Cost savings associated with timely treatment of botulism with botulism antitoxin heptavalent product
Bibliographic record
Abstract
BACKGROUND: Botulism is a rare, serious, and sometimes fatal paralytic illness caused by exposure to neurotoxins produced by Clostridium botulinum bacteria. Patients with documented or suspected exposure to botulinum toxin serotypes A-G can be treated with BAT® [Botulism Antitoxin Heptavalent (A, B, C, D, E, F, G)-(Equine)] product, which was approved in 2013 in the United States (US). Patients with botulism have demonstrated greater clinical benefit with early BAT product treatment (≤2 days from symptom onset) versus late treatment (>2 days). OBJECTIVE: Economic outcomes associated with improved clinical outcome benefits of BAT product treatment have not yet been reported. This ad hoc analysis aimed to estimate and compare costs associated with hospitalization, intensive care unit stay, and mechanical ventilation for patients with botulism administered BAT product treatment early or late. METHODS: Clinical outcomes data for early and late BAT product treatment were obtained from a patient registry conducted between October 2014 and July 2017. Total per patient mean daily costs were estimated based on information from published literature. Total population costs per group were calculated by multiplying estimated mean cost per patient by the average annual number of non-infant botulism cases in the US. RESULTS: Mean per patient costs were 2.5 times lower for patients treated with BAT product early versus late. On average in the US, early BAT product treatment could save greater than $3.9 million per year versus late treatment. CONCLUSION: Substantial economic savings can be achieved with early BAT product treatment. The findings support the recommendation for public health authorities to ensure antitoxin treatment is readily available in sufficient quantities to manage botulism cases, including sporadic outbreaks and potential mass exposure biological attacks.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".