Probabilistic model to predict the outcome in acute suicidal chemical poisoning cases from age and gender of patient and type of chemical poison consumed

Abstract

Background: Acute chemical poisoning is a significant global health problem. Chemical poisons include agrochemical, household and industrial poison subtypes. The present study used a probabilistic model based on age, gender and type of poison consumed by the patient to predict the outcome in acute suicidal poisoning cases. Material and methods: A prospective observational study was conducted at emergency department of SMS Hospital, Jaipur, India, from January 2019 to February 2020. Patients over 15 years of age with poisoning severity score 2 or above were included in the study. Probabilistic model was used to predict the outcome measured in terms of cure, death and left against medical advice (LAMA) using Minitab 14. Results: Poisoning cases were 0.32 % of all emergency presentations. Out of them, 857 (59.6 %) had consumed chemical poison. Their mean age was 32 years and men to women ratio was 1.22. Agrochemical subtype was most common followed by household and industrial poisoning. Analysis by Probabilistic model showed that person between 30-60 years is more likely to be cured and chances of death and LAMA are highest in age group 60-75. Gender-wise, men have higher possibility for recovery. Besides, a person has highest chances of recovery in case of household poisons; death is most common in industrial poisons and LAMA in agrochemical poisons. Conclusion: The study concluded that in poisoning, patients' basic information like age, gender, type of poison consumed can be used to identify high death probability and LAMA risk patients. It will assist in designing and monitoring the most effective strategies for them.

Keywords

• cure
• death
• lama
• outcome
• poisoning
• probabilistic model.