training zones (e.g., Zone 1: <55% of PO40min) could be more concise and visually distinct. Defining the Feeling legs scale (1-9) directly in the table or caption would improve readability.
  • The use of mean (SD) and statistical annotations is appropriate. However, visually separating the two groups more clearly would enhance readability. Also, the footnotes could be more concise and directly linked to specific table cells.
  • The table is suitable for a scientific audience, but the terminology (e.g., PO40min) might require some explanation for a broader readership. Clarifying the meaning of "performance level" (mentioned in the related text) within the table context would improve understanding.
  • The table generally follows conventions for presenting training data. However, including units for all metrics directly in the table header would improve clarity. Also, providing more context about the training program itself (e.g., periodization scheme) would be beneficial.
Key Values
  • Total Training (h: m): The HIGH%VO2max group performed significantly more total training (9:43 (02:24) h:m) than the LOW%VO2max group (7:40 (02:28) h:m). This difference raises questions about whether the observed performance improvements in HIGH%VO2max are solely attributable to the higher fraction of VO2max during intervals or also influenced by the greater overall training volume.
  • Zone 1 Training (h: m): The HIGH%VO2max group performed significantly more Zone 1 training (3:12 (01:29) h:m) compared to the LOW%VO2max group (1:48 (00:48) h:m). This difference in low-intensity training volume could be a contributing factor to the overall training volume difference.
  • Interval Training (Zones 4-5, h: m): While not statistically significant, the LOW%VO2max group performed slightly more high-intensity interval training (Zone 4 + Zone 5: 2:00 h:m) than the HIGH%VO2max group (1:45 h:m). This suggests that the total time spent at high intensities might not be the sole determinant of training adaptations.
Key Insights
  • The substantial difference in total training volume between the HIGH%VO2max and LOW%VO2max groups confounds the interpretation of the study's primary findings. It remains unclear whether the observed performance benefits in HIGH%VO2max are solely due to the higher fraction of VO2max during intervals or also influenced by the greater overall training load.
  • The lack of detailed information on "other types of endurance training" and the inconsistent use of intensity metrics across different training modes limit the ability to accurately assess and compare training loads. This weakens the study's conclusions about the relationship between training intensity and adaptation.
  • The table highlights the importance of considering and controlling for total training volume when investigating the effects of training intensity. Future studies should aim to better isolate the effects of training intensity by minimizing variations in training volume.
  • The inclusion of perceived well-being data (Feeling legs) is a valuable addition, but its interpretation is limited without further context on how this measure relates to training load and adaptation.
Table 3: Interval session data for all participants and groups eliciting the highest and lowest average fraction of maximal oxygen uptake during interval sessions (HIGH%VO2max and LOW%VO2max, respectively), presented as averages of all collected measurements per interval session during period 1, 2 and 3.
First Reference in Text
10 min after each interval session, the participants reported their session RPE using a 10-point scale (sRPE; Table 3; Foster et al., 2001).

This table provides detailed data on the interval sessions performed during the three 3-week training periods. It's organized by period (1, 2, and 3) and shows data for all participants, as well as the HIGH%VO2max and LOW%VO2max groups. Metrics include time spent at or above 90% of VO2max and HRmax, average percentage and absolute values of VO2max and HRmax during intervals, average power output (PO), blood lactate concentration ([La-]), rating of perceived exertion (RPE), feeling legs score, session RPE (sRPE), and the number of completed sessions. Means and standard deviations are provided, along with statistical annotations indicating significant differences between periods and groups.

Methodological Critique
  • Presenting data as averages across all interval sessions within each period obscures potential within-period variations and trends. Analyzing individual session data or providing more granular time-series data would offer richer insights.
  • The table includes numerous metrics, but the rationale for selecting these specific variables and their relative importance to the research question could be more explicitly stated. Clarifying how 'Feeling legs' relates to other subjective measures like RPE and sRPE would strengthen the analysis.
  • The reference to Foster et al. (2001) only justifies the use of sRPE but doesn't provide context for other metrics or the overall methodological approach to analyzing interval training data. A more comprehensive discussion of the chosen metrics and their relevance to training adaptations is needed.
  • The statistical analysis appropriately uses linear mixed models to account for repeated measures, but the table lacks information on the specific model structure and assumptions. Including effect sizes for the significant differences would enhance interpretation.
Presentation Critique
  • The table is dense and complex, making it challenging to grasp key findings quickly. Simplifying the presentation by focusing on the most relevant metrics or using visual aids (e.g., graphs) could improve clarity. Clearly distinguishing between percentage and absolute values for VO2max and HRmax in the headers would also be helpful.
  • The use of mean (SD) and statistical annotations is standard practice. However, the table's visual organization could be improved by using clearer headings, more spacing between rows, and visual cues to highlight significant differences. The extensive footnotes also make it difficult to follow the data.
  • The table is suitable for a scientific audience familiar with exercise physiology, but the numerous abbreviations and technical terms might be overwhelming for a broader readership. Providing more concise explanations within the table or caption would improve accessibility.
  • While the table generally follows conventions for presenting interval training data, the sheer volume of information and complex layout hinder effective communication. A more streamlined presentation with clearer visual hierarchy and concise explanations would be more impactful.
Key Values
  • % of VO2max: The HIGH%VO2max group maintained a consistently higher % of VO2max across all three periods (86.3%, 86.2%, 85.9%) compared to the LOW%VO2max group (79.0%, 79.7%, 81.0%). This confirms the effectiveness of the group assignment based on % of VO2max.
  • Time ≥90% of VO2max: The HIGH%VO2max group spent considerably more time above 90% of VO2max in all periods, especially in period 3 (14:52 vs. 05:52). This difference highlights the distinct training stimulus experienced by the two groups.
  • [La-]: Blood lactate values progressively increased across the three periods in both groups, reflecting the increasing intensity of the interval protocols. However, there were no significant differences between the groups within each period.
  • sRPE: Session RPE values were generally higher for the HIGH%VO2max group compared to the LOW%VO2max group, particularly in period 3 (7.4 vs. 6.3). This suggests that the higher intensity efforts were perceived as more strenuous.
Key Insights
  • The table provides valuable data supporting the study's main finding that a higher % of VO2max during intervals leads to greater training adaptations. The differences in time spent ≥90% of VO2max and sRPE further reinforce this conclusion.
  • The progressive increase in [La-] across the training periods suggests an effective manipulation of training intensity. However, the lack of between-group differences in [La-] raises questions about its sensitivity as a marker of training stimulus in this context.
  • The table's complex presentation hinders its effectiveness in communicating key findings. Simplifying the presentation and focusing on the most relevant metrics would improve clarity and impact.
  • The lack of individual session data and detailed explanations of the chosen metrics limits the depth of analysis. Future studies could benefit from a more granular approach to data presentation and interpretation, providing richer insights into the dynamics of interval training adaptations.

Results

Overview

This section presents the findings of the study, highlighting the positive relationship between the percentage of V̇O2max achieved during interval training and changes in performance indicators like Wmax, PO4mmol, and the performance index. It also compares the training adaptations between participants with the highest and lowest % of V̇O2max during intervals, showing greater improvements in the high %V̇O2max group. Finally, it explores the relationship between baseline measures and %V̇O2max during intervals and examines other adaptive potential measures and their reproducibility.

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Figure 1: Average fraction of maximal oxygen uptake (% of VO2max) elicited during the 8-min work intervals during all interval sessions for all participants (dashed lines), as well as divided into groups eliciting the highest and lowest % of VO2max during intervals (HIGH%VO2max, black solid line and LOW%VO2max, gray solid line, respectively). The light gray areas represent 95% confidence intervals.
First Reference in Text
All participants performed the 8-min work intervals at an average % of VO2max in the range of 74.2%-90.8%, with the mean values of HIGH%VO2max and LOW%VO2max being 86.2 (3.8)% and 79.9 (4.0)%, respectively (Figure 1).

This figure displays the average fraction of VO2max achieved during 8-minute work intervals across all interval training sessions. It presents data for all participants, as well as separate lines for the HIGH%VO2max and LOW%VO2max groups. The x-axis represents time within the 8-minute interval, and the y-axis represents the percentage of VO2max. Shaded areas around the group lines depict 95% confidence intervals.

Methodological Critique
  • The figure effectively visualizes the differences in %VO2max between the two groups and the overall trend within each interval. However, it doesn't show the variability between individual participants within each group, which could be substantial.
  • While the caption mentions 95% confidence intervals, it's unclear how these intervals were calculated (e.g., across participants, sessions, or both). More details on the statistical methods used to generate the confidence intervals would improve transparency.
  • The figure supports the claim that the HIGH%VO2max group maintained a higher %VO2max during intervals. However, it doesn't directly address the relationship between %VO2max and training adaptations, which is the study's primary focus.
  • The figure adheres to standard conventions for presenting time-series data, but adding individual data points (or perhaps box plots at each time point) would provide a more comprehensive picture of the data distribution.
Presentation Critique
  • The figure is generally clear and easy to understand. The lines and confidence intervals are clearly labeled, and the axes are appropriately scaled. However, the dashed line for all participants is somewhat redundant given the separate lines for the two groups.
  • The visual organization is effective in highlighting the differences between the groups. The use of different line styles and shading for confidence intervals enhances readability. However, the figure could be improved by adding a legend directly within the figure area for easier interpretation.
  • The figure is appropriate for a scientific audience familiar with exercise physiology concepts. However, for a broader audience, a brief explanation of VO2max and its significance in training would be beneficial.
  • The figure generally adheres to field conventions, but the lack of a clear legend within the figure itself is a minor shortcoming. Also, providing more context within the figure (e.g., the specific training period) would be helpful.
Key Values
  • HIGH%VO2max Average: The HIGH%VO2max group maintained an average %VO2max of approximately 85-90% throughout most of the 8-minute interval. This indicates a sustained high-intensity effort.
  • LOW%VO2max Average: The LOW%VO2max group's average %VO2max was consistently lower, ranging from approximately 75-85% during the interval. This difference visually confirms the group separation based on %VO2max.
  • Initial VO2max Response: Both groups exhibit a rapid increase in %VO2max within the first minute of the interval, followed by a more gradual increase towards a plateau. This reflects the typical physiological response to high-intensity exercise.
  • Confidence Intervals: The relatively narrow confidence intervals for the HIGH%VO2max group suggest greater consistency in %VO2max compared to the LOW%VO2max group, especially in the latter half of the interval.
Key Insights
  • The figure clearly demonstrates the effectiveness of the group assignment methodology in separating participants based on their ability to achieve and maintain a high %VO2max during intervals.
  • The consistent difference in %VO2max between the two groups throughout the 8-minute interval suggests that this metric is a reliable indicator of training intensity.
  • The figure visually supports the study's premise that %VO2max is a key factor in training adaptations. However, further analysis is needed to establish a direct relationship between %VO2max and performance outcomes.
  • The figure could be enhanced by providing more details on the statistical methods and individual data variability. Adding a clear legend and more context within the figure itself would also improve clarity and interpretation.
Figure 2: Multiple linear regression of the average fraction of maximal oxygen uptake (% of VO2max) elicited during the intervals related to changes in (A) maximal 1-min incremental power output during the VO2max test (Wmax), (B) power output at 4 mmol·L⁻¹ lactate concentration (PO4mmol), (C) maximal average power output during a 15-min cycling trial (PO15min), (D) the performance index, (E) VO2max, and (F) fractional utilization of VO2max at 4 mmol·L⁻¹ lactate concentration (%VO2max@4mmol) when controlling for baseline values, change in body mass, and sex. Individual data points for groups eliciting the highest (HIGH%VO2max; black dots) and lowest (LOW%VO2max; white dots) average % of VO2max during intervals in addition to pooled regression slopes (solid lines) with 95% confidence intervals (light gray areas) are shown. "80%-90%" in the panels with significant or tendencies toward relationships represent the theoretical increase in the given outcome variable if % of VO2max during intervals is increased from 80% to 90%.
First Reference in Text
There was a positive relationship between % of VO2max achieved during all interval sessions and changes in both Wmax (p = 0.009; R²adjusted = 0.44; estimate = 0.04 W·kg⁻¹ [0.01, 0.06]; Figure 2A), PO4mmol (p = 0.035, R²adjusted = 0.25; estimate = 0.02 W·kg⁻¹ [0.00, 0.04]; Figure 2B), and the performance index (p = 0.013; R²adjusted = 0.36; estimate = 0.004 AU [0.001, 0.007]; Figure 2D), whereas no such association was applicable for change in PO15min (p = 0.215; R²adjusted = 0.15; estimate = 0.02 W·kg⁻¹ [-0.01, 0.04]; Figure 2C).

This figure presents six scatter plots (A-F), each showing the relationship between the average % of VO2max during interval training and changes in various performance measures. Each plot includes individual data points for the HIGH%VO2max and LOW%VO2max groups, a regression line representing the overall relationship, and a shaded area representing the 95% confidence interval for the regression. The "80%-90%" annotation in some panels indicates the predicted change in the outcome variable for a 10% increase in %VO2max.

Methodological Critique
  • Using multiple linear regression is appropriate for analyzing the relationship between %VO2max and performance changes while controlling for covariates. However, the figure caption doesn't specify the covariates included in the model, which should be explicitly stated.
  • The figure provides p-values and adjusted R-squared values, which are essential for interpreting the statistical significance and strength of the relationships. However, it lacks information on the sample size and the distribution of residuals, which are important for assessing the validity of the regression model.
  • The figure supports the claim of a positive relationship between %VO2max and certain performance measures. However, it doesn't show the actual regression equations, making it difficult to quantify the magnitude of the effects precisely.
  • The figure adheres to standard conventions for presenting regression results, but adding more statistical details (e.g., standardized beta coefficients, confidence intervals for the estimates) would strengthen the analysis.
Presentation Critique
  • The figure is generally clear and well-organized, with separate panels for each outcome variable. However, the labels for the y-axes could be more descriptive and include units for better readability.
  • The use of different symbols for the two groups and shaded areas for confidence intervals is effective. However, the figure could be improved by adding a legend directly within the figure area and using more distinct markers for the data points.
  • The figure is suitable for a scientific audience familiar with statistical methods. However, for a broader audience, a brief explanation of linear regression and the interpretation of R-squared values would be helpful.
  • The figure generally adheres to field conventions, but the lack of a comprehensive legend and detailed statistical information within the figure itself limits its standalone interpretability.
Key Values
  • Wmax (Panel A): A clear positive relationship is observed (p = 0.009, R²adjusted = 0.44), indicating that a higher %VO2max during intervals is associated with a greater increase in Wmax.
  • PO4mmol (Panel B): A positive relationship is also evident for PO4mmol (p = 0.035, R²adjusted = 0.25), although the relationship appears weaker than for Wmax.
  • Performance Index (Panel D): A positive relationship is observed for the performance index (p = 0.013, R²adjusted = 0.36), suggesting that %VO2max is a good predictor of overall performance improvements.
  • PO15min (Panel C): No significant relationship is found for PO15min (p = 0.215), indicating that %VO2max during intervals is not a strong predictor of changes in this specific performance measure.
Key Insights
  • The figure provides strong visual evidence supporting the study's main finding that %VO2max during interval training is a key determinant of training adaptations, particularly for measures of maximal power output and overall performance.
  • The lack of a significant relationship between %VO2max and PO15min suggests that the benefits of high %VO2max training might be more specific to certain types of performance measures.
  • The figure highlights the importance of controlling for covariates (baseline values, body mass, sex) when analyzing the relationship between training intensity and adaptations.
  • The figure's presentation could be improved by adding more statistical details, a comprehensive legend, and clearer axis labels. This would enhance its clarity and interpretability, especially for a broader audience.
Figure 3: Individual data points (dashed lines) and mean values (solid lines) for (A) maximal 1-min incremental power output during the maximal oxygen uptake (VO2max) test (Wmax), (B) power output at 4 mmol-L-¹ lactate concentration (PO4mmol), (C) maximal average power output during a 15-min cycling trial (PO15min), (D) the performance index, (E) VO2max, and (F) fractional utilization of VO2max at 4 mmol·L-1 lactate concentration (% of VO2max@4mmol), before (pre) and after (post) the training intervention for groups eliciting the highest and lowest average fraction of VO2max during intervals (HIGH%VO2max and LOW%VO2max, respectively). The values presented in each panel represent the mean (SD) percentage change in the variable of interest for HIGH%VO2max and LOW%VO2max, respectively. * Absolute change significantly different from LOW%VO2max (p ≤ 0.05). # Absolute change tends to be different from LOW%VO2max (p < 0.1 and >0.05).
First Reference in Text
Compared to LOW%VO2max, HIGH%VO2max displayed larger absolute increases in Wmax (0.51 (0.33) versus 0.23 (0.14) W·kg⁻¹; p = 0.022; Figure 3A), PO4mmol (0.31 (0.15) versus 0.12 (0.18) W·kg⁻¹; p = 0.015; Figure 3B), the performance index (0.059 (0.028) versus 0.027 (0.021) AU; p = 0.005; Figure 3D), and VO2max (5.23 (2.76) versus 1.78 (1.72) mL·min⁻¹·kg⁻¹; p = 0.003; Figure 3E).

This figure displays pre- and post-training values for six performance measures (Wmax, PO4mmol, PO15min, performance index, VO2max, %VO2max@4mmol) in the HIGH%VO2max and LOW%VO2max groups. Each panel (A-F) shows individual data points connected by dashed lines, as well as solid lines representing group means. The percentage change from pre- to post-training is displayed within each panel for both groups. Asterisks and hash symbols denote statistically significant and trending differences, respectively, between the groups.

Methodological Critique
  • Presenting both individual data points and group means is a good practice, allowing readers to assess both individual responses and overall group trends. However, the sheer number of data points and lines can make the figure visually cluttered, especially in panels with overlapping data.
  • While the caption and reference text provide p-values for the group comparisons, the figure itself would benefit from displaying the exact p-values within each panel. Additionally, reporting effect sizes (e.g., Cohen's d) would provide a more complete picture of the magnitude of the differences.
  • The figure supports the claim that the HIGH%VO2max group experienced greater improvements in certain performance measures. However, it doesn't directly address the potential influence of the observed differences in total training volume between the groups (as highlighted in Table 2).
  • The figure generally adheres to standard conventions for presenting pre- and post-training data, but using a different visualization method (e.g., box plots with superimposed individual data points) might improve clarity and reduce visual clutter.
Presentation Critique
  • The figure is generally understandable, but the dense presentation of individual data points and overlapping lines can make it difficult to discern patterns and compare groups, especially in panels C and F. Simplifying the visual presentation or using separate figures for each outcome variable might improve clarity.
  • The use of different line styles and symbols for groups and individuals is helpful, but the figure would benefit from a clear and comprehensive legend within the figure area. The statistical annotations are helpful, but placing them directly next to the relevant data points would improve readability.
  • The figure is suitable for a scientific audience familiar with exercise physiology terminology. However, for a broader audience, providing more context and explanations within the figure itself (e.g., defining the performance measures, explaining the meaning of statistical significance) would enhance understanding.
  • The figure generally follows conventions for presenting pre- and post-training data, but the visual clutter and lack of a comprehensive legend hinder its effectiveness. Using a cleaner visual design and providing more explanatory information within the figure would improve its communicative impact.
Key Values
  • Wmax (Panel A): The HIGH%VO2max group showed a larger percentage improvement in Wmax (8.6%) compared to the LOW%VO2max group (4.2%), and this difference was statistically significant (p ≤ 0.05).
  • PO4mmol (Panel B): A similar pattern was observed for PO4mmol, with a larger and statistically significant increase in the HIGH%VO2max group (7.8%) compared to the LOW%VO2max group (3.4%).
  • VO2max (Panel E): The HIGH%VO2max group also experienced a significantly greater improvement in VO2max (8.0%) compared to the LOW%VO2max group (2.7%).
  • PO15min (Panel C): While the HIGH%VO2max group showed a larger percentage improvement in PO15min (6.9%) compared to the LOW%VO2max group (3.6%), this difference was only a trend (p < 0.1 and > 0.05) and not statistically significant.
Key Insights
  • The figure provides further evidence supporting the study's main conclusion that training at a higher %VO2max during intervals leads to greater improvements in key performance measures, particularly those related to maximal power output and VO2max.
  • The trending difference in PO15min improvement suggests that the benefits of high-%VO2max training might be less pronounced for performance measures assessed in a fatigued state.
  • The figure highlights the importance of considering individual responses to training, as evidenced by the variability in pre- to post-training changes within each group.
  • The figure's impact could be enhanced by addressing the potential confounding effect of training volume differences between the groups and by improving its visual clarity and providing more detailed statistical information within the figure itself.
Table 4: Multiple linear regression of baseline measures related to % of VO2max during intervals, all when controlling for sex.
First Reference in Text
PO4mmol, PO15min, and % of VO2max@4mmol at baseline were all positively related to % of VO2max during intervals (Table 4).

This table presents the results of multiple linear regression analyses examining the relationships between baseline performance measures and the average percentage of VO2max achieved during interval training (% of VO2max during intervals). The table includes estimates, p-values, 95% confidence intervals, and adjusted R-squared values for each predictor variable. All analyses controlled for sex as a covariate. Footnotes clarify the meaning of the variables and provide an interpretation of the estimates.

Methodological Critique
  • Controlling for sex is appropriate given potential physiological differences between males and females. However, the table doesn't provide information on the proportion of males and females in the sample, which would be helpful for interpreting the results.
  • The table provides essential statistical information, including estimates, p-values, and confidence intervals. However, it lacks details on the model diagnostics (e.g., normality of residuals, multicollinearity), which are important for assessing the validity of the regression model.
  • The table supports the claim that certain baseline measures are related to %VO2max during intervals. However, it doesn't explain the practical significance of these relationships or their implications for training prescription.
  • The table adheres to standard conventions for presenting regression results, but adding more information on the model characteristics (e.g., sample size, model fit statistics) would enhance transparency and allow for a more thorough evaluation of the findings.
Presentation Critique
  • The table is generally clear and concise, but the abbreviations for some variables (e.g., PO4mmol, GE175w) might not be immediately clear to all readers. Providing more descriptive labels or a separate table of abbreviations would improve readability.
  • The use of standard statistical notation and annotations is appropriate. However, visually highlighting the statistically significant relationships (e.g., with bold text or asterisks) would enhance readability.
  • The table is suitable for a scientific audience familiar with statistical methods. However, for a broader audience, a brief explanation of linear regression and the interpretation of the estimates and confidence intervals would be beneficial.
  • The table generally adheres to field conventions, but providing more context and explanations within the table itself (e.g., explaining the practical significance of the findings) would improve its standalone interpretability.
Key Values
  • Baseline PO4mmol (Estimate = 4.70, p = 0.028): This indicates a positive and statistically significant relationship between baseline PO4mmol and %VO2max during intervals. For each 1 W·kg⁻¹ increase in baseline PO4mmol, the %VO2max during intervals is predicted to increase by 4.70 percentage points, holding sex constant.
  • Baseline PO15min (Estimate = 4.76, p = 0.013): Similar to PO4mmol, baseline PO15min is also positively and significantly associated with %VO2max during intervals. A 1 W·kg⁻¹ increase in baseline PO15min predicts a 4.76 percentage point increase in %VO2max during intervals.
  • Baseline % of VO2max@4mmol (Estimate = 0.42, p = 0.011): A higher baseline % of VO2max@4mmol is also positively and significantly related to %VO2max during intervals. For each 1 percentage point increase in baseline %VO2max@4mmol, the %VO2max during intervals is predicted to increase by 0.42 percentage points.
  • Baseline VO2max (Estimate = -0.06, p = 0.757): There is no statistically significant relationship between baseline VO2max and %VO2max during intervals.
Key Insights
  • The table suggests that individuals with higher baseline power output at 4 mmol/L lactate (PO4mmol) and higher maximal power output during a 15-minute cycling trial (PO15min) tend to achieve a higher percentage of VO2max during subsequent interval training.
  • The positive relationship between baseline %VO2max@4mmol and %VO2max during intervals suggests that individuals with a greater ability to utilize oxygen at higher lactate levels are also better able to maintain a high %VO2max during interval training.
  • The lack of a significant relationship with baseline VO2max suggests that the ability to achieve a high %VO2max during intervals is not solely determined by maximal oxygen uptake capacity.
  • The table provides valuable insights into the factors influencing %VO2max during interval training, but further research is needed to explore the practical implications of these findings for training optimization. Improving the table's clarity and providing more detailed statistical information would also enhance its scientific value.
Table 5: Multiple linear regression of the adaptive potential measures time ≥90% of VO2max, % of HRmax, and time ≥90% of HRmax during intervals related to training adaptations when controlling for baseline values, change in body mass, and sex.
First Reference in Text
There was a positive relationship between time ≥90% of VO2max during intervals and change in Wmax, PO4mmol, and the performance index, and a tendency for change in VO2max and % of VO2max@4mmol (Table 5).

This table presents the results of multiple linear regression analyses examining the relationships between three adaptive potential measures (time ≥90% of VO2max, % of HRmax, and time ≥90% of HRmax during intervals) and changes in several performance outcomes. The table is divided into three sections, one for each adaptive potential measure. Each section includes estimates, p-values, 95% confidence intervals, and adjusted R-squared values for each outcome variable. All analyses controlled for baseline values, change in body mass, and sex. Footnotes clarify the meaning of the variables and provide an interpretation of the estimates.

Methodological Critique
  • The table appropriately controls for baseline values, change in body mass, and sex, which helps to isolate the effects of the adaptive potential measures. However, it doesn't address the potential confounding effect of total training volume, which differed significantly between the HIGH%VO2max and LOW%VO2max groups (as shown in Table 2).
  • The table provides essential statistical information, but it lacks details on the model diagnostics and the specific model structure used for each analysis. This information would enhance transparency and allow for a more thorough evaluation of the findings.
  • The table supports the claim of a positive relationship between time ≥90% of VO2max and certain performance outcomes. However, it doesn't discuss the practical significance of these findings or their implications for training prescription.
  • The table generally adheres to standard conventions for presenting regression results, but including effect sizes (e.g., standardized beta coefficients) would provide a more complete picture of the magnitude of the effects.
Presentation Critique
  • The table is well-organized and presents a large amount of information effectively. However, the use of abbreviations and technical terms (e.g., Wmax, PO4mmol, %VO2max@4mmol) might be challenging for readers unfamiliar with exercise physiology. Providing a separate table of abbreviations or more descriptive labels within the table itself would improve clarity.
  • The use of standard statistical notation and annotations is appropriate. However, visually highlighting the statistically significant relationships (e.g., with bold text or asterisks) would enhance readability and make it easier to identify key findings.
  • The table is suitable for a scientific audience with a background in exercise physiology and statistics. However, for a broader audience, providing more context and explanations within the table itself (e.g., defining the performance measures, explaining the meaning of statistical significance) would improve accessibility.
  • The table generally adheres to field conventions, but enhancing its visual clarity and providing more explanatory information within the table itself would improve its communicative impact and make it more accessible to a wider audience.
Key Values
  • Time ≥90% of VO2max and ΔWmax (Estimate = 0.02, p = 0.026): This indicates a positive and statistically significant relationship between time spent at or above 90% of VO2max during intervals and the change in Wmax. For each additional minute spent at ≥90% VO2max, Wmax is predicted to increase by 0.02 W·kg⁻¹, controlling for other variables.
  • Time ≥90% of VO2max and ΔPO4mmol (Estimate = 0.01, p = 0.045): A similar positive and statistically significant relationship is observed between time ≥90% of VO2max and the change in PO4mmol. Each additional minute at ≥90% VO2max predicts a 0.01 W·kg⁻¹ increase in PO4mmol.
  • % of HRmax and ΔPerformance Index (Estimate = 0.01, p = 0.036): A higher average percentage of HRmax during intervals is positively and significantly associated with a greater improvement in the performance index. Each 1 percentage point increase in %HRmax predicts a 0.01 AU increase in the performance index.
  • Time ≥90% of HRmax and ΔPO4mmol (Estimate = 0.02, p = 0.043): Spending more time at or above 90% of HRmax during intervals is also positively and significantly related to the change in PO4mmol. Each additional minute at ≥90% HRmax predicts a 0.02 W·kg⁻¹ increase in PO4mmol.
Key Insights
  • The table provides further evidence supporting the importance of time spent at high intensities (≥90% of VO2max) for improving maximal power output (Wmax and PO4mmol) and overall performance (performance index).
  • The findings suggest that both % of HRmax and time ≥90% of HRmax during intervals can be useful predictors of training adaptations, particularly for PO4mmol and the performance index.
  • The table highlights the complex relationships between different training intensity metrics and performance outcomes, emphasizing the need for a multifaceted approach to training prescription and analysis.
  • The table's clarity and accessibility could be improved by providing more descriptive labels, highlighting significant findings, and adding more context and explanations within the table itself. Addressing the potential confounding effect of training volume and providing more detailed statistical information would further strengthen the analysis.

Discussion

Overview

This discussion section interprets the study's findings, emphasizing the positive relationship between %V̇O2max during interval training and improvements in endurance performance measures (Wmax, PO4mmol, performance index). It supports the hypothesis that higher %V̇O2max elicits greater training adaptations, discussing this in the context of existing literature. The discussion also analyzes the effects of %V̇O2max on physiological determinants of endurance performance (V̇O2max, fractional utilization of V̇O2max, gross efficiency), and compares the effectiveness of %V̇O2max with other training variables like %HRmax. Finally, it acknowledges limitations and suggests %V̇O2max as a robust measure for optimizing interval training.

Key Aspects

Strengths

Suggestions for Improvement

Conclusion

Overview

This conclusion reiterates the study's main finding: gains in endurance measures after 9 weeks of interval training in cyclists are positively related to the percentage of V̇O2max and time spent at or above 90% of V̇O2max during interval sessions. It emphasizes that percentage of maximal heart rate (%HRmax) and time spent at or above 90% of maximal heart rate are less accurate indicators of adaptive stimulus compared to V̇O2max-based metrics.

Key Aspects

Strengths

Suggestions for Improvement

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