Adequacy of an altitude fitness program (Living and Training) plus intermittent exposure to hypoxia for improving hematological biomarkers and sports performance of elite athletes: A single-blind randomized clinical trial

Citation: Fernández-Lázaro, D.; Mielgo-Ayuso, J.; Santamaría, G.; Gutiérrez-Abejón, E.; Domínguez- Ortega, C.; García-Lázaro, S.M.; Seco-Calvo, J. Adequacy of an Altitude Fitness Program (Living and Training) plus Intermittent Exposure to Hypoxia for Improving Hematological Biomarkers and Sports Performance of Elite Athletes: A Single-Blind Randomized Clinical Trial. Int. J. Environ. Res. Public Health 2022,19, 9095. https://doi.org/ 10.3390/ijerph19159095 Academic Editor: Paul B. Tchounwou Received: 30 June 2022 Accepted: 25 July 2022 Published: 26 July 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). International Journal of Environmental Research and Public Health Article Adequacy of an Altitude Fitness Program (Living and Training) plus Intermittent Exposure to Hypoxia for Improving Hematological Biomarkers and Sports Performance of Elite Athletes: A Single-Blind Randomized Clinical Trial Diego Fernández-Lázaro 1,2,* , Juan Mielgo-Ayuso 3,* , Gema Santamaría1, Eduardo Gutiérrez-Abejón4,5,6 , Carlos Domínguez-Ortega 1,7, Sandra María García-Lázaro 8and Jesús Seco-Calvo 9,10 1Department of Cellular Biology, Genetics, Histology and Pharmacology, Faculty of Health Sciences, Campus of Soria, University of Valladolid, 42003 Soria, Spain; [email protected] (G.S.); [email protected] (C.D.-O.) 2Neurobiology Research Group, Faculty of Medicine, University of Valladolid, 47005 Valladolid, Spain 3Department of Health Sciences, Faculty of Health Sciences, University of Burgos, 09001 Burgos, Spain 4 Pharmacological Big Data Laboratory, Faculty of Medicine, University of Valladolid, 47005 Valladolid, Spain; [email protected] 5Pharmacy Directorate, Castilla y León Health Council, 47007 Valladolid, Spain 6Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (Group CB21/13/00051), Carlos III Institute of Health, 28029 Madrid, Spain 7 Hematology Service of Santa Bárbara Hospital, Castile and Leon Health Network (SACyL), 42003 Soria, Spain 8 Department of Surgery, Ophthalmology, Otorhinolaryngology, and Physiotherapy, Faculty of Health Sciences, Campus of Soria, University of Valladolid, 42003 Soria, Spain; sandramaria.gar[email protected] 9Physiotherapy Department, Institute of Biomedicine (IBIOMED), Campus of Vegazana, University of Leon, 24071 Leon, Spain; dr[email protected] 10 Psychology Department, Faculty of Medicine, Basque Country University, 48900 Leioa, Spain *Correspondence: [email protected] (D.F.-L.); [email protected] (J.M.-A.) Abstract: Athletes incorporate altitude training programs into their conventional training to improve their performance. The purpose of this study was to determine the effects of an 8-week altitude training program that was supplemented with intermittent hypoxic training (IHE) on the blood biomarkers, sports performance, and safety profiles of elite athletes. In a single-blind randomized clinical trial that followed the CONSORT recommendations, 24 male athletes were randomized to an IHE group (HA, n= 12) or an intermittent normoxia group (NA, n= 12). The IHE consisted of 5-min cycles of hypoxia–normoxia with an FIO 2 of between 10–13% for 90 min every day for 8 weeks. Hematological (red blood cells, hemoglobin, hematocrit, hematocrit, reticulated hemoglobin, reticulocytes, and erythropoietin), immunological (leukocytes, monocytes, and lymphocytes), and renal (urea, creatinine, glomerular filtrate, and total protein) biomarkers were assessed at the baseline (T1), day 28 (T2), and day 56 (T3). Sports performance was evaluated at T1 and T3 by measuring quadriceps strength and using three-time trials over the distances of 60, 400, and 1000 m on an athletics track. Statistically significant increases (p< 0.05) in erythropoietin, reticulocytes, hemoglobin, and reticulocyte hemoglobin were observed in the HA group at T3 with respect to T1 and the NA group. In addition, statistically significant improvements (p< 0.05) were achieved in all performance tests. No variations were observed in the immunological or renal biomarkers. The athletes who were living and training at 1065 m and were supplemented with IHE produced significant improvements in their hematological behavior and sports performance with optimal safety profiles. Keywords: hypoxia; athletes; blood biomarkers; sports performance; safety profile; altitude training Int. J. Environ. Res. Public Health 2022,19, 9095. https://doi.org/10.3390/ijerph19159095 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2022,19, 9095 2 of 21 1. Introduction Recently, the sports performance levels in elite competitions have increased considerably and the differences between the results among the top positions have become smaller and smaller. Therefore, coaches and elite athletes of different specialties often combine additional preparation strategies (biological, pharmacological, mechanical, etc.) with their usual training programs in the hope of improving their physiological responses (muscular, blood, cardiovascular, respiratory, endocrine–metabolic, etc.), which could induce improvements in their sports performance, especially for endurance sports, such as athletics, cycling, and triathlon [ 1 ]. One strategy that is employed is altitude training (in any of its forms), which has been endorsed by the world’s top athletes. Continuous exposure to hypoxia, which is typical of altitude training, triggers a series of physiological responses and adaptations that are beneficial to sports performance when the arterial saturation of oxygen (SaO 2 ) is lower than 90% (Table 1) [2]. Table 1. The changes that are caused by hypoxia in the different body systems. Adapted with permission from Fernández-Lázaro et al. [2]. Body System Adaptive Physiological Response to Hypoxia Respiratory Increase in breathing rate and inspired volume Facilitation of the elimination of CO2 Alveolar vasoconstriction Peripheral vasodilatation Cardiovascular Increase in heart rate and cardiac output Decrease in maximum heart rate Reduction in VO2max Increase in the number and diameter of blood capillaries Decrease in muscular and peripheral vascular resistance Increase in the Borg effect (the difference between the pH of arterial and venous blood) Increase in 2,3-DPG and oxygen release to tissues Decrease in hemoglobin affinity for oxygen Endocrine Increase in adrenaline, noradrenaline, cortisol, growth hormone, thyroid-stimulating hormone, T3 and T4 hormones, and testosterone Decrease in aldosterone and insulin Metabolic Utilization of carbohydrates Reference by glycolytic pathways Increase in glycolytic pathway activity Increase in the expression of glucose transporters at the membrane level Facilitation of the control of postprandial blood glucose Hematological Stimulation of EPO secretion Increase in iron demand Expansion of erythrocyte volume Increase in the volume of red blood cells and blood viscosity Immunological Acute response: Increase in cardiac output, ventilation, bronchodilation, NK cells, and pro-inflammatory cytokines (such as IL-6) Maintained response: Elevation of IL-6 and increase in monocyte levels Muscular Increase in oxidative activity, mitochondrial activity, and myoglobin content Changes in aerobic metabolism Increase in volume, strength, and cross-sectional area of muscle fibers Abbreviations: CO 2 , carbon dioxide; VO 2 max, maximum oxygen volume; 2,3-DPG, 2,3-bisphosphoglyceric acid; T 3 hormone, triiodothyronine; T 4 hormone, tetraiodothyronine or tyrosine; EPO, erythropoietin; NK, natural killer cells; IL-6, interleukin-6. Int. J. Environ. Res. Public Health 2022,19, 9095 3 of 21 To increase the likelihood of achieving beneficial physiological adaptations, especially for hematological biomarkers, it has been reported that it is necessary for athletes to be exposed to an actual altitude of at least 2000–2500 m for at least 90% of daytime hours for at least 4 weeks [ 3 ]. However, these extended stays at high altitudes could have negative impacts on the intensity of training and affect sports performance [ 4 ]. To counteract these disadvantages of living and training at altitude, new instruments have been proposed that can simulate the effects of altitude training [ 5 ]. The simulated altitude training strategies that are most commonly used among elite athletes are intermittent hypoxia exposure (IHE) and intermittent hypoxic training (IHT). Both conditions are applied using reduced oxygen (O 2 ) breathing instruments (i.e., mixed gas masks, chambers, tents or rooms, and reduced O 2 breathing devices) [ 6 ]. IHE alternates phases of hypoxia and normoxia. IHT consists of continuous or intervallic training under hypoxic conditions (normobaric or hypobaric) [ 2 ]. IHT programs appear to be much more useful than IHE programs in terms of achieving physiological adaptations (especially hematological adjustments) and sports performance [ 7 ]. However, IHT can cause an increase in wear and tear, which induces notable muscular catabolism, greater fatigue, and alterations in immunological biomarkers that trigger immunosuppression compared to training under normoxic conditions [ 8 – 11 ]; therefore, the recovery time between workouts has to be longer, which can alter classic training systems [12]. Although combining the use of IHE with physical training at altitude is not common [ 13 ], it could potentially be a suitable alternative for achieving the benefits and minimizing the risks of IHT. To our knowledge, only one study has evaluated living and training at low altitude (825 m) with supplementary IHT sessions [ 14 ] and no studies have investigated the effects of living and training at medium altitude (1065 m) with supplementary IHE sessions. In view of this situation, we decided to evaluate the differences between the hematological biomarkers and sports performance of professional athletes who were living and training continuously at altitude (1065 m) and completed an 8-week program of normobaric IHE and a group of professional athletes who completed the same training and were living at altitude but were not exposed to normobaric IHE. In addition, the safety profiles of the normobaric IHE were evaluated using immunological and renal biomarkers. We hypothesized that IHE would substantially improve performance because of the potential benefits for hematological biomarkers that could be induced without causing harmful effects on the athletes. 2. Material and Methods 2.1. Design and Participants Twenty-four (n= 24) professional male athletes (middle- and long-distance) participated in a blinded randomized clinical trial to evaluate the effects of 8 weeks of IHE on different hematological parameters (white blood cells (WBC), monocytes (MON), lymphocytes (LYN), red blood cells (RBC), hemoglobin (Hb), hematocrit (Hct), reticulocyte hemoglobin (RET-Hb), reticulocytes (RET), and erythropoietin (EPO)) and biomarkers for renal performance (urea, creatinine (Cr), glomerular filtration rate CDK-EPI (GFR CDKEPI) and total protein (TP)) and sports performance (strength, speed, aerobic power, and anaerobic power). During the study, the recommendations of the Consolidated Standards of Reporting Trials (CONSORT) group for the conduct of randomized parallel group trials were followed (Appendix A) [ 15 ]. The sample size estimation was performed using the G* Power 3.1.97 statistical power analysis program (University of Dusseldorf, Dusseldorf, Germany; available at https://es.freedownloadmanager.org/Windows-PC/Gpower-GRATIS.html) (accessed on 1 June 2022) [ 16 ]. To estimate the number of subjects that was needed to evaluate the differences between the independent groups, we followed the approach that was proposed by Calvo-Lobo et al. [ 17 ] for studies with small sample sizes. Thus, we considered the differences between the values that were found in the pilot study, which was conducted (n= 10) using two groups of ten patients with an α error of 0.05 and a β Int. J. Environ. Res. Public Health 2022,19, 9095 4 of 21 error of 0.20. This calculation indicated that at least 12 subjects were needed in each group (n= 24), considering a possible dropout rate of 20%. The participants underwent cardiopulmonary and electrocardiographic examinations and were asked to complete a medical questionnaire before entering the study. The exclusion criteria included any pre-existing physical health problems, alcohol consumption or the use of illegal drugs or substances (stimulants, blood derivatives, anabolic agents, etc.) that could alter hematological or renal responses or sports performance. There were no reported injuries before or during the study as injured participants were ruled out by their history and clinical examinations. A dietitian–nutritionist developed an individual diet for each participant that was based on the pre-established nutritional, energy, and macronutrient guidelines for adequate sports performance and the participant’s training volume and training load [ 18 ]. All athletes performed the same training sessions during the precompetitive period (Table 2). The training program was supervised by a coach from the Royal Spanish Athletics Federation, who had more than 30 years of experience with athletes who achieved international success in long-distance and middle-distance events. Table 2. The main contents of the typical weekly training program that was followed by both groups during the 8 weeks of the study. Day Morning Afternoon Monday Lactic Capacity: Interval training series between 200–400 m Aerobic Capacity: Continuous running for 50–60 min Tuesday Aerobic Power: 8–12 km of controlled pace at aerobic threshold Aerobic Capacity: Continuous running for 50–60 min Wednesday Resistance Strength: Interval training on a hill between 200–300 m Mixed Aerobic–Anaerobic: Fartlek training with changes of pace every 2–5 min for 50–60 min Thursday Lactic Power: Interval training series between 300–1000 m Aerobic Capacity: Continuous running for 50–60 min Friday Resistance Speed: Interval training between 100–150 m Aerobic Capacity: Continuous running for 50–60 min Saturday Mixed Aerobic–Anaerobic: Interval training between 1000 and 4000 m Aerobic Capacity: Continuous running for 50–60 min Sunday Aerobic Capacity: Continuous running for between 75–90 min Rest 2.2. Experimental Protocol The athletes in the IHE intervention (HA) group completed a 90-min session of IHE every day for 8 weeks, which took place 1 h after morning training and during which they were seated at rest. The IHE was administered at a ratio of 5 min under hypoxic conditions followed by 5 min of normoxic conditions. Normobaric hypoxic gas was administered using a GO 2 altitude hypoxia device (Biomedtech, Victoria, Australia). According to the manufacturer’s instructions, the O 2 concentration was progressively reduced to allow for sufficient adaptation time (Table 3). Int. J. Environ. Res. Public Health 2022,19, 9095 5 of 21 Table 3. The intermittent hypoxia exposure (IHE) protocol. Weeks Duration (Minutes) FIO2(%) SaO2(%) Simulated Altitude (Meters) Range of Altitude Classification 1–2 90 13 88–84 4000 High altitude 3–4 90 12 84–80 4500 5–6 90 11 80–78 5000 7–8 90 10 <78 5500 Very high altitude Abbreviations: FIO2, inspired fraction of oxygen; SaO2, oxygen saturation. The athletes in the control (NA) group also completed a 90-min session of simulated therapy every day for 8 weeks, which took place 1 h after morning training. To perform the simulated therapy, the GO 2 altitude hypoxia device was used (as for the HA group) but performed 5-min cycles of normobaric normoxic air and normoxic room air. Both groups had their SaO 2 levels constantly measured, either automatically using the GO 2 altitude hypoxia device or manually using a finger pulse oximeter (INVIPOX LTD800, Dimer, Vizcaya, Spain). None of the participants were acclimatized or previously exposed to hypoxia, except for living in Soria (1065 m). The participants were from provinces in Spain that are at lower altitudes than Soria and they had not completed any training camps at altitude in the previous 6 months. 2.3. Anthropometry Skinfolds (mm) (tricipital, bicipital, abdominal, suprailiac, subscapular, iliac crest, front thigh, and calf) were analyzed using a Holtain ® skinfold caliper (Crosswell, Crymych, Pembs., SA41 3UF, UK) with a precision of within 0.5 mm. In order to obtain more information about body fat, the sums of six skinfolds (mm) ( Σ 6 SF) were examined following validated procedures [ 19 ]. Body fat percentage (BF%) was calculated using the Yuhasz equation, following the recommendations of the International Society for the Advancement of Kinanthropometry (ISAK) [ 20 ]. All participants were measured by the same internationally certified anthropometrist (certificate number: #636739292503670742). 2.4. Maximal Oxygen Consumption For the determination of the maximal O 2 consumption (VO 2 max), a modified Bruce treadmill protocol was followed [ 21 ]. This test was performed to ensure that all participants were at a similar level of physical condition and that there was homogeneity within the sample. 2.5. Dietary Evaluation A professional registered nutritionist participated in the study (J.M.-A.) and documented the athletes’ daily food and fluid intake throughout the trial. The athletes followed a specific method for dietary recall, which consisted of a food frequency questionnaire (FFQ) that has previously been used for other sports populations [ 22 ] being completed at T3. They completed the FFQ to record the “frequency” with which they had consumed 139 different types of food and drink over the previous 8 weeks. The frequency categories were based on the number of times that a food or beverage was consumed per day, week or month and the portion size. The serving sizes were estimated using the standard weight of the food items or using a book that contained over 500 photographs of food [ 22 ]. Energy (kcal) and macronutrient (g) consumption was determined by dividing the reported intake by the frequency (in days) using a validated software package (Easy diet©, online version 2020, Spanish Academy of Nutrition and Dietetics, Madrid, Spain) [ 23 ]. In addition, the total energy intake/kg was calculated for each athlete. Int. J. Environ. Res. Public Health 2022,19, 9095 6 of 21 2.6. Blood Collection and Analysis We followed the World Anti-Doping Agency (WADA) regulations when collecting and transporting the samples [ 24 ]. All of our samples were collected under baseline conditions and on an empty stomach, with a period of at least 12 h of fasting since the last meal. All of the blood samples were taken at 08:30 and all of the participants were resting comfortably in a sitting or lying position. The participants were called to the laboratory at 8:30 a.m. on three specific days throughout the study: at the baseline (T1), day 28 (T2), and day 56 (T3) (as shown in Figure 1). The vacutainer system was used (10 mL for serum and 5 mL and 3 mL for EDTA). Immediately after extraction, the tubes were inverted 10 times and were placed in a sealed box to be stored at 4 ◦ C. The temperature during transportation was controlled using a specific label (Libero Ti1, Elpro, Buchs, Switzerland), which was used to measure and register the temperature. The samples were transported under suitable conditions, and they arrived at the laboratory 30 min after extraction. Delays did not affect the analytical quality of the parameters that were studied. The EDTA (anti-coagulant) samples were homogenized for 15 min before being analyzed, as recommended by the WADA. Int. J. Environ. Res. Public Health 2022, 19, 9095 6 of 20 2.6. Blood Collection and Analysis We followed the World Anti-Doping Agency (WADA) regulations when collecting and transporting the samples [24]. All of our samples were collected under baseline conditions and on an empty stomach, with a period of at least 12 h of fasting since the last meal. All of the blood samples were taken at 08:30 and all of the participants were resting comfortably in a sitting or lying position. The participants were called to the laboratory at 8:30 a.m. on three specific days throughout the study: at the baseline (T1), day 28 (T2), and day 56 (T3) (as shown in Figure 1). The vacutainer system was used (10 mL for serum and 5 mL and 3 mL for EDTA). Immediately after extraction, the tubes were inverted 10 times and were placed in a sealed box to be stored at 4 °C. The temperature during transportation was controlled using a specific label (Libero Ti1, Elpro, Buchs, Switzerland), which was used to measure and register the temperature. The samples were transported under suitable conditions, and they arrived at the laboratory 30 min after extraction. Delays did not affect the analytical quality of the parameters that were studied. The EDTA (anti-co- agulant) samples were homogenized for 15 min before being analyzed, as recommended by the WADA. Figure 1. A descriptive diagram of the study timeline. The tubes that contained blood plus EDTA were centrifuged at 2000 rpm for 15 min. The plasma was extracted using a Pasteur pipette, then transferred to a sterile storage tube and kept at −20 °C until the analysis. The hematological biomarkers of WBC, MON, LYN, RBC, Hb, and Hct were established using a System Coulter Counter MAX-M hematological counter. To determine the EPO biomarker, an immunometric and chemiluminescent trial was conducted in solid phase using the Immulite 2000 EPO analyzer (Diagnostic Products Corporation, Los Angeles CA, USA). The RET biomarker was measured by fluorescence using flow cytometry (Beckman Dickinson, Beckman Coulter). To quantify the contents of the RET-Hb, the XE-2100 analyzer (Sysmex, Mundelein, IL, USA) was used. Cr and urea were measured using an automatic biochemical analyzer (Cobas ® 8000 detection system (775 module); Roche Diagnostics GmbH, Barcelona, Spain). The GFR CDK-EPI was estimated using the equations that were described by Canal et al. [25]. The TP was measured using another automatic analyzer (Hitachi 917, Tokyo, Japan). The percentage changes in the plasmatic volume (% ΔPV) were calculated using the Van Beaumont equation [26]. Furthermore, the hematological indicator values were adjusted to the changes in the plasmatic volume using the following formula: Corrected value = Uncorrected value × ((100 + % ΔPV)/100) [27]. Figure 1. A descriptive diagram of the study timeline. The tubes that contained blood plus EDTA were centrifuged at 2000 rpm for 15 min. The plasma was extracted using a Pasteur pipette, then transferred to a sterile storage tube and kept at − 20 ◦ C until the analysis. The hematological biomarkers of WBC, MON, LYN, RBC, Hb, and Hct were established using a System Coulter Counter MAX-M hematological counter. To determine the EPO biomarker, an immunometric and chemiluminescent trial was conducted in solid phase using the Immulite 2000 EPO analyzer (Diagnostic Products Corporation, Los Angeles CA, USA). The RET biomarker was measured by fluorescence using flow cytometry (Beckman Dickinson, Beckman Coulter). To quantify the contents of the RET-Hb, the XE-2100 analyzer (Sysmex, Mundelein, IL, USA) was used. Cr and urea were measured using an automatic biochemical analyzer (Cobas ® 8000 detection system (775 module); Roche Diagnostics GmbH, Barcelona, Spain). The GFR CDK-EPI was estimated using the equations that were described by Canal et al. [ 25 ]. The TP was measured using another automatic analyzer (Hitachi 917, Tokyo, Japan). The percentage changes in the plasmatic volume (% ∆ PV) were calculated using the Van Beaumont equation [ 26 ]. Furthermore, the hematological indicator values were adjusted to the changes in the plasmatic volume using the following formula: Corrected value = Uncorrected value ×((100 + % ∆PV)/100) [27]. 2.7. Performance Tests The physical performance of the athletes was assessed using individual time trials that were completed at the baseline (T1) and on the final day of the study (T3)., which assessed aerobic power, anaerobic power, and speed over the distances of 60, 400, and 1000 m on an athletics track. The athletics track was 400 m long with eight lanes and was approved by the Royal Spanish Athletics Federation (RFEA). Quadriceps strength was recorded using a dynamometer (Leg Jamar, Chicago, IL, USA). Int. J. Environ. Res. Public Health 2022,19, 9095 7 of 21 2.8. Blinding The blinding index was calculated using a questionnaire at T2 and T3. The value of this index ranged from 1 (none of the subjects knew to which group they were assigned) to 0 (all subjects knew to which group they were assigned). Values above 0.5 indicated that the blinding was successful [28]. 2.9. Statistical Analysis The study participants were randomly assigned to the HA and NA groups using a stratified block design, which used a sequence that was generated by the “Random Sequence Generator” application according to the date of admission to the study (available at https://apps.apple.com/es/app/random-number-generator-app/id1476396989) (accessed on 5 June 2022). The analyses were performed using STATA version 15.0 (StataCorp, College Station, TX, USA), SPSS software version 24.0 (SPSS, Inc., Chicago, IL, USA), Graphpad Prism (Graphpad Software version 6.01 San Diego, CA, USA), and Microsoft Excel (Microsoft Excel version 19). The data were presented as means and standard deviations and pvalues < 0.05 were considered statistically significant. The Shapiro–Wilk test was used to determine the normality of the variables. Parametric tests were used because the data followed a normal distribution. To determine the differences between the groups (HA and NA) at time points during the study, a t-test for independent variables was used for the sample characteristics, dietary assessments, and performance tests. On the other hand, a t-test for dependent variables was used to determine the existence of significant differences between the performance tests at T1 and T3. An analysis of variance (ANOVA) with repeated measures was performed to examine the effects of the time × IHE interaction on the different groups (HA and NA) and the hematological behavior, renal function, and sports performance of the groups. The differences between the biomarkers at during times during the study were determined using the Scheffétest. The percentage changes in the performance variables of each group between T1 and T3 were calculated using the following formula: ∆ % = ((T3 − T1)/T1) × 100. The t-test for independent variables was used to determine whether the differences between these percentages were significant. 2.10. Ethical Considerations The study was approved by the Ethics Committee of the Valladolid East Health Area of University Clinical Hospital of Valladolid (Spain) under CASVE-NM-22-586. All subjects provided written informed consent, in accordance with the Declaration of Helsinki and the 2013 Fortaleza revision (World Medical Association, 2013) [29]. 3. Results 3.1. Recruitment and Randomization In total, 40 athletes were initially recruited; however, nine athletes decided not to participate in the study. The remaining 31 athletes underwent the VO 2 max test, of which five were excluded for presenting results that could distort the homogeneity of the sample. These five athletes had just overcome musculoskeletal injuries and were therefore not physically fit enough to follow the training program without risking relapse. In addition, two other athletes were excluded because they were taking drugs that could alter their hematological biomarkers. Overall, 24 athletes were included in the study and were randomly divided into two groups by means of a stratified block design: the hypoxic intervention group (HA; n= 12) and the normoxic control group (NA; n= 12). None of the 24 participants dropped out of the study or interrupted the intervention, so all participants were tested at T2 and T3 (Figure 2). Int. J. Environ. Res. Public Health 2022,19, 9095 8 of 21 Int. J. Environ. Res. Public Health 2022, 19, 9095 8 of 20 hematological biomarkers. Overall, 24 athletes were included in the study and were randomly divided into two groups by means of a stratified block design: the hypoxic intervention group (HA; n = 12) and the normoxic control group (NA; n = 12). None of the 24 participants dropped out of the study or interrupted the intervention, so all participants were tested at T2 and T3 (Figure 2). Figure 2. A flow chart of the enrolment and randomization process, according to the CONSORT regulations. 3.2. Characteristics of the Study Participants No significant differences (p > 0.05) between the evaluated variables among the groups (HA and NA) were observed at the baseline (age, weight, height, Σ6 SF, body fat, and VO 2 max) (Table 4). Table 4. The characteristics of the athletes at the baseline of the study. HA Athletes NA Athletes p Value Sample Size (n) 12 12 Age (years) 26.12 ± 2.90 25.31 ± 4.40 0.619 Body Mass (kg) 63.37 ± 3.72 62.00 ± 4.53 0.353 Height (m) 1.75 ± 0.02 1.73 ± 0.03 0.874 ∑ 6 Skinfolds (mm) 32.61 ± 1.50 1.75 ± 0.02 0.561 Figure 2. A flow chart of the enrolment and randomization process, according to the CONSORT regulations. 3.2. Characteristics of the Study Participants No significant differences (p> 0.05) between the evaluated variables among the groups (HA and NA) were observed at the baseline (age, weight, height, Σ 6 SF, body fat, and VO 2 max) (Table 4). Table 4. The characteristics of the athletes at the baseline of the study. HA Athletes NA Athletes pValue Sample Size (n) 12 12 Age (years) 26.12 ±2.90 25.31 ±4.40 0.619 Body Mass (kg) 63.37 ±3.72 62.00 ±4.53 0.353 Height (m) 1.75 ±0.02 1.73 ±0.03 0.874 ∑6 Skinfolds (mm) 32.61 ±1.50 1.75 ±0.02 0.561 Body Fat (%) 13.34 ±0.90 13.75 ±1.01 0.310 Maximal Oxygen Consumption (mL/kg/min) 57.36 ±0.96 55.37 ±1.90 0.417 Data are expressed as mean ± standard deviation. Differences between the groups with pvalues < 0.05 were statistically significant, according to the independent t-test. Int. J. Environ. Res. Public Health 2022,19, 9095 9 of 21 3.3. Dietary Evaluation During the study, there were no statistically significant differences (p> 0.05) between the energy, macronutrient, and iron intake of the athletes in the different groups (Table 5). Table 5. The energy, macronutrient, and iron intake of the athletes in the two study groups during the 8 weeks of the study. HA Athletes NA Athletes pValue Sample Size (n) 12 12 Energy (kcal) 3130 ±405 3268 ±358 0.693 Energy (kcal/kg) 49.60 ±4.30 52.00 ±5.60 0.126 Protein (g) 151.60 ±29.40 157.60 ±2.50 0.786 Protein (%) 17.00 ±3.20 16.90 ±2.70 0.318 Protein (g/kg) 2.40 ±0.70 2.52 ±0.70 0.830 Animal Protein (g) 83.10 ±19.30 86.60 ±24.60 0.531 Vegetal Protein (g) 60.30 ±19.10 59.30 ±15.30 0.594 Fat (g) 93.80 ±20.80 92.60 ±21.00 0.252 Fat (%) 26.20 ±4.80 25.60 ±4.20 0.169 Fat (g/kg) 1.51 ±0.60 1.48 ±0.50 0.154 Total Carbohydrates (g) 556.50 ±58.20 562.20 ±60.10 0.445 Carbohydrates (%) 64.80 ±6.10 65.00 ±5.20 0.320 Carbohydrates (g/kg) 8.82 ±1.20 9.06 ±1.30 0.180 Iron (Fe) (mg) 33.00 ±5.80 32.90 ±6.10 0.611 Data are expressed as mean ± standard deviation. Differences between the groups with pvalues < 0.05 were statistically significant, according to the independent t-test. 3.4. Biomarkers The % ∆ VP of the participants decreased by 4.5% between T1 and T2 and by 4% between T1 and T3, after adjusting for all of the biomarkers that were analyzed at the different points during the study. 3.5. Blood Biomarkers Table 6shows the evolution of the biomarkers of hematological behavior at the three time points of the study (T1, T2, and T3) for both groups (HA and NA). No significant differences (p> 0.05) between the time points nor between the groups were observed for WBC, MON, LYN, RBC, and Hct. For the HA group, a significant increase (p< 0.05) in Hb was observed at T3 (16.15 ± 0.85 g/dL) with respect to T1 (15.21 ± 1.11 g/dL) and with respect to the NA group (14.97 ± 0.92 g/dL). For the HA group, RET and RET- Hb were also significantly increased (p< 0.05) at T3 and T2 with respect to T1 and with respect to the NA group. Significant (p< 0.05) increases in EPO were observed for the HA group at T2 (6.69 ± 0.88 mU/mL) and T3 (7.05 ± 1.13 mU/mL) with respect to T1 (6.18 ± 1.59 mU/dL) and with respect to the NA group (6.19 ± 1.65 mU/dL). Significant increases in EPO were also seen for the HA group at T3 (7.05 ± 1.13 mU/mL) with respect to T2 (6.69 ±0.88 mU/mL). Int. J. Environ. Res. Public Health 2022,19, 9095 16 of 21 7. Practical Application This study involved to athletes who participated in the Spanish Athletics Championships in Nerja, Malaga (Spain), in June 2022 and the World Athletics Championships in Eugene, Oregon (United States) in July 2022 and who will participate in the European Athletics Championships in Munich (Germany) in August 2022. In general, IHE plus altitude training could be used prior to high-performance competitions, tournaments, or competitive events to improve hematological biomarkers and sports performance. However, the application of IHE plus altitude training as an ergogenic aid should be considered in light of the sporting objective and the monitoring of the athletes would be necessary. This training program could be applied not only to endurance sports athletes, such as those who compete in athletics, cycling or triathlon, but also to athletes whose competitions are extended over long periods of time and require long and continuous efforts, such as tennis gram slam events or team sports championships (e.g., soccer and basketball, among others). Author Contributions: D.F.-L. conceived and designed the research, analyzed and interpreted the data, drafted the paper, and approved the final version that was submitted for publication; J.M.-A. and J.S.-C. analyzed and interpreted the data and critically reviewed the paper; G.S. and E.G.-A. drafted the paper and critically reviewed the paper; S.M.G.-L. and C.D.-O. critically reviewed the paper and interpreted the data. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki and was approved by the Ethics Committee of the Valladolid East Health Area of University Clinical Hospital of Valladolid (Spain) under CASVE-NM-22-586. Informed Consent Statement: Informed consent was obtained from all subjects who were involved in the study and no patients can be identified. Data Availability Statement: Not applicable. Acknowledgments: The authors would like to thank (i) the Neurobiology Research Group from the Department of Cellular Biology, Genetics, Histology and Pharmacology, Faculty of Medicine, the University of Valladolid, for their collaboration on the infrastructures, consumables, and inventoriable material that was necessary to carry out the study, (ii) the Hematology and Hemotherapy Service of the Hospital Santa Bárbara de Soria for their analysis of the participants’ blood samples, and (iii) Cesar I. Fernández-Lázaro for his help with the statistical analyses. Conflicts of Interest: The authors declare no conflict of interest. Appendix A Table A1. The CONSORT 2010 checklist of information to include when reporting a randomized trial. Section/Topic Item Nº Checklist Item Reported on Page No. Title and Abstract 1a Identification as a randomized trial in the title 1 1b A structured summary of the trial design, methods, results, and conclusions (for specific guidance, see CONSORT for abstracts) 2 Introduction Background and Objectives 2a The scientific background and an explanation of the rationale 3 2b The specific objectives or hypotheses 4 Int. J. Environ. Res. Public Health 2022,19, 9095 17 of 21 Table A1. Cont. Section/Topic Item Nº Checklist Item Reported on Page No. Methods Trial Design 3a A description of the trial design (such as parallel, factorial) including allocation ratio 5 3b Important changes to the methods after trial commencement (such as eligibility criteria), with reasons - Participants 4a The eligibility criteria for the participants 5 4b The settings and locations where the data were collected - Interventions 5The interventions for each group with sufficient details to allow for replication, including how and when they were actually administered 5–6 Outcomes 6a Completely defined and prespecified primary and secondary outcome measures, including how and when they were assessed 6–8 6b Any changes to trial outcomes after the trial commenced, with reasons - Sample Size 7a How the sample size was determined 5 7b When applicable, an explanation of any interim analyses and stopping guidelines - Randomization Sequence Generation 8a The method that was used to generate the random allocation sequence 8 8b The type of randomization and details of any restrictions (such as blocking and block sizes) 8 Allocation Concealment Mechanism 9 The mechanism that was used to implement the random allocation sequence (such as sequentially numbered containers) and a description of any steps that were taken to conceal the sequence until interventions were assigned 8 Implementation 10 Who generated the random allocation sequence, who enrolled the participants, and who assigned the participants to interventions 8 Blinding 11a When relevant, who was blinded after assignment to interventions (for example, participants, care providers, those assessing outcomes, etc.) and how 6 11b When relevant, a description of the similarity of interventions 5–6 Statistical methods 12a The statistical methods that were used to compare groups for primary and secondary outcomes 8–9 12b The methods that were used for additional analyses, such as subgroup analyses and adjusted analyses - Results Participant Flow (a diagram is strongly recommended) 13a The number of participants who were randomly assigned, received intended treatment, and were analyzed for the primary outcome in each group 10 and 35 13b The losses and exclusions from each group after randomization, with reasons 10 and 35 Recruitment 14a The dates of the periods of recruitment and follow-ups 7 and 34 14b Why the trial ended or was stopped - Baseline Data 15 A table showing the baseline demographic and clinical characteristics for each group 9 and 28 Int. J. Environ. Res. Public Health 2022,19, 9095 18 of 21 Table A1. Cont. Section/Topic Item Nº Checklist Item Reported on Page No. Numbers Analyzed 16 The number of participants (denominator) in each group that were included in each analysis and whether the analysis was performed for the original assigned groups 10 and 35 Outcomes and Estimation 17a The presentation of the results for each primary and secondary outcome for each group and the estimated effect sizes and precision (such as 95% confidence interval) 10–11 and 29–32 and 36 17b The presentation of both absolute and relative effect sizes is recommended for binary outcomes - Ancillary Analyses 18 The results of any other analyses performed, including subgroup analyses and adjusted analyses (distinguishing prespecified from exploratory) - Harm 19 All significant sources of harm or unintended effects on each group (for specific guidance, see CONSORT for harms) - Discussion Limitations 20 The trial limitations and sources of potential bias, imprecision, and, if relevant, multiplicity of analyses 16 Generalizability 21 The generalizability (external validity, applicability, etc.) of the trial findings 12–16 Interpretation 22 An interpretation that is consistent with results, a balance of benefits and harm, and a consideration of other relevant evidence 12–16 Other Information Registration 23 Registration number and name of trial registry - Protocol 24 Where the full trial protocol can be accessed, when available - Funding 25 The sources of funding and other support (such as supply of drugs) and the role of funders - References 1. 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