A quarter of admitted poisoned patients have a mild poisoning and require no treatment: An observational study

Predicting the outcome in poisoned patients: look at the past!

INTRODUCTION

When predicting future events, we often rely on analyzing past occurrences and projecting them forward. This methodology is crucial in various fields, including toxicology, in which predicting outcomes in poisoned patients plays a vital role in guiding treatment decisions and improving patient care.

IMPORTANCE OF PREDICTING OUTCOMES IN POISONED PATIENTS

In cases of poisoning, understanding a patient's medical history, current physiological status, and the toxicokinetics of the ingested substance is essential for predicting potential outcomes and determining appropriate interventions.

WHAT TO PREDICT?

Predicting whether an intoxicated patient needs (further) treatment or even admission to the hospital is one of the most difficult decisions a clinician needs to make. The prediction of the course of an intoxication often lacks crucial information, leaving physicians with a sense of uncertainty in treating and advising patients. A significant source of this uncertainty stems from patients' limited awareness of the specific chemical(s) causing their symptoms, making a targeted approach challenging. Adding to the complexity, both patients and physicians frequently lack knowledge of the exposure dose, onset time, and potential interactions, further complicating the prediction of symptom progression. Patients are commonly placed in observation wards until the pharmacodynamic effects have diminished, leading to extended observation periods and unnecessary healthcare utilization and costs. Therefore, a key objective of a predictive model is to determine the necessity for intensive care unit admission.

PREDICTING THE REQUIREMENT FOR ADMISSION TO AN INTENSIVE CARE UNIT

Factors such as age, Glasgow Coma Scale, and specific comorbidities like dysrhythmias and chronic respiratory insufficiency significantly influence the likelihood of intensive care unit admission. By examining a patient's trajectory based on past medical history and organ function deterioration, clinicians can better anticipate the need for critical care support.

ENHANCING PREDICTION MODELS FOR IMPROVED PATIENT CARE

To enhance prediction models, leveraging modern methodologies like machine learning on large datasets (big data) are crucial. These advanced techniques can uncover previously unknown patient groups with similar outcomes or treatment responses, leading to more personalized and effective interventions. Regular updates to clustering, discrimination, and calibration processes ensure that predictive models remain accurate and relevant as new data emerges.

CONCLUSIONS

The field of clinical toxicology stands to benefit greatly from the creation and integration of large datasets to advance toxicological prognostication. By embracing innovative approaches and incorporating diverse data sources, clinicians can enhance their ability to predict outcomes in poisoned patients and improve overall patient management strategies.

Epidemiology of poisoning in Syria (1999 through 2020)

INTRODUCTION

Acute poisoning is a significant international public health issue and one of the leading causes of death in the emergency department (ED). In the absence of any previous reports describing the poisoning profile in Syria, we present this study to assess the epidemiological and clinical characteristics of poisoning over 21 years.

METHODS

We collected the data retrospectively from the Syrian Poisons Information Centre (SPIC) from January 1999 until December 2020. The data included patients who had accidental or non-accidental exposure to poisons, either by drugs, medicaments, and biological substances or substances chiefly nonmedicinal sources such as soaps and detergents, corrosive substances, pesticides, and other miscellaneous products.

RESULTS

We collected the data of 120,972 poisoned patients, of whom 52.6% were females, and 47.4% were males. Aleppo governorate reported the highest number of poisoned cases (28.6%), followed by Damascus governorate (19.9%). The highest poisoning rates were recorded in 2020, 2014, and 2010. Pharmaceutical (37.0%) and animal (33.8%) sources were the most common causative agents. The oral route was the route of poisoning in 58.3% of patients, and 33.4% through the skin. The most common poison was scorpion stings 19.5% while the most common cause of death was organophosphates 15.7%.

DISCUSSION

The differences in socioeconomic status, cultural habits, and agricultural and industrial activities between countries have led to a state of fluctuation regarding the most common poisoning agents.

CONCLUSION

Damascus and Aleppo, the two major governorates in Syria, had the highest poisoning cases. Oral administration of pharmaceutical agents was responsible for most of the poisoning cases. The most common individual poison was the scorpion poison, while the top killer was organophosphates.

Paracetamol (acetaminophen) overdose and hepatotoxicity: mechanism, treatment, prevention measures, and estimates of burden of disease

INTRODUCTION

Paracetamol is one of the most used medicines worldwide and is the most common important poisoning in high-income countries. In overdose, paracetamol causes dose-dependent hepatotoxicity. Acetylcysteine is an effective antidote, however despite its use hepatotoxicity and many deaths still occur.

AREAS COVERED

This review summarizes paracetamol overdose and toxicity (including mechanisms, risk factors, risk assessment, and treatment). In addition, we summarize the epidemiology of paracetamol overdose worldwide. A literature search on PubMed for poisoning epidemiology and mortality from 1 January 2017 to 26 October 2022 was performed to estimate rates of paracetamol overdose, liver injury, and deaths worldwide.

EXPERT OPINION

Paracetamol is widely available and yet is substantially more toxic than other analgesics available without prescription. Where data were available, we estimate that paracetamol is involved in 6% of poisonings, 56% of severe acute liver injury and acute liver failure, and 7% of drug-induced liver injury. These estimates are limited by lack of available data from many countries, particularly in Asia, South America, and Africa. Harm reduction from paracetamol is possible through better identification of high-risk overdoses, and better treatment regimens. Large overdoses and those involving modified-release paracetamol are high-risk and can be targeted through legislative change.