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Objectives: Drug overdose deaths in Connecticut increasingly involve a growing number of fentanyl analogs and other novel nonfentanyl synthetic opioids (ie, novel synthetics). Current postmortem toxicology testing methods often lack the sophistication needed to detect these compounds. We examined how improved toxicology testing of fatal drug overdoses can determine the prevalence and rapidly evolving trends of novel synthetics., Methods: From 2016 to June 2019, the Connecticut Office of the Chief Medical Examiner increased its scope of toxicology testing of suspected drug overdose deaths in Connecticut from basic to enhanced toxicology testing to detect novel synthetics. The toxicology laboratory also expanded its testing panels during this time. We analyzed toxicology results to identify and quantify the involvement of novel synthetics over time., Results: From 2016 to June 2019, 3204 drug overdose deaths received enhanced toxicology testing; novel synthetics were detected in 174 (5.4%) instances. Ten different novel synthetics were detected with 205 total occurrences. Of 174 overdose deaths with a novel synthetic detected, most had 1 (n = 146, 83.9%) or 2 (n = 26, 14.9%) novel synthetics detected, with a maximum of 4 novel synthetics detected. Para -fluorobutyrylfentanyl/FIBF, furanylfentanyl, and U-47700 were most identified overall, but specific novel synthetics came in and out of prominence during the study period, and the variety of novel synthetics detected changed from year to year., Conclusions: Enhanced toxicology testing for drug overdose deaths is effective in detecting novel synthetics that are not identified through basic toxicology testing. Identifying emerging novel synthetics allows for a timely and focused response to potential drug outbreaks and illustrates the changing drug market.

The Toxicology Investigators Consortium (ToxIC) Registry was established by the American College of Medical Toxicology in 2010. The registry collects data from participating sites with the agreement that all bedside and telehealth medical toxicology consultation will be entered. This eleventh annual report summarizes the Registry's 2020 data and activity with its additional 6668 cases. Cases were identified for inclusion in this report by a query of the ToxIC database for any case entered from January 1 to December 31, 2020. Detailed data was collected from these cases and aggregated to provide information which included demographics, reason for medical toxicology evaluation, agent and agent class, clinical signs and symptoms, treatments and antidotes administered, mortality, and whether life support was withdrawn. Gender distribution included 50.6% cases in females, 48.4% in males, and 1.0% identifying as transgender. Non-opioid analgesics were the most commonly reported agent class, followed by opioid and antidepressant classes. Acetaminophen was once again the most common agent reported. There were 80 fatalities, comprising 1.2% of all registry cases. Major trends in demographics and exposure characteristics remained similar to past years' reports. Sub-analyses were conducted to describe race and ethnicity demographics and exposures in the registry, telemedicine encounters, and cases related to the COVID-19 pandemic., (© 2021. American College of Medical Toxicology.)

It is tempting to base (eco-)toxicological assay evaluation solely on statistical significance tests. The approach is stringent, objective and facilitates binary decisions. However, tests according to null hypothesis statistical testing (NHST) are thought experiments that rely heavily on assumptions. The generic and unreflected application of statistical tests has been called "mindless" by Gigerenzer. While statistical tests have an appropriate application domain, the present work investigates how unreflected testing may affect toxicological assessments. Dunnett multiple-comparison and Williams trend testing and their compatibility intervals are compared with dose-response-modelling in case studies, where data do not follow textbook behavior, nor behave as expected from a toxicological point of view. In such cases, toxicological assessments based only on p-values may be biased and biological evaluations based on plausibility may be prioritized. If confidence in a negative assay outcome cannot be established, further data may be needed for a robust toxicological assessment., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

<b>Background and Objective:</b> The accumulation of heavy metals such as cadmium and lead in mussels is very high compared to that in another marine biota. The mussels are sessile, widely distributed filter-feeding organisms, with the ability to sequester many lipophilic organic compounds, absorb anything in their surroundings. The very low mobility allows heavy metal bioaccumulation to occur and cannot avoid pollutants, which increase over time. This bioaccumulation can be toxic to mussels. This study aimed to evaluate the effect of different toxic chemicals and histological changes in green mussels. <b>Materials and Methods:</b> All archive gonad sample of green mussels in 2015 was fixed in paraformaldehyde 4% solution and were sliced by a rotary microtome at 8 μm thickness and finally, the slides were stained with a solution of hematoxylin-eosin. <b>Results:</b> The obtained results demonstrated that developmental disorders in the testes are characterized by the arrangement of follicle cells in a relatively less dense state and some follicles are not fully filled with spermatozoa. It means that the male gonad samples of green mussels in the port of Muara Angke undergoing toxicity and the process of gonad developmental was disrupted. <b>Conclusion:</b> The effects of toxicity of the male gonad of green mussels were more sensitive and were more susceptible than the female gonad of the green mussels.

Recently it was recommended to avoid significance tests, in particular dichotomization into significant/non-significant on the basis of a p-value and a fixed 5% significance level (i.e. false positive rate). As an alternative, the interpretation of a suitable effect size and its compatibility interval is recommended, i.e. confidence intervals whose compatibility with the data, the assumptions, and the models is shown. This concept is used for the evaluation of assays in regulatory toxicology with special emphasis on the proof of hazard and proof of safety. Three case studies for multiple endpoints, multiple models and the consideration of historical controls illustrate the applicability of this concept. The corresponding software code for the open-source R project for statistical computing (www.r-project.org) is provided., (Copyright © 2020. Published by Elsevier Inc.)

In the field of nano- and microscale science and technology, Small has become one of the worldwide leading journals since its initiation 15 years ago. Among all the topics covered in Small, "nanosafety" has received growing interest over the years, which accounts for a large proportion of the total publications of Small. Herein, inspired by its coming Special Issue "Rethinking Nanosafety," a general bibliometric overview of the nanosafety studies that have been published in Small is presented. Using the data derived from the Web of Science Core Collection, the annual publication growth, most influential countries/institutions as well as the visualized collaborations between different countries and institutions based on CiteSpace software are presented. A special emphasis on the impact of the previous Special Issue from Small that is related to nanosafety research is given and the research trend from the most highly cited papers during last 15 years is analyzed. Lastly, future research directions are also proposed., (© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Introduction: This study aims to describe the epidemiology of toxicological exposures reported to a telephonic medical toxicology service at a tertiary care center in Lebanon during a 46-months period. Methods: This study is a secondary analysis of a database for a telephonic medical toxicology service at a tertiary care center in Lebanon. Clinical information from all pediatric and adult patients, presenting with intentional or unintentional toxicological exposure, was entered into the database by the medical toxicology team. Results: Four hundred and seventy-seven exposures were recorded from 1 March 2015 to 31 December 2018. Female patients were involved in 60.2% of cases. Children less than 5 years old constituted 23.5% of cases and adults aged 20-49 constituted 48.6%. Up to 51.6% of cases were intentional, with 37.7% resulting from suicidal attempts. The majority of patients displayed no effects (33.1%) or minor effects (39.2%). Almost half of patients were treated and discharged from the Emergency Department (ED) without further hospitalization, and another 18.9% of patients left the ED against medical advice. The most common pharmaceutical agents involved were sedative/hypnotics/antipsychotics (14.7%), analgesics (12.6%) and antidepressants (11.3%). The most common non-pharmaceutical agents involved were household cleaning substances (8.0%), pesticides (5.2%) and bites and envenomations (3.8%). Conclusions: The results of this study suggest that sedative/hypnotics/antipsychotics, analgesics, antidepressants and household cleaning substances are the most common agents involved. Adult women and children ≤5 years old constitute a large portion of patients with toxicological exposures. Prevention strategies and policies should be implemented to mitigate these hazards.

In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical advances and the ever growing amount of available toxicity data enabled machine learning, especially neural networks, to impact the field of predictive toxicology. In this study, cytotoxicity prediction, one of the earliest handles in drug discovery, is investigated using a deep learning approach trained on a highly consistent in-house data set of over 34,000 compounds with a share of less than 5% of cytotoxic molecules. The model reached a balanced accuracy of over 70%, similar to previously reported studies using Random Forest. Albeit yielding good results, neural networks are often described as a black box lacking deeper mechanistic understanding of the underlying model. To overcome this absence of interpretability, a Deep Taylor Decomposition method is investigated to identify substructures that may be responsible for the cytotoxic effects, the so-called toxicophores. Furthermore, this study introduces cytotoxicity maps which provide a visual structural interpretation of the relevance of these substructures. Using this approach could be helpful in drug development to predict the potential toxicity of a compound as well as to generate new insights into the toxic mechanism. Moreover, it could also help to de-risk and optimize compounds.

Risk assessment for mixtures of chemicals requires to investigate the magnitude of their potential adverse effects on living organisms. This is usually done by assessing how experimental toxicological mixture data depart from the model of Loewe additivity. Several recent scientific studies propose to perform this task using an ad hoc method known as model deviation ratio (MDR) method. Moreover, the first official European regulatory document for the study of combined exposures explicitly recommends the use of the MDR method (EFSA Scientific Committee et al. Guidance on harmonised methodologies for human health, animal health and ecological risk assessment of combined exposure to multiple chemicals. EFSA Journal, 2019). We show here that the MDR method is not rooted in statistical principles and can lead to erroneous claims. We show however that the distribution of the MDR can be evaluated by simulations and show how this allows us to devise and carry out a bona fide statistical test. The proposed method accounts for uncertainty in the estimation of ED/EC50 and does not require a minimum sample size. The computer code developped in this study is made available as an R package called MDR., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Serotonin toxicity is a common cause of drug-induced altered mental status. However, data on the causes of serotonin toxicity, symptomatology, complications, and rate of antidotal treatment are limited., Methods: This study evaluated cases of serotonin toxicity in the ToxIC registry, an international database of prospectively collected cases seen by medical toxicologists. Serotonin toxicity was diagnosed by bedside evaluation of medical toxicology specialists and explicit criteria were not used. The database was searched for "serotonin syndrome" between January 1, 2010, and December 31, 2016., Results: There were 1010 cases included. Females made up 608 (60%) cases. Ages are as follows: younger than 2 years (3, 0.3%), 2 to 6 years (8, 0.8%), 7 to 12 years (9, 0.9%), 13 to 18 years (276, 27.3%), 19 to 65 years (675, 67%), older than 66 years (33, 3.4%), unknown (6, 0.6%). Reasons for encounter: intentional (768, 76%), adverse drug event/reaction (127, 12.6%), unintentional (66, 6%), and unknown (55, 5.4%). Signs/symptoms: hyperreflexia/clonus/myoclonus (601, 59.5%), agitation (337, 33.4%), tachycardia (256, 25.3%), rigidity (140, 13.9%), seizures (139, 13.7%), and hyperthermia (29, 2.9%)., Complications: rhabdomyolysis (97, 9.7%), dysrhythmias (8, 0.8%), and death (1, 0.1%)., Treatments: benzodiazepines 67% (677/1010), cyproheptadine 15.1% (153/1010). There were 192 different xenobiotics reported with 2046 total exposures. Antidepressants were most common (915, 44.7%) with bupropion the most frequent overall (147, 7.2%). Common non-antidepressants were dextromethorphan (95, 6.9%), lamotrigine (64, 3.1%), and tramadol (60, 2.9%)., Discussion: Serotonin toxicity most often occurred in adult patients with intentional overdose. Antidepressants were the most common agents of toxicity. Interestingly, bupropion, a norepinephrine/dopamine reuptake inhibitor, was the most frequently mentioned xenobiotic. Though often cited as a potential antidote, only 15% of patients received cyproheptadine. Severe toxicity was rare. A single death was reported.

Objective: We aimed to investigate the impact of the toxicological results found in cases of sudden death (SD) and to correlate the clinical, autopsy and genetic findings with the toxicology results., Materials and Methods: Consecutive SD in people aged between 16 and 50 years with medico-legal autopsies and toxicology studies were included over a 3-year period. The comparison between the toxicological data and demographic characteristics, clinical circumstances, autopsy, and genetic results were taken into account., Results: 101 cases were finally included. They were predominately males (84%) and the mean age was 39.8 years. 52 (51.5%) cases had positive toxicological findings and in 25 cases (24.8%), toxic compounds were considered the first cause of death. Ethanol was the most frequently identified agent (69%), following by licit drugs (56%) and drugs of abuse (39%). Cases with positive toxicology were younger than those with negative results (37.9±9.1 vs. 41.9±7.8; p=0.02). Patients with more than 3 comorbidities showed an association with positive toxicological results (n=14 vs. n=3; p=0.017). The genetic study was performed in 70 (69.3%) SD cases. We identified pathogenic or likely pathogenic variants in 17.1% cases and uncertain significance variants in 42.8% cases. 58% of these variants were probably related to the cause of death., Conclusions: A large fraction of SD victims had positive toxicological findings and a quarter of deaths were directly caused by toxic substances. The identification of the factors that trigger SD provides a good approach to contribute in avoiding future episodes.

Introduction: Adverse drug events/reactions (ADE/ADRs) cost more than $30 billion annually and are among the leading causes of death in the USA. Little is known about patients treated at the bedside for ADE/ADR by medical toxicologists., Methods: We conducted a retrospective study of ADE/ADR cases reported to the Toxicology Investigators Consortium (ToxIC) registry between January 1, 2010, and December 31, 2016. Clinical and demographic data were collected including age, sex, circumstances surrounding exposure, suspected offending substance, clinical manifestations, treatment, disposition, and outcome., Results: Among 51,440 ToxIC cases during this time period, 673 ADE/ADR cases were reported (337 females). By age, ADE/ADRs were seen most commonly among adults age 19-65 years (442/673, 65.7% of ADE/ADR) and older adults age 65-89 years (134/673, 19.9% of ADE/ADR). 222/673 (33%) of consults for ADE/ADR were seen in the emergency department (ED); 181/673 (26.9%) were seen in the hospital ward; and 160/673 (23.8%) were seen in the intensive care unit (ICU). The most commonly reported sign for ADE/ADR was tachycardia: 51/673 (7.6%), followed by bradycardia: 49/673 (7.3%). Most commonly reported agents associated with ADE/ADR were as follows: 97/673 (14.4%) due to cardiovascular medications; 76/673 (11.3%) due to antipsychotic medications; and 61/673 (9.1%) due to antidepressants. 429/673 (63.7%) of ADE/ADR were reported as due to a single agent, and 212/673 (31.5%) were reported as due to multiple agents., Conclusions: 4.2% of cases managed at the bedside by a consulting toxicologist and reported to the ToxIC registry between 2010 and 2016 had ADE/ADR as the reason for consultation. Agents most commonly involved in ADE/ADRs included cardiovascular medications, antipsychotic medications, and antidepressants.

The Toxicology Investigators Consortium (ToxIC) Registry was established by the American College of Medical Toxicology (ACMT) in 2010. The Registry collects data from participating sites with the agreement that all bedside medical toxicology consultation will be entered. The objective of this ninth annual report is to summarize the Registry's 2018 data and activity with its additional 7043 cases. Cases were identified for inclusion in this report by a query of the ToxIC database for any case entered from 1 January to 31 December 2018. Detailed data was collected from these cases and aggregated to provide information which included demographics, reason for medical toxicology evaluation, agent and agent class, clinical signs and symptoms, treatments and antidotes administered, mortality, and whether life support was withdrawn. A total of 51.5% of cases were female, 48% were male, and 0.6% transgender. Non-opioid analgesics were the most commonly reported agent class, followed by antidepressants and opioids. Acetaminophen was once again the most common agent reported. There were 106 fatalities, comprising 1.5% of all registry cases. Major trends in demographics and exposure characteristics remained similar to past years' reports. Sub-analyses were conducted to describe exposures in elderly patients, addiction consultation practices, and risk factors for bupropion-induced seizures. The launch of the ToxIC Qualified Clinical Data Registry (TQCDR) is also described.

Purpose: Classification of overdose deaths is often geographically and demographically inconsistent. Incomplete surveillance records may distort estimates of drug overdose rates across time and place. We examined incomplete toxicology reporting among drug overdose decedents by demographic and geographic characteristics, measuring changes in missingness rates and their associations with decedent characteristics over time., Methods: We estimated the percentage of overdose deaths reported in the National Vital Statistics System with missing toxicology results from 2010 to 2016, overall and by decedents' demographic and geographic characteristics. Multilevel logistic regression models evaluated prevalence of missingness by decedent characteristics, accounting for geographic clustering., Results: Overall, 20.3% of death certificates did not indicate a specific drug, declining from 24.4% in 2010 to 14.6% in 2016. Deaths were less likely to have missing information if they occurred in counties with medical examiners versus coroners. Female decedents were more likely to have missing information than males, as were non-Hispanic whites compared with Hispanics and non-Hispanic blacks., Conclusions: The percentage of deaths with missing toxicology information declined over time, but demographic and geographic differences in missingness persist. This yields detection biases that skew temporal trends and understanding of groups impacted by the opioid epidemic., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background and Purpose: Clinical toxicology is a blend of science, research, and patient management practices involving human poisonings from exposure to natural and synthetic toxins. The objective of this study was to describe the components of an elective advanced pharmacy practice experience (APPE) in clinical toxicology at California Poison Control System (CPCS)., Educational Activity and Setting: The APPE requirements included a mix of active participation in case management and supplemental educational exercises, case presentations and consultations, and a structured self-study component consisting of readings and on-line modules. In addition, there were two active learning activities, high acuity poisoning simulation scenarios utilizing a high-fidelity mannequin, and an antidote tasting session., Findings: From April 2012 to October 2017, 82 student pharmacists completed this APPE. Pharmacy students completed 85 pre-simulation surveys and 80 post-simulation surveys. Survey results showed an increase in pharmacy student beliefs that a clinical pharmacist should be involved in the differential diagnosis and management of patients (60% pre-simulation vs. 78.8% post-simulation, p = 0.009). APPE pharmacy students completed an evaluation of the preceptors(s), site, and learning experience. The average score for all areas on the preceptor and site evaluations was >4.5 on a 5-point Likert scale. Qualitative data themes included student satisfaction with opportunities, feedback, and the interprofessional and collaborative environment., Summary: An APPE in the CPCS was successfully designed and implemented. The APPE provides an interprofessional collaborative learning environment that allows student pharmacists to understand the unique role of the pharmacist in this setting., (Copyright © 2019 Elsevier Inc. All rights reserved.)

As the community of toxicological researchers, risk assessors, and risk managers adopt the adverse outcome pathway (AOP) framework for organizing toxicological knowledge, the number and diversity of AOPs in the online AOP knowledgebase (KB) continues to grow. To track and investigate this growth, AOPs in the AOP-KB were assembled into a single network. Summary measures on the current state of the AOP-KB and the overall connectivity and structural features of the resulting network were calculated. Our results show that networking the 187 user-defined AOPs currently described in the AOP-KB resulted in the emergence of 9405 unique, previously undescribed, linear AOPs (LAOPs). To investigate patterns in this emerging knowledge, we assembled the AOP-KB network retrospectively by sequentially adding each of the 187 user-defined AOPs and found that the creation of new AOPs that borrowed components from previously existing AOPs in the KB most described emergence of new LAOPs. However, the introduction of nonadjacent key event relationships and cycles among KEs also play key roles in emergent LAOPs. We provide examples of how to identify application-specific critical paths from this large number of LAOPs. Our research shows that the global AOP network may have considerable value as a source of emergent toxicological knowledge. These findings are not only helpful for understanding the nature of this emergent information but can also be used to manage and guide future development of the AOP-KB, and how to tailor this wealth of information to specific applications., (Published by Oxford University Press on behalf of the Society of Toxicology 2019.)

The relative potency of one agent to another is commonly represented by the ratio of two quantal response parameters; for example, the LD 50 of animals receiving a treatment to the LD 50 of control animals, where LD 50 is the dose of toxin that is lethal to 50% of animals. Though others have considered interval estimators of LD 50 , here, we extend Bayesian, bootstrap, likelihood ratio, Fieller's and Wald's methods to estimate intervals for relative potency in a parallel-line assay context. In addition to comparing their coverage probabilities, we also consider their power in two types of dose designs: one assigning treatment and control the same doses vs. one choosing doses for treatment and control to achieve same lethality targets. We explore these methods in realistic contexts of relative potency of radiation countermeasures. For larger experiments (e.g., ≥100 animals), the methods return similar results regardless of the interval estimation method or experiment design. For smaller experiments (e.g., < 60 animals), Wald's method stands out among the others, producing intervals that hold closely to nominal levels and providing more power than the other methods in statistically efficient designs. Using this simple statistical method within a statistically efficient design, researchers can reduce animal numbers.

Objectives: To demonstrate the severity of undercounting opioid-involved deaths in a local jurisdiction with a high proportion of unspecified accidental poisoning deaths., Methods: We matched toxicology data to vital records for all accidental poisoning deaths (n = 1238) in Marion County, Indiana, from January 2011 to December 2016. From vital records, we coded cases as opioid involved, specified other substance, or unspecified. We extracted toxicology data on opioid substances for unspecified cases, and we have reported corrected estimates of opioid-involved deaths after accounting for toxicology findings., Results: Over a 6-year period, 57.7% of accidental overdose deaths were unspecified and 34.2% involved opioids. Toxicology data showed that 86.8% of unspecified cases tested positive for an opioid. Inclusion of toxicology results more than doubled the proportion of opioid-involved deaths, from 34.2% to 86.0%., Conclusions: Local jurisdictions may be undercounting opioid-involved overdose deaths to a considerable degree. Toxicology data can improve accuracy in identifying opioid-involved overdose deaths. Public Health Implications. Mandatory toxicology testing and enhanced training for local coroners on standards for death certificate reporting are needed to improve the accuracy of local monitoring of opioid-involved accidental overdose deaths.

Discrete data in the form of proportions with overdispersion and zero inflation can arise in toxicology and other similar fields. In regression analysis of such data, another problem that also may arise in practice is that some responses may be missing. In this paper, we develop estimation procedure for the parameters of a zero-inflated overdispersed binomial model in the presence of missing responses under three different missing data mechanisms. A weighted expectation maximization algorithm is used for the maximum likelihood estimation of the parameters involved. Extensive simulations are conducted to study the properties of the estimates in terms of average of estimates, relative bias, variance, mean squared error, and coverage probability of estimates. Simulations show much superior properties of the estimates obtained using the weighted expectation maximization algorithm. Some illustrative examples and a discussion are given., (Copyright © 2018 John Wiley & Sons, Ltd.)

A time-to-event (TTE) model has been developed to characterize a histopathology toxicity that can only be detected at the time of animal sacrifice. The model of choice was a hazard model with a Weibull distribution and dose was a significant covariate. The diagnostic plots showed a satisfactory fit of the data, despite the high degree of left and right censoring. Comparison to a probabilistic logit model shows similar performance in describing the data with a slight underestimation of survival by the Logit model. However, the TTE model was found to be more predictive in extrapolating toxicity risk beyond the observation range of a truncated dataset. The diagnostic and comparison outcomes would suggest using the TTE approach as a first choice for characterizing short and long-term risk from nonclinical toxicity studies. However, further investigations are needed to explore the domain of application of this kind of approach in drug safety assessment.

Study design, statistical analysis, interpretation of results, and conclusions should be a part of all research papers. Statistics are integral to each of these components and are therefore necessary to evaluate during manuscript peer review. Research published in Toxicological Pathology is often focused on animal studies that may seek to compare defined treatment groups in randomized controlled experiments or focus on the reliability of measurements and diagnostic accuracy of observed lesions from preexisting studies. Reviewers should distinguish scientific research goals that aim to test sufficient effect size differences (i.e., minimizing false positive rates) from common toxicologic goals of detecting a harmful effect (i.e., minimizing false negative rates). This journal comprises a wide range of study designs that require different kinds of statistical assessments. Therefore, statistical methods should be described in enough detail so that the experiment can be repeated by other research groups. The misuse of statistics will impede reproducibility.

Objectives: Assessment factors (AFs) are commonly used for deriving reference concentrations for chemicals. These factors take into account variabilities as well as uncertainties in the dataset, such as inter-species and intra-species variabilities or exposure duration extrapolation or extrapolation from the lowest-observed-adverse-effect level (LOAEL) to the noobserved- adverse-effect level (NOAEL). In a deterministic approach, the value of an AF is the result of a debate among experts and, often a conservative value is used as a default choice. A probabilistic framework to better take into account uncertainties and/or variability when setting occupational exposure limits (OELs) is presented and discussed in this paper., Material and Methods: Each AF is considered as a random variable with a probabilistic distribution. A short literature was conducted before setting default distributions ranges and shapes for each AF commonly used. A random sampling, using Monte Carlo techniques, is then used for propagating the identified uncertainties and computing the final OEL distribution., Results: Starting from the broad default distributions obtained, experts narrow it to its most likely range, according to the scientific knowledge available for a specific chemical. Introducing distribution rather than single deterministic values allows disclosing and clarifying variability and/or uncertainties inherent to the OEL construction process., Conclusions: This probabilistic approach yields quantitative insight into both the possible range and the relative likelihood of values for model outputs. It thereby provides a better support in decision-making and improves transparency. Int J Occup Med Environ Health 2018;31(4):475-489., (This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.)

Aims and Objective: Chemical toxicity effect is one of the major reasons for declining candidate drugs. Detecting the toxicity effects of all chemicals can accelerate the procedures of drug discovery. However, it is time-consuming and expensive to identify the toxicity effects of a given chemical through traditional experiments. Designing quick, reliable and non-animal-involved computational methods is an alternative way., Method: In this study, a novel integrated multi-label classifier was proposed. First, based on five types of chemical-chemical interactions retrieved from STITCH, each of which is derived from one aspect of chemicals, five individual classifiers were built. Then, several integrated classifiers were built by integrating some or all individual classifiers., Result and Conclusion: By testing the integrated classifiers on a dataset with chemicals and their toxicity effects in Accelrys Toxicity database and non-toxic chemicals with their performance evaluated by jackknife test, an optimal integrated classifier was selected as the proposed classifier, which provided quite high prediction accuracies and wide applications., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

Aims: Proprietary Chinese medicines (pCMs) and health products, generally believed to be natural and safe, are gaining popularity worldwide. However, the safety of pCMs and health products has been severely compromised by the practice of adulteration. The current study aimed to examine the problem of adulteration of pCMs and health products in Hong Kong., Methods: The present study was conducted in a tertiary referral clinical toxicology laboratory in Hong Kong. All cases involving the use of pCMs or health products, which were subsequently confirmed to contain undeclared adulterants, from 2005 to 2015 were reviewed retrospectively., Results: A total of 404 cases involving the use of 487 adulterated pCMs or health products with a total of 1234 adulterants were identified. The adulterants consisted of approved drugs, banned drugs, drug analogues and animal thyroid tissue. The six most common categories of adulterants detected were nonsteroidal anti-inflammatory drugs (17.7%), anorectics (15.3%), corticosteroids (13.8%), diuretics and laxatives (11.4%), oral antidiabetic agents (10.0%) and erectile dysfunction drugs (6.0%). Sibutramine was the most common adulterant (n = 155). The reported sources of these illicit products included over-the-counter drug stores, the internet and Chinese medicine practitioners. A significant proportion of patients (65.1%) had adverse effects attributable to these illicit products, including 14 severe and two fatal cases. Psychosis, iatrogenic Cushing syndrome and hypoglycaemia were the three most frequently encountered adverse effects., Conclusions: Adulteration of pCMs and health products with undeclared drugs poses severe health hazards. Public education and effective regulatory measures are essential to address the problem., (© 2017 The British Pharmacological Society.)

A framework for the quantitative weight-of-evidence (QWoE) analysis of 'omics data for regulatory purposes is presented. The QWoE framework encompasses seven steps to evaluate 'omics data (also together with non-'omics data): (1) Hypothesis formulation, identification and weighting of lines of evidence (LoEs). LoEs conjoin different (types of) studies that are used to critically test the hypothesis. As an essential component of the QWoE framework, step 1 includes the development of templates for scoring sheets that predefine scoring criteria with scores of 0-4 to enable a quantitative determination of study quality and data relevance; (2) literature searches and categorisation of studies into the pre-defined LoEs; (3) and (4) quantitative assessment of study quality and data relevance using the respective pre-defined scoring sheets for each study; (5) evaluation of LoE-specific strength of evidence based upon the study quality and study relevance scores of the studies conjoined in the respective LoE; (6) integration of the strength of evidence from the individual LoEs to determine the overall strength of evidence; (7) characterisation of uncertainties and conclusion on the QWoE. To put the QWoE framework in practice, case studies are recommended to confirm the relevance of its different steps, or to adapt them as necessary., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: Since 2001, U.S. military personnel and active duty, uniformed physicians providing medical support have been deployed to Afghanistan. Medical toxicologists are among the physicians deployed. There is a paucity of information present in the literature that has documented cases treated by toxicologists in theater. This prospective observational study describes 15 male patients treated in theater by a military medical toxicologist., Methods: We performed a prospective observational study in which a medical toxicologist consulted and reported on deployed toxicology cases occurring during a 5-month deployment to Bagram, Afghanistan., Results: Fifteen toxicology cases were collected during the 5-month period. The patients included three Afghan civilians, three U.S. civilians, and nine U.S. military personnel. Eight cases were attempts at recreational euphoria, two were self-harm attempts, two were from performance-enhancing supplements, two were accidental occupational exposures and one was alcohol withdrawal. Methanol was the most common exposure followed by dextromethorphan, supplements, opiates, and chlorine gas., Conclusion: In our study, we found that toxic alcohols and nonprescription medications were the most common exposures. In addition, this is the first study to describe bedside toxicology consults for U.S. combat forces in theater and the use of an observation unit for critically ill patients., (Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.)

The vast majority of toxicological papers summarize experimental data as bar charts of means with error bars. While these graphics are easy to generate, they often obscure essential features of the data, such as outliers or subgroups of individuals reacting differently to a treatment. In particular, raw values are of prime importance in toxicology; therefore, we argue they should not be hidden in messy supplementary tables but rather unveiled in neat graphics in the results section. We propose jittered boxplots as a very compact yet comprehensive and intuitively accessible way of visualizing grouped and clustered data from toxicological studies together with individual raw values and indications of statistical significance. A web application to create these plots is available online.

Poison centers advance knowledge in the field of toxicology through publication in peer-review journals. This investigation describes the pattern of poison center-related publications. Cases were poison center-related research published in peer-review journals during 1995-2014. These were identified through searching the PubMed database, reviewing the tables of contents of selected toxicology journals, and reviewing abstracts of various national and international meetings. The following variables for each publication were identified: year of publication, journal, type of publication (meeting abstract vs. other, i.e. full article or letter to the editor), and the country(ies) of the poison center(s) included in the research. Of the 3147 total publications, 62.1% were meeting abstracts. There were 263 publications in 1995-1999, 536 in 2000-2004, 999 in 2005-2009, and 1349 in 2010-2014. The publications were in 234 different journals. The journals in which the highest number of research was published were Clinical Toxicology (69.7%), Journal of Medical Toxicology (2.2%), and Veterinary and Human Toxicology (2.1%). The research was reported from 62 different countries. The countries with the highest number of publications were the United States (67.9%), United Kingdom (6.5%), Germany (3.9%), France (2.5%), and Italy (2.4%). The number of publications increased greatly over the 20 years. Although the publications were in a large number of journals, a high proportion of the publications were in one journal. While the research came from a large number of countries, the preponderance came from the United States., (© The Author(s) 2015.)

Dose-response relations can be obtained from systems at any structural level of biological matter, from the molecular to the organismic level. There are two types of approaches for analyzing dose-response curves: a deterministic approach, based on the law of mass action, and a statistical approach, based on the assumed probabilities distribution of phenotypic characters. Models based on the law of mass action have been proposed to analyze dose-response relations across the entire range of biological systems. The purpose of this paper is to discuss the principles that determine the dose-response relations. Dose-response curves of simple systems are the result of chemical interactions between reacting molecules, and therefore are supported by the law of mass action. In consequence, the shape of these curves is perfectly sustained by physicochemical features. However, dose-response curves of bioassays with quantal response are not explained by the simple collision of molecules but by phenotypic variations among individuals and can be interpreted as individual tolerances. The expression of tolerance is the result of many genetic and environmental factors and thus can be considered a random variable. In consequence, the shape of its associated dose-response curve has no physicochemical bearings; instead, they are originated from random biological variations. Due to the randomness of tolerance there is no reason to use deterministic equations for its analysis; on the contrary, statistical models are the appropriate tools for analyzing these dose-response relations., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

In this paper, we compare the traditional ANOVA approach to analysing data from 90-day toxicity studies with a more modern LMM approach, and we investigate the use of standardized effect sizes. The LMM approach is used to analyse weight or feed consumption data. When compared to the week-by-week ANOVA with multiple test results per week, this approach results in only one statement on differences in weight development between groups. Standardized effect sizes are calculated for the endpoints: weight, relative organ weights, haematology and clinical biochemistry. The endpoints are standardized, allowing different endpoints of the same study to be compared and providing an overall picture of group differences at a glance. Furthermore, in terms of standardized effect sizes, statistical significance and biological relevance are displayed simultaneously in a graph.

Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine., (© The Author 2015. Published by Oxford University Press.)

Nonlinear regression is often used to evaluate the toxicity of a chemical or a drug by fitting data from a dose-response study. Toxicologists and pharmacologists may draw a conclusion about whether a chemical is toxic by testing the significance of the estimated parameters. However, sometimes the null hypothesis cannot be rejected even though the fit is quite good. One possible reason for such cases is that the estimated standard errors of the parameter estimates are extremely large. In this paper, we propose robust ridge regression estimation procedures for nonlinear models to solve this problem. The asymptotic properties of the proposed estimators are investigated; in particular, their mean squared errors are derived. The performances of the proposed estimators are compared with several standard estimators using simulation studies. The proposed methodology is also illustrated using high throughput screening assay data obtained from the National Toxicology Program., (Copyright © 2014 John Wiley & Sons, Ltd.)

Background: In this paper the structure of poisonings is described, based on the material collected from tele-toxicology consults by the Pomeranian Center of Toxicology in Gdańsk and harvested from its Electronic Poison Information Management System. In addition, we analyzed conclusions drawn from a 27-month operation of the system., Material and Methods: Data were harvested from the Electronic Poison Information Management System developed in 2012 and used by the Pomeranian Center of Toxicology since then. The research was based on 2550 tele-toxicology consults between January 1 and December 31, 2014. Subsequently the data were electronically cleaned and presented using R programming language., Results: The Pomeranian voivodeship was the prevalent localisation of calls (N = 1879; 73.7%). Most of the calls came from emergency rooms (N = 1495; 58.63%). In the case of 1396 (54.7%) patients the time-lag between intoxication and the consult was less than 6 h. There were no differences in the age distribution between genders. Mean age was 26.3 years. Young people predominated among intoxicated individuals. The majority of intoxications were incidental (N = 888; 34.8%) or suicidal (N = 814; 31.9%) and the most of them took place in the patient's home., Conclusions: Information about Poison Control Center consultations access should be better spread among medical service providers. The extent of poison information collected by Polish Poison Control Centers should be limited and unified. This should contribute to the increased percentage of properly documented consultations. Additional duties stemming from the need of digital archiving of consults provided, require the involvement of additional staff, leading to the increased operation costs incurred by Poison Control Centers., (This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.)

Background: Toxicology in Malaysia has experienced rapid development and made great progress in education and research in conjunction with economic development in Malaysia over the past two decades., Objectives: The main objectives of this study were to analyse the research originating from Malaysia and published in toxicology journals and to examine the authorship pattern and the citations retrieved from the Scopus database., Methods: Data from 1 January 2003 till 31 December 2012 were searched for documents with specific words in the toxicology field as a 'source title' and Malaysia as an affiliation country. Research productivity was evaluated based on a methodology we developed and used in other bibliometric studies by analysing: (a) total and trends of contributions in toxicology fields between 2003 and 2012; (b) Malaysian authorship pattern and productivity; (c) collaboration patterns; (d) journals in which Malaysian researchers publish; (e) the classification of journals to Institute for Scientific Information (ISI) or non-ISI; (f) impact factors (IFs) of all publications; and (g) citations received by the publications., Results: In total, 290 documents were retrieved from 55 international peer-reviewed toxicology journals. The quantity of publication increased by around 10-fold from 2003 to 2012. The h-index of the retrieved documents was 20. Of the 55 journal titles, 42 (76.4%) have their IF listed in the journal citation reports 2012. Forty-two documents (14.5%) were published in journals that had no official IF. The total number of citations, at the time of manuscript writing (5 August 2013), was 1707, with a median (interquartile range) of 3 (0-7). Malaysia collaborated mostly with countries in the Asia-Pacific regions (18.3%), especially India and Japan, followed by the Middle East and Africa (10.0%), especially Palestine and Yemen., Conclusion: The present data show a promising rise and a good start for toxicology research activity in Malaysia. The sharing of relevant research questions by developed and developing countries can lead to research opportunities in the field of toxicology., (© The Author(s) 2014.)

Organization of existing and emerging toxicological knowledge into adverse outcome pathway (AOP) descriptions can facilitate greater application of mechanistic data, including those derived through high-throughput in vitro, high content omics and imaging, and biomarker approaches, in risk-based decision making. The previously ad hoc process of AOP development is being formalized through development of internationally harmonized guidance and principles. The goal of this article was to outline the information content desired for formal AOP description and some rules of thumb and best practices intended to facilitate reuse and connectivity of elements of an AOP description in a knowledgebase and network context. For example, key events (KEs) are measurements of change in biological state that are indicative of progression of a perturbation toward a specified adverse outcome. Best practices for KE description suggest that each KE should be defined as an independent measurement made at a particular level of biological organization. The concept of "functional equivalence" can help guide both decisions about how many KEs to include in an AOP and the specificity with which they are defined. Likewise, in describing both KEs and evidence that supports a causal linkage or statistical association between them (ie, a key event relationship; KER), best practice is to build from and contribute to existing KE or KER descriptions in the AOP knowledgebase rather than creating redundant descriptions. The best practices proposed address many of the challenges and uncertainties related to AOP development and help promote a consistent and reliable, yet flexible approach., (Published by Oxford University Press on behalf of the Society of Toxicology 2014. This work is written by a US Government employees and is in the public domain in the US.)

Background: Bibliometric studies are increasingly being used for research assessment by involving the application of statistical methods to scientific publications to obtain the bibliographics for each country. The main objective of this study was to analyse the research productivity originating from 13 Middle Eastern Arab (MEA) countries with articles published in toxicology journals., Methods: Data from January 1, 2003 till December 31, 2012 were searched for documents with specific words in the toxicology field as a "source title" in any one of the 13 MEA countries. Research productivity was evaluated based on a methodology developed and used in other bibliometric studies. Research productivity was adjusted to the national population and nominal gross domestic product (GDP) per capita., Results: Documents (n = 1,240) were retrieved from 73 international peer-reviewed toxicology journals. The h-index of the retrieved documents was 39. Of the 73 journal titles, 52 (69.9%) have their IF listed in the ISI Journal Citation Reports 2012; 198 documents (16.0%) were published in journals that had no official IF. After adjusting for economy and population power, Egypt (193.6), Palestine (18.1), Kingdom of Saudi Arabia (KSA) (13.0), and Jordan (11.5) had the highest research productivity. Countries with large economies, such as the Kuwait, United Arab Emirates (UAE), and Oman, tended to rank relatively low after adjustment of GDP. The total number of citations at the time of data analysis (August 4, 2013) was 10,991, with a median (interquartile range) of 4 (1-11). MEA collaborated more with countries in the MEA regions (16.7%), especially KSA, Egypt, and UAE, followed by Europe (14.4%), especially with the United Kingdom and Germany., Conclusions: The present data show a promising rise and a good start for toxicology research activity in toxicology journals in the Arab world. Research output is low in some countries, which can be improved by investing in more international and national collaborative research projects in the field of toxicology.

Metabolomics use in toxicology is rapidly increasing, particularly owing to advances in mass spectroscopy, which is widely used in the life sciences for phenotyping disease states. Toxicology has the advantage of having the disease agent, the toxicant, available for experimental induction of metabolomics changes monitored over time and dose. This review summarizes the different technologies employed and gives examples of their use in various areas of toxicology. A prominent use of metabolomics is the identification of signatures of toxicity - patterns of metabolite changes predictive of a hazard manifestation. Increasingly, such signatures indicative of a certain hazard manifestation are identified, suggesting that certain modes of action result in specific derangements of the metabolism. This might enable the deduction of underlying pathways of toxicity, which, in their entirety, form the Human Toxome, a key concept for implementing the vision of Toxicity Testing for the 21st century. This review summarizes the current state of metabolomics technologies and principles, their uses in toxicology and gives a thorough overview on metabolomics bioinformatics, pathway identification and quality assurance. In addition, this review lays out the prospects for further metabolomics application also in a regulatory context., (Copyright © 2013 John Wiley & Sons, Ltd.)

In a 2008 survey of the 73 emergency and critical care centers around the nation that were equipped with the drug and chemical analytical instrument provided by the Ministry of Welfare (currently the Ministry of Health, Labour, and Welfare) in 1998, 36 of those facilities were using the analytical instruments. Of these 36 facilities, a follow-up survey of the 17 facilities that recorded 50 or analyses per year. Responses were gained from 16 of the facilities and we learned that of those, 14 facilities (87.5%) were conducting analyses using the instrument. There was a positive mutual correlation between the annual number of cases of the 14 facilities conducting analyses with the instrument and the number of work hours. Depending on the instrument in use, average analytical instrument parts and maintenance expenses were roughly three million yen and consumables required a maximum three million yen for analysis of 51-200 cases per year. From this, we calculate that such expenses can be covered under the allowed budget for advanced emergency and critical care centers of 5,000 NHI points (1 point = 10 yen). We found there were few facilities using the instrument for all 15 of the toxic substances recommended for testing by the Japanese Society for Clinical Toxicology. There tended to be no use of the analytical instrument for compounds with no toxicology cases. However, flexible responses were noted at each facility in relation to frequently analyzed compounds. It is thought that a reevaluation of compounds subject to analysis is required.

There are 12 centers of acute poisoning treatment and 9 round the clock toxicological laboratories. Most of the laboratories access evidence of activity run by National Clinical Toxicology Consultant. The paper presents actual status of medical toxicology laboratories in Poland and summarizes activity of the laboratories in the year 2012. In 2012 toxicological laboratories reported 113,719 assays. There were diagnosed 63.8% men and 34.8% women. The toxicological laboratories determine most substances and markers of exposition to chemical compounds important for diagnosis and treatment of acute poisonings (i.e. ethanol, methanol, ethylene glycol, acetaminophen, salicylates, anticonvulsants, carboxyhemoglobin, methemoglobin). There is not possible to determine heavy metals, all medicines and "designed" drugs of abuse in all laboratories. Limited access to reference methods, that enable to confirm results obtained by screening methods (immunological cassette and strip tests) is also a problem.

In 2009, the National Research Council (NRC) released the latest in a series of advisory reports on human health risk assessment, titled Science and Decisions: Advancing Risk Assessment. This wide-ranging report made a number of recommendations related to risk assessment practice at the U.S. Environmental Protection Agency that could both influence and be influenced by evolving toxicological practice. In particular, Science and Decisions emphasized the scientific and operational necessity of a new approach for dose-response modeling; addressed the recurring challenge of defaults in risk assessment and the question of when research results can be used in place of defaults; and reinforced the value of cumulative risk assessment, which would require enhanced understanding of the joint influence of chemical and nonchemical stressors on health outcomes. The objective of this article is to summarize key messages from Science and Decisions, both as a stand-alone report and in comparison with another recent NRC report, Toxicity Testing in the 21st Century: A Vision and a Strategy. Although these reports have many conclusions in common and reinforce similar themes, there are important differences that merit careful consideration, such as the move away from apical endpoints in Toxicity Testing and the emphasis on benefit-cost analyses and related decision tools in Science and Decisions that would be strengthened by quantification of apical endpoints. Moving risk assessment forward will require toxicologists to wrestle with the implications of Science and Decisions from a toxicological perspective.

Objectives: To analyze the number and trends in calls to the Toxicological Information Center (TIC) concerning pharmaceutical poisoning retrospectively during the past 15 years and to compare selected characteristics of the poisonings., Design: Inquiries arising from drug poisonings in the years 1997-2012 were extracted and evaluated from the Czech database recording the consultations of TIC specialists. In addition, their cause, severity and dose evaluation (data electronically collected after 2005) were compared in the years 2005-2012 using standard statistical methods., Results: During 15 years total 152,649 calls due to all types of potentially toxic agents were recorded in the TIC database. Central nervous system (CNS) affecting drugs represented 39.8% of calls due to all pharmaceutical poisonings. The proportion of adults was 72.2% and women comprised 64.4% of all patients. Whereas the number of calls caused by poisoning with tricyclic antidepressants (TCAs) and barbiturates decreased (by 366.7% and 340%, respectively), the calls due to selective serotonin reuptake inhibitors (SSRIs) and benzodiazepines overdose increased (by 1347.4% and 359.8%). The dose of CNS affecting drugs in 2005-2012 was considered lethal in 14.6% of the inquiries due to barbiturates and 8.6% due to TCAs, but only in 1.6% calls due to SSRIs and 0.5% of benzodiazepines. The highest percentage of medications errors was found during the treatment with barbiturates (16.4%)., Conclusions: The current drugs prescription with improved safety profiles brings the beneficial effect of lowering the severity of poisonings and better prognosis of intoxications as observed in the TIC statistics.

We describe deployment of electronic toxicological information database in poison control center of Pomeranian Center of Toxicology. System was based on Google Apps technology, by Google Inc., using electronic, web-based forms and data tables. During first 6 months from system deployment, we used it to archive 1471 poisoning cases, prepare monthly poisoning reports and facilitate statistical analysis of data. Electronic database usage made Poison Center work much easier.

Several doses and a control group can be compared under order restriction using the Williams procedure for normally distributed endpoints assuming variance homogeneity. Comparison of the survival functions represents a secondary endpoint in long-term in vivo bioassays of carcinogenicity. Therefore, a Williams-type procedure for the comparison of survival functions is proposed for the assumption of the Cox proportional hazards model or the general frailty Cox model to allow a joint analysis over sex and strains. Interpretation according to both statistical significance and biological relevance is possible with simultaneous confidence intervals for hazard ratios. Related survival data can be analyzed using the R packages survival, coxme, and multcomp. Together with the R packages MCPAN and nparcomp, Dunnett- or Williams-type procedures are now available for the statistical analysis of the following endpoint types in toxicology: (i) normally distributed, (ii) non-normally distributed, (iii) score (ordered categorical) data, (iv) crude proportions, (v) survival functions, and (vi) time-to-tumor data with and without cause-of-death information., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Aim: Determine major substances and risk factors for suicide by chemical overdose in New Zealand between 2001 and 2005., Method: All intentional deaths between 2001 and 2005 were reviewed. Primary substances causing death were verified from toxicology reports., Results: The chemical suicide rate was higher among older Europeans, women and those in paid work than other groups. Carbon monoxide and tricyclic antidepressants (TCAs) continue to be the most common chemicals used, in spite of market changes. Anaesthetics and cyanide deaths among workers were noted., Conclusion: Restricted access to work-related chemicals and stricter prescription/dispensing controls for TCAs may reduce self-poisoning in New Zealand.

Objective: To identify the hospital admission data set that best captures the incidence of acute poisoning in rural Sri Lanka., Methods: Data were collected on all acute poisoning cases admitted to 34 primary and 1 referral hospital in Anuradhapura district from September 2008 to January 2010. Three admission data sets were compared with the "true" incidence of acute poisoning to determine the systematic bias inherent to each data set. "True" incidence was calculated by adding all direct admissions (not transfers) to primary hospitals and to the referral hospital. The three data sets were: (i) all admissions to primary hospitals only; (ii) all admissions to the referral hospital only (direct and referrals), and (iii) all admissions to both primary hospitals and the referral hospital ("all admissions"). The third is the government's routine statistical method but counts transfers twice, so for the study transferred patients were counted only once through data linkage., Findings: Of 3813 patients admitted for poisoning, 3111 first presented to a primary hospital and 2287 (73.5%) were later transferred to the referral hospital, where most deaths (161/177) occurred. All data sets were representative demographically and in poisoning type, but referral hospital data yielded a more accurate case-fatality rate than primary hospital data or "all admissions" data. Admissions to primary hospitals only or to the referral hospital only underestimated the incidence of acute poisoning by about 20%, and data on "all admissions" overestimated it by 60%., Conclusion: Admission data from referral hospitals are easily obtainable and accurately reflect the true poisoning incidence.

Retrospective study in a toxicological unit care (TUC) performed to know the epidemiology of acute intoxication (AI) in Verona (Italy) during years 2008-2009. All data regarding patients with a diagnosis of certain/suspected AI were collected and evaluated: some demographic information, the characteristics of the agent involved, the pattern of exposure, the triage at the admission to TUC and the outcome. 244 cases were analyzed: 45.9% males and 54.9% females, mean age respectively 45.1 and 43.9 years. The monthly distribution of admitted patients resulted fairly constant, except from a light rising prevalence in autumn, with a majority of yellow (45.9%) and green (43.4%) triage code. The pattern of exposure resulted: ingestion (82.7% of cases; age peaks: 18-34 and 35-51 years old; mostly due to food (as mushrooms), drinks, detergents, soap, pharmaceutical, drugs of abuse, caustics substances), contact (10.2% of cases; age peak 18-51) and inhalation (6.9% of cases). In 17.2% of cases the poisoning exposure was intentional. In 63.5% the patients were sent to their general practitioners (45.5% of the yellow and 81.1% of the green coded patients) and in 22.1% of cases they were admitted to clinical rooms (44.6% of the yellow coded patients). In most cases the triage code assigned to the studied patients resulted yellow and green. Considering that the seriousness of the symptoms can appear after several hours from the exposure to toxic substances, a quick and specific intervention to obtain the best therapeutical effectiveness is suitable, in order to save lives or to avoid irremediable health damages.