Capillary Blood Recovery Variables in Young Swimmers: An Observational Case Study

agnostics is still in pursuit of the optimal combination of biochemical and hema- tological markers to assess training loads and the effectiveness of recovery. The biochemical and hematological markers selected for a panel should be speci c to the sport and training program. Therefore, the aim of this study was to evaluate the usefulness of selected biochemical and hema- tological variables in professional long-distance and sprint swimming. Twenty-seven participants aged 15–18 years took part in the study. Alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH) and alkaline phosphatase (ALP) activities and creatinine (Cr), C-reactive protein (CRP), ferritin, total bilirubin (TB), direct bilirubin (DB) and iron concentrations were measured for 10 weeks and compared with the traditional sport diagnostic markers of creatine kinase (CK) activity and urea (U) concentration. Additionally, capillary blood morphology was analyzed. An effective panel should consist of measurements of CK and AST activities and urea, TB, DB

and creatinine (Cr), C-reactive protein (CRP), ferritin, total bilirubin (TB), direct bilirubin (DB) and iron concentrations were measured for 10 weeks and compared with the traditional sport diagnostic markers of creatine kinase (CK) activity and urea (U) concentration. Additionally, capillary blood morphology was analyzed. An effective panel should consist of measurements of CK and AST activities and urea, TB, DB and ferritin concentrations. These markers provide a good overview of athletes' post-training effort changes, can help assess the effectiveness of their recovery regardless of sex or competitive distance and are affordable. Moreover, changes in ferritin concentration can indicate in ammation status and, when combined with iron concentration and blood morphology, can help to avoid iron de ciencies, anemia and adverse in ammatory states in swimmers. Keywords:athletes; bilirubin; blood morphology; enzyme markers; ferritin 1. Introduction Training for competitive swimming has a long history of focusing on developing endurance and strength and improving specialized swimming techniques [1–3]. One of the key aspects of specialized training is determining the athlete's threshold speed (i.e., speed at the anaerobic threshold). It is also important to increase the athletes' phosphagen system capacity. Extending training process in the eld of improving athletes' aerobic abilities is important in building the predisposition to strength and speed efforts. It should be emphasized, however, that in swimming training it is important to shape both aerobic and anaerobic capacity, allowing to overcome water resistance. This allows the entire training macrocycle to be planned and the appropriate swimming speed to be selected in relation to intensity ranges [2–5]. In competitive swimming, it is necessary to use diagnostic tools and tests to determine the athlete's ef ciency and individualize training. These tools and tests can help maximize performance and monitor the impact of training loads on the athlete's body by measuring markers such as lactic acid (LA) concentration immediately after or during training. Creatine kinase (CK) activity and urea (U) concentrations can also be Int. J. Environ. Res. Public Health2022,19, 8580.

loads on the athlete's body by measuring markers such as lactic acid (LA) concentration immediately after or during training. Creatine kinase (CK) activity and urea (U) concentrations can also be Int. J. Environ. Res. Public Health2022,19, 8580.

Int. J. Environ. Res. Public Health2022,19, 8580 2 of 23 used to monitor muscle damage and the energy cost of long lasting high-intensity training, respectively [6,7]. An optimal biochemical marker for assessing the degree of an athlete's post-training recovery should respond only to exercise and react in a predictable and sustained manner. However, different sports require different training plans, trigger different responses and utilize energy pathways differently. Thus, there is a need for sport-speci c blood test panels to determine the effectiveness of recovery. On the other hand, the high individual variability of CK activity as a marker makes it dif cult for trainers to interpret the results. It should also be noted, that with an increase in the athlete's conditioning, the maximum plasma CK activity in response to a training load may appear 24–36 h post-training [7–11]. Consequently, sport diagnostics require other biochemical markers. Some studies show that aminotransferases can be used as auxiliary diagnostic markers in sports, including swim- ming and replace the CK activity measurement commonly used by trainers, as they re ect the current level of muscle damage in a manner similar to plasma or serum CK activity [9]. However, the optimal solution seems to be to use them together, thus minimizing possible measurement errors and allowing the current state of the athletes' liver to be diagnosed, remembering that initially alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were used in laboratory diagnostics only in the case of suspected liver disease or damage [7–11]. Our previous study investigating long-term measurement of biochemical markers in elite soccer players indicated that AST, CK and lactate dehydrogenase (LDH) activity and creatinine (Cr) concentration, when analyzed together, could constitute a useful set of markers for monitoring the athletes' recovery periods. AST, LDH and Cr seem to be particularly good markers because of the lower inter-individual variability of these parameters in comparison to CK [6,11,12]. Insuf cient recovery time during training cycles can lead to fatigue and predispose young swimmers to mineral de ciency. Iron is one of several important micronutrients for athletes. Iron de ciency may be associated with the development

LDH and Cr seem to be particularly good markers because of the lower inter-individual variability of these parameters in comparison to CK [6,11,12]. Insuf cient recovery time during training cycles can lead to fatigue and predispose young swimmers to mineral de ciency. Iron is one of several important micronutrients for athletes. Iron de ciency may be associated with the development of anemia and im- paired sports performance [13,14]. For this reason measuring plasma iron and magnesium concentrations in swimmers could be an additional tool to monitor recovery effectiveness. Athletes' capability to improve their training performance can also be re ected in their blood morphology [15]. It is known that VO2max correlates with O2transport capacity, aerobic capacity and total hemoglobin concentration in athletes [16]. Our previous study also showed that changes in red blood cell distribution width (RDW), as well as other red blood cell-related parameters including mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC), suggest that erythropoiesis may decrease at the end of training cycle [15]. White blood cell (WBC) count often decreases after a long-term training program [17,18]. On the other hand, our previous study found a post-exercise increase in WBC parameters related to the immune system's response to the physical effort [19–21]. According to the literature, an important observation in the context of recovery pro les is that the baseline mean platelet volume (MPV) may be a predictor of endurance capacity [22,23]. Our previous study suggested that a training program focused on motor performance may cause a decrease in plateletcrit (PCT) associated with a decrease in platelet count (de ned as a decrease in peak values) from the beginning to the end of the training program [15]. Increased brinolytic activity after physical effort is frequently observed in professional athletes [24]. Symptoms of platelet fatigue (i.e., functional im- pairment) have been observed in trained people during recovery [24,25]. In addition, it has been found that coagulation and brinolytic function in athletes are reduced or at least comparable to sedentary counterparts. It is possible that these changes are bene cial for physically active people, as they may be

in professional athletes [24]. Symptoms of platelet fatigue (i.e., functional im- pairment) have been observed in trained people during recovery [24,25]. In addition, it has been found that coagulation and brinolytic function in athletes are reduced or at least comparable to sedentary counterparts. It is possible that these changes are bene cial for physically active people, as they may be involved in protecting against thrombosis and adverse cardiovascular events [24–26]. Therefore, blood morphology assessment should be an important part of a panel used for monitoring recovery effectiveness in professional athletes. Competitive swimming is an individual sport discipline in which competitors are di- vided in training programs into three basic groups depending on their anatomical and phys-

Int. J. Environ. Res. Public Health2022,19, 8580 3 of 23 iological predisposition affecting the preferred start distance: sprint (50–100 m), middle- distance (200 m) and long-distance (400–1500 m) [27]. Monitoring changes in several peripheral blood markers is important for assessing athletes' responses to training loads and the effectiveness of their recovery. This work demonstrates the use of routine laboratory diagnostic markers to evaluate the effectiveness of swimming athletes' recovery compared to the traditional sport diagnostic markers of CK activity and U concentration. The main goal of this observational study was to compare the use of selected markers of clinical biochemistry (ALT, AST, LDH, ALP activities and Cr, CRP, ferritin, TB, DB) with the variability of CK activity and U concentration after recovery in champion-class sports swimmers. 2. Materials and Methods 2.1. Study Protocol and Participants To evaluate the effectiveness of selected biochemical and hematological parameters as markers of recovery effectiveness in professional long-distance and sprint swimming, 27 participants aged 15–18 years and belonging to Polish swimming clubs were recruited for this observational study. The main inclusion criteria included required age, training experience, competitive distance and belonging to the championship-class. Participants not meeting inclusion criteria, not giving or retracting their consent to participate were excluded from the study. Taking the small number of participants into account, this work should be recognized as a case study. Participants were divided by sex and according to their competitive distance, giving male and female sprint (50–100 m) groups (MS and FS groups, respectively) and male and female long-distance (400–800 m) groups (ML and FL groups, respectively). All quali ed female athletes were already after the pubertal spike. The general characteristics of the groups are presented in Table. Detailed participants' training data regarding distance swam, water and dry-land trainings during the observation period are summarized in Supplementary Table S1. Changes in the biochemical and hematological parameters were observed for 10 weeks starting from the rst day of the preparatory training stage after the summer holiday. Table 1.Participant characteristics. Variable FS Group FL Group MS Group ML Group (N = 5) (N = 4) (N = 9)

and dry-land trainings during the observation period are summarized in Supplementary Table S1. Changes in the biochemical and hematological parameters were observed for 10 weeks starting from the rst day of the preparatory training stage after the summer holiday. Table 1.Participant characteristics. Variable FS Group FL Group MS Group ML Group (N = 5) (N = 4) (N = 9) (N = 9) Age (years) 17 (15–18) 16 (15–18) 16 (15–18) 17 (16–18) Height (cm) 180 (175–185) 175 (168–178) 183 (175–187) 188 (176–189) Weight (kg) 64.0 (60.0–64.5) 61.0 (56.5–68.2) 67.6 (65.0–70.0) 78.0 (76.0–82.0) Body Mass Index (kg/m 2 ) 21.1 (18.3–22.0) 20.3 (19.8–21.7) 20.8 (20.1–21.5) 22.5 (22.1–24.8) Average FINA 1 points708 (658–794) 664 (656–691) 664 (610–858) 665 (600–817) Length of training experience (years) 9.0 (9.0–11.0) 10.5 (8.5–12.0) 9.0 (8.0–9.0) 10.0 (7.0–11.0) Weekly training volumes (h) 18.0 (16.5–20.0) 23.5 (19.0–28.5) 18.0 (18.0–20.0) 22.5 (20.0–27.0) Weekly distance swam (km) 35.0 (14.5–53.0) 34.5 (20.0–51.4) 33.7 (19.0–51.0) 51.2 (22.0–61.2) Weekly water training sessions 9 (4–11) 10 (5–12) 8 (4–11) 10 (5–12) Weekly dry-land trainings (h) 5 (2–9) 7 (4–10) 8 (4–12) 6 (2–12) 1 FINA—International Swimming Federation (F²d²ration Internationale de Natation). The table presents median (Q1–Q3) values, except for age, average FINA points, weekly distance swam, weekly training sessions and weekly dry-land training, where median (min–max) is presented. N—number of participants. Eleven standard medical diagnostic markers including ALT, AST, LDH and alkaline phosphatase (ALP) activities and Cr, CRP, ferritin, total bilirubin (TB), direct (conjugated) bilirubin (DB) and iron concentrations were chosen to evaluate their usefulness as indicators

Int. J. Environ. Res. Public Health2022,19, 8580 4 of 23 of recovery effectiveness compared to the traditional sport diagnostic markers of CK activity and U concentration. Additionally, blood morphology indices were observed in all participants. All participants had been engaged in swimming training for at least 5 years and were classi ed as a junior or younger junior. The participants had no history of any metabolic syndrome according to the International Diabetes Federation description (diabetes, pre- diabetes, abdominal obesity, high cholesterol and high blood pressure) or cardiovascular disease (de ned by the World Health Organization as disorders of the heart and blood vessels). Participants were non-smokers and refrained from taking any medications or supplements known to affect metabolism. Participants (and their parents if appropriate) were fully informed of any risks and discomfort associated with the experimental pro- cedures before giving their written consent to participate. The study was approved by the Local Ethics Committee (approval number: 05/KB/VII/2019) in accordance with the Helsinki Declaration. 2.2. Blood Sampling Fasted blood samples were obtained according to standard diagnostic procedures. Fingertip capillary blood collection systems (KABE-Labortechnik GmbH, Nümbrecht- Elsenroth, Germany) were used to collect blood samples for biochemical and hematological analyses using lithium heparin (2 capillaries per 200 L of blood; cat. No. 077201) and ethylenediaminetetraacetic acid (EDTA; 1 capillary per 100 L of blood; cat. No. 077103), respectively, as anticoagulants [28,29]. Capillary blood was collected between 6.00 am and 6.30 am after one day of recovery (i.e., a day where no training took place). 2.3. Blood Analysis All blood analyses were performed no longer than 60 min after collection. Blood plasma was used to determine CK, AST, ALT, ALP and LDH activities and U, Cr, TB, DB, CRP, ferritin and iron concentrations. All parameters were determined using a standardized diagnostic method, following the manufacturer's instructions (BioMaxima S.A., Lublin, Poland or, in the case of ferritin, Quimica Clinica Aplicada S.A., Amposta, Spain). The biochemical tests were carried out using an Auto Chemistry Analyzer BM-100 (BioMaxima S.A., Lublin, Poland). All analyses were veri ed using a multiparametric control serum and normal (BioNorm) and high (BioPath)

parameters were determined using a standardized diagnostic method, following the manufacturer's instructions (BioMaxima S.A., Lublin, Poland or, in the case of ferritin, Quimica Clinica Aplicada S.A., Amposta, Spain). The biochemical tests were carried out using an Auto Chemistry Analyzer BM-100 (BioMaxima S.A., Lublin, Poland). All analyses were veri ed using a multiparametric control serum and normal (BioNorm) and high (BioPath) level control serums (BioMaxima S.A., Lublin, Poland). Blood morphology parameters were obtained using an automatic hematology analyzer ABX Micros 60 (Horiba ABX Sp. z o.o., Warsaw, Poland). 2.4. Statistical Analysis All data are presented as the median (Q1–Q3) of the measurements taken. Statistical analyses were carried out using Statistica (version 13, TIBCO Software Inc., Palo Alto, CA, USA, 2017) or R (https://cran.r-project.org/ normality of the data distribution within the subgroups was assessed using the Shapiro- Wilk test. Since the data was not normally distributed, nonparametric statistical analyses were carried out. Differences between the parameters obtained from females and males and between sprint and long-distance groups were analyzed using the Mann-Whitney U test. Differences between time points were analyzed using Friedman's analysis of variance for repeated measures followed by Dunn's post-hoc test with a Bonferroni correction. Correlations between variables were analyzed using Spearman's rank correlation coef cient. For all analyses, apvalue < 0.05 was considered signi cant. General linear mixed model (GLMM) was used to examine whether laboratory param- eters changed differently throughout the study in the short and long distance swimmers. The week of the study (time, treated as a categorical variable) and distance were xed ef- fects. Individuals were treated as random factors. The signi cance of the time and distance interaction was evaluated by comparing two models, with and without the interaction term using the likelihood ratio test. Results with FDR (False Discovery Rate)-adjustedp< 0.05

Int. J. Environ. Res. Public Health2022,19, 8580 5 of 23 were considered statistically signi cant. General linear mixed models were tted using lme4 package in R (https://cran.r-project.org/ Statistical power of the tests was calculated using G* Power version 3.1.9.2 software (http://www.gpower.hhu.de 3. Results 3.1. Analysis of Selected Enzyme Activities The recovery pro le of CK, AST, ALT, ALP and LDH activities during the 10 weeks is presented in Figure. There were no signi cant differences between the female sprint and long-distance groups for CK, ALT and ALP activities (FigureA,C,D). In the male groups, no differences in CK, AST and ALT activities were observed (FigureA–C). CK activity was negatively correlated with AST activity in the FS group, whilst there was a positive correlation between CK activity and AST and ALT activity in both male groups and LDH activity in the MS group (Table).Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 5 of 24 distance interaction was evaluated by comparing two models, with and without the inter- action term using the likelihood ratio test. Results with FDR (False Discovery Rate)-ad- justed p < 0.05 were considered statistically significant. General linear mixed models were fitted using lme4 package in R (https://cran.r-project.org/ (accessed on 20 June 2022)). Statistical power of the tests was calculated using G* Power version 3.1.9.2 software (http://www.gpower.hhu.de (accessed on 15 October 2014)). 3. Results 3.1. Analysis of Selected Enzyme Activities The recovery profile of CK, AST, ALT, ALP and LDH activities during the 10 weeks is presented in Figure 1. There were no significant differences between the female sprint and long-distance groups for CK, ALT and ALP activities (Figure 1A,C,D). In the male groups, no differences in CK, AST and ALT activities were observed (Figure 1A–C). Figure 1.Cont.

Int. J. Environ. Res. Public Health2022,19, 8580 6 of 23Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 6 of 24 Figure 1. Capillary plasma median activity during recovery of: (A) creatine kinase (CK), (B) aspar- agine aminotransferase (AST), (C) alanine aminotransferase (ALT), (D) alkaline phosphatase (ALP), (E) lactate dehydrogenase (LDH) in female long-distance (FL) and sprint (FS) swimmers and male Figure 1. Capillary plasma median activity during recovery of: (A) creatine kinase (CK), (B) as- paragine aminotransferase (AST), (C) alanine aminotransferase (ALT), (D) alkaline phosphatase (ALP), (E) lactate dehydrogenase (LDH) in female long-distance (FL) and sprint (FS) swimmers and male long-distance (ML) and sprint (MS) swimmers. The midpoint represents the median; whiskers

This study evaluates biochemical and hematological variables in young swimmers to assess recovery effectiveness.