Systematic evaluation of evidence on veterinary viscoelastic testing Part 1: System comparability
Bibliographic record
Abstract
OBJECTIVE: To systematically examine the evidence on system comparability between the thromboelastography and the rotational thromboelastometry viscoelastic point-of-care instruments and to identify knowledge gaps. DESIGN: Standardized, systematic evaluation of the literature, categorization of relevant articles according to level of evidence and quality, and development of consensus on conclusions for application of the concepts to clinical practice. SETTING: Academic and referral veterinary medical centers. RESULTS: Medline via PubMed, CAB abstracts, and Google Scholar were searched. A total of 8 relevant articles were chosen, none were in support of the question, 1 was neutral to the question (level of evidence [LOE] 6, Poor), and 7 were in opposition to the question (LOE 3 Good; LOE 6 Good; LOE 6 Fair; LOE 6 Poor). CONCLUSIONS: Results from the 2 analyzers are not directly comparable and extrapolation of the results from one machine to the other should be avoided. Standardization of the preanalytical variables (eg, blood collection, holding time, and temperature during holding) is strongly recommended. It is recommended that each site create their own "site specific" reference values for each machine and that test samples be compared only to the standardized reference values established at that center. Start-up and consumable costs vary between countries and local comparisons should be performed. Decisions should be made based on the expected use of the machine and if multiple operators will be using it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".