Early risk prognosis of free-flap transplant failure by quantitation of the macrophage colony-stimulating factor in patient plasma using 2-dimensional liquid-chromatography multiple reaction monitoring-mass spectrometry
Bibliographic record
Abstract
Although great success of microvascular free-flap transplantation surgery has been achieved in recent years, between 1.5% and 15% of flaps are still lost due to vascular occlusion. The clinical challenge remains to salvage a transplant in the case of vascular complications. Since flap loss is devastating for the patient, it is of utmost importance to detect signs of complications or of conspicuities as soon as possible. Rescue success rates highly depend on early revision. In this study, we collected blood samples during transplantation surgery from either the contributory artery or the effluent vein of the flap and applied a targeted mass spectrometry-based approach to quantify 24 acute phase proteins, cytokines, and growth factors in 63 plasma samples from 21 hospitalized patients, generating a dataset with 9450 protein concentration values. Biostatistical analyses of the targeted plasma protein concentrations in all 63 plasma samples showed that venous concentrations of macrophage colony-stimulating factor (M-CSF) provided the highest accuracy for discriminating patients with either clinical conspicuities or complications from control individuals. Using 21.33 ng/mL of M-CSF as the diagnostic threshold when analyzing venous blood plasma samples, the assay obtained a sensitivity of 0.93 and a specificity of 0.85 with an area under the curve value of 0.902 in the receiver operating characteristic analysis. Overall, our results indicate that M-CSF is a potential molecular marker for early risk prognosis of free-flap transplant failure.
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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 | 0.000 | 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 | 0.000 |
| 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".