Timing of surgery in professional baseball—an analysis of Major League Baseball pitchers who underwent ulnar collateral ligament reconstruction
Bibliographic record
Abstract
Background The rates of return to the same level of play (RTSP), time to RTSP in Major League Baseball (MLB) pitchers, and missed days of the season after ulnar collateral ligament reconstruction (UCLR) have been reported previously. However, previous studies have shown a large disparity between time to RTSP and missed playing time during the season after UCLR. Additionally, the literature has not investigated the relation between the timing of UCLR during a season and the time to RTSP. The purpose of this study was to investigate how the timing of UCLR during the season affects the time it takes to RTSP. Methods The data of MLB pitchers who underwent UCLR between January 2012 and December 2022 were obtained from publicly available online records. The rate of RTSP, the rate of RTSP in the next season, and the time to RTSP at the MLB level were collected. The timing of surgery performed during the season was grouped into 3 categories: early season (January to April), middle season (May to August), and late season (September to December). The rate of RTSP and time to RTSP were compared across each category. Results Two hundred seventy-two MLB pitchers who underwent UCLR were included. Two hundred twelve pitchers successfully returned to MLB. Overall, the rate of RTSP after UCLR in MLB pitchers was 77.9% without any statistical difference among the 3 timing categories ( P = .45). The rate of RTSP in the next MLB season after UCLR was 56.7% in the early season, 37.0% in the middle season, and 4.2% in the late season. Time to RTSP was 19.0 ± 7.2 months in the early season group, 20.7 ± 10.0 months in the middle season group, and 23.0 ± 8.6 months in the late season group. Time to RTSP in the early season group was significantly faster than in the late season group ( P < .001). Conclusion The timing of UCLR during the season has a significant effect on the absolute time to RTSP in MLB pitchers. Those who undergo surgery later in the season have significantly longer absolute time to RTSP than those earlier in the season.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".