Shoulder and Elbow Symptoms in Dutch High School Baseball Pitchers: Results of a Two-Season Prospective Study
Bibliographic record
Abstract
CONTEXT: Baseball pitching requires fast and coordinated motions of the whole body to reach high ball speeds, putting considerable strain on the musculoskeletal system, particularly the shoulder and elbow. OBJECTIVE: To describe musculoskeletal symptoms and the functional status of the shoulder and elbow in male high school baseball pitchers. DESIGN: Descriptive epidemiology study. SETTING: Dutch baseball talent academies. PATIENTS OR OTHER PARTICIPANTS: One hundred twenty-five male high school baseball pitchers aged 12 to 18 years who participated in 1 of the 6 Dutch baseball talent academies and the Dutch National U-18 team were recruited and enrolled. MAIN OUTCOME MEASURE(S): Musculoskeletal symptoms, functional status of the shoulder and elbow were registered for each player every 6 months over 2 consecutive baseball seasons through self-assessment questionnaires, including the Kerlan-Jobe Orthopaedic Clinic (KJOC) and the Western Ontario Shoulder Instability Index (WOSI) questionnaires. RESULTS: Five hundred seventy musculoskeletal (MSS) symptoms in 93 of the 125 players were reported. The average 6-month prevalence for symptoms of the throwing shoulder was 37% (95% CI = 33%-41%), and for the elbow 37% (95% CI = 31%-42%), followed by the lower back with 36% (95% CI = 26%-45%). The baseball pitchers who experienced only shoulder symptoms had an average KJOC score of 80.0 (95% CI = 75.3-84.7) points, whereas those with only elbow symptoms reported a score of 90.2 (95% CI = 89.2-95.3). On the WOSI questionnaire, baseball pitchers scored an average of 421.2 (95% CI = 200.1-642.4) points. CONCLUSIONS: In a cohort of Dutch high school baseball pitchers, one-third reported shoulder and elbow symptoms on the throwing side, with reduced functional status and lower back symptoms. Future efforts should focus on developing preventive strategies through early symptom detection, aiming to prevent symptom progression and, ultimately, the development of severe injuries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".