Evaluation of Triton X-100 Effect on Coagulation Tests
Bibliographic record
Abstract
Abstract CONTEXT: Triton X-100 is a non-ionic surfactant that has been proposed as a virus inactivator in a laboratory setting for it causes cell lysis through lipid membrane disruption without denaturing proteins. Very few studies have tried to evaluate its effect on laboratory tests, especially on coagulation tests that require a phospholipid subtract. METHOD: Plasma samples were collected. Triton X-100 was spiked at a concentration of 0,25% and specimens were incubated for an hour. We performed international normalized ratio (INR), activated partial thromboplastin time (aPTT), thrombin time (TT), fibrinogen dosing and D-Dimer dosing, comparing the standard plasma with the triton X-100 exposed plasma. We also dosed coagulation factors, and performed dilution and lupus anticoagulant studies. Finally, we compared prothrombin time and aPTT using reagents from various manufacturers. RESULTS: We observed an important difference for the INR and the aPTT with addition of triton x-100. A slight decrease of an average of 6.6 to 16.4% was also found in factor assays. Differences in the INR and the aPTT were dependent respectively on the ISI and the phospholipids content of the reagent. CONCLUSION: The addition of triton x-100 significantly modifies INR and aPTT results with every reagent tested. The impact on TT and fibrinogen is not clinically relevant, and the D- Dimer dosage is not affected. The slight decrease in all coagulation factors does not explain those results. The interference could result from an interaction with phospholipids, calcium or some enzymatic reactions caused by the presence of triton x-100 in the analyzed specimen. Table. Test Mean Mean Mean of difference p-value (paired t-test) without Triton with Triton INR 1,59 2,87 68,80% p<0,001 aPTT 31,59 sec 61,80 sec 86,10% p<0,001 TT 16,82 sec 17,42 sec 3,50% p<0,001 Fibrinogen 3,27 g/L 3,21 g/L -0,70% p=0,001 D-Dimer 2897 mcg/L 2905 mcg/L 4,30% p=0,697 Disclosures No relevant conflicts of interest to declare.
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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 | 0.000 |
| 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".