Evaluation of Rapid Readout Biological Indicators for 132°C Gravity and 132°C Vacuum-Assisted Steam Sterilization Cycles Using a New Automated Fluorescent Reader
Bibliographic record
Abstract
OBJECTIVE: The primary objective of this study was to evaluate fluorescent readout results of Attest 1291 Biological Indicators (BIs) (3M Health Care, St. Paul, MN) and Attest 1296 BI test packs (containing Attest 1292 BIs) using full and fractional cycles compared with the growth data when prolonged incubation (7 days) was included. Gravity displacement and vacuum-assisted steam sterilization cycles were evaluated. A secondary objective of this study was to evaluate the new automated rapid fluorescent reader (Attest 290 Auto Reader). DESIGN: The rapid readout BIs for gravity displacement and vacuum-assisted steam autoclave cycles at 132 degrees C were processed using full (4 minutes) and four fractional cycles that provided 30% to 80% positive results for growth after 24 hours of incubation (48 hours of incubation for Attest 1292 BIs from the Attest 1296 test packs). Sixty of each type of BI were tested for each cycle (300 of each BI type in total). RESULTS: For all full steam sterilization cycles, results of the rapid fluorescent readout and the 24-hour, 48-hour, and 7-day growth tests were negative for all Attest 1291 and 1292 BIs tested. For all fractional cycles, the 24- and 48-hour growth results for the Attest 1291 and 1292 BIs, respectively, were the same as the 7-day growth results. The fractional cycle data indicated that fluorescent rapid readout was a more sensitive indicator than growth. There were rare (0.9%) false-negative results for BIs under fractional cycle conditions and these all correlated with short fractional cycle exposure times. CONCLUSIONS: The fluorescent rapid readout results of the 1291 BIs and 1296 BI test packs reliably predict both 24- and 48-hour and 7-day growth. These data support the value of rapid readout BIs for sterilizer monitoring for both the vacuum-assisted and the gravity displacement steam sterilization cycles. The new automated reader requires less manipulation of the BI and makes monitoring user friendly and less prone to user errors.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".