Misidentification of Risk Group 3/Security Sensitive Biological Agents by MALDI-TOF MS in Canada: November 2015–October 2017
Bibliographic record
Abstract
BACKGROUND: Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) is a technology increasingly used in diagnostic identification of microorganisms. However, anecdotal evidence suggests that this technology is associated with misidentification of Risk Group 3 (RG3)/Security Sensitive Biological Agents (SSBA) resulting in exposure risks to laboratory personnel. OBJECTIVE: To investigate and characterize incidents related to the use of MALDI-TOF MS in Canada between November 6, 2015, and October 10, 2017. METHODS: . A questionnaire was developed to identify potential risk factors leading to the exposure. Reporters from organizations with selected incidents were interviewed using the questionnaire. Data were entered into an Excel spreadsheet and standard descriptive statistical analysis performed to assess common characteristics and identify possible risk factors. RESULTS: There were eight eligible incidents and a total of 39 laboratory workers were exposed to RG3/SSBA organisms. In five (out of eight) of the incidents, the reporters indicated that their device was equipped with both clinical and research reference libraries. For six incidents where reporters knew the type of library used, only the clinical library was employed at the time of the incident even though both libraries were available in five of these incidents. In all eight cases, the exposure occurred during the sample preparation stage with analyses performed on an open bench and directly from the specimen. And in all eight cases, patient specimens were received without information regarding potential risk. CONCLUSION: This first national study characterizing the nature and extent of laboratory incidents involving RG3/SSBA that are related to the use of MALDI-TOF MS identifies risk factors and provides baseline data that can inform mitigation strategies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".