Measurement of the International Normalized Ratio (INR) in Hemodialysis Patients with Heparin-Locked Central venous Catheters: Evaluation of a Novel Blood Sampling Method
Bibliographic record
Abstract
BACKGROUND: Accurate measurement of the international normalized ratio (INR) may be difficult in hemodialysis (HD) patients with heparin-locked central catheters. Blood contamination with locking solutions may interfere with INR measurement when samples are collected directly from the catheter. METHODS: The aim of our study was to evaluate a novel sampling method for the measurement of INR in HD patients with heparin-locked central catheters. This novel method consists of measuring the INR directly from the dialysis circuit (arterial bloodline sample port) after 1 hr of treatment regardless of heparin administration during dialysis. We compared this method to the gold standard (peripheral venipuncture prior to dialysis) using the paired t-test. We included 30 patients (23 with warfarin therapy and 7 without). RESULTS: INRs obtained using the novel sampling method were only minimally overestimated compared to venipuncture values (mean INR overestimation: 0.2 +/- 0.2). This overestimation was not clinically significant and did not lead to changes in warfarin prescription for any of the patients. Correlation tests confirmed the influence of heparin administration on INR overestimation (R=0.4; p=0.05). This influence was present mostly among patients receiving more than 100 Units/kg of heparin during their treatment. CONCLUSION: This novel sampling technique provides a convenient and simple method of monitoring INR among HD patients.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".