Validation of the New MINI-CUBE for Clinic Determination of Erythrocyte Sedimentation Rate
Bibliographic record
Abstract
Background: Erythrocyte sedimentation rate (ESR) indirectly measures blood fibrinogen, and it is altered by all those pathological conditions that modify the aggregation of red blood cells. The international guidelines by the International Council for Standardization in Hematology (ICSH) define the Westergren method as the gold standard for ESR, although it is completely operator-dependent, time-consuming, and requires a patient's blood consumption. Therefore, the validation of new ESR analyzers is needed. The aim of this study is the validation of a new automated ESR analyzer, MINI-CUBE (DIESSE, Diagnostica Senese, Italy). Methods: The samples (n = 270) were collected at the University Hospital of the University of Rome Tor Vergata. A comparison between the automated instrument and the gold standard was performed. Statistical analyses were processed by MedCalc software. Results: The comparison analysis performed on the overall samples reported a good agreement, showing a Spearman rank correlation coefficient of 0.94 (P < 0.001), compared to the Westergren test. The Bland-Altman analysis showed a mean bias of 1.5 (maximum (max.):19.6; minimum (min.): -16.6). Inter-run (level 1 coefficient of variation (CV): 4.9%; level 2 CV: 0.8%), intra-run (level 1 CV: 21.1%; level 2 CV: 3.2%), and inter-instrument (level 1 CV: 27.1%; level 2 CV: 5.6%) precision were also assessed. The hematocrit value did not interfere with the analysis: Spearman rank correlation coefficient of 0.929 (P < 0.001); mean bias of 1.3 (max.:18.3; min.: -15.6). Conclusions: Overall results from MINI-CUBE asserted a good correlation rate with the gold standard, and it could be considered an accurate, and objective alternative for the Westergren test.
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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".