Pattern and predictors of death from aluminum and zinc phosphide poisoning: A two years prospective study

Hegazy, Mofrih; Elagamy, Situhom Elsayed; Salem, Eman Abdel-Azeem

doi:10.21608/ejfsat.2019.7676.1050

Cited by 4 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, these pesticides can cause severe acute and chronic poisoning due to the release of phosphine gas when exposed to water or hydrochloric acid in the stomach. The toxic effects of phosphine gas include impaired tissue respiration, cardiac muscle toxicity, adrenal gland toxicity, and circulatory collapse, which can lead to death 3 . Aluminum Phosphide (AlP) has been reported also to cause methemoglobinemia, hemolysis, and inhibition of the cholinesterase enzyme 4 – 6 .…”

Section: Introductionmentioning

confidence: 99%

Pattern and predictors of death from aluminum and zinc phosphide poisoning using multi-kernel optimized relevance vector machine

Abdelghafar

Farrag

Zanaty

et al. 2023

Sci Rep

View full text Add to dashboard Cite

The use of metal phosphides, particularly aluminum phosphide, poses a significant threat to human safety and results in high mortality rates. This study aimed to determine mortality patterns and predictive factors for acute zinc and aluminum phosphide poisoning cases that were admitted to Menoufia University Poison and Dependence Control Center from 2017 to 2021. Statistical analysis revealed that poisoning was more common among females (59.7%), aged between 10 and 20 years, and from rural regions. Most cases were students, and most poisonings were the result of suicidal intentions (78.6%). A new hybrid model named Bayesian Optimization-Relevance Vector Machine (BO-RVM) was proposed to forecast fatal poisoning. The model achieved an overall accuracy of 97%, with high positive predictive value (PPV) and negative predictive value (NPV) values of 100% and 96%, respectively. The sensitivity was 89.3%, while the specificity was 100%. The F1 score was 94.3%, indicating a good balance between precision and recall. These results suggest that the model performs well in identifying both positive and negative cases. Additionally, the BO-RVM model has a fast and accurate processing time of 379.9595 s, making it a promising tool for various applications. The study underscores the need for public health policies to restrict the availability and use of phosphides in Egypt and adopt effective treatment methods for phosphide-poisoned patients. Clinical suspicion, positive silver nitrate test for phosphine, and analysis of cholinesterase levels are useful in diagnosing metal phosphide poisoning, which can cause various symptoms.

show abstract

Section: Introductionmentioning

confidence: 99%

Pattern and predictors of death from aluminum and zinc phosphide poisoning using multi-kernel optimized relevance vector machine

Abdelghafar

Farrag

Zanaty

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

Comparative Study of Management of Aluminium Phosphide Poisoning - Our Experience

Vaidyanathan¹,

Adarsh²,

H.G³

et al. 2020

jebmh

View full text Add to dashboard Cite

Predictive Variables of Acute Aluminum Phosphide Poisoning Outcome: A New Proposed Model

Ghonem

Sharkawy

Lashin

2020

The Egyptian Journal of Forensic Sciences and Applied Toxicolog

View full text Add to dashboard Cite

Introduction: Acute aluminum phosphide (AlP) poisoning is a major toxicological challenge in developing countries especially in absence of specific antidote. Aim of the study:The current study aimed to identify predictive variables of outcome in acute AlP poisoning, then propose and validate a prediction model. Patients and Methods: This study was conducted on patients with acute AlP poisoning admitted at Tanta Poison Control Center from January 2018 to December 2018 (derivation group) and from January 2019 to June 2019 (validation group). For each patient, age, sex and toxicological characteristics were obtained. Clinical examination, routine laboratory investigations, central venous pressure measurement and electrocardiography were also done. Results: Data of the derivation group (110 patients) revealed that, systolic blood pressure, central venous pressure, pH and prothrombin time were significant predictive variables. Using univariate and multivariate regression analysis, systolic blood pressure, central venous pressure and pH were valid to construct the prediction model at cut off ≤85 mmHg, >22 cmH 2 O and ≤7.33 respectively. Variables were given points and the maximum sum points were 10. The power of the proposed model to discriminate between survivors and non-survivors at cut off ≥4 and ≥5 sum points was excellent (AUC: 0.974). The discrimination power in the validation group (58 patients) was excellent (AUC: 0.917). Conclusion: This proposed model could be considered a simple and excellent tool to predict acute aluminum phosphide poisoning outcome.

show abstract

Pattern and predictors of death from aluminum and zinc phosphide poisoning: A two years prospective study

Cited by 4 publications

References 20 publications

Pattern and predictors of death from aluminum and zinc phosphide poisoning using multi-kernel optimized relevance vector machine

Pattern and predictors of death from aluminum and zinc phosphide poisoning using multi-kernel optimized relevance vector machine

Comparative Study of Management of Aluminium Phosphide Poisoning - Our Experience

Predictive Variables of Acute Aluminum Phosphide Poisoning Outcome: A New Proposed Model

Contact Info

Product

Resources

About