Indicators of Neuromuscular, Metabolic and Perceptual Fatique Following a 5 km Run

1. Introduction

The performance of long-distance runners depends heavily on a complex interaction of physiological, biomechanical, neuromuscular, and psychological factors that collectively shape the athlete’s individual profile [1,2]. Within this multidimensional phenomenon, key determinants of performance include aerobic capacity, running economy, and the ability to maintain a high percentage of VO₂max over an extended period, alongside the vital role of neuromuscular characteristics such as muscle strength and tendon stiffness [3]. High-intensity running efforts are characterized by significant physiological stress; during competitive efforts, trained runners can reach 90–100% of VO₂max, leading to a pronounced disruption of muscle-metabolic homeostasis [4]. In this context, fatigue is not manifested solely at the muscular level through a reduced capacity to generate force but is the result of a complex interaction between peripheral and central mechanisms. Peripheral fatigue is associated with impaired muscle fiber function and the accumulation of metabolic by-products, including increased blood lactate concentration [5], while central fatigue refers to the decreased efficiency of the nervous system in activating motor units [4,6].

In experimental settings, the capacity for force production is most commonly assessed by measuring maximal voluntary isometric contraction (MVIC), which is considered a reliable indicator of changes in neuromuscular function and fatigue [7,8]. Previous research indicates that running loads of various durations and intensities can lead to a significant reduction in lower-limb isometric strength. For instance, following half-marathon running, a decrease in knee extensor MVIC was observed alongside simultaneous indicators of central and peripheral fatigue, while a pronounced decline in MVIC, particularly in men, was recorded after a high-intensity 5 km running test [4,9]. Such findings suggest that the reduction in force-generating capacity after intense running arises from the interplay of peripheral changes in the contractile apparatus and alterations in neural muscle activation. These changes can have functional consequences, including alterations in stride mechanics, which may negatively impact running economy and increase the risk of injury [10]. In addition to neuromuscular indicators, muscle architecture represents an important determinant of force-generating capacity and the mechanical properties of skeletal muscles [11]. Since running-induced fatigue can alter spatiotemporal and kinetic running parameters, including ground contact time, stride length, and lower-limb stiffness monitoring neuromuscular and morphological indicators can provide additional insight into the functional consequences of acute running loads [12,13].

In this context, B-mode ultrasound represents a reliable and non-invasive method for assessing the morphological and architectural characteristics of skeletal muscles, including the rectus femoris and vastus lateralis. Its application allows for the quantification of indicators such as muscle thickness, cross-sectional area, fascicle length, and pennation angle, which are frequently used to evaluate acute and chronic changes in muscle tissue [14,15]. Previous research indicates that even short term, high-intensity loads can lead to transient changes in muscle thickness and pennation angle, further confirming the sensitivity of muscle architecture to acute mechanical stress. Such changes are most commonly associated with acute muscle swelling, alterations in fluid distribution, and the temporary morphological response of the tissue to contractile loading [16]. Therefore, ultrasonic assessment of muscle architecture can provide additional information regarding the local morphological response of the muscle, complementing data obtained through measurements of isometric strength and other neuromuscular indicators. A comprehensive analysis of the organism’s response to running loads, in addition to neuromuscular and morphological parameters, includes the assessment of metabolic and perceptual load. Blood lactate concentration is often used as an indicator of metabolic stress and the contribution of anaerobic metabolism during high-intensity work, while the rating of perceived exertion (RPE) provides insight into the perception of effort and exercise tolerance. The correlation of RPE with physiological indicators, including blood lactate and heart rate, confirms its value as a practical measure of an athlete’s internal load [17,18]. In this sense, the integration of objective and subjective indicators allows for a more holistic understanding of the physiological, metabolic, and perceptual responses of the organism to high-intensity running efforts [19].

The perception of effort plays a crucial role in regulating pacing strategies, whereby athletes continuously adjust their work intensity during performance in accordance with physiological load, previous experience, and the expected duration of the activity. Research shows that RPE, alongside physiological and muscular factors, contributes to the shaping of pacing strategies during self-paced running efforts [20,21,22]. In this context, a high-intensity 5 km run serves as an appropriate model of acute exertion for studying the neuromuscular, morphological, metabolic, and perceptual responses of the organism. Such an effort requires maintaining high intensity under time constrained conditions and allows for the simultaneous analysis of changes in isometric strength, muscle morphology, blood lactate concentration, and the subjective feeling of exertion. Although previous research has primarily analyzed individual aspects of fatigue and muscle function following running loads, there is a limited number of studies tracking these indicators in an integrated manner immediately following the same protocol. Therefore, this study aimed to examine the acute neuromuscular, metabolic, and perceptual response to high-intensity 5 km running.

2. Materials and Methods

2.1. Participants

The study involved 21 recreational male runners with multi-year experience in long-distance road running events, with an average age of 35,43 ± 11,42 years. The participants have been regularly executing structured training programs for over five years, which include aerobic long runs, tempo runs, and high-intensity interval training. All participants volunteered to take part in the study, and before the commencement of measurements, they were informed of the study’s aim and protocol and provided written informed consent. Inclusion criteria comprised a minimum age of 18 years, at least five years of continuous running experience in long-distance events, and the absence of any musculoskeletal injuries in the past six months. This ensured that the participants possessed an adequate level of training status and could safely tolerate the prescribed workload within the study. The research was conducted in accordance with the principles of the Declaration of Helsinki, and the research protocol was approved by the Ethics Committee of the Faculty of Kinesiology Osijek (Class: 029-01/25-01/05; Registry number: 2158-110-01-25-4).

2.2. Experimental Design

The study was conducted in November 2025, with all measurements performed under approximately identical conditions for all participants. A within-subjects (pre–post) experimental design was employed to assess acute neuromuscular, metabolic, and perceptual changes following the running workload. Initially, anthropometric data were collected and body composition was assessed, followed by baseline measurements of resting blood lactate concentration. Subsequently, ultrasound measurements of the m. rectus femoris thickness of the right leg and assessments of maximal voluntary isometric contraction (MVIC) of the quadriceps for both legs were performed.

Immediately before the exercise bout, participants performed a standardized 10 minute dynamic warm-up according to a predefined protocol. The experimental load consisted of a 5 km run conducted on an athletic track in Osijek. Participants ran in small groups of no more than three runners, formed based on previously achieved comparable times over the same distance to ensure similar running dynamics within the groups. The participants were instructed to run at a pace corresponding to their individual maximum sustainable intensity.

During the run, exercise intensity was continuously monitored using chest strap heart rate monitors (HRM) synchronized with the participants’ smartwatches. Upon completion of the run, average and maximal heart rate values were recorded, and the rating of perceived exertion (RPE) was assessed using the Borg scale. Immediately after the effort, measurements of blood lactate concentration, ultrasound of the m. rectus femoris (right leg), and MVIC of the quadriceps (both legs) were repeated to determine the acute changes induced by the running workload.

2.3. Measurements

Anthropometric measurements included the measurement of body height and the assessment of body composition. Body height was measured using a portable anthropometer (Harpenden Anthropometer 601, Holtain Ltd., UK), while body composition was assessed via bioelectrical impedance analysis (BIA) using a segmental body composition analyzer (Tanita BC-601, Tanita Corp., Tokyo, Japan). The analyzed variables included body mass (kg), body mass index (kg·m⁻²), body fat percentage (%), and muscle mass (kg). Measurements were conducted under standardized conditions with participants barefoot and wearing light clothing.

Blood lactate concentration was determined from capillary blood samples taken from the earlobe using a portable analyzer (Lactate Scout, EKF Diagnostics, Germany) at rest and immediately post-exercise.

M. rectus femoris thickness was measured using B-mode diagnostic ultrasonography with a linear probe frequency of 5–12 MHz (set at 10 MHz). Measurement parameters were standardized (depth 3.7–4.6 cm, dynamic range 70 dB, gain 50). Measurements were performed on the right thigh at 40% of the distance between the greater trochanter and the lateral femoral epicondyle. Before measurement, participants remained in a supine position for 10 minutes to allow for tissue stabilization. Three images were recorded per participant, and the final value represented the mean thickness measured between the superficial and deep aponeuroses.

Maximal voluntary isometric contraction (MVIC) of the m. quadriceps femoris was assessed using an S2P isometric dynamometer (S2P, Ljubljana, Slovenia). Measurements were performed in a seated position (85° angle between the trunk and thigh), with the trunk and pelvis stabilized using straps to minimize compensatory movements. The protocol consisted of three maximal isometric contractions lasting three seconds each, with a 30-second rest interval between trials. Measurements were conducted bilaterally, and the highest recorded force (N) was taken as the final value.

Heart rate (HR) was continuously monitored during the run using a chest strap heart rate monitor (Polar H10, Polar Electro, Vantaa, Finland) compatible with the participants smartwatches. Average and maximal heart rate values were analyzed.

The rating of perceived exertion (RPE) was assessed using the validated Borg CR10 scale (range 0–10) immediately following the completion of the run. Performance was recorded as the finish time for the 5 km distance (s).

2.4. Statistical Analysis

Statistical data analysis was performed using the Jamovi software package (version 2.6.44.0). Descriptive statistics are presented as the arithmetic mean (M), standard deviation (SD), minimum (Min), and maximum (Max) values, along with skewness (Skew) and kurtosis (Kurt) coefficients. Data normality was assessed using the Shapiro–Wilk test. Since certain variables did not meet the assumption of normal distribution, non-parametric statistical methods were employed for further analysis.

Differences between pre- and post-exercise measurements were analyzed using the Wilcoxon signed-rank test. Effect size was expressed using the r coefficient and interpreted according to Cohen’s guidelines as small (r = 0.10), medium (r = 0.30), and large (r = 0.50). To assess the relationship between variables, Spearman’s correlation coefficient (ρ) was utilized. The level of statistical significance was set at p < 0.05.

3. Results

Table 1 presents the descriptive indicators of anthropometric, physiological, and neuromuscular variables, including the values assessed before and after the 5 km running load, as well as the magnitude of change between measurements. Blood lactate concentration was low at rest (0.81 ± 0.35 mmol·L⁻¹), whereas significantly higher values were recorded post-exercise (6.90 ± 1.44 mmol·L⁻¹; Δ = 6.09 ± 1.37 mmol·L⁻¹), indicating a pronounced metabolic response to the high-intensity running effort. The wider range of values post-exercise further points to marked inter-individual variability in the metabolic response. Quadriceps MVIC was lower post-exercise for both legs. For the right leg, values decreased from 305.26 ± 98.83 N to 258.85 ± 88.46 N (Δ = −46.42 ± 58.07 N), and for the left leg from 264.63 ± 97.11 N to 241.38 ± 86.78 N (Δ = −23.25 ± 60.77 N). This decline in MVIC indicates an acute reduction in force-generating capacity following the running load, while the large range of individual changes suggests a heterogeneous neuromuscular response among participants. Values for average heart rate (165.05 ± 16.23 bpm) and maximal heart rate (180.29 ± 16.43 bpm) demonstrate that the 5 km run was performed at a high intensity, with notable inter-individual variability in the cardiovascular response. The rating of perceived exertion (RPE) was also high (8.33 ± 1.16), confirming the high perceptual demand of the exercise protocol. The subjective feeling of exertion remained consistently high across the sample (RPE = 8.33 ± 1.16).

The results of the Wilcoxon signed-rank test, which analyzed differences in m. rectus femoris thickness, MVIC, and blood lactate concentration before and after the 5 km run, are presented in Table 2. The maximal voluntary contraction of the right quadriceps was significantly lower post-exercise (p = 0.002) with a large effect size (r = 0.74), indicating a pronounced decline in neuromuscular strength following the run. For the left leg, no statistically significant change in MVIC was observed (p = 0.103); however, a medium effect size (r = 0.41) suggests a trend toward a reduction in strength that likely did not reach statistical significance due to the limited sample size. Blood lactate concentration significantly increased after the exercise bout (p < 0.001) with a very large effect size (r = 1.00), confirming substantial metabolic stress induced by the 5 km run. Overall, the findings indicate clearly pronounced metabolic and neuromuscular fatigue, while the acute workload was not accompanied by significant changes in m. rectus femoris thickness.

Spearman correlation analysis was used to examine the associations between anthropometric, physiological, and neuromuscular variables and 5 km running performance. The results of the statistically significant correlations are presented in Table 3. Within the anthropometric variables, expected and statistically significant associations were identified; body mass index (BMI) was positively correlated with body fat percentage (ρ = 0.64; p < 0.01), while muscle mass was strongly negatively correlated with body fat (ρ = - 0.90; p < 0.001) and moderately negatively correlated with BMI (ρ = - 0.58; p < 0.01). This pattern indicates consistent relationships between body composition indicators within the studied sample.

Age showed a significant negative correlation with maximal heart rate (ρ = - 0.76; p < 0.001) and average heart rate (ρ = - 0.56; p < 0.01), as well as a positive correlation with 5 km finish time expressed in seconds (ρ = 0.56; p < 0.01), indicating that older participants achieved longer running times.

Regarding the physiological response, maximal heart rate was moderately positively correlated with the change in lactate concentration (ρ = 0.49; p < 0.05), suggesting that participants with higher maximal heart rates experienced a more pronounced increase in lactate following the exercise bout. Post-exercise lactate concentration was very strongly correlated with the change in lactate concentration (ρ = 0.97; p < 0.001), which is expected given the low baseline values and the marked increase following the run.

The change in m. rectus femoris thickness was negatively correlated with BMI (ρ = - 0.51; p < 0.05) and body fat percentage (ρ = - 0.45; p < 0.05), which may indicate varying acute muscle tissue responses depending on body composition.

In relation to performance, 5 km finish time was positively correlated with age (ρ = 0.56; p < 0.01) and BMI (ρ = 0.44; p < 0.05). No significant correlations were found between changes in neuromuscular variables and most physiological indicators (p > 0.05), suggesting a relative independence between metabolic and neuromuscular responses to the workload.

4. Discussion

The aim of this study was to examine the acute neuromuscular, metabolic, and perceptual responses to high-intensity 5 km running. The objective was to obtain a comprehensive insight into the immediate post-run changes by analyzing quadriceps MVIC, blood lactate concentration, rating of perceived exertion (RPE), and m. rectus femoris thickness as an indicator of acute alterations in muscle architecture. The findings suggest that the 5 km high-intensity running stimulus resulted in a pronounced metabolic and a partial neuromuscular response, whereas no significant acute changes in m. rectus femoris thickness were identified. A statistically significant increase in blood lactate concentration, accompanied by a very large effect size, confirms the substantial metabolic demand of the prescribed high-intensity 5 km running effort. Simultaneously, a statistically significant decrease in right leg quadriceps MVIC was observed with a large effect size, while the change in the left leg did not reach the level of statistical significance. Such a pattern suggests that the acute neuromuscular response to high-intensity running may be partially manifested and potentially asymmetrical, with the response not being equally reflected across both limbs. In conclusion, the results indicate that high-intensity 5 km running induces acute responses of varying magnitudes depending on the specific indicator observed. This underscores the importance of an integrated approach in assessing acute fatigue, as individual indicators do not necessarily exhibit the same sensitivity to the same running stimulus.

The Relationship Between Age, Body Composition, Physiological Indicators, and Running Performance

Correlation analysis revealed that 5 km running performance is associated with age, body composition, and the physiological response to the workload. The statistically significant negative correlations between age and both maximal and average heart rate indicate that older participants achieved lower values for these physiological indicators during the 5 km running task at submaximal and maximal sustainable intensities (Table 3). In this context, the lower maximal and average heart rate values in older participants can be viewed as an expected consequence of age-related cardiovascular changes, most notably a decrease in maximal heart rate and reduced chronotropic β-adrenergic sensitivity [23]. Since relying exclusively on heart rate for prescribing and monitoring intensity can be limiting due to these age-related and physiological changes, it is highly beneficial to integrate rating of perceived exertion (RPE) and blood lactate concentration into the effort assessment. Zinoubi et al. [17] confirm a strong association between heart rate, lactate, and RPE during exercise, highlighting RPE as a reliable and essential tool for intensity monitoring, particularly in situations where the normal heart rate response to stress is impaired or altered. Furthermore, the total time achieved in the 5 km running task was in a statistically significant positive correlation with the participants age and body mass index (BMI). Given that a higher finish time indicates slower performance, these findings demonstrate that advanced age and a higher BMI are associated with poorer 5 km running results. These results are consistent with previous research [24,25,26] which states that increased age and an unfavorable anthropometric profile, especially higher body mass, lead to changes in running biomechanics, reduced running economy, and a subsequent decline in overall running performance in older athletes compared to younger age groups. This is further supported by the findings of Nummela et al. [27], who emphasize that, alongside oxygen utilization capacity, running economy and maximal oxygen uptake VO_2max are the primary parameters determining the sustainable running speed over long distances. Additionally, the decline in VO_2max values is closely linked to the aging of the cardiovascular system and serves as a primary factor for the decline in long-distance performance among older runners [28].

Neuromuscular Response Following the Running Load

Furthermore, following the 5 km run, a statistically significant decrease in right quadriceps MVIC of approximately 15% was observed in recreational runners, while the 9% decline in the left leg did not reach statistical significance. Despite this, the MVIC results for the left leg show a trend toward statistical significance, suggesting a consistent pattern of reduced force-generating capacity in both limbs. Although the reduction in quadriceps MVIC was recorded bilaterally, a statistically significant decrease was only established in the dominant (right) leg. These results clearly indicate specific characteristics in running biomechanics and the functional roles of the quadriceps as the primary knee extensor during the running cycle. Namely, the quadriceps, which initially displays a higher level of muscle strength, likely assumes a dominant role in generating propulsive force during running, thereby being exposed to greater mechanical work and increased metabolic demands [29]. Consequently, this leads to the accumulation of a higher degree of peripheral and central fatigue specifically, a reduced ability of the nervous system to maintain high levels of motor unit activation ultimately resulting in a more pronounced decline in MVIC [4]. In biomechanical terms, during the ground contact phase, the quadriceps eccentrically controls knee flexion and absorbs mechanical energy, while during the transition to the push-off phase, it participates in stabilization and the efficient transfer of force through the lower extremity. Repetitive exposure to these demands across a high number of running cycles results in cumulative loading of the musculoskeletal system, especially in the dominant limb, further contributing to more pronounced fatigue [29,30]. Therefore, our assumptions are based on similar research, such as the study by da Rosa et al. [31], who describe the existence of functional and lateral asymmetry within stride mechanics, highlighting that the dominant and non-dominant legs do not participate equally in force generation and load absorption. The researchers clearly state that the push-off phase involves the release of previously stored elastic energy and the generation of positive mechanical work, where the limb assuming a greater role in propulsion simultaneously bears a higher mechanical and metabolic load.

Although research directly investigating the impact of MVIC on long-distance runners remains scarce, several studies support the direction of the results obtained in this study. One such study by Nummela et al. [32], conducted on 18 well-trained runners, tested bilateral MVIC on a specialized leg press device before and after a 5 km run and found a 15% decrease in MVIC. A similar study by Pons et al. [4] identified a significant reduction in knee extensor MVIC of 15.1% in men immediately after a 5 km run, concluding that the observed decrease in force-generating capacity was a direct consequence of a combination of peripheral and central fatigue namely, impaired contractile function of the muscle itself and a reduced ability of the central nervous system to fully activate the muscles. Furthermore, similar studies involving MVIC measurements of other muscle groups have recorded even greater reductions. A study by Girard et al. [33] reported a decrease in plantar flexor MVIC of as much as 27% immediately following a 5 km running test, which, as in previous studies, was attributed to reduced muscle activation. The results of the present study are further supported by Taipale et al. [10], who emphasize that 5 km running loads typically reduce lower-limb isometric strength and power by about 15%, while longer durations, such as a two-hour run or combined training loads, cause a reduction in maximal force ranging from 14% to 19%. Therefore, we can assume that the reduction in maximal voluntary contraction, assessed via quadriceps isometric strength, is a clear indicator of acute neuromuscular fatigue manifested by a reduced ability to generate force after running, which is largely driven by peripheral fatigue mechanisms. These mechanisms cause a reduction in action potential conduction velocity along the motoneurons, ultimately impairing excitation-contraction coupling and reducing calcium ion release from the sarcoplasmic reticulum, which is one of the key actors in muscle contraction [34,35].

Metabolic and Perceptual Response to the 5 km Run

In addition to the reduction in MVIC, this study recorded a statistically significant increase in blood lactate concentration following the 5 km run, indicating a markedly enhanced metabolic and energetic activation of the muscles during the effort (Table 2). Simultaneously, it was found that maximal heart rate moderately correlates with the change in lactate levels, while post-race lactate concentration is very strongly associated with its overall change, further confirming the high internal consistency of the metabolic measurements performed (Table 3). Such a robust metabolic response, accompanied by lactate accumulation and a subsequent increase in intramuscular metabolic stress, leads to impaired contractile function and is directly reflected in the reduced capacity to generate maximal force. These results are further supported by the research of Girard et al. [33], who state that the accumulation of metabolic by-products, such as hydrogen ions which increase proportionally with lactate, severely disrupts excitation-contraction coupling within the muscle tissue. Specifically, a drop in intracellular pH reduces the sensitivity of myofilaments to calcium and limits its release within the sarcoplasmic reticulum, directly weakening the strength of the muscle contraction itself [33]. Alongside objective indicators of fatigue, we utilized the RPE scale (Rating of Perceived Exertion) to numerically assess the intensity of fatigue during physical activity. In practice, linear models such as the CR10 scale are frequently used, where workload is graded from 0 (complete rest) to 10 (maximal possible effort) [36]. This provided a subjective insight into the runners fatigue, which we correlated with other study parameters. These findings fully align with previous research indicating that, in addition to mechanical indicators of force decline, a 5 km performance induces significant metabolic and perceptual stress. Similar observations were reported by de Sousa et al. [19], who monitored physiological and perceptual responses in trained runners during a 5 km bout performed in both continuous and interval modes. In their study, parameters were monitored at the first and fifth kilometers; RPE values increased significantly as the effort progressed, reaching extremely high levels at the very end of the bout, clearly reflecting cumulative perceptual stress during the race. Conversely, blood lactate concentration at the end of the continuous race was 2.8 mmol/L, whereas in the interval race, it reached 4.5 mmol/L, indicating that interval loading caused more significant lactate accumulation compared to continuous running. Consistent with our study, where lactate levels rose significantly above the anaerobic threshold alongside a high maximal heart rate (180 ± 16 bpm), we can confirm an intense metabolic response and a high rate of reliance on anaerobic energy sources, as also seen in Girard et al. [5]. Furthermore, the maximal heart rates recorded in our research mirror the rating of perceived exertion (RPE), which was consistently high across all participants (RPE = 8.33± 1.16 on the CR10 scale). This suggests that participants performed the race near submaximal intensity, balancing their running speed precisely at the threshold of high-effort perception tolerance. This relationship between physiological and perceptual indicators strongly supports research highlighting RPE as a key factor in limiting tolerance to training workloads [37]. Such observations were confirmed in practice by Marcora and Bosio [38], who showed that runners with pre-induced leg muscle fatigue achieved a 4% poorer result in a 30-minute race. Since cardiovascular and metabolic parameters (heart rate and lactate) remained unaffected, while the reported perception of effort was equally high despite a significantly slower pace, the authors proved that the performance decline was not a result of poorer physiological economy. Instead, the brain translates impaired muscle function into an increased perception of effort, causing runners to unconsciously decrease their pace to keep the rising fatigue within tolerable limits and avoid premature exhaustion [38].

Changes in m. rectus femoris Thickness Following a 5 km Run

Regarding the objective assessment of muscle architecture, despite clearly demonstrated neuromuscular and metabolic fatigue, our study found no statistically significant change in resting m. rectus femoris thickness. Our results suggest that an acute 5 km running workload does not result in immediate measurable morphological changes in the relaxed muscle, such as cellular swelling, immediately following the cessation of activity. This further confirms that the acute decline in force generating capacity at this stage is primarily metabolic and neural in nature, rather than structural-morphological. This interpretation is directly supported by the findings of Landers-Ramos et al. [39], who utilized ultrasound to examine acute changes in muscle architecture (m. rectus femoris) in 11 runners and concluded that muscle thickness (cellular swelling) does not increase immediately after exhaustive running; instead, such structural-morphological changes manifest only after a delay, specifically 24 hours later. Despite the precision of the method, neither our study nor previous research on long-distance running has recorded significant acute changes in resting m. rectus femoris thickness immediately post-run. It is important to emphasize that the lack of observed changes in the m. rectus femoris is not due to insufficient sensitivity of the measurement method. On the contrary, several studies have shown that ultrasound is sensitive enough to detect morphological and functional changes in the m. rectus femoris and represents a reliable method for monitoring muscle architecture and its adaptations. For instance, Baroni et al. [40] used ultrasound to identify significant long-term morphological adaptations, such as increased muscle thickness and fascicle length, resulting exclusively from a 12-week eccentric strength training program on an isokinetic device. Furthermore, in the context of assessing muscle function, Delaney et al. [14] demonstrated the validity of ultrasound by tracking acute changes in m. rectus femoris dimensions (such as decreased width and a slight increase in thickness) during isometric contractions of varying intensities on a dynamometer. Although both studies confirmed the sensitivity of ultrasound in detecting morphological and functional changes, they were primarily conducted under strictly controlled, isolated conditions rather than immediately following a running workload. This suggests that changes in muscle architecture occur over a time delay rather than immediately after the race. Although no significant increase in m. rectus femoris thickness was observed across the entire sample, a more detailed analysis revealed that the change in thickness was negatively correlated with BMI and body fat percentage (Table 3). These results suggest that the acute muscle tissue response to running loads depends, at least partially, on body composition, with runners possessing higher BMIs and body fat percentages exhibiting a different pattern of muscular response. In this context, as noted by Landers-Ramos et al. [39], changes in muscle thickness immediately following exertion may reflect intracellular swelling caused by cytoskeletal micro-damage due to repetitive muscle contractions and changes in osmotic pressure. Therefore, this negative correlation logically aligns with the aforementioned physiological mechanisms, as runners with greater body mass and an unfavorable body composition endure a significantly higher biomechanical load with every stride [15]. Such additional mechanical stress can result in faster muscle fiber fatigue and an altered morphological response on ultrasound immediately following exertion compared to runners with a lower body fat percentage [39].

This study has several important limitations that should be considered when interpreting the results. First, the participants were not monitored over an extended recovery period (e.g., 24–48 hours), which limits the ability to detect delayed morphological and inflammatory changes and precludes a more detailed insight into the time course of neuromuscular fatigue and recovery processes. Second, the assessment of muscle thickness was restricted solely to the m. rectus femoris and the period immediately following the race; consequently, potential changes in other muscle groups essential for running, as well as the dynamics of the subsequent muscular response, remain unknown. Furthermore, the sample consisted of a specific group of recreational male runners, which reduces the generalizability of the findings to other age and gender groups or runners with different training levels. Finally, it should be noted that some of the variables employed, such as the rating of perceived exertion (RPE), depend on individual perception and can be influenced by motivational and psychological factors despite the standardized measurement procedure. This potentially increases the variability of the results.

5. Conclusions

The results of this study clearly indicate that high-intensity 5 km running in recreational runners induces pronounced metabolic stress and significant acute neuromuscular fatigue. This is primarily manifested through an increase in blood lactate concentration, high RPE values, and elevated heart rate, with a subsequent decrease in quadriceps MVIC. The muscles of the dominant leg experienced the greatest decline in maximal voluntary contraction, resulting from a combination of impaired neural activation and peripheral fatigue. At the same time, the absence of acute changes in m. rectus femoris thickness immediately post-exercise suggests that the reduced force-generating capacity is not primarily a result of immediate morphological changes, such as cellular swelling, but is predominantly driven by neural and metabolic fatigue mechanisms. Analysis of m. rectus femoris thickness indicates that the acute morphological muscle response is not uniform across all participants; rather, it is modulated by individual body composition, where body mass index and body fat percentage define a higher mechanical load per stride and consequently alter the muscular response to exertion. Furthermore, anthropometric characteristics showed that chronological age and elevated BMI directly correlate with poorer 5 km performance, with older runners also exhibiting a decline in maximal heart rate, pointing to a natural reduction in functional capacities. Therefore, these results provide a comprehensive insight into the mechanisms of acute fatigue and emphasize the importance of individual anthropometric characteristics and the integrated monitoring of metabolic and mechanical parameters for a deeper understanding of performance and the optimization of training processes and recovery in recreational long-distance running.