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Introduction: Glucagon-like peptide-1 agonists have gained attention in recent years due to their efficacy in managing type II diabetes mellitus and their emerging role in weight management. The purpose of this study was to characterize glucagon-like peptide-1 agonist exposures reported to a single United States regional poison center over nine years, including causes of exposure, associated clinical effects, and potential areas for improving patient education and safety., Methods: This retrospective cohort study analyzed all poison center calls involving glucagon-like peptide-1 agonists submitted to a single United States regional poison center from 14 January 2014 to 1 May 2023. Data were abstracted from the electronic medical record of the poison center, including demographics, call volume, drug involved, type of exposure, frequency of hypoglycemia, and other side effects., Results: Two hundred and thirty-seven cases involving glucagon-like peptide-1 agonists were reported to the poison center. The annual number of cases increased sharply over this period. Most patients ( n  = 166, 70.0%) were females. Most calls ( n  = 164, 69.2%) were due to unintentional therapeutic errors. Semaglutide was the most frequently involved medication ( n  = 72, 36.0%). Hypoglycemia was identified in eight patients (3.4%). The lowest mean (±SD) blood glucose concentration in these hypoglycemic patients was 49.6 ± 23.7 mg/dL (2.76 ± 1.3 mmol/L)., Discussion: Unintentional therapeutic errors were involved in 164 (69.2%) cases. Despite the generally mild clinical effects observed in this study, the occurrence of hypoglycemia in a subset of patients, often requiring hospitalization, is of concern. With reports of the acquisition of these medications through online platforms and poorly regulated compounding sources, this trend may pose public health risks., Conclusions: This study demonstrates the increasing incidence of glucagon-like peptide-1 agonist exposures reported to a United States regional poison center, predominantly due to unintentional overdoses, which highlights the need for ongoing patient education.

Background: Clinical toxicology is not a certified specialty in Israel, consequently there are a limited number of toxicologists and toxicology services available for consultation., Objectives: To establish a medical toxicology consultation service focusing on bedside consultations, which had not previously been available in Israel., Methods: This single-center, retrospective chart review of toxicology consults was conducted during the first years after the initiation of a new toxicology service., Results: From September 2017 to December 2021, 1703 toxicology consultations were conducted. The most common exposures and reasons for consultation included psychotropic medications (427, 23%), analgesics and anti-inflammatory medications (353, 19%), household products (312, 17%), substances of abuse (240, 13%), and natural toxins (142, 8%). Bedside medical toxicology consultations were performed in 1036 cases (62%) during daytime and night shifts. The number of consultation requests increased steadily over the study period., Conclusions: The new toxicology service led to a significant change in the institution's approach to toxicological patients. A bedside toxicology service could help reduce the healthcare burden on national poison centers and can offer readily available, personalized, medical toxicology care.

Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utilizes National Poison Data System (NPDS) data. The severity of outcomes was derived from the NPDS Coding Manual. Our database was divided into training (70%) and test (30%) sets. We used a light gradient boosting machine (LGBM), extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR) to predict the outcomes of methadone poisoning. A total of 3847 patients with methadone exposures were included. Our results demonstrated that machine learning models conferred high accuracy and reliability in determining the outcomes of methadone poisoning cases. The performance evaluation showed all models had high accuracy, precision, specificity, recall, and F 1-score values. All models could reach high specificity (more than 96%) and high precision (80% or more) for predicting major outcomes. The models could also achieve a high sensitivity to predict minor outcomes. Finally, the accuracy of all models was about 75%. However, XGBoost and LGBM models achieved the best performance among all models. This study showcased the accuracy and reliability of machine learning models in the outcome prediction of methadone poisoning.

Introduction: Efficient and complete medical charting is essential for patient care and research purposes. In this study, we sought to determine if Chat Generative Pre-Trained Transformer could generate cogent, suitable charts from recorded, real-world poison center calls and abstract and tabulate data., Methods: De-identified transcripts of real-world hospital-initiated poison center consults were summarized by Chat Generative Pre-Trained Transformer 4.0. Additionally, Chat Generative Pre-Trained Transformer organized tables for data points, including vital signs, test results, therapies, and recommendations. Seven trained reviewers, including certified specialists in poison information and board-certified medical toxicologists, graded summaries using a 1 to 5 scale to determine appropriateness for entry into the medical record. Intra-rater reliability was calculated. Tabulated data was quantitatively evaluated for accuracy. Finally, reviewers selected preferred documentation: original or Chat Generative Pre-Trained Transformer organized., Results: Eighty percent of summaries had a median score high enough to be deemed appropriate for entry into the medical record. In three duplicate cases, reviewers did change scores, leading to moderate intra-rater reliability (kappa = 0.6). Among all cases, 91 percent of data points were correctly abstracted into table format., Discussion: By utilizing a large language model with a unified prompt, charts can be generated directly from conversations in seconds without the need for additional training. Charts generated by Chat Generative Pre-Trained Transformer were preferred over extant charts, even when they were deemed unacceptable for entry into the medical record prior to the correction of errors. However, there were several limitations to our study, including poor intra-rater-reliability and a limited number of cases examined., Conclusions: In this study, we demonstrate that large language models can generate coherent summaries of real-world poison center calls that are often acceptable for entry to the medical record as is. When errors were present, these were often fixed with the addition or deletion of a word or phrase, presenting an enormous opportunity for efficiency gains. Our future work will focus on implementing this process in a prospective fashion.

Introduction: Scientific societies aim to provide a collective voice and unified stance on important issues. The Clinical Toxicology Recommendations Collaborative was formed in 2016 to develop evidence- and consensus-based recommendations for the management of patients exposed to common and/or serious poisonings for which the management is unclear or controversial., Organization: The Clinical Toxicology Recommendations Collaborative is led jointly by the American Academy of Clinical Toxicology, the Asia Pacific Association of Medical Toxicology, and the European Association of Poison Centres and Clinical Toxicologists. The Governance Committee is chaired by a Past-President of one of these Societies and comprised of the six Presidents and Immediate Past-Presidents of the three Societies. A Steering Committee oversees the process of each project workgroup., Methodology: The overall process is guided by standards set forth by the Institute of Medicine for developing trustworthy guidelines and the Appraisal of Guidelines for Research and Evaluation Instrument. Systematic reviews are produced using the framework set in the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) methodology. Workgroup members jointly review the evidence and prepare statements on which they vote anonymously using a 9-point Likert scale. A two-round modified Delphi method is used to reach a consensus on clinical recommendations using the RAND/UCLA Appropriateness Method. Final recommendations are approved by unanimous consent of the workgroup and are expressed as both levels of evidence and strength of recommendations., Limitations: The major limitations of the Clinical Toxicology Recommendations Collaborative process centre around the amount and quality of evidence, the assessment of that evidence, and the voting of the panel., Conclusions: By using a transparent evidence- and consensus-based approach to produce systematic reviews and clinical recommendations, the Clinical Toxicology Recommendations Collaborative aims to create an international framework for clinical toxicology education and decision-making and foster positive change for the benefit of poisoned patients.

Objective: The QRS complex duration is commonly used to prognosticate severity, predict outcomes, and indicate treatment in overdose. However, literature to support this practice is mixed in tricyclic antidepressant overdoses and absent in non-tricyclic antidepressant overdoses. Our objective was to assess the validity of QRS complex duration as a prognostic marker in overdose., Methods: This was a secondary analysis of cases reported to the Toxicology Investigators Consortium between January 1, 2010, and December 31, 2022. Cases were assessed to determine the six xenobiotics most associated with QRS complex prolongation. All cases involving these six xenobiotics, regardless of QRS complex duration, constituted the study cohort. Inclusion criteria were cases of patients older than 12 years old with single-xenobiotic exposures. Clinical outcomes evaluated were seizure, ventricular dysrhythmia, metabolic acidosis, and death., Results: Of 94,939 total cases, diphenhydramine, amitriptyline, bupropion, quetiapine, nortriptyline, and cocaine were most associated with QRS complex prolongation. Inclusion criteria were met by 4,655 cases of exposure to these xenobiotics. QRS complex prolongation was associated with increased odds ratio of seizure in all included xenobiotics, of ventricular dysrhythmia in all included xenobiotics except nortriptyline, and of metabolic acidosis or death in all included xenobiotics except nortriptyline and quetiapine. A normal QRS complex duration had a negative predictive value of greater than or equal to 93.0 percent of developing metabolic acidosis and 98.0 percent of developing a ventricular dysrhythmia or death from the xenobiotics studied., Discussion: This study demonstrates that patients with QRS complex prolongation from all six xenobiotics studied had an increased prevalence and odds of developing severe outcomes. Furthermore, patients who did not develop QRS complex prolongation were unlikely to develop a ventricular dysrhythmia, metabolic acidosis, or death. These findings were noted in six xenobiotics that mechanistically can cause QRS complex prolongation through sodium channel or gap junction inhibition., Conclusion: Identification of patients at risk for severe outcomes after overdose can be aided by measuring the QRS complex duration. If prospectively validated, these outcomes have implications on risk stratification, disposition level of care, and appropriateness of treatments.

Background: Presentation of intoxicated patients to hospitals is frequent, varied, and increasing. Medical toxicology expertise could lead to important changes in diagnosis and treatment, especially in patients presenting with altered mental status., Objectives: To describe and analyze clinical scenarios during a 1-year period after the establishment of a medical toxicology consultation service (MTCS)., Methods: Cases of 10 patients with altered mental status at presentation were evaluated. Medical toxicology consultation suggested major and significant changes in diagnosis and management., Results: Of 973 toxicology consultations performed during the study period, bedside consultation was provided for 413 (42%) patients. Of these 413, 88 (21%) presented with some level of altered mental status. We described 10 patients in whom medical toxicology consultation brought about major and significant changes in diagnosis and management., Conclusions: Benefits may be derived from medical toxicology consultations, especially in patients with altered mental status. Medical toxicology specialists are well positioned to provide high value and expedited patient care.

This study is aimed at establishing the outcome of RSTI exposure to acetaminophen based on a decision tree algorithm for the first time. This study used the National Poison Data System (NPDS) to conduct a six-year retrospective cohort analysis, which included 4522 individuals. The patients had a mean age of 26.75 ± 16.3 years (1-89). 3160 patients (70%) were females. Most patients had intentional exposure to acetaminophen. Almost all the patients had acetaminophen exposure via ingestion. In addition, 400 (8.8%) experienced major outcomes, 1500 (33.2%) experienced moderate outcomes, and 2622 (58%) of the patients experienced mild ones. The decision tree model performed well in the training and test groups. In the test group, the accuracy was 0.813, precision of 0.827, recall being 0.798, specificity 0.898, and an F1 score 0.80. In the training group, accuracy was 0.831, recall was 0.825, precision was 0.837, specificity was 0.90, and F1 score was 0.829. Our results showed that serum liver enzymes being present at elevated levels (Alanine aminotransferase (ALT), Aspartate aminotransferase (AST) greater than 1000 U/L followed by ALT, AST between 100 and 1000 U/L), prothrombin time (PT) prolongation, bilirubin increase, renal failure, confusion, age, hypotension, other coagulopathy (such as partial thromboplastin time (PTT) prolongation), acidosis, and electrolyte abnormality were the effective factors in determining the outcomes in these patients. The decision tree algorithm is a dependable method for establishing the prognosis of patients who have been exposed to RSTI acetaminophen and can be used throughout the patients' hospitalization period.

Background: Tarantula envenomations are encountered infrequently but may increase with increased exotic animal ownership. This case report presents the first documented toxicity from a Venezuelan suntiger tarantula (VST), Psalmopoeus irminia, and provides a general framework for approaching patients with tarantula exposures., Case Report: A 35-year-old man presented to an emergency department 4 h after experiencing a bite from his pet VST. He developed erythema, pain, and edema to the bite site on the left thenar eminence that extended proximally. Within 4 h, he developed abdominal pain, nausea, vomiting, throat itching, and tightness. The patient had a blood pressure of 131/105 mm Hg, heart rate of 102 beats/min, 36.6°C, respiratory rate of 20 breaths/min, and SpO 2 of 94%. Laboratory evaluations were within normal limits (other than chronically elevated but improved transaminases). The patient received 0.5 mg epinephrine intramuscularly, 50 mg diphenhydramine IV, 20 mg famotidine IV, 0.4 mg ondansetron IV, and 1 L of normal saline for a suspected anaphylactic reaction. Shortly after epinephrine administration, his gastrointestinal and upper airway symptoms resolved. All symptoms resolved within 1 week. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Little is known about VST toxicity. Therefore, providers should rely on a general framework for approaching patients with tarantula exposures. Morbidity from tarantula exposures is mediated by mechanical injury, venom effects, and hypersensitivity reactions. Typical clinical findings include local pain, pruritis, edema, erythema, and burning. Muscle cramping, ophthalmia nodosa, and hypersensitivity reactions may occur. Treatment is primarily supportive and includes decontamination, cool compresses, analgesia, treatment of anaphylaxis, and ophthalmology evaluation if ocular exposure., Competing Interests: Declaration of Competing Interest The authors have no competing interests to declare that are relevant to the content of this article, (Copyright © 2023 Elsevier Inc. All rights reserved.)

Introduction: An increasing number of jurisdictions have legalized recreational cannabis for adult use. The subsequent availability and marketing of recreational cannabis has led to a parallel increase in rates and severity of pediatric cannabis intoxications. We explored predictors of severe outcomes in pediatric patients who presented to the emergency department with cannabis intoxication., Methods: In this prospective cohort study, we collected data on all pediatric patients (<18 years) who presented with cannabis intoxication from August 2017 through June 2020 to participating sites in the Toxicology Investigators Consortium. In cases that involved polysubstance exposure, patients were included if cannabis was a significant contributing agent. The primary outcome was a composite severe outcome endpoint, defined as an intensive care unit admission or in-hospital death. Covariates included relevant sociodemographic and exposure characteristics., Results: One hundred and thirty-eight pediatric patients (54% males, median age 14.0 years, interquartile range 3.7-16.0) presented to a participating emergency department with cannabis intoxication. Fifty-two patients (38%) were admitted to an intensive care unit, including one patient who died. In the multivariable logistic regression analysis, polysubstance ingestion (adjusted odds ratio = 16.3; 95% confidence interval: 4.6-58.3; P  < 0.001)) and cannabis edibles ingestion (adjusted odds ratio = 5.5; 95% confidence interval: 1.9-15.9; P  = 0.001) were strong independent predictors of severe outcome. In an age-stratified regression analysis, in children older than >10 years, only polysubstance abuse remained an independent predictor for the severe outcome (adjusted odds ratio 37.1; 95% confidence interval: 6.2-221.2; P  < 0.001). As all children 10 years and younger ingested edibles, a dedicated multivariable analysis could not be performed (unadjusted odds ratio 3.3; 95% confidence interval: 1.6-6.7)., Conclusions: Severe outcomes occurred for different reasons and were largely associated with the patient's age. Young children, all of whom were exposed to edibles, were at higher risk of severe outcomes. Teenagers with severe outcomes were frequently involved in polysubstance exposure, while psychosocial factors may have played a role.

Background: This study aimed to compare clinical and laboratory characteristics of supra-therapeutic (RSTI) and acute acetaminophen exposures using a predictive decision tree (DT) algorithm., Methods: We conducted a retrospective cohort study using the National Poison Data System (NPDS). All patients with RSTI acetaminophen exposure (n = 4,522) between January 2012 and December 2017 were included. Additionally, 4,522 randomly selected acute acetaminophen ingestion cases were included. After that, the DT machine learning algorithm was applied to differentiate acute acetaminophen exposure from supratherapeutic exposures., Results: The DT model had accuracy, precision, recall, and F1-scores of 0.75, respectively. Age was the most relevant variable in predicting the type of acetaminophen exposure, whether RSTI or acute. Serum aminotransferase concentrations, abdominal pain, drowsiness/lethargy, and nausea/vomiting were the other most important factors distinguishing between RST and acute acetaminophen exposure., Conclusion: DT models can potentially aid in distinguishing between acute and RSTI of acetaminophen. Further validation is needed to assess the clinical utility of this model., (© 2023. The Author(s).)

Background: Biguanides and sulfonylurea are two classes of anti-diabetic medications that have commonly been prescribed all around the world. Diagnosis of biguanide and sulfonylurea exposures is based on history taking and physical examination; thus, physicians might misdiagnose these two different clinical settings. We aimed to conduct a study to develop a model based on decision tree analysis to help physicians better diagnose these poisoning cases., Methods: The National Poison Data System was used for this six-year retrospective cohort study.The decision tree model, common machine learning models multi layers perceptron, stochastic gradient descent (SGD), Adaboosting classiefier, linear support vector machine and ensembling methods including bagging, voting and stacking methods were used. The confusion matrix, precision, recall, specificity, f1-score, and accuracy were reported to evaluate the model's performance., Results: Of 6183 participants, 3336 patients (54.0%) were identified as biguanides exposures, and the remaining were those with sulfonylureas exposures. The decision tree model showed that the most important clinical findings defining biguanide and sulfonylurea exposures were hypoglycemia, abdominal pain, acidosis, diaphoresis, tremor, vomiting, diarrhea, age, and reasons for exposure. The specificity, precision, recall, f1-score, and accuracy of all models were greater than 86%, 89%, 88%, and 88%, respectively. The lowest values belong to SGD model. The decision tree model has a sensitivity (recall) of 93.3%, specificity of 92.8%, precision of 93.4%, f1&#95;score of 93.3%, and accuracy of 93.3%., Conclusion: Our results indicated that machine learning methods including decision tree and ensembling methods provide a precise prediction model to diagnose biguanides and sulfonylureas exposure., (© 2023. The Author(s).)

Background: Acetaminophen overdose is a leading cause of liver failure, and a leading cause of pediatric poisoning requiring hospital admission. The antidote, N-acetylcysteine (NAC), is traditionally administered as a three-bag intravenous infusion. Despite its efficacy, NAC is associated with high incidence of nonallergic anaphylactoid reactions (NAARs). Adult evidence demonstrates that alternative dosing regimens decrease NAARs and medication errors (MEs)., Objectives: To compare NAARs and MEs associated with two- versus three-bag NAC for acetaminophen overdose in a pediatric population., Methods: This is a retrospective observational cohort study comparing pediatric patients who received three- versus two-bag NAC for acetaminophen toxicity. The primary outcome was incidence of NAARs. Secondary outcomes were rates of MEs and relevant hospital outcomes (length of stay [LOS], intensive care unit (ICU) admission, liver transplant, death)., Results: Two hundred forty-three patients met inclusion criteria (median age of 15 years): 150 (62%) three-bag NAC and 93 (38%) two-bag NAC. There was no difference in overall NAARs ( p = 0.54). Fewer cutaneous NAARs were observed in the two-bag group, three-bag: 15 (10%), two-bag: 2 (2%), p = 0.02. MEs were significantly decreased with the two-bag regimen, three-bag: 59 (39%), two-bag: 21 (23%), p = 0.01. No statistical differences were observed in LOS, ICU admissions, transplant, or death., Conclusion and Relevance: A significant decrease in cutaneous NAARs and MEs was observed in pediatric patients by combining the first two bags of the traditional three-bag NAC regimen. In pediatric populations, a two-bag NAC regimen for acetaminophen overdose may improve medication tolerance and safety.

Introduction: Acute poisoning is a significant global health burden, and the causative agent is often unclear. The primary aim of this pilot study was to develop a deep learning algorithm that predicts the most probable agent a poisoned patient was exposed to from a pre-specified list of drugs., Research Design & Methods: Data were queried from the National Poison Data System (NPDS) from 2014 through 2018 for eight single-agent poisonings (acetaminophen, diphenhydramine, aspirin, calcium channel blockers, sulfonylureas, benzodiazepines, bupropion, and lithium). Two Deep Neural Networks (PyTorch and Keras) designed for multi-class classification tasks were applied., Results: There were 201,031 single-agent poisonings included in the analysis. For distinguishing among selected poisonings, PyTorch model had specificity of 97%, accuracy of 83%, precision of 83%, recall of 83%, and a F1-score of 82%. Keras had specificity of 98%, accuracy of 83%, precision of 84%, recall of 83%, and a F1-score of 83%. The best performance was achieved in the diagnosis of single-agent poisoning in diagnosing poisoning by lithium, sulfonylureas, diphenhydramine, calcium channel blockers, then acetaminophen, in PyTorch (F1-score = 99%, 94%, 85%, 83%, and 82%, respectively) and Keras (F1-score = 99%, 94%, 86%, 82%, and 82%, respectively)., Conclusion: Deep neural networks can potentially help in distinguishing the causative agent of acute poisoning. This study used a small list of drugs, with polysubstance ingestions excluded.Reproducible source code and results can be obtained at https://github.com/ashiskb/npds-workspace.git.

The primary aim of this pilot study was to develop a machine learning algorithm to predict and distinguish eight poisoning agents based on clinical symptoms. Data were used from the National Poison Data System from 2014 to 2018, for patients 0-89 years old with single-agent exposure to eight drugs or drug classes (acetaminophen, aspirin, benzodiazepines, bupropion, calcium channel blockers, diphenhydramine, lithium and sulfonylureas). Four classifier prediction models were applied to the data: logistic regression, LightGBM, XGBoost, and CatBoost. There were 201 031 cases used to develop and test the algorithms. Among the four models, accuracy ranged 77%-80%, with precision and F1 scores of 76%-80% and recall of 77%-78%. Overall specificity was 92% for all models. Accuracy was highest for identifying sulfonylureas, acetaminophen, benzodiazepines and diphenhydramine poisoning. F1 scores were highest for correctly classifying sulfonylureas, acetaminophen and benzodiazepine poisonings. Recall was highest for sulfonylureas, acetaminophen, and benzodiazepines, and lowest for bupropion. Specificity was >99% for models of sulfonylureas, calcium channel blockers, lithium and aspirin. For single-agent poisoning cases among the eight possible exposures, machine learning models based on clinical signs and symptoms moderately predicted the causal agent. CatBoost and LightGBM classifier models had the highest performance of those tested., (© 2022 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society). Published by John Wiley & Sons Ltd.)

Purpose: The objective of this study was to evaluate trends and characteristics in adolescent poison center (PC) exposure calls before and during the COVID-19 pandemic., Methods: A retrospective review of PC calls for adolescents aged 13-17 years from January 1, 2018 through June 30, 2021., Results: During the pandemic, US PCs had a higher proportion of adolescent exposure calls managed in a healthcare facility (71.9% vs. 67.4%) and hospital admissions (27.2% vs. 25.7%) than prior to the pandemic. There was a higher proportion with suicide intent (55.8% vs. 48.8%), moderate/major clinical effects (22.8% vs. 20.1%), and deaths (0.07% vs. 0.05%). Monthly calls significantly increased from 30 calls/month to 204 calls/month (p < .001). The slope of hospital admissions significantly increased (0.19% per month, p < .001) during the pandemic., Discussion: During the COVID-19 pandemic, US PCs observed an increase in adolescent suicidal intent exposure calls with more severe outcomes, hospitalizations, and deaths., (Copyright © 2022 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.)

Background: With diabetes incidence growing globally and metformin still being the first-line for its treatment, metformin's toxicity and overdose have been increasing. Hence, its mortality rate is increasing. For the first time, we aimed to study the efficacy of machine learning algorithms in predicting the outcome of metformin poisoning using two well-known classification methods, including support vector machine (SVM) and decision tree (DT)., Methods: This study is a retrospective cohort study of National Poison Data System (NPDS) data, the largest data repository of poisoning cases in the United States. The SVM and DT algorithms were developed using training and test datasets. We also used precision-recall and ROC curves and Area Under the Curve value (AUC) for model evaluation., Results: Our model showed that acidosis, hypoglycemia, electrolyte abnormality, hypotension, elevated anion gap, elevated creatinine, tachycardia, and renal failure are the most important determinants in terms of outcome prediction of metformin poisoning. The average negative predictive value for the decision tree and SVM models was 92.30 and 93.30. The AUC of the ROC curve of the decision tree for major, minor, and moderate outcomes was 0.92, 0.92, and 0.89, respectively. While this figure of SVM model for major, minor, and moderate outcomes was 0.98, 0.90, and 0.82, respectively., Conclusions: In order to predict the prognosis of metformin poisoning, machine learning algorithms might help clinicians in the management and follow-up of metformin poisoning cases., (© 2022. The Author(s).)

Introduction: While the opioid crisis has claimed the lives of nearly 500,000 in the U.S. over the past two decades, and pediatric cases of opioid intoxications are increasing, only sparse data exist regarding risk factors for severe outcome in children following an opioid intoxication. We explore predictors of severe outcome (i.e., intensive care unit [ICU] admission or in-hospital death) in children who presented to the Emergency Department with an opioid intoxication., Methods: In this prospective cohort study we collected data on all children (0-18 years) who presented with an opioid intoxication to the 50 medical centers in the US and two international centers affiliated with the Toxicology Investigators Consortium (ToxIC) of the American College of Medical Toxicology, from August 2017 through June 2020, and who received a bedside consultation by a medical toxicologist. We collected relevant demographic, clinical, management, disposition, and outcome data, and we conducted a multivariable logistic regression analysis to explore predictors of severe outcome. The primary outcome was a composite severe outcome endpoint, defined as ICU admission or in-hospital death. Covariates included sociodemographic, exposure and clinical characteristics., Results: Of the 165 (87 females, 52.7%) children with an opioid intoxication, 89 (53.9%) were admitted to ICU or died during hospitalization, and 76 did not meet these criteria. Seventy-four (44.8%) children were exposed to opioids prescribed to family members. Fentanyl exposure (adjusted OR [aOR] = 3.6, 95% CI: 1.0-11.6; p  = 0.03) and age ≥10 years (aOR = 2.5, 95% CI: 1.2-4.8; p  = 0.01) were independent predictors of severe outcome., Conclusions: Children with an opioid toxicity that have been exposed to fentanyl and those aged ≥10 years had 3.6 and 2.5 higher odds of ICU admission or death, respectively, than those without these characteristics. Prevention efforts should target these risk factors to mitigate poor outcomes in children with an opioid intoxication.

Objectives: Biguanides and sulfonylureas are anti-hyperglycemic drugs commonly used in the United States. Poisoning with these drugs may lead to serious consequences. The diagnosis of biguanide and sulfonylurea poisoning is based on history, clinical manifestations, and laboratory studies., Methods: This study is a six-year retrospective cohort analysis based on the National Poison Data System. Clinical effects of 6183 biguanide and sulfonylurea exposures were identified using binary logistic regression., Results: The mean age of patients with biguanide and sulfonylurea exposure was 39.27 ± 28.91 and 28.91 ± 30.41 years, respectively. Sulfonylurea exposure is most commonly seen via unintentional exposure, while biguanide exposure frequently occurs as a result of intentional ingestion. Minor and moderate outcomes commonly developed following biguanide and sulfonylurea exposure, respectively. Sulfonylurea exposure was less likely to develop clinical effects abdominal pain, metabolic acidosis, diarrhea, nausea, vomiting, and elevated creatinine than patients ingesting biguanides. However, sulfonylurea exposure was more likely to cause dizziness or vertigo, tremor, drowsiness or lethargy, agitation, diaphoresis, and hypoglycemia., Conclusions: Our study is the first to use a wide range of national data to describe the clinical characteristics that differentiate the toxicologic exposure to biguanides and sulfonylureas. Sulfonylurea exposure is commonly seen via unintentional exposure, while metformin exposure is frequently seen via intentional exposure. Sulfonylurea toxicity is more likely to cause agitation, dizziness or vertigo, tremor, diaphoresis, and hypoglycemia, while metformin exposure induces abdominal pain, acidosis, diarrhea, nausea, vomiting, and elevated creatinine., Competing Interests: Declaration of Competing Interest Authors declare no conflict of interest., (Copyright © 2022. Published by Elsevier Inc.)

Background: Antivenom has been used successfully to treat systemic and progressive, local manifestations of envenomations inflicted by Echis coloratus , the second most common cause of snake envenomation in Israel. There is a paucity of published data regarding the use of monovalent (equine) immunoglobulin G antivenom in children. This study describes outcomes from the regimen used in two large, tertiary care pediatric centers., Methods: A retrospective chart review of children admitted with definite or probable signs of Echis coloratus envenomation to Sourasky (Tel Aviv) and Soroka (Be'er Sheva) Medical Centers from January 1st 2008-to June 1st 2019. Extracted data included age, location of bite, time to hospital arrival, laboratory test results, complications, time to antivenom administration if indicated, adverse effects of the antivenom, and outcomes. Indications for antivenom were: diagnosis of Echis coloratus as the etiology of envenomation, local and systemic signs e.g. skin puncture wounds, swelling of the involved limb, local hematoma, and abnormal coagulation blood test results., Results: During the study period, 11 children were treated with intravenous Echis coloratus antivenom. Median age was 9 years and 10 of 11 patients were male. Two patients underwent fasciotomy; in one, compartment syndrome was diagnosed by pressure measurement, and in the second, clinically. One patient developed mild urticaria 30 min after initiation of the antivenom; the treatment was stopped and then restarted at a slower rate after he was treated with hydrocortisone and diphenhydramine. No further adverse reactions were observed., Conclusions: In children, Echis coloratus antivenom appeared to be effective and safe for the treatment of systemic and progressive local manifestations of envenomation by Echis coloratus .

Acetaminophen is one of the most commonly used analgesic drugs in the United States. However, the outcomes of acute acetaminophen overdose might be very serious in some cases. Therefore, prediction of the outcomes of acute acetaminophen exposure is crucial. This study is a 6-year retrospective cohort study using National Poison Data System (NPDS) data. A decision tree algorithm was used to determine the risk predictors of acetaminophen exposure. The decision tree model had an accuracy of 0.839, an accuracy of 0.836, a recall of 0.72, a specificity of 0.86 and an F1&#95;score of 0.76 for the test group and an accuracy of 0.848, a recall of 0.85, a recall of 0.74, a specificity of 0.87 and an F1&#95;score of 0.78 for the training group. Our results showed that elevated serum levels of liver enzymes, other liver function test abnormality, anorexia, acidosis, electrolyte abnormality, increased bilirubin, coagulopathy, abdominal pain, coma, increased anion gap, tachycardia and hypotension were the most important factors in determining the outcome of acute acetaminophen exposure. Therefore, the decision tree model is a reliable approach in determining the prognosis of acetaminophen exposure cases and can be used in an emergency room or during hospitalization., (© 2021 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society). Published by John Wiley & Sons Ltd.)

Acetaminophen is a frequently used over-the-counter or prescribed medication in the United States. Exposure to acetaminophen can lead to acute liver cytolysis, acute liver failure, acute kidney injury, encephalopathy, and coagulopathy. This retrospective cohort study (1/1/2012 to 12/31/2017) investigated the clinical outcomes of intentional and unintentional acetaminophen exposure using the National Poison Data System data. The frequency of outcomes, chronicity, gender, route of exposure, the reasons for exposure, and treatments as described. Binary logistic regression was used to estimate the prognostic factors and odds ratios (OR) with 95% confidence intervals (CI) for outcomes. This study included 39,022 patients with acetaminophen exposure. Our study demonstrated that the likelihood of developing severe outcomes increased by aging (OR = 1.12, 95% CI: 1.08-1.015) and was lower in females (OR = 0.88, 95% CI: 0.78-0.99). Drowsiness/lethargy (OR = 1.48, 95% CI: 1.22-1.82), agitation (OR = 1.66, 95% CI: 1.11-2.50), coma (OR = 23.95, 95% CI: 17.05-33.64), bradycardia (OR = 2.29, 95% CI: 1.22-4.32), rhabdomyolysis (OR = 8.84, 95% CI: 3.71-21.03), hypothermia (OR = 4.1, 95% CI: 1.77-9.51), and hyperthermia 2.10 (OR = 2.10, 95% CI: 1.04-4.22) were likely associated with major outcomes or death. Treatments included intravenous N-acetylcysteine (61%), oral N-acetylcysteine (10%), vasopressor (1%), hemodialysis (0.7%), fomepizole (0.1%), hemoperfusion (0.03%), and liver transplant (0.1%). In conclusion, it is important to consider clinical presentations of patients with acetaminophen toxicity that result in major outcomes and mortality to treat them effectively.

Background: Toxic alcohol exposures are an ongoing concern in the United States. In the US, few studies characterize the local epidemiology of toxic alcohols over time., Objectives: The objective was to examine the incidence of toxic alcohol ingestions and changes in management over time., Methods: This retrospective cohort study evaluates toxic alcohol ingestion phone calls to a regional poison center in the United States covering four states. Data were queried for this poison center from the National Poison Data System (NPDS) using generic codes for each toxic alcohol. Inclusion criteria were ingestion of toxic alcohol, age ≥ 13 years, from January 1, 2000 to Dec 31, 2017. Exclusion criteria were unrelated effects coded in the medical outcome, duplicate data, or incomplete demographic data., Results: Of 926 subjects (adults and teenagers), 71.5% were male, and the mean age was 34.5 years. Toxic alcohol ingestion was more common in individuals younger than 40 years, with a significant relationship between age and intentional abuse or misuse (p = 0.001). There was also a significant relationship between age and reason for ingestion, with younger patients more likely to be suicidal (p < 0.001). Ethyleneglycol was the most common toxic alcohol. There was no change in the incidence of toxic alcohol ingestions over the study period. The mortality rate was 1.7%, and 31.2%of patients were hospitalized in a critical care unit. Major effects and death were more common in younger patients (p < 0.001). There was a significant difference in medical outcomes based on the type of toxic alcohol(p = 0.03). Fomepizole was the most common treatment. A Poisson regression model found no change in fomepizole use during the study period (p = 0.1). Ethanol administration over the study period increased (p = 0.02), while hemodialysis decreased (p = 0.02)., Conclusion: Data obtained from a single regional United States poison center showed low mortality related to toxic alcohol ingestions. The most prevalent toxic alcohol was Ethylene glycol. In all cases, toxic alcohol ingestion was higher in the 20-29-year-old age group. Reasons for ingestion, in most cases, were suicidal. Fomepizole was the most common treatment, ethanol administration as an antidote is rising, and hemodialysis utilization is decreasing. Data may not be nationally representative., (© 2021. Springer Nature Switzerland AG.)

Background: Methadone is well known for its long duration of action and propensity for mortality after an overdose. The present research was aimed at evaluating the clinical manifestations and time trends of methadone exposure in patients in US hospitals., Methods: We queried the American College of Medical Toxicology's Toxicology Investigators Consortium case registry for all cases of methadone exposure between January 1, 2010, and December 31, 2017. The collected information included demographic features, clinical presentations, therapeutic interventions, poisoning type (acute, chronic, or acute on chronic), and the reason(s) for exposure. Descriptive data and relative frequencies were used to investigate the participants' characteristics. Our data analysis was performed using SPSS version 19 and Prism software. The trends and clinical manifestations of methadone poisoning over the time period of the study were specifically investigated., Results: Nine hundred and seventy-three patients who met our inclusion criteria, with a mean age of 41.9 ± 16.6 years (range: 11 months-78 years) were analyzed. Five hundred eighty-two (60.2%) were male. The highest rate of methadone poisoning was observed in 2013. There was an increasing rate of methadone exposures in 2010-2013, followed by a decline in 2014-2017. The most common clinical manifestations in methadone-poisoned patients were coma (48.6%) and respiratory depression (33.6%). The in-hospital mortality rate of methadone poisoning was 1.4%., Conclusion: ToxIC Registry data showed that inpatient methadone exposures enhanced from 2010 to 2013, after which a reduction occurred in the years 2014 to 2017.

Introduction: Studies comprehensively summarizing the impact of tramadol use on glucose homeostasis are very sparse. Thus, the present study was performed to collect and summarize the latest information about this issue in a systematic way., Areas Covered: An exhaustive literature search was carried out using relevant keywords. Web of Sciences, PubMed, Scopus, and Google scholar were interrogated until 30 June 2019. Case-control, cohort, cross-sectional, clinical trial, case report, and animal studies that focused on the objective of the study were retrieved. This review summarizes the results of 761 papers on glycemic changes due to tramadol exposure. Thirty-six publications reported hypoglycemia and 17 hyperglycemia during tramadol use. Twenty-two studies either reported normal blood glucose concentrations, or did not observe any difference in the blood glucose levels following tramadol use. Finally, hypoglycemia was reported in diabetic individuals exposed to tramadol in 12 studies., Expert Opinion: The data suggest that primarily hypoglycemia but some degree of hyperglycemia has been reported with tramadol use. Importantly, all studies on tramadol use in diabetes reported hypoglycemia. Tramadol-induced hypoglycemia may be severe in some cases. The risk of alterations in glucose homeostasis accompanying tramadol exposure indicates time importance of careful blood glucose monitoring during tramadol use.

Introduction: Scientific conferences are useful in disseminating medical research and advancing the medical and scientific fields. An important measure of the success of such conferences is the proportion of research that is published in peer-reviewed journals. The conversion rates for toxicology abstracts to full-text publications at previous North American toxicology meetings were low. No study has assessed the publication rate from the 2013 North American Congress of Clinical Toxicology (NACCT) conference. Methods: We reviewed 316 abstracts presented at the 2013 NACCT Conference. We searched the PubMed, EMBASE, and Medline databases using the authors' names and keywords, through September 2019. We then identified and excluded cases and case reports to reanalyze the data. Results: Thirty-three of 316 abstracts (10.4%) subsequently appeared in 17 different peer-reviewed journals, led by Clinical Toxicology (13 out of 33, 3%). Leading countries of origin for abstract submission were the USA (285), Canada (9), and the UK (8). Excluding case reports, 25 out of 207 abstracts (12.0%) achieved publication in peer-reviewed journals. Conclusions: Fewer than one in eight abstracts reached publication within six years of the 2013 NACCT meeting, even after accounting for and excluding case reports. This rate is lower than in other specialty medical societies.

Introduction: The timely and formal publication of material presented at national and international meetings is critical to the dissemination of new information to the medical community. The conversion rates for toxicology abstracts to full-text publications at previous North American toxicology meetings were low. No study has assessed the publication rate from the European Association of Poisons Centers and Clinical Toxicologists (EAPCCT)., Methods: We reviewed 269 abstracts presented at the 2013 EAPCCTcongress. We searched the PubMed, EMBASE, and Medline databases using the first, second, and last authors' names and keywords, through November 2018., Results: Forty-seven of 269 abstracts (17%) subsequently appeared in 29 different peer-reviewed journals, led by Clinical Toxicology (13 out of 47, 28%). Leading countries of origin were the USA (8), UK (7) and Italy (6). The proportions of publications from native English-speaking and non-native English-speaking countries were similarly low (16% vs. 19%)., Conclusions: Fewer than one in six abstracts reached publication within five years of the 2013 EAPCCT meeting. This rate is lower than in other specialty medical societies.

Deposition of Amyloid-beta (Aβ) peptide in the brain is the leading source of the onset and progression of Alzheimer's Disease (AD). Recent studies have suggested that anti-amyloidogenic agents may be a suitable therapeutic strategy for AD. The current review was proposed to address the beneficial effects of cannabis-based drugs for the treatment of AD, focusing primarily on Aβ modifications. Keywords related to AD, Aβ, and cannabis-based on MeSH were identified and were searched in PubMed, Google Scholar, Scopus, Ovid-Medline, and Web of Science from inception until 15 March 2020. The full text of identified papers was obtained and assessed based on exclusion and inclusion criteria. The review is based on articles that have focused on AD and the amyloidogenic pathway. A total of 17 studies were identified based on the inclusion criteria; however, nine studies qualified for this systematic review. The maximum and minimum cannabis dosages, mostly CBD and THC in animal studies, were 0.75 and 50 mg/kg, respectively. Cannabis (CBD and THC) was injected for 10 to 21 days. The findings of the 9 articles indicated that cannabis-based drugs might modulate Aβ modifications in several AD models. Our findings establish that cannabis-based drugs inhibited the progression of AD by modulating Aβ modifications., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

In the 1920s, guanidine, the active component of Galega officinalis , was shown to lower glucose levels and used to synthesize several antidiabetic compounds. Metformin (1,1 dimethylbiguanide) is the most well-known and currently the only marketed biguanide in the United States, United Kingdom, Canada, and Australia for the treatment of non-insulin-dependent diabetes mellitus. Although phenformin was removed from the US market in the 1970s, it is still available around the world and can be found in unregulated herbal supplements. Adverse events associated with therapeutic use of biguanides include gastrointestinal upset, vitamin B 12 deficiency, and hemolytic anemia. Although the incidence is low, metformin toxicity can lead to hyperlactatemia and metabolic acidosis. Since metformin is predominantly eliminated from the body by the kidneys, toxicity can occur when metformin accumulates due to poor clearance from renal insufficiency or in the overdose setting. The dominant source of metabolic acidosis associated with hyperlactatemia in metformin toxicity is the rapid cytosolic adenosine triphosphate (ATP) turnover when complex I is inhibited and oxidative phosphorylation cannot adequately recycle the vast quantity of H+ from ATP hydrolysis. Although metabolic acidosis and hyperlactatemia are markers of metformin toxicity, the degree of hyperlactatemia and severity of acidemia have not been shown to be of prognostic value. Regardless of the etiology of toxicity, treatment should include supportive care and consideration for adjunct therapies such as gastrointestinal decontamination, glucose and insulin, alkalinization, extracorporeal techniques to reduce metformin body burden, and metabolic rescue.

Background: Echis coloratus (Burton Carpet viper), a highly venomous snake belonging to the family Viperidae, is responsible for a large proportion of the venomous snakebites in Israel and Palestinian Authority. Procoagulant enzymes are present in Echis coloratus venom and significant coagulopathy is typical after envenomation. Here we report a case of envenomation by Echis coloratus that involved severe coagulopathy as the main systemic manifestation with severe bleeding after fasciotomy., Case Details: A 3-year-old boy was admitted to our pediatric critical care unit after a snakebite to his left hand, 2-3 hours post-bite. Based on the possibility of compartment syndrome, a fasciotomy was performed before administration of antivenom. At our hospital, he had altered prothrombin time (PT) and activated partial thromboplastin time (aPTT), with low fibrinogen levels. The snake responsible for the bite was later identified as a 38-cm long Echis coloratus. Five vials of Israeli monovalent antivenom were subsequently administered with step-wise improvement in hematological abnormalities. Other treatments included massive blood products transfusion (packed RBC, FFP, cryoprecipitate, PLT), inotropes and ventilatory support. After a prolonged hospital course the patient had a positive outcome., (Copyright © 2019. Published by Elsevier Ltd.)

Background: Although rare, symptomatic hyperammonemia is sometimes associated with valproic acid (VPA), especially in children. L-carnitine (levocarnitine), sometimes classified as an essential amino acid, is vital to mitochondrial utilization of fatty acids and can be helpful in treating this condition. The data supporting this, however, are limited., Study Question: The aim of the study was to illustrate the role of L-carnitine in the treatment of patients with VPA-induced hyperammonemic encephalopathy (VPE) at 2 different institutions., Methods: Medical records of affected patients were reviewed; data collected included exposure history, clinical manifestations, physical examination, and laboratory values., Results: There were 13 cases of VPE; 12 were associated with therapeutic dosing and 1 with an overdose. The maximum ammonia concentration was 557 μmol/L, and blood concentrations of VPA ranged from 68 to 600 μg/mL (therapeutic range 50-100 μg/mL). In all cases, liver function tests were normal or only mildly increased. In this study, 12 patients received a daily dose of L-carnitine 100 mg/kg, and 1 received 200 mg/kg (intravenous infusion over 30 minutes) divided every 8 hours until clinical improvement. All patients made a full recovery. None developed adverse effects or reactions, and no cases of toxicity were reported., Conclusion: Our series suggests that intravenous L-carnitine, at a dose of 100 mg·kg·d in 3 divided doses each over 30 minutes until clinical improvement occurs, is a safe and effective treatment in the management of VPE in children.