The Effect of Inadequate Presample Blood Volume Withdrawal from Intravenous Catheter and Extension Sets on Measured Circulating L-Blood Lactate Concentration in Horses Receiving Lactated Ringer's Solution
Bibliographic record
Abstract
BACKGROUND: Circulating l-lactate concentration is commonly measured in hospitalized horses by sampling from indwelling intravenous (IV) catheters. However, there are no published evidence-based recommendations to prevent contamination by lactated Ringer's solution (LRS). HYPOTHESIS: Withdrawing 10 mL of blood from the LRS-containing extension set connected to the IV catheter before obtaining the sample for analysis should be adequate to obtain accurate measurement of blood lactate concentration (BLC). ANIMALS: Thirty-three adult hospitalized horses receiving constant rate infusion of LRS. METHODS: Immediately after disconnecting the LRS, 5 sequential 5 mL blood samples were obtained by aspiration from an extension set connected to an indwelling IV catheter, followed by 3 samples collected by direct venipuncture of the contralateral jugular vein. Samples were analyzed with 1 portable blood lactate analyzer. A linear mixed model was used to examine differences in lactate concentrations among samples collected from the catheter and by direct venipuncture. RESULTS: After considering differences in age, breed, sex, and reason for hospitalization, BLCs were higher (P < .001) in the first and second 5 mL samples collected through the extension set/catheter than in all other extension set/catheter samples or the direct venipuncture samples. The largest difference observed between the third and subsequent catheter or venipuncture samples was 0.34 mmol/L with an upper 95% CI of 1.12 mmol/L. CONCLUSIONS AND CLINICAL IMPORTANCE: Withdrawing 15 mL of blood from a LRS-containing extension set connected to an IV catheter (5.9 mL total volume capacity) before obtaining the sample for blood lactate analysis is suggested to optimize accuracy of BLC measurements.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".