Effect of delayed entry of blood culture bottles in BACTEC automated blood culture system in the context of laboratory consolidation
Bibliographic record
Abstract
Delayed entry of blood culture bottles is frequent in consolidated laboratories. A retrospective study evaluated time from insertion to detection and total detection time as a function of preincubation time, and we prospectively looked for false negative results. 69,604 blood culture bottles were reviewed for preincubation time, incubation time and total detection time. Positive cultures for specific bacterial subtypes were reviewed to assess the effect of preincubation time on likelihood of detection. 492 negative blood cultures were prospectively tested by 16S RNA PCR and Staphylococcus-specific PCR for the presence of bacterial DNA. Mean preincubation time for samples collected within the city-limits was 3.94 h versus 9.49-18.89 h for other client sites. Higher preincubation times were partially mitigated by a lower incubation time, with an overall increase in total detection time. A lower odds ratio of recovery of Staphylococcus spp was identified, but not confirmed by terminal subcultures and molecular assays. Prolonged preincubation of blood cultures affects total detection time despite a reduction in incubation time. Successful centralization of microbiological services may depend upon optimization of courier routes for inoculated blood culture bottles. Our data supports consideration for an increase in suggested maximum preincubation times.
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 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 | 0.041 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".