Racial differences in serological markers across the first year of injury in spinal cord injury: a retrospective analysis of a multi-center interventional study
Bibliographic record
Abstract
STUDY DESIGN: Secondary analysis of a randomized, multi-center, placebo-controlled study(Sygen®). OBJECTIVES: To evaluate racial differences in serological markers in individuals with spinal cord injury(SCI) across the first year of injury. SETTING: Hospitals in North America. METHODS: Serological markers (e.g.,cell count, liver, kidney, and pancreatic function, metabolism, and muscle damage) were assessed among 316 participants (247 White, 69 Black) at admission, weeks 1, 2, 4, 8, and 52 post-injury. Linear mixed models were employed to explore the main effects of time, race (Black vs. White), and their interaction, with adjustment of covariates such as study center, polytrauma, injury (level, completeness), treatment group, and sex. RESULTS: A main effect of race was observed where White individuals had higher alanine transaminase, blood urea nitrogen(BUN), BUN/Creatinine ratio, sodium, and chloride, while Black individuals had higher calcium, total serum protein, and platelets. For markers with interaction effects, post-hoc comparisons showed that at week 52, White individuals had higher mature neutrophils, hematocrit, hemoglobin, mean corpuscular hemoglobin, albumin, and triglycerides, and Black individuals had higher amylase. Eosinophils, monocytes, red blood cells, aspartate aminotransferase, bilirubin, cholesterol, partial thromboplastin time, urine specific gravity, urine pH, CO2, and inorganic phosphorus did not differ between races. CONCLUSIONS: Our results revealed racial differences in serological markers and underscores the importance of considering race as a determinant of physiological responses. Future studies are warranted to explore the causes and implications of these racial disparities to facilitate tailored clinical management and social policy changes that can improve health equity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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".