Evaluating accelerations across multiple routes of a pneumatic tube system to ensure sample integrity for LDH measurement
Bibliographic record
Abstract
OBJECTIVES: Lactate dehydrogenase (LDH) concentrations can falsely increase due to the acceleration forces generated in the pneumatic tube system (PTS) during blood sample transport, potentially leading to altered medical decisions. This study evaluated the accelerations and elevated LDH concentrations in 11 routes during PTS transport in an academic hospital. METHODS: Three blood samples were collected from each healthy volunteer and transported via hand carrier, PTS carrier, and PTS carrier with an additional foam insert. Five samples were included in the same carrier for every transport. An accelerometer was placed with the samples to record pressure, acceleration and transport time for each PTS route. The samples were then tested for hemoglobin and LDH concentrations on core laboratory chemistry analyzers. Three acceleration parameters were calculated. RESULTS: Transport time across the 11 routes varied widely from 78 to 455 s. Hemoglobin concentrations showed a slight increase during PTS transport, which was associated with a significant increase in LDH concentrations (r 0.716, p < 0.001). On average, LDH increased from 9.5 to 59.2 % during PTS transport. Total accelerations, percentages of acceleration > 5 g, and maximum accelerations ranged from 172.7 to 617.9 g, 3.5 to 14.7 %, and 15.31 to 24.28 g, respectively. When routes were scored based on any of the three parameters exceeding their average, routes with an LDH increase > 15 % had higher scores than those with an LDH increase ≤ 15 %. CONCLUSIONS: This study supports using accelerometers to validate and monitor the accelerations of each route generated during PTS blood sample transport and to identify the routes unsuitable for LDH measurement. Further studies are warranted to determine appropriate acceleration parameters and their thresholds to ensure sample integrity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".