Hip and Groin Injuries in Professional Basketball Players: Impact on Playing Career and Quality of Life After Retirement
Bibliographic record
Abstract
BACKGROUND: Professional basketball players are at increased risk of hip and groin pain. Epidemiologic data exist on the prevalence of hip and groin issues among players in the National Basketball Association (NBA), but little is known about how these injuries affect athletes after retirement. HYPOTHESIS: A high proportion of retired NBA athletes would have hip and/or groin pain. STUDY DESIGN: Cross-sectional survey. LEVEL OF EVIDENCE: Level 4. METHODS: A survey was developed through an interdisciplinary focus group. The survey was developed to capture data regarding demographics, collegiate and professional athletic injuries, and current quality of life and musculoskeletal health. The questionnaire was electronically distributed to all members of the National Basketball Players Association using SurveyMonkey (N = 900). RESULTS: A total of 108 (12%) retired NBA players completed the survey. More than one-third (36.3%) of athletes report currently experiencing hip and/or groin pain, and 17.6% had received injections for hip or groin conditions since retiring from the NBA. Since retiring, 14.7% of respondents had undergone total hip arthroplasty. The median Tegner activity level scale was 3 out of 10. Nearly one-third (32.4%) of athletes report moderate to severe problems with mobility, and close to half (48%) had moderate to extreme pain/discomfort. CONCLUSION: Hip and groin injuries are common among NBA athletes, affecting players throughout their careers and into retirement. A subset of athletes may exist in whom intra-articular hip pathology is not appropriately identified and treated while playing in the NBA. CLINICAL RELEVANCE: Retired NBA athletes are at high risk of hip and groin pain after retirement and are more likely to require total hip arthroplasty compared with the general population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".