Outbreak of Foodborne Botulism in Alexandria, Egypt: Modulating Indications for Administration of Heptavalent Botulinum Antitoxin
Bibliographic record
Abstract
Abstract Background: In October 2019, 94 patients were admitted into Alexandria Poison Center (APC) with a history of ingestion of Feseekh (salted fish). As a trial to allocate the resources, not all patients were given Heptavalent botulinum antitoxin (HBAT) immediately.The current study aimed to portray the clinical characteristics of the cases, explore the possible relation between these characteristics and necessity of HBAT administration, explore the reliability of MLT, and to establish a clinical guide for management with preservation of resources.Subject and Method: the current prospective study included 94 patients who were admitted to Alexandria Poison Center (APC) in the period from 29 th September to 27 th October 2019. The patients' data was recorded using a checklist that includes: personal data, past medical history, clinical assessment, investigations, treatment and the outcome. The checklist was carried out to assess and follow up each patient. Hospitalized patients were categorized according to symptoms consistent with botulism. The equine HBAT, made by Emergent BioSolutions Canada Inc. (formerly Can gene Corporation) was used in the treatment.Results: HBAT was given to (36.2%) patients only out of the total admission. However, 87.2% of patients were completely cured, whereas 10.6% of patients were discharged with mild neurological sequelea and death occurred only in two cases (2.2%).Conclusion: 63.8% of cases with suspected foodborne botulism toxicity could be managed by supportive treatment only with no need for HBAT.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".