Skeletal muscle oxygenation and fluid content in upper extremity postthrombotic syndrome: a proof-of-concept study
Bibliographic record
Abstract
Background Little is known about the pathophysiology of upper extremity (UE) postthrombotic syndrome (PTS). Objectives We aimed to investigate the effect of PTS severity on UE muscle oxygen saturation (SmO 2 ) and fluid content during exercise and recovery in adolescents and young adults. Methods Eleven cases with unilateral or bilateral UE-PTS who sustained deep vein thrombosis (DVT) in childhood, and 11 age- and sex-matched controls from the general population were recruited for this case-control study. PTS was measured using CAPTSure (0-100-point score). SmO 2 and segmental extracellular fluid content were measured in both UEs using near-infrared spectroscopy (NIRS) and bioimpedance spectroscopy (BIS), respectively. Incremental and constant load UE exercise tests were completed using an ergometer while monitoring NIRS and BIS parameters in both UEs. NIRS and BIS changes throughout exercise and recovery were analyzed using mixed models to account for nested data. Results Median age of DVT diagnosis among cases was 5.6 years (quartile [Q]1-Q3, 0.2-16.1 years). At the time of the study, median CAPTSure score in the DVT-affected UE was 39 points (Q1-Q3, 27-55 points); 55% of DVTs were associated with a central venous catheter. Mixed models showed that increasing PTS severity was associated with lower SmO 2 during both incremental and constant load exercise and exercise recovery. We found no evidence of fluid accumulation during exercise. Conclusion The lower SmO 2 suggests that UE-PTS severity is associated with muscle microvascular dysfunction and impaired blood flow during and following exercise.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".