Evaluation of activated partial thromboplastin time coagulation waveform analysis for identification of patients with acquired factor VIII inhibitors
Bibliographic record
Abstract
Abstract Introduction Activated partial thromboplastin time (PTT) coagulation waveforms produced by optical detection system coagulation analyzers provide additional potentially useful and routinely underutilized information for the evaluation of a patient's coagulation system. We aimed to identify features of PTT coagulation waveforms, available for all PTT assays performed in our hospital laboratories, that may prove useful in directing early investigations in patients with unexplained prolonged PTT. Methods We retrospectively reviewed 211 PTT coagulation waveforms from patient testing and categorized them based on the underlying hemostatic abnormality: normal, therapeutic anticoagulation, lupus anticoagulant, congenital factor deficiency, or acquired factor VIII inhibitor. We compared quantitative waveform parameters and the frequency of qualitatively abnormal double‐peaked first derivative waveform curves between these groups. Results Partial thromboplastin time and derivative curve maxima and minima differed significantly between acquired factor VIII inhibitors and other diagnostic categories, and the second derivative curve minimum demonstrated the highest area under the receiver operator characteristic curve for identification of acquired factor VIII inhibitors (0.860; maximum accuracy: 79.5% for 2Dmin> −39.3 mAbs/s 2 [sensitivity 90.5%; specificity 77.2%]). The presence of an abnormal double‐peaked first derivative curve had a sensitivity of 83.3% and specificity of 81.6% for identification of acquired factor VIII inhibitors in cases with PTT >50 seconds. Conclusion Partial thromboplastin time coagulation waveform analysis can aid in identification of patients with acquired factor VIII inhibitors and may be of clinical utility in directing early laboratory investigations to identify patients at risk of severe bleeding without prompt intervention.
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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 | 0.001 |
| 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".