Reliability of Point-of-Care Testing of INR in Acute Stroke
Bibliographic record
Abstract
BACKGROUND: In the emergency department, portable point-of-care testing (POCT) coagulation devices may facilitate stroke patient care by providing rapid International Normalized Ratio (INR) measurement. The objective of this study was to evaluate the reliability, validity, and impact on clinical decision-making of a POCT device for INR testing in the setting of acute ischemic stroke (AIS). METHODS: A total of 150 patients (50 healthy volunteers, 51 anticoagulated patients, 49 AIS patients) were assessed in a tertiary care facility. The INR's were measured using the Roche Coaguchek S and the standard laboratory technique. RESULTS: The interclass correlation coefficient and 95% confidence interval between overall POCT device and standard laboratory value INRs was high (0.932 (0.69 - 0.78). In the AIS group alone, the correlation coefficient and 95% CI was also high 0.937 (0.59 - 0.74) and diagnostic accuracy of the POCT device was 94%. CONCLUSIONS: When used by a trained health professional in the emergency department to assess INR in acute ischemic stroke patients, the CoaguChek S is reliable and provides rapid results. However, as concordance with laboratory INR values decreases with higher INR values, it is recommended that with CoaguChek S INRs in the > 1.5 range, a standard laboratory measurement be used to confirm the results.
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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 | 0.016 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".