Human serum mast cell tryptase levels in elbow fractures or dislocations and its association with injury severity
Bibliographic record
Abstract
Mast cells contain an abundance of tryptase, and preclinical models have shown elevated serum mast cell tryptase (SMCT) in the setting of posttraumatic joint contractures. Therefore, SMCT emerged as a potential biomarker to help recognize patients with more severe injuries and a higher likelihood of developing contractures. The objective of this study is to assess SMCT levels in participants with varying severity of elbow fractures and/or dislocations. A prospective cohort including 13 participants with more severe injuries that required an operation and 28 participants with less severe injuries managed nonoperatively were evaluated. A control group of eight individuals without elbow injuries was also evaluated. The SMCT levels were measured using an enzyme-linked immunosorbent assay kit specific for human mast cell tryptase. A one-way analysis of variance and Tukey's Honest Significance test was used to assess for statistical significance among and between the three groups. The average time from injury to the collection of the blood samples was 4 ± 2 days. Highly significant differences were identified between the operative, nonoperative, and control groups (P = .0005). In the operative group, SMCT levels were significantly higher than the nonoperative group (P = .0005) and the control group (P = .009), suggesting a correlation between SMCT levels and injury severity. There was no statistically significant difference in SMCT levels between the nonoperative and control groups. The SMCT levels were elevated in participants with acute elbow injuries requiring operative intervention, suggesting that SMCT levels were higher in injuries regarded as more severe.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".