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Screening for Predictors of Chronic Ciguatera Poisoning: An Exploratory Analysis among Hospitalized Cases from French Polynesia
- Source :
- Toxins, Volume 13, Issue 9, Toxins, Vol 13, Iss 646, p 646 (2021), Toxins (2072-6651) (MDPI AG), 2021-09, Vol. 13, N. 9, P. 646 (14p.)
- Publication Year :
- 2021
- Publisher :
- MDPI, 2021.
-
Abstract
- Ciguatera poisoning is a globally occurring seafood disease caused by the ingestion of marine products contaminated with dinoflagellate produced neurotoxins. Persistent forms of ciguatera, which prove to be highly debilitating, are poorly studied and represent a significant medical issue. The present study aims to better understand chronic ciguatera manifestations and identify potential predictive factors for their duration. Medical files of 49 patients were analyzed, and the post-hospitalization evolution of the disease assessed through a follow-up questionnaire. A rigorous logistic lasso regression model was applied to select significant predictors from a list of 37 patient characteristics potentially predictive of having chronic symptoms. Missing data were handled by complete case analysis, and a survival analysis was implemented. All models used standardized variables, and multiple comparisons in the survival analyses were handled by Bonferroni correction. Among all studied variables, five significant predictors of having symptoms lasting ≥3 months were identified: age, tobacco consumption, acute bradycardia, laboratory measures of urea, and neutrophils. This exploratory, hypothesis-generating study contributes to the development of ciguatera epidemiology by narrowing the list from 37 possible predictors to a list of five predictors that seem worth further investigation as candidate risk factors in more targeted studies of ciguatera symptom duration.
- Subjects :
- Adult
Male
medicine.medical_specialty
Ciguatera
Health, Toxicology and Mutagenesis
Disease
Toxicology
01 natural sciences
ciguatera poisoning
Article
Polynesia
survival analysis
010104 statistics & probability
03 medical and health sciences
symbols.namesake
Internal medicine
Epidemiology
medicine
Prevalence
medical informatics
Humans
0101 mathematics
Survival analysis
030304 developmental biology
0303 health sciences
business.industry
Ciguatera Poisoning
Exploratory analysis
Middle Aged
medicine.disease
3. Good health
Hospitalization
Bonferroni correction
machine learning
Multiple comparisons problem
foodborne diseases
symbols
Medicine
epidemiology
Female
data science
least absolute shrinkage and selection operator
business
Subjects
Details
- Language :
- English
- ISSN :
- 20726651
- Volume :
- 13
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- Toxins
- Accession number :
- edsair.doi.dedup.....337ebe046818888ca6cbae6c199e52a7