Comparison of time-motion analysis of conventional stool culture and the BD MAX™ Enteric Bacterial Panel (EBP)
Bibliographic record
Abstract
BACKGROUND: Conventional bacterial stool culture is one of the more time-consuming tests in a routine clinical microbiology laboratory. In addition, less than 5 % of stool cultures yield positive results. A molecular platform, the BD MAX™ System (BD Diagnostics, Sparks, MD) offers the potential for significantly more rapid results and less hands-on time. Time-motion analysis of the BD MAX Enteric Bacterial Panel (EBP) (BD Diagnostics, Quebec, Canada) on the BD MAX System was compared to conventional stool culture in the microbiology laboratory of a tertiary care pediatric hospital. METHODS: The process impact analysis of time-motion studies of conventional cultures were compared to those of EBP with 86 stool specimens. Sample flow, hands-on time, processing steps, and overall turnaround time were determined and analyzed. Data were obtained and analyzed from both standard operating procedures and direct observation. A regression analysis was performed to ensure consistency of measurements. Time and process measurements started when the specimens were logged into the accessioning area of the microbiology laboratory and were completed when actionable results were generated. RESULTS: With conventional culture, negative culture results were available from 41:14:27 (hours:minutes:seconds) to 54:17:19; with EBP, positive and negative results were available from 2:28:40 to 3:33:39. CONCLUSIONS: This study supports the suggestion that use of the EBP to detect commonly encountered stool pathogens can result in significant time savings and a shorter time-to-result for patients with acute bacterial diarrhea.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".