Diagnosis and Management of Little League Shoulder: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Little League shoulder (LLS) is an overuse injury characterized by throwing-related pain that commonly presents in adolescent male athletes. Investigations into the optimal duration of rest from throwing and protocols for graduated return to sports (RTS) are lacking. PURPOSE: To summarize the current literature with respect to the diagnosis, management, RTS, and return to throwing for LLS. DESIGN: Systematic review; Level of evidence, 4. METHODS: The databases EMBASE, MEDLINE, and PubMed were searched between inception and April 22, 2020. References of retrieved records were reviewed for potentially eligible studies. English-language studies that reported the diagnosis and/or management of LLS in children or adolescents were included. Studies of animals or cadavers, review articles, and non-peer reviewed records were excluded. Data were summarized narratively using descriptive statistics. RESULTS: Overall, 23 studies (21 level 4 studies, 2 level 3 studies) met the criteria for a total of 266 participants with a weighted mean age of 12.8 years (range, 7.4-17 years). Treatment recommendations evolved from prolonged rest and complete cessation of throwing to shorter periods of rest and graduated RTS. Less than half (11/23) of studies reported specific criteria to RTS; 1 case report discussed a coaching strategy to resume throwing, and 1 case report discussed a regimented throwing program. The proportion of participants returning to any sport participation was 94.0% (n = 157/167). The proportion returning to their preinjury level of sport was 92.5% (n = 123/133). Upon RTS, 18.7% (n = 35/187) of participants experienced a recurrence of symptoms. Premature closure of the epiphysis was reported in 1 participant. CONCLUSION: Young athletes with LLS may return to play after a period of rest, and a high proportion return to their preinjury level of sport. Further prospective studies are warranted to develop evidence-based, graduated RTS protocols and to better capture any long-term sequelae of the condition.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".