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Record W2740069615 · doi:10.1136/bjsports-2017-097956

Sports injury and illness incidence in the Rio de Janeiro 2016 Olympic Summer Games: A prospective study of 11274 athletes from 207 countries

2017· article· en· W2740069615 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBritish Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Calgary
FundersInternational Olympic Committee
KeywordsAthletesIncidence (geometry)Prospective cohort studyMedicinePhysical therapySports injuryInjury preventionSuicide preventionPoison controlMedical emergencySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the pattern of injuries and illnesses sustained during the Games of the XXXI Olympiad, hosted by Rio de Janeiro from 5 to 21 August 2016. METHODS: We recorded the daily incidence of athlete injuries and illnesses (1) through the reporting of all National Olympic Committee (NOC) medical teams and (2) in the polyclinic and medical venues by the Rio 2016 medical staff. RESULTS: In total, 11 274 athletes (5089 women, 45%; 6185 men, 55%) from 207 NOCs participated in the study. NOC and Rio 2016 medical staff reported 1101 injuries and 651 illnesses, equalling 9.8 injuries and 5.4 illnesses per 100 athletes over the 17-day period. Altogether, 8% of the athletes incurred at least one injury and 5% at least one illness. The injury incidence was highest in BMX cycling (38% of the athletes injured), boxing (30%), mountain bike cycling (24%), taekwondo (24%), water polo (19%) and rugby (19%), and lowest in canoe slalom, rowing, shooting, archery, swimming, golf and table tennis (0%-3%). Of the 1101 injuries recorded, 40% and 20% were estimated to lead to ≥1 and >7 days of absence from sport, respectively. Women suffered 40% more illnesses than men. Illness was generally less common than injury, with the highest incidence recorded in diving (12%), open-water marathon (12%), sailing (12%), canoe slalom (11%), equestrian (11%) and synchronised swimming (10%). Illnesses were also less severe; 18% were expected to result in time loss. Of the illnesses, 47% affected the respiratory system and 21% the gastrointestinal system. The anticipated problem of infections in the Rio Olympic Games did not materialise, as the proportion of athletes with infectious diseases mirrored that of recent Olympic Games (3%). CONCLUSION: Overall, 8% of the athletes incurred at least one injury during the Olympic Games, and 5% an illness, which is slightly lower than in the Olympic Summer Games of 2008 and 2012.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.294
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it