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Acute and Long-Term Variations in Variables Related to Redox, Inflammation and Hormonal Status in Male Football Players: A Systematic Review and Recommendations

Article Information

Evdokia Varamenti1*, Catherine Beattie2, David Tod3, Tulasiram Bommasamudram4, Cristian Savoia5, Samuel A Pullinger6*

1Sports Science Department, Aspire Academy, Doha, Qatar

2 Science and Medical Department, Bolton Wanderers Football Club, Bolton, UK

3 Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK

4Department of Exercise and Sports Science, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, India

5 Federazione Italiana Giuoco Calcio (F.I.G.C.), Rome, Italy

6 Sport Science Department, Inspire Institute of Sport, Vidyanagar, Dist. Bellary, India

*Corresponding Author:

Evdokia Varamenti, Sports Science Department, Aspire Academy, Doha, Qatar

Samuel Pullinger, Sport Science Department, Inspire Institute of Sport, Vidyanagar, Bellary, India

Received: 14 August 2022; Accepted: 26 September 2022; Published: 10 October 2022

Citation:

Varamenti E, Beattie C, Tod D, Bommasamudram T, Savoia C, Pullinger SA. Acute and Long-Term Variations in Variables Related to Redox, Inflammation and Hormonal Status in Male Football Players: A Systematic Review and Recommendations. Journal of Orthopedics and Sports Medicine 4 (2022): 246-262.

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Abstract

Introduction: The present study aimed to review the acute and long-term variations in variables related to redox, inflammation and hormonal status in male footballers.

Materials and methods: A PRISMA-compliant systematic review was conducted. The entire content of PubMed, Scopus and Science Direct were systematically searched until May 2022. Studies with outcomes including: (1) adult male football players, (2) a redox and/or an inflammatory and/or a hormonal marker after a training period, and (3) variables measured in blood/saliva.

Results: Thirty-four studies met the inclusion criteria for the qualitative synthesis. Fourteen studies on redox status, 16 on inflammation/muscle damage and 20 on hormonal variations. Only 4 studies incorporated markers related to all 3 statuses, while 8 studies looked at a combination of 2. Studies around redox homeostasis found several markers to fluctuate with MDA, TBARS, protein carbonyls, GSSG, GPx, CAT, and uric acid increasing immediately after a game. Hormonal markers, such as testosterone in blood, revealed no significant change after training. Some found T to increase post-exercise, and some a decrease. Cortisol increased in both short- and long monitoring periods. Markers associated with inflammation and muscle damage found creatine kinase elevated immediately post-game and over extended periods. LDH, C-RP, and IL-6 were also higher post-match.

Discussion: Exposure to short or long-term participation in football training and competitions could significantly affect footballers' redox, inflammation and hormonal status. However, greater consistency across studies is required to ascertain the implications of structured training regimens on measured variables. Selecting the most relevant protocol/ conditions and biochemical markers, including the collection time and the type of specimen, must be considered.

Keywords

Oxidative stress; Cytokines; Testosterone, Cortisol; Football; Review

Oxidative stress articles; Cytokines articles; Testosterone articles, Cortisol articles; Football articles; Review articles

Article Details

Abbreviations:

RONS - Reactive Oxygen and Nitrogen Species; MDA – Malondialdehyde; TBARS - Thiobarbituric Acid Reactive Substances; LOOH - Lipid Hyperoxides; PC - Protein Carbonyls; SH-group - Sulfhydryl-Group; GPx - Glutathione Peroxidase; CAT - Catalase; SOD - Superoxide Dismutase; GSH - Reduced Glutathione; GSSG - Oxidized Glutathione; UA - Uric Acid; TAC - Total Antioxidant Capacity; TAS - Total Antioxidant Status; T - Testosterone; C - Cortisol; T:C ratio – Testosterone to Cortisol Ratio; CK - Creatine Kinase; LDH - Lactate Dehydrogenase; Mb - Myoglobin; CRP – C-Reactive Protein; IL-6 - Interleukin-6.

1. Introduction

High-level football players are continuously exposed to many training sessions and competitions during the training season. This level of exposure poses a potential issue when it comes to player fatigue or sports injuries. The accumulation of training and competition load without adequate recovery can lead to overtraining syndrome or possible injuries because of the tremendous physical, psychological, and loading demands placed on the individual. Recent investigations have found that sports teams or individual athletes that can avoid injuries demonstrate greater success during the competitive season [1-3]. The absence of several training sessions, both because of sports injuries or overtraining can affect the athletes’ performance and expected financial benefits.

Furthermore, severe disturbances in professional sports like football can cause the elimination of contracts and sponsorships. Sports performance deterioration can markedly affect athletes from a physical and a mental aspect. To improve, athletes must spend an extended period performing specific activities while dedicating a lot of time following specialised programs to gain benefits. Therefore, there is a great need to monitor athletes and gather vital and insightful information about their physical condition, which can help and guide practitioners in preventing injury. Since a proper recovery approach integrates the 4Rs [4] (refuel, rehydrate, remodelling and recovery), some main parameters to consider are biochemical variables related to athletes’ redox, inflammation, muscle damage and hormonal status.

It is well known that sports exercise and participation in events can significantly alter the athletes’ redox, hormonal, and inflammation condition [5,6]. By continuously engaging in well-structured training programmes, players are exposed to diversified types of stress that ultimately benefit them to accomplish the desired body adaptations and performance improvements. The oxidative stress generated from exercise can be viewed as signalling to determine adaptations, especially in endurance workouts [7]. Typically, acute alterations in oxidative stress molecules pre-, during, and post-exercise stimulate the body’s upregulation and transformations. At the same time, an increment in distinct redox homeostasis biomarkers for an extended duration might indicate the need for adjustments in the provided training prescription [8].

Oxidative stress mechanisms can be strongly correlated with inflammation (acute or systemic) through the activities of neutrophils and macrophages. After an injury, leucocyte subpopulations relocate to the impaired tissue for healing by discharging Reactive and Nitrogen-Oxygen Species (RONS). Besides, when an athlete’s immune status is suppressed, an enhanced presence of pro-inflammatory cytokines occurs [9,10]. Cytokines, such as IL-6, play a central role in controlling inflammation, clearing antigens, and repairing tissue [11].

During a football game, players perform definite movements during their attacking or defending attempts, frequently producing intense muscle contractions that eventually contribute to muscle damage. This transient period of muscle damage is characterized by muscle strength loss and Delayed Onset of Muscle Soreness (DOMS) [12]. Throughout the football training season, alterations in specific hormones, such as testosterone and cortisol, are observed, which are essential in determining the performance adaptations. Free bioavailable testosterone is closely associated to anabolism, cortisol, to catabolic processes, while the ratio of those two hormones can be used as an indicator of overtraining [13].

The effect of training on footballers' performance adaptation and health protection depends, among other factors, on the specificity of applied training load and recovery period, individual's training background and current physical status [14]. Recent recommendations indicate that different types of exercise may provoke varying degrees of metabolic stress and lead to redox, hormonal, and inflammatory responses in adult footballers. However, the related information is not straightforward because studies assessing different biomarkers diversify in testing protocols and sample collection timings. The lack of standardization of methods and procedures has hindered some results and needs further clarification.

The periodical assessment of variables linked to oxidative stress hormones, inflammation, and muscle damage can help coaches, and sports practitioners optimise training load sequences, maximize adaptations, and positively influence football performance. Therefore, the paper aimed to systematically review data documenting acute and long-term changes in variables related to redox status, inflammation, and hormonal responses in adult football players over short- or prolonged training periods.

2. Materials and Methods

2.1 Reporting standard

This systematic review conforms to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines [15]. The PRISMA 2020 checklist is presented in Appendix 1, indicating the page numbers where items of information are present in the current manuscript.

2.2 Eligibility criteria

The inclusion criteria were based on the Cochrane guidelines for conducting systematic reviews [16]. The criteria for inclusion and exclusion were set and agreed upon by all five authors. Following the initial selection process of studies, two authors (EV and SP) independently completed the eligibility assessment in a blinded, standardized way by screening the titles and abstracts. To be considered eligible, the manuscript had to meet the following inclusion criteria:

  1. Population: Only healthy males and adult participants (≤18 years of age). Females were excluded due to the impact of the menstrual cycle (hormonal fluctuations) on football performance parameters, thereby rendering it difficult to interpret findings accurately. Female sex hormones have displayed substantial physiological effects on altering fluid regulation and modifications in thermoregulatory, muscular, and metabolic responses. Maximal endurance performance, injury rates, weight gain, mood profiles, and dysmenorrhea have all been negatively affected in female soccer players during different menstrual cycle stages [17].
  2. “Football” specific: Only studies related to Association football (soccer) were included, meaning any studies related to Rugby football (e.g., Rugby Union or Rugby League), Gridiron football (e.g., American football or Canadian football), Australian Rules Football (AFL) and Gaelic football were excluded.
  3. Training period: Short-term training (i.e., a soccer match, a Loughborough test) and/or long-term training periods (i.e., a more extensive training period).
  4. Biomarkers: Biomarkers associated with redox status, specific hormones, inflammation, and muscle damage measured in saliva or blood were included.
  5. Design: Non-Randomised Control Trials (NRCTs) and case-control study designs were considered.

2.3 Literature search strategy and information sources

A computerised English-language literature search of the grey literature (EV); Liverpool John Moores University Library (SP); and electronic databases: PubMed (MEDLINE), Scopus and Science Direct were conducted (November 2021 – May 2022) and ended on the 22nd of May 2022. A search for relevant content related to differences in biomarkers associated with oxidative stress, inflammation mediators and hormonal variations in male soccer players using the following three search syntaxes using Boolean operators in titles, abstracts, and keywords of indexed documents was conducted:

(“oxidative stress” OR “oxidative damage” OR “redox alterations” OR “redox status”) AND (“adult”) AND (“soccer” OR “football”).

(“CK” OR “inflammation” OR “IL-6” OR “C-RP” OR “LDH” OR “Myoglobin”) AND (“adult”) AND (“soccer” OR “football”).

(“testosterone” OR “cortisol” OR “ratio”) AND (“adult”) AND (“soccer” OR “football”).

Additional search techniques using wildcards, truncation and proximity searching were incorporated to widen the search. Secondary searches consisting of the reference lists of all papers included were screened manually for additional relevant documents as part of the secondary search (CB and CS). In addition, forward reference searching was conducted to explore potential follow-up studies through citations and authors (SP). One author (EV) independently carried out the searches for study selection to minimize potential selection bias. Figure 1 presents the flow of papers through the study selection process using the PRISMA 2020 flow diagram [17].

2.4 Study selection

Where both male and female participants took part in a research study, the article was included if the data from male participants could independently be identified. In instances where the title and abstract did not contain enough detail to indicate whether an article was relevant to the review, the complete article was obtained and read. This process enabled the authors to determine whether the paper met the primary inclusion criteria. In instances where the article's primary purpose was not an investigation related to redox status and/or hormonal variations and/or inflammation markers, the papers were excluded from the review. Letters to the editor, conference abstracts and literature reviews were excluded as these studies were not found to be methodologically-quality-assessable and/or critically appraisable.

Figure 1: PRISMA 2020 flow diagram of the study selection process [15].

2.5 Data extraction

Data extraction was performed by two authors (CB and CS) independently and a data check was following performed by two authors (EV and SP) with the following data extracted from the included studies: The study authors and date.

  1. The number of participants, their age, and the level of soccer they “compete/perform” (e.g., professional players from Serie A in Italy, professional players from a 2nd Division soccer team in Brazil).
  2. The considered variables concerning redox status, hormonal variations, inflammation, and muscle damage.
  3. The sampling time and the description of the activity and performance test used (e.g., training phase, the number of assessed time-points, the time of sampling.
  4. The effects of the activities or performance tests on the selected variables at different time points.

2.6 Quality assessment

A modified 27-item methodological quality assessment checklist on each included article using the Downs and Black scale was conducted [18]. The checklist consisted of 27 “yes”-or- “no” questions which were scored, totaling up to a possible 28 points. Item 27: “Did the study have sufficient power to detect a clinically important effect where the probability value for a difference being due to chance is less than 5%?” to a yes (1-point) or no/unable to determine (0 points) scoring. The questions were categorized under 5 sections: Reporting (10 items; 1-10), External validity (3 items; 11-13), Internal validity study bias (7 items; 14-20), internal validity confounding selection bias (7 items; 21-26) and power (1 item; 27). The quality assessment of the articles was conducted by two reviewers (CB and SP) independently, with disagreement on 26 answers across the 34 manuscripts (2.8 %). The observed differences were resolved by a third reviewer (CS).

2.7 Selected biochemical parameters

The biochemical parameters analysed within the review were divided into three categories:

  1. Redox homeostasis: molecules related with lipid peroxidation (Malondialdehyde – MDA; Thiobarbituric Acid Reactive Substances – TBARS; Lipid Hyperoxides - LOOH), Protein Modifications (Protein Carbonyls – PC; SH-group - Sulfhydryl-group), Enzymatic Antioxidants (Glutathione Peroxidase – GPx; Catalase – CAT; Superoxide Dismutase - SOD), Non-enzymatic Antioxidant (reduced glutathione – GSH; Oxidized Glutathione – GSSG; Uric Acid - UA) and total antioxidant capacity (Total Antioxidant Capacity – TAC; Total Antioxidant Status - TAS).
  2. Hormonal responses: endocrinological variations in testosterone, cortisol, and their ratio T: C.
  3. Muscle damage and inflammation markers: activity of intracellular enzymes (Creatine Kinase -CK; Lactate Dehydrogenase – LDH; Myoglobin – Mb; C-Reactive Protein - CRP) and Pro- and Anti -inflammatory cytokines (interleukin-6 - IL-6).

3. Results

3.1 Search results

The primary database revealed 730 articles identified from databases and 1309 articles via organisation and citation searching. Figure 1 presents the number of articles found in each electronic database or through other methods and a detailed flow chart of the literature search, including all the steps performed. Once all duplicates were removed, 491 manuscripts obtained via databases remained in the reference manager (Mendeley, Elsevier, Amsterdam, The Netherlands). After examining titles, abstracts, and keywords, 61 were sought for retrieval and retained for full-text analysis. When assessing for eligibility, 29 were deemed eligible, and 32 were excluded. A further 34 reports identified via organization’s and citation searching were assessed for eligibility, with an additional 5 articles considered eligible. Therefore, a total of 34 reports were included in the review. The reasons for exclusion can be found in Table 1.

Table icon

Table 1: Summary of all studies on redox status of adult soccer players with an overview of the variables examined the type of activity and sampling times and the main findings in relation to each variable.

3.2 Study characteristics

The detailed participant characteristics for each study included within the review are shown in Tables 1, 2 and 3. In total 1130 male football athletes were included across the 34 studies, with an average of 33 participants per study, with the lowest number of participants included 5 [19] and the highest number of participants included 467 [20]. The average age of participants was 23.2 ± 2.9 yrs, with a total of 3 studies failing to mention the age or age range of participants [21-23]. The total number of studies looking at redox status was 14 (Table 1), while 20 were on hormonal variations (Table 2) and 16 related to inflammation and/or muscle damage (Table 3).

Table icon

Table 2: Summary of all studies on hormonal variations in adult soccer players with an overview of the variables examined the type of activity and sampling times and the main findings in relation to each variable.

Table icon

Table 3: Summary of all studies on inflammation and/or muscle damage markers of adult soccer players with an overview of the variables examined the type of activity and sampling times and the main findings in relation to each variable.

Four studies assessed biomarkers associated with redox status, specific hormones, inflammation, and muscle damage combined [21, 24-26], 4 other studies assessed biomarkers associated with redox status and inflammation and muscle damage [27-30], and a further 4 studies assessed biomarkers associated with hormonal fluctuations and inflammation and muscle damage [31-34]. All other studies either assess biomarkers associated with redox status or biomarkers associated to hormonal fluctuations or biomarkers associated to inflammation and muscle damage alone.

3.3 Redox homeostasis

3.3.1 Lipid and protein peroxidation

The two most frequently used molecules to determine lipid peroxidation were MDA and TBARS (Table 1). Acute levels of MDA displayed an increase following a competitive/simulated soccer match [25-27,35], a training session/performance trial [36-38] or a combination of both [28]. After completing a Loughborough Intermittent Shuttle Test (LIST), MDA values increased immediately after completion of the test, even remaining elevated up to 72-h post a soccer match. When comparing values at different time points throughout a competitive season, MDA values increased during the mid-and the end of a competitive season in soccer, while no differences were established during pre-season or at the end of the transition period. When assessing values after a single training session, values decreased 45 days after [38]. However, no differences were established in MDA levels in saliva following an acute High-Intensity Interval Exercise (HIIE) protocol [37].

Salivary TBARS also fluctuated at different time points throughout the competitive season, with the lowest values observed before the pre-season with higher values at the start, the mid and the end of the season [21]. A study performed by Viana-Gomes et al. [30] found TBARS in saliva to increase immediately after 2 soccer matches performed 4 days apart (day 2 and day 6), while plasma TBARS also showed to increase 48-h post the second match (day 6). Salivary TBARS did not change immediately after an HIIE protocol [37] or in plasma post a simulated match [39].

Protein Carbonyls (PC), as an index of protein carbonylation, showed increases in all examined studies. Two studies found PC values to differ across a competitive season [21] and at different time points after two competitive games spaced 4 days apart [30]. Values were also higher immediately, 24-h, 37-h, or 48-h post competitive soccer match, while other time points did not differ [29,35]. The redox status of protein sulfhydryl groups (SH-group related proteins) increased after a competitive match at different time points throughout the season or after 45 days of training [26,38]. However, some studies found SH-group related proteins to decrease following a LIST protocol or 45 days of training [28,38].

3.3.2 Glutathione, antioxidant enzymes, and total antioxidant capacity

Glutathione (GSH) levels dropped immediately post [39], 13-h post [29], 24-h and 48-h post [35] a soccer game. When two matches were performed four days apart, GSH values increased 48-h after the second competitive game [30]. GSH fluctuated throughout a soccer training season in professional players of the Italian series A, with values increasing after 4 months and then decreasing after 6 months into the training season. However, GSH samples collected after an HIIE protocol did not change [37].

Glutathione Peroxidase (GPx) and glutathione oxidized (GSSG) also showed to vary, with values increased 24-h and 48-h post-match [35]. However, Silva et al. [25] found values of GPx to decrease 24-h post-match, with no differences observed 48-h post. When assessing the GSH/GSSG ratio, it was observed that values increased at the start of the season in September in a group of players competing in the French League [40] and players of the Italian League [21]. Acutely, Fatouros et al. [35] found this ratio to decrease 24-h and 48-h post-match.

Superoxide Dismutase (SOD) increased 24-h after the completion of a soccer match [25], at mid-and end of the competitive season, to decrease at the end of the transition period compared to the pre-season levels [26]. However, SOD did not change in players competing in the French league throughout the season [40]. Catalase (CAT) increased immediately post-match, but it did not differ from 13-h to 109-h post-match [29,35]. Antioxidant enzymes, SOD & CAT, remained unaltered when measured in saliva [37].

Uric Acid (UA) showed increases in most studies, with higher values directly after the completion of a LIST test [28] and 24-h up until 72-h post-match [27,29,35]. Besides, plasma UA also increased after two competitive matches with a four-day break in-between [30]. On the contrary, UA decreased when measured in saliva after an HIIT protocol [37]. At the same time, it did not fluctuate in a group of Portuguese footballers when measured short- or long-term [25,26]. Total antioxidant capacity and total antioxidant status increased immediately after a LIST assessment [28] and up to 72-h after a soccer match [26,27,35]. Some studies did not find any variations following a simulated soccer [39], a period of 8 days where players had 2 games [30], at different time points during the competitive season [26] or after 45 days of training [38].

3.4 Hormones

3.4.1 Testosterone

The measurement of Testosterone (T) in blood did not reveal significant changes in ten of the examined studies either after short- or long periods of monitoring, e.g., two seasons where several samples were collected at different time points during the pre-season, preparatory phase, or in-season [13,19,21,24,33], or pre-and-post a tournament [41] or immediately after a soccer game [25,31,32]. The concentration of T did not also show noteworthy changes from 24-h to 144-h post-game [31].

However, five studies showed T increased immediately post-match [34], following a running exercise performed at the start and end of the 7-week preparation period [42] and before the pre-competition phase when compared to the beginning of preparatory phase [22]. In Ali et al. [43] and Francavilla et al. [19], concentration was high as well. Still, we must mention that the free testosterone was analysed in the first study, and the second study also contained saliva samples.

Further, four studies found T to decrease; immediately and 45 min post-game [44], after 12-weeks of training [45], post the re-building period, and mid-season [23] and post-competition phase compared to preparatory and pre-competition stages [22]. When T was analysed in saliva, two studies displayed low levels: 10-mins post-match [46] and after 4-months of training into the season at 11:30 h and 17:00 h [47].

3.4.2 Cortisol

Cortisol (C) values in most studies showed an increase at mid-season [23], at the end of the season (May) [21] and two days after the final match of a 19-game Championship [14]. Acutely, C increased directly after an official soccer match [25,31,33] or training match [48,49]) and immediately after a collegiate tournament [41]. Levels of C were also high during halftime, immediately after and 45-min after a match [44]. Though, C levels dropped following a 6-week training regimen [43], before the pre-competition phase [22], and at the end of the competitive season when compared to the start of the season [26]. However, C concentration did not change significantly over two training seasons when it was tested at several different time points [13], after a running exercise performed twice, at the beginning and the end of the seventh-week preparatory period [42], over 12 weeks of training [45], and from 90-min, 24-h, to 48-h after a match [32].

3.4.3 Testosterone to cortisol ratio

In six studies, the T:C ratio significantly decreased immediately and up to 72-h post-game [25,46] post a collegiate tournament [41], at mid-season [23], after 12-weeks of training [45] and at the end of the competitive season [26]. In two studies, the T:C ratio increased post-competition phase [22] immediately and at the end of the seventh week of the preparatory period [42]. Two further studies did not find fluctuations in the T:C ratio immediately post-match [34] or when molecules were evaluated every two months throughout a season [24].

3.4.4 Inflammation and muscle damage related variables

Creatine Kinase (CK) is the most frequently explored biomarker, with 15 studies analysing CK and mentioning increases (Table 3). Levels of CK increased immediately post-match until 96-h post-match. Increases in CK were also observed over more extended periods of training: as at the beginning of the season and one month of training [21], after 2 months [50], following 9 months [20], during the mid and end of a competitive season [26], over 8 days when during 2 games played 4 days apart [30], and after an exhaustive exercise (Hoff session) performed pre and post 4 weeks of special soccer training [51].

The concentration of Lactate Dehydrogenase (LDH) was elevated in three studies, such as after a post-Hoff test performed pre and post 4 weeks of training [51], and 13-h to 37-h post-match [29,33]. During more extended periods, LDH levels gradually dropped during the season compared to baseline levels [21], although one study found no differences throughout the season [24]. Myoglobin (Mb) significantly raised up to 20-min post-game [28,34], during mid-season [26] and at the end of the season [21].

Similarly, C-Reactive Protein (C-RP) increased in most considered studies, with higher values mentioned immediately post-match up to 24-h post-match [25,31,33]. C-RP was also higher over more extended training periods, such as after 2-months in-season [24] and during mid-season [26]. However, it did not fluctuate after a simulated soccer protocol [52] or at different time points throughout a competitive soccer season [20]. Interleukin-6 (IL-6) values increased immediately post-match [29,31,33], 30-min post-match [32]. However, IL-6 values remained unchanged throughout the season when measured every 2 months [24]).

3.4.5 Methodological quality control and publication bias

Based on a modified 27-item Downs and Black [18] checklist, the results of the methodological quality assessment of the included studies ranged from 13 to 22, with an average of 16 or 60 % over the 34 included studies. Reporting (10 items; items 1-10) showed 4 items to be fully met by all studies (Items 1, 2, 4 and 6), with no studies meeting all the item criteria for reporting. External validity (3 items; items 11-13) displayed all three items to be met by 9 studies, while no items were met by all studies. Internal validity study bias (7 items; items 14-20) reported no items (items 16-20) to be fully met. Items 14 and 15 were met by no studies. Confounding selection bias (6 items; items 21-26) also reported no studies to meet all the item criteria. Power (Item 27) was met by only 2 studies [37,42]. Detailed methodological quality assessment scores can be found in Table 4.

Table icon

Table 4: Results of the detailed methodological quality assessment scores based on Downs and Black (1998) checklist.

4.Discussion

4.1 Redox Homeostasis related variables

Lipid peroxidation denotes the reaction of reactive species with different types of lipids producing several by-products. Most investigations focus on responses on cell membranes despite the existence of more types of lipids placed in the cytosol [53]. The reaction of oxygen with unsaturated lipids produces a wide assortment of oxidation products, with the primary product being lipid hydroperoxides (LOOH). One study assessed LOOH variations before, during and after a LIST, but without significant changes [36]. Most of the studies have used blood samples compared to saliva ones. Within this review, lipid peroxidation-associated indicators (MDA, TBARS) of examined studies increased acutely, such as after a soccer game or performance test, and over longer periods, such as following a more extended period throughout the training season [25-28,35,36,38). The use of saliva is a straightforward, non-invasive process that can be applied frequently; however, the use of this specimen to evaluate redox status markers requires more examinations to get a better understanding. Currently, there is a lack of data on the biological fluctuation of the same biomarker in differing fluids [6].

Protein modifications have meaningful physiological consequences because they directly influence the function of many proteins and may lead to an indirect transformation of biomolecules [54]. Protein oxidation has been mostly measured through protein carbonyls [55]. In the present review, protein carbonyls were found raised after all types of engaging stimuli. Two studies found SH-group related proteins to be decreased following a HIIT protocol or 45 days of training [38]. However, it is crucial to be mentioned that sampling time plays a significant role in results. Indicatively, a research study reveals that the best sample time-point for PC assessment is 4 hours post-exercise for non-muscle damage exercises [49].

Many studies incorporated the measure of non-enzymatic low molecular weight fragments such as GSH, UA and the ratio of GSH/GSSG. Immediately and 24-h post soccer game, GSH dropped, but it fluctuated during the training cycle. The GSH/GSSG ratio increased during extended periods, implying adaptations of antioxidant enzymes [21,40], while acutely, after a game, it was dropped [35]. UA levels increased in plasma samples immediately and up to 72-h post-game [27-29,30,35].

All enzymatic antioxidants showed a tendency to increase mostly acutely. SOD increased in most examined acutely and chronically studies [25,26]. However, in the French league, SOD did not change when players were monitored for 10 months [40]. CAT and GPx increased post-game [29,35] until 48-h post-match [45]. One study by Silva et al. [25] observed GPx levels to decrease post-match.

TAC and TAS increased immediately post-match [25,27,28,45] and remained high up to 72-h post [28]. Though, these markers did not change during a simulated game [39] or an extensive training period [26,38]. The measurement of those variables in saliva samples needs further exploration since, as in most cases, no changes were detected.

These findings further highlight that the sampling time is pivotal for detecting fluctuations in specific molecules as the time-to-peak differs. Besides more detailed information about the applied training programme during lengthy periods is required. There is no “best” or “most accurate” time-point for assessing all markers at once. The literature refers, for example, that the best sampling time for CAT is immediately after completing an aerobic exercise and for TBARS 1-h post. Molecules like TAC, GSH, and GSSG require a 2-h post sampling time while PC 4-h post. [49]. Studies investigating variables related to redox homeostasis should possibly prioritize the biomarkers of interest and arrange proper timing.

4.2 Hormones

Testosterone is a commonly used biomarker within soccer but yields inconsistent results. In this review, nine studies found T levels in the blood to reveal no significant changes. Studies observed variations in testosterone when the free or bioavailable portion was assessed, where decreases were noted immediately and 45-min post-game [44]. Longer-term observations also established free T levels to decrease after 12 weeks of training [45], during the post-re-building period and mid-season measures [23], and during the post-competition period compared to post-evaluation [22]. When T levels were assessed in saliva, two studies did yield significant decreases 10 min post-match [46] and after 4 months of soccer training [47].

One key point for consideration when the analysis of T is required is that the total T is typically measured in blood samples unless this has been accurately specified. In some cases, when the free or bioavailable T is measured, mainly in saliva samples, outcomes can reflect the effect of training. Free or bioavailable is the amount of this hormone that is not bound to albumin or Sex Hormone-Binding Protein (SHBP) and thus is available for use (anabolic processes, etc.). Cortisol is a catabolic hormone secreted by the adrenal cortex and consists of one of the primary physical and physiological stress markers. It has been established that exercises requiring 60% or more of an individual's maximal oxygen consumption (VO2max) can result in physical stress that causes increased cortisol secretion [56]. Besides, among the vital functions of cortisol are the quick spurts of energy and the maintenance of blood glucose levels.

Cortisol acts on the skeletal muscle and adipose tissue to increase the mobilisation of amino acids and lipids and stimulate gluconeogenesis. Most studies found C levels raised in soccer, irrespective of whether these were measured in the blood [21,23,31,33,41,44,48] or saliva samples [34,47]. Differences were observed acutely [31,33,34,41,48] and after more extended examinations [21,23].

When viewing the ratio of T to C, it is crucial to notice the distinction between “T to C” and “free T to C” ratios since they compare different testosterone portions. The ratio of these two hormones may illustrate the balance between training and recovery desired to maintain the body in an “optimal” state to reach muscle mass and strength increments. In five studies, the ratio was significantly lower after a scholarly tournament [41], up to 72 h post-game [25], in mid-season [23], after 12 weeks of training [45], and at the end of the competitive season [26]. Corresponding to some researchers, a drop in the ratio of around 30% between assessments potentially represents an overtraining state [57]. Recently, the free T:C ratio has been recommended as a more sensitive marker to evaluate overreaching overtraining in athletes [13].

4.3 Inflammation and muscle damage variables

Variations in CK activity can be used to assess muscle tolerance, skeletal muscle micro-injury and athletes' adaptation. Movement patterns in football require individuals to change direction regularly and involve a stop-and-start nature, leading to a severe eccentric biomechanical strain on the working muscles [20,58]. The return of CK to baseline may consist of athletes' recovery index. CK levels rose acutely in all investigations immediately post-game, with values increasing as much as 96-h post [25,27-29,31-33,51,52]. Values of CK also increased after applying a considerably extended period of training [20,21,30,50].

Levels of LDH were elevated after performing a Hoff session, pre- and post-two months of training [51], immediately, 13-h post [29], and 37-h post an official match [33]. Like CK, LDH increases significantly during exercise, and the level and intensity of training influence the response to exercise. Values of LDH have risen markedly in untrained individuals, and its efflux from the tissue into circulation after strenuous exercise continues until the ninth day after the end of the effort [59]. Monitoring metabolites like CK and LDH can enhance our understanding of muscle response to exercise and adaptation to physical work [60].

Other markers, such as Mb and IL-6, also showed variations in football players. Mb is a protein that supports the store of oxygen in myocytes, and its concentration is associated with mitochondrial enzyme activity and the capillary supply [61]. Levels of Mb increased significantly in several examined studies, such as immediately post until 20-min post-match [28,34], in mid-season [26] and at the end of the season [21].

In the present systematic review, IL-6 was raised post-match [29,31-33]. Based on work conducted by Helsten [62], IL-6 has shown to peak up to 90-min post-exercise and can remain elevated for 4 days. IL-6 has pro- and anti-inflammatory roles and might significantly affect metabolic and musculoskeletal adaptation to exercise. Besides, in skeletal muscle, IL-6 enhances both glucose uptake and fat oxidation [63].

C-RP is an acute phase inflammation protein that transient increases after medium to high-intensity exercise. Long-term, systematic training is linked to lower values of both pro-inflammatory cytokines and acute-phase proteins in the blood [64]; this point might explain why some studies did not observe changes over longer time periods. C-RP was elevated in most studies, such as immediately, 13-h [29,33] and 24 h post-game [25,31]. Also, it raised after 4 months of training (V2) when athletes were monitored every 2 months [24], and at the mid-period of the competitive season (Jan) and the end-period of the competitive season [26]. However, it did not significantly change after a simulated soccer protocol [52], or long term when 4 samples were collected from July 2008 till May 2009 [20].

5. Conclusion

The results showed that exposure to short or long-term participation in football training and competitions could significantly affect players' redox, inflammation and hormonal status. However, greater consistency across studies is required to ascertain the implications of structured training regimens on examined variables. Depending on the research or the purpose of the athlete's evaluation, selecting the most relevant testing protocol/condition and markers, including the collection time and type of specimen, must be considered. The measurement of redox status-related variables in saliva requires more examination regarding the variability of those molecules in diverse specimens. To be accurately identified, many molecules need different sampling times; thus, studies exploring specific biomarkers should prioritize the collection time close to the variables of interest.

References

  1. Arnason A, Sigurdsson SB, Gudmundsson A, et al. Risk Factors for Injuries in Football. The American Journal of Sports Medicine 32 (2004): 5-16.
  2. Eirale C, Tol JL, Farooq A, et al. Low injury rate strongly correlates with team success in Qatari professional football. British Journal of Sports Medicine 47 (2012): 807-808.
  3. Hägglund M, Waldén M, Magnusson H, et al. Injuries affect team performance negatively in professional football: an 11-year follow-up of the UEFA Champions League injury study. British Journal of Sports Medicine 47 (2013): 38-742.
  4. Jeukendrup A, Gleeson M. Sports nutrition: an introduction to energy production and performance. 3rd Illinois: Human Kinetics (2018).
  5. Lewis NA, Howatson G, Morton K, et al. Alterations in redox homeostasis in the elite endurance athlete. Sports Med 45 (2015): 379-409.
  6. Nikolaidis MG, Margaritelis NV, Paschalis V, et al. Common Questions and Tentative Answers on How to Assess Oxidative Stress after Antioxidant Supplementation and Exercise. In: Lamprecht M (eds). Antioxidants in Sport Nutrition. CRC Press/Taylor & Francis (2015).
  7. Margaritelis NV, Theodorou AA, Paschalis V, et al. Adaptations to endurance training depend on exercise-induced oxidative stress: exploiting redox interindividual variability. Acta Physiol (Oxf) 222 (2018): 1-15.
  8. Nikolaidis MG, Kyparos A, Dipla K, et al. Exercise as a model to study redox homeostasis in blood: the effect of protocol and sampling point. Biomarkers 17 (2012): 28-35.
  9. Radak Z, Chung HY, Koltai E, et al. Exercise, oxidative stress and hormesis. Ageing Res Rev 7 (2008): 34-42.
  10. Tiidus PM. Radical species in inflammation and overtraining. Canadian journal of physiology and pharmacology 76 (1998): 533-538.
  11. Ostrowski K, Rohde T, Asp S, et al. Pro- and anti-inflammatory cytokine balance in strenuous exercise in humans. J Physiol 515 (1999): 287-291.
  12. Khaitin V, Bezuglov E, Lazarev A, et al. Markers of muscle damage and strength performance in professional football (soccer) players during the competitive period. Annals of translational medicine 9 (2021): 113.
  13. Banfi G, Dolci A. Free testosterone/cortisol ratio in soccer: usefulness of a categorization of values. J Sports Med Phys Fitness 46 (2006): 611-616.
  14. He F, Li J, Liu Z, et al. Redox Mechanism of Reactive Oxygen Species in Exercise. Front Physiol 7 (2016): 1-10.
  15. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. PLoS Med 18 (2020): e1003583.
  16. Higgins JPT, Thomas J, Chandler J, et al. Cochrane handbook for systematic reviews of interventions version (2021).
  17. Meignié A, Duclos M, Carling C, et al. The effects of menstrual cycle phase on elite athlete performance: A critical and systematic review. Front Physiol 12 (2021): 654585.
  18. Downs SH, Black N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J Epidemiol Community Health 52 (1998): 377-384.
  19. Francavilla VC, Vitale F, Ciaccio M, et al. Use of Saliva in Alternative to Serum Sampling to Monitor Biomarkers Modifications in Professional Soccer Players. Front Physiol 20 (2018): 1828.
  20. Meyer T, Meister S. Routine blood parameters in elite soccer players. Int J Sports Med 32 (2011): 875-881.
  21. Becatti M, Mannucci A, Barygina V, et al. Redox status alterations during the competitive season in élite soccer players: focus on peripheral leukocyte-derived ROS. Intern Emerg Med 12 (2017): 777-788.
  22. Handziski Z, Maleska V, Petrovska S, et al. The changes of ACTH, cortisol, testosterone and testosterone/cortisol ratio in professional soccer players during a competition half-season. Bratisl Lek Listy 107 (2006): 259-263.
  23. Michailidis Y. Stress hormonal analysis in elite soccer players during a season, Journal of Sport and Health Science 3 (2014): 279-283.
  24. Bolner A, Berizzi C, Benedetto S, et al. Marked differences in redox status of professional soccer players depending on training types. American Journal of Research in Medical Sciences 6 (2019): 8-20.
  25. Silva JR, Ascensão A, Marques F, et al. Neuromuscular function, hormonal and redox status and muscle damage of professional soccer players after a high-level competitive match. Eur J Appl Physiol 113 (2013): 2193-2201.
  26. Silva JR, Rebelo A, Marques F, et al. Biochemical impact of soccer: an analysis of hormonal, muscle damage, and redox markers during the season. Appl Physiol Nutr Metab 39 (2014): 432-438.
  27. Ascensão A, Rebelo A, Oliveira E, et al. Biochemical impact of a soccer match - analysis of oxidative stress and muscle damage markers throughout recovery. Clin Biochem 41 (2008): 841-851.
  28. Magalhães J, Rebelo A, Oliveira E, et al. Impact of Loughborough Intermittent Shuttle Test versus soccer match on physiological, biochemical and neuromuscular parameters. Eur J Appl Physiol 108 (2010): 39-48.
  29. Souglis A, Bogdanis GC, Chryssanthopoulos C, et al. Time Course of Oxidative Stress, Inflammation, and Muscle Damage Markers for 5 Days After a Soccer Match: Effects of Sex and Playing Position. Journal of strength and conditioning research 32 (2018): 2045-2054.
  30. Viana-Gomes D, Rosa FLL, Mello R, et al. Oxidative stress, muscle and liver cell damage in professional soccer players during a 2-game week schedule, Science & Sports 33 (2018): e221-e228.
  31. Ispirlidis I, Fatouros IG, Jamurtas AZ, et al. Time-course of changes in inflammatory and performance responses following a soccer game. Clin J Sport Med 18 (2008): 423-431.
  32. Romagnoli M, Sanchis-Gomar F, Alis R, et al. Changes in muscle damage, inflammation, and fatigue-related parameters in young elite soccer players after a match. J Sports Med Phys Fitness 56 (2016): 1198-1205.
  33. Souglis A, Bogdanis GC, Giannopoulou I, et al. Comparison of inflammatory responses and muscle damage indices following a soccer, basketball, volleyball and handball game at an elite competitive level. Res Sports Med 23 (2015): 59-72.
  34. Thorpe R, Sunderland C. Muscle damage, endocrine, and immune marker response to a soccer match. J Strength Cond Res 26 (2012): 2783-2790.
  35. da Costa C, Barbosa M, Spineti J, et al. Oxidative Stress Biomarkers Response to Exercise in Brazilian Junior Soccer Players. Food and Nutrition Sciences 2 (2011): 407-413.
  36. Fatouros IG, Chatzinikolaou A, Douroudos II, et al. Time-course of changes in oxidative stress and antioxidant status responses following a soccer game. J Strength Cond Res 24 (2010): 3278-3286.
  37. Rodrigues de Araujo V, Lisboa P, Boaventura G, et al. Acute high-intensity exercise test in soccer athletes affects salivary biochemical markers. Free Radic Res 52 (2018): 850-855.
  38. Sopic M, Bogavac-Stanojevic N, Baralic I, et al. Effects of short- and long-term physical activity on DNA stability and oxidative stress status in young soccer players. J Sports Med Phys Fitness 54 (2014): 354-361.
  39. Mello R, Mello R, Gomes D, et al. Oxidative stress and antioxidant biomarker responses after a moderate-intensity soccer training session. Res Sports Med 25 (2017): 322-332.
  40. Le Moal E, Groussard C, Paillard T, et al. Redox Status of Professional Soccer Players is Influenced by Training Load Throughout a Season. Int J Sports Med 37 (2016): 680-686.
  41. Coelho DB, Pimenta EM, Veneroso CE, et al. Assessment of acute physiological demand for soccer. Rev Bras Cineantropom Desempenho Hum 15 (2013): 667-676.
  42. Opaszowski B, Tyc Z, Obminski Z, et al. The Influence of a 7-Week Preparatory Period on Hormonal and Metabolic Responses in Soccer Players / Metabolic and Hormonal Response to Training. Polish Journal of Sport and Tourism 19 (2013): 178-183.
  43. Ali K, Verma S, Ahmad I, et al. Comparison of Complex Versus Contrast Training on Steroid Hormones and Sports Performance in Male Soccer Players. J Chiropr Med 18 (2019): 131-138.
  44. Lupo C, Baldi L, Bonifazi M, et al. Androgen levels following a football match. Eur J Appl Physiol Occup Physiol 54 (1985): 494-496.
  45. Saidi K, Ben Abderrahman A, Boullosa D, et al. The Interplay Between Plasma Hormonal Concentrations, Physical Fitness, Workload and Mood State Changes to Periods of Congested Match Play in Professional Soccer Players. Front Physiol 11 (2020): 835.
  46. Peñailillo L, Maya L, Niño G, et al. Salivary hormones and IgA in relation to physical performance in football. J Sports Sci 33 (2015): 2080-2087.
  47. Filaire E, Bernain X, Sagnol M, et al. Preliminary results on mood state, salivary testosterone: cortisol ratio and team performance in a professional soccer team. Eur J Appl Physiol 86 (2001): 179-184.
  48. Moreira A, Arsati F, de Oliveira Lima Arsati YB, et al. Salivary cortisol in top-level professional soccer players. Eur J Appl Physiol 106 (2009): 25-30.
  49. Michailidis Y, Jamurtas A.Z, Nikolaidis M.G. et al. Sampling time is crucial for measurement of aerobic exercise-induced oxidative stress. Med Sci Sports Exerc 39 (2007): 1107-1113.
  50. Pimenta EM, Coelho D, Capettini LSA, et al. Analysis of creatine kinase and alpha-actin concentrations in soccer pre-season. Revista Brasileira de Ciência e Movimento 23 (2015): 5-11.
  51. Gharahdaghi N, Kordi MR, Shabkhiz F. Acute exercise-induced muscular damage after one month training in soccer players. Ovidius University Annals, Series Physical Education and Sport/Science, Movement and Health 13 (2013): 269-273.
  52. Fransson D, Vigh-Larsen JF, Fatouros IG, et al. Fatigue Responses in Various Muscle Groups in Well-Trained Competitive Male Players after a Simulated Soccer Game. J Hum Kinet 201 (2018): 85-97.
  53. Wu GH, Jarstrand C, Nordenström J. Phagocyte-induced lipid peroxidation of different intravenous fat emulsions and counteractive effect of vitamin E. Nutrition 15 (1999): 359-364.
  54. Halliwell B, Gutteridge J. Free Radicals in Biology and Medicine. New York: Oxford University Press (2007).
  55. Weber D, Davies MJ, Grune T. Determination of protein carbonyls in plasma, cell extracts, tissue homogenates, isolated proteins: Focus on sample preparation and derivatization conditions. Redox Biol 5 (2015): 367-380.
  56. De Luccia, TBP. Use of the Testosterone/Cortisol Ratio Variable in Sports. Open Sport Science Journal 9 (2016): 104-113.
  57. Adlercreutz H, Harkonen M, Kuoppasalmi K, et al. Effect of training on plasma anabolic and catabolic steroid hormones and their response during physical exercise. Int J Sports Med 7 (1986): 27-38.
  58. Newham DJ, Jones DA, Edwards RH. Plasma creatine kinase changes after eccentric and concentric contractions. Muscle Nerve 9 (1986): 59-63.
  59. Wu H-J, Chen K-T, Shee B-W, et al. Effects of 24 h ultra-marathon on biochemical and hematological parameters. World J Gastroenterol 10 (2004): 2711-2714.
  60. Brancaccio P, Maffulli N, Buonauro R, et al. Serum enzyme monitoring in sports medicine. Clin Sports Med 27 (2008): 1-18.
  61. Kamga C, Krishnamurthy S, Shiva S. Myoglobin and mitochondria: a relationship bound by oxygen and nitric oxide. Nitric Oxide 26(2012): 251-258.
  62. Hellsten Y, Frandsen U, Orthenblad N, et al. Xanthine oxidase in human skeletal muscle following eccentric exercise: a role in inflammation. J Physiol 498 (1997): 239-248.
  63. Pedersen BK, Fischer CP. Beneficial health effects of exercise: the role of IL-6 as a myokine. Trends Pharmacol Sci 28 (2007): 152-156.
  64. Moldoveanu AI, Shephard RJ, Shek PN. The cytokine response to physical activity and training. Sport Med 31 (2001): 115-144.

Appendix 1:

PRISMA 2020 Checklist.

Section and Topic

Item#

Checklist Item

Location where item is reported

Title

Title

1

Identify the report as a systematic review.

1

Abstract

Abstract

2

See the PRISMA 2020 for Abstracts checklist.

1

Introduction

Rationale

3

Describe the rationale for the review in the context of existing knowledge.

2-3

Objectives

4

Provide an explicit statement of the objective(s) or question(s) the review addresses.

3

Methods

Eligibility criteria

5

Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses.

4

Information sources

6

Specify all databases, registers, websites, organisations, reference lists and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted.

4-5

Search strategy

7

Present the full search strategies for all databases, registers and websites, including any filters and limits used.

4-5, Figure 1,

Selection process

8

Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process.

4-5

Data collection process

9

Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process.

5-6

Data items

10a

List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g. for all measures, time points, analyses), and if not, the methods used to decide which results to collect.

5-6

10b

List and define all other variables for which data were sought (e.g. participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information.

5-6

Study risk of bias assessment

11

Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process.

6

Effect measures

12

Specify for each outcome the effect measure(s) (e.g. risk ratio, mean difference) used in the synthesis or presentation of results.

6

Synthesis methods

13a

Describe the processes used to decide which studies were eligible for each synthesis (e.g. tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)).

4-5

13b

Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions.

n/a

13c

Describe any methods used to tabulate or visually display results of individual studies and syntheses.

5-6

13d

Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used.

6

13e

Describe any methods used to explore possible causes of heterogeneity among study results (e.g. subgroup analysis, meta-regression).

n/a

13f

Describe any sensitivity analyses conducted to assess robustness of the synthesized results.

n/a

Reporting bias assessment

14

Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases).

6

Certainty assessment

15

Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome.

n/a

Results

Study selection

16a

Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram.

7, Figure 1

16b

Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded.

Figure 1

Study characteristics

17

Cite each included study and present its characteristics.

Figure 1

Risk of bias in studies

18

Present assessments of risk of bias for each included study.

Table 4

Results of individual studies

19

For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g. confidence/credible interval), ideally using structured tables or plots.

Table 4

Results of syntheses

20a

For each synthesis, briefly summarise the characteristics and risk of bias among contributing studies.

Table 4

20b

Present results of all statistical syntheses conducted. If meta-analysis was done, present for each the summary estimate and its precision (e.g. confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect.

Table 4

20c

Present results of all investigations of possible causes of heterogeneity among study results.

n/a

20d

Present results of all sensitivity analyses conducted to assess the robustness of the synthesized results.

n/a

Reporting biases

21

Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed.

Table 4

Certainty of evidence

22

Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed.

Table 4

Discussion

Discussion

23a

Provide a general interpretation of the results in the context of other evidence.

11-15

23b

Discuss any limitations of the evidence included in the review.

11-15

23c

Discuss any limitations of the review processes used.

11-15

23d

Discuss implications of the results for practice, policy, and future research.

11-15

Other Information

Registration and protocol

24a

Provide registration information for the review, including register name and registration number, or state that the review was not registered.

n/a

24b

Indicate where the review protocol can be accessed, or state that a protocol was not prepared.

n/a

24c

Describe and explain any amendments to information provided at registration or in the protocol.

n/a

Support

25

Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review.

n/a

Competing interests

26

Declare any competing interests of review authors.

n/a

Availability of data, code and other materials

27

Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review.

Supplemental

Material

From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71

For more information, visit: http://www.prisma-statement.org/

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