Iron deficiency in athletes: Prevalence and impact on VO2 peak.

BACKGROUND: Iron is an important micronutrient in pathways of energy production, adequate nutrient intake and its balance is essential for optimal athletic performance. However, large studies elucidating the impact of iron deficiency on athletes' performance are sparse. METHODS: Competitive athletes of any age who presented for preparticipation screening 04/2020-10/2021 were included in this study and stratified for iron deficiency (defined as ferritin level <20 µg/l with and without mild anemia [hemoglobin levels ≥11 g/dl]). Athletes with and without iron deficiency were compared and the impact of iron deficiency on athletic performance was investigated. RESULTS: Overall, 1190 athletes (mean age 21.9 ± 11.6 years; 34.2% females) were included in this study. Among these, 19.7% had iron deficiency. Patients with iron deficiency were younger (18.1 ± 8.4 vs. 22.8 ± 12.1 years, P < 0.001), more often females (64.5% vs. 26.8%, P < 0.001), had lower VO2 peak value (43.4 [38.5/47.5] vs. 45.6 [39.1/50.6]ml/min/kg, P = 0.022) and lower proportion of athletes reaching VO2 peak of >50 ml/min/kg (8.5% vs. 16.1%, P = 0.003). Female sex (OR 4.35 [95% CI 3.13-5.88], P > 0.001) was independently associated with increased risk for iron deficiency. In contrast, the risk for iron deficiency decreased by every life year (OR 0.97 [95% CI 0.95-0.99], P = 0.003). Iron deficiency was independently associated with reduced VO2 peak (OR 0.94 [0.91-0.97], P < 0.001) and lower probability to reach VO2 peak >50 ml/min/kg (OR 0.42 [95% CI 0.25-0.69], P = 0.001). CONCLUSIONS: Iron deficiency is common in athletes (predominantly in female and in young athletes). Iron deficiency was independently associated with reduced VO2 peak during exercise testing and lower probability to reach a VO2 peak >50 ml/min/kg.

COVID-19 in Female and Male Athletes: Symptoms, Clinical Findings, Outcome, and Prolonged Exercise Intolerance-A Prospective, Observational, Multicenter Cohort Study (CoSmo-S).

BACKGROUND: An infection with SARS-CoV-2 can lead to a variety of symptoms and complications, which can impair athletic activity. OBJECTIVE: We aimed to assess the clinical symptom patterns, diagnostic findings, and the extent of impairment in sport practice in a large cohort of athletes infected with SARS-CoV-2, both initially after infection and at follow-up. Additionally, we investigated whether baseline factors that may contribute to reduced exercise tolerance at follow-up can be identified. METHODS: In this prospective, observational, multicenter study, we recruited German COVID elite-athletes (cEAs, n = 444) and COVID non-elite athletes (cNEAs, n = 481) who tested positive for SARS-CoV-2 by PCR (polymerase chain reaction test). Athletes from the federal squad with no evidence of SARS-CoV-2 infection served as healthy controls (EAcon, n = 501). Questionnaires were used to assess load and duration of infectious symptoms, other complaints, exercise tolerance, and duration of training interruption at baseline and at follow-up 6 months after baseline. Diagnostic tests conducted at baseline included resting and exercise electrocardiogram (ECG), echocardiography, spirometry, and blood analyses. RESULTS: Most acute and infection-related symptoms and other complaints were more prevalent in cNEA than in cEAs. Compared to cEAs, EAcon had a low symptom load. In cNEAs, female athletes had a higher prevalence of complaints such as palpitations, dizziness, chest pain, myalgia, sleeping disturbances, mood swings, and concentration problems compared to male athletes (p < 0.05). Until follow-up, leading symptoms were drop in performance, concentration problems, and dyspnea on exertion. Female athletes had significantly higher prevalence for symptoms until follow-up compared to male. Pathological findings in ECG, echocardiography, and spirometry, attributed to SARS-CoV-2 infection, were rare in infected athletes. Most athletes reported a training interruption between 2 and 4 weeks (cNEAs: 52.9%, cEAs: 52.4%), while more cNEAs (27.1%) compared to cEAs (5.1%) had a training interruption lasting more than 4 weeks (p < 0.001). At follow-up, 13.8% of cNEAs and 9.9% of cEAs (p = 0.24) reported their current exercise tolerance to be under 70% compared to pre-infection state. A persistent loss of exercise tolerance at follow-up was associated with persistent complaints at baseline, female sex, a longer break in training, and age > 38 years. Periodical dichotomization of the data set showed a higher prevalence of infectious symptoms such as cough, sore throat, and coryza in the second phase of the pandemic, while a number of neuropsychiatric symptoms as well as dyspnea on exertion were less frequent in this period. CONCLUSIONS: Compared to recreational athletes, elite athletes seem to be at lower risk of being or remaining symptomatic after SARS-CoV-2 infection. It remains to be determined whether persistent complaints after SARS-CoV-2 infection without evidence of accompanying organ damage may have a negative impact on further health and career in athletes. Identifying risk factors for an extended recovery period such as female sex and ongoing neuropsychological symptoms could help to identify athletes, who may require a more cautious approach to rebuilding their training regimen. TRIAL REGISTRATION NUMBER: DRKS00023717; 06.15.2021-retrospectively registered.

Former SARS-CoV-2 Infection Was Related to Decreased VO2 Peak and Exercise Hypertension in Athletes.

The impact of former COVID-19 infection on the performance of athletes is not fully understood. We aimed to identify differences in athletes with and without former COVID-19 infections. Competitive athletes who presented for preparticipation screening between April 2020 and October 2021 were included in this study, stratified for former COVID-19 infection, and compared. Overall, 1200 athletes (mean age 21.9 ± 11.6 years; 34.3% females) were included in this study from April 2020 to October 2021. Among these, 158 (13.1%) athletes previously had COVID-19 infection. Athletes with COVID-19 infection were older (23.4 ± 7.1 vs. 21.7 ± 12.1 years, p < 0.001) and more often of male sex (87.7% vs. 64.0%, p < 0.001). While systolic/diastolic blood pressure at rest was comparable between both groups, maximum systolic (190.0 [170.0/210.0] vs. 180.0 [160.0/205.0] mmHg, p = 0.007) and diastolic blood pressure (70.0 [65.0/75.0] vs. 70.0 [60.0/75.0] mmHg, p = 0.012) during the exercise test and frequency of exercise hypertension (54.2% vs. 37.8%, p < 0.001) were higher in athletes with COVID-19 infection. While former COVID-19 infection was not independently associated with higher blood pressure at rest and maximum blood pressure during exercise, former COVID-19 infection was related to exercise hypertension (OR 2.13 [95%CI 1.39-3.28], p < 0.001). VO2 peak was lower in athletes with compared to those without COVID-19 infection (43.4 [38.3/48.0] vs. 45.3 [39.1/50.6] mL/min/kg, p = 0.010). SARS-CoV-2 infection affected VO2 peak negatively (OR 0.94 [95%CI 0.91-0.97], p < 0.0019). In conclusion, former COVID-19 infection in athletes was accompanied by a higher frequency of exercise hypertension and reduced VO2 peak.

COVID-19 in German Competitive Sports: Protocol for a Prospective Multicenter Cohort Study (CoSmo-S).

Objective: It is unclear whether and to what extent COVID-19 infection poses health risks and a chronic impairment of performance in athletes. Identification of individual health risk is an important decision-making basis for managing the pandemic risk of infection with SARS-CoV-2 in sports and return to play (RTP). Methods: This study aims 1) to analyze the longitudinal rate of seroprevalence of SARS-CoV-2 in German athletes, 2) to assess health-related consequences in athletes infected with SARS-CoV-2, and 3) to reveal effects of the COVID-19 pandemic in general and of a cleared SARS-CoV-2 infection on exercise performance. CoSmo-S is a prospective observational multicenter study establishing two cohorts: 1) athletes diagnosed positive for COVID-19 (cohort 1) and 2) federal squad athletes who perform their annual sports medical preparticipation screening (cohort 2). Comprehensive diagnostics including physical examination, laboratory blood analyses and blood biobanking, resting and exercise electrocardiogram (ECG), echocardiography, spirometry and exercise testing added by questionnaires are conducted at baseline and follow-up. Results and Conclusion: We expect that the results obtained, will allow us to formulate recommendations regarding RTP on a more evidence-based level.

Correction: Physical and cognitive doping in university students using the unrelated question model (UQM): Assessing the influence of the probability of receiving the sensitive question on prevalence estimation.

[This corrects the article DOI: 10.1371/journal.pone.0197270.].

Physical and cognitive doping in university students using the unrelated question model (UQM): Assessing the influence of the probability of receiving the sensitive question on prevalence estimation.

STUDY OBJECTIVES: In order to increase the value of randomized response techniques (RRTs) as tools for studying sensitive issues, the present study investigated whether the prevalence estimate for a sensitive item [Formula: see text] assessed with the unrelated questionnaire method (UQM) is influenced by changing the probability of receiving the sensitive question p. MATERIAL AND METHODS: A short paper-and-pencil questionnaire was distributed to 1.243 university students assessing the 12-month prevalence of physical and cognitive doping using two versions of the UQM with different probabilities for receiving the sensitive question (p ≈ 1/3 and p ≈ 2/3). Likelihood ratio tests were used to assess whether the prevalence estimates for physical and cognitive doping differed significantly between p ≈ 1/3 and p ≈ 2/3. The order of questions (physical doping and cognitive doping) as well as the probability of receiving the sensitive question (p ≈ 1/3 or p ≈ 2/3) were counterbalanced across participants. Statistical power analyses were performed to determine sample size. RESULTS: The prevalence estimate for physical doping with p ≈ 1/3 was 22.5% (95% CI: 10.8-34.1), and 12.8% (95% CI: 7.6-18.0) with p ≈ 2/3. For cognitive doping with p ≈ 1/3, the estimated prevalence was 22.5% (95% CI: 11.0-34.1), whereas it was 18.0% (95% CI: 12.5-23.5) with p ≈ 2/3. Likelihood-ratio tests revealed that prevalence estimates for both physical and cognitive doping, respectively, did not differ significantly under p ≈ 1/3 and p ≈ 2/3 (physical doping: χ2 = 2.25, df = 1, p = 0.13; cognitive doping: χ2 = 0.49, df = 1, p = 0.48). Bayes factors computed with the Savage-Dickey method favored the null ("the prevalence estimates are identical under p ≈ 1/3 and p ≈ 2/3") over the alternative ("the prevalence estimates differ under p ≈ 1/3 and p ≈ 2/3") hypothesis for both physical doping (BF = 2.3) and cognitive doping (BF = 5.3). CONCLUSION: The present results suggest that prevalence estimates for physical and cognitive doping assessed by the UQM are largely unaffected by the probability for receiving the sensitive question p.