Medicine utilization studies in Australian individual-level dispensing data: A blinded, multi-center replicated analysis.

PURPOSE: Medicine dispensing data require extensive preparation when used for research and decisions during this process may lead to results that do not replicate between independent studies. We conducted an experiment to examine the impact of these decisions on results of a study measuring discontinuation, intensification, and switching in a cohort of patients initiating metformin. METHODS: Four Australian sites independently developed a HARmonized Protocol template to Enhance Reproducibility (HARPER) protocol and executed their analyses using the Australian Pharmaceutical Benefits Scheme 10% sample dataset. Each site calculated cohort size and demographics and measured treatment events including discontinuation, switch to another diabetes medicine, and intensification (addition of another diabetes medicine). Time to event and hazard ratios for associations between cohort characteristics and each event were also calculated. Concordance was assessed by measuring deviations from the calculated median of each value across the sites. RESULTS: Good agreement was found across sites for the number of initiators (median: 53 127, range: 51 848-55 273), gender (56.9% female, range: 56.8%-57.1%) and age group. Each site employed different methods for estimating days supply and used different operational definitions for the treatment events. Consequently, poor agreement was found for incidence of discontinuation (median 55%, range: 34%-67%), switching (median 3.5%, range: 1%-7%), intensification (median 8%, range: 5%-12%), time to event estimates and hazard ratios. CONCLUSIONS: Differences in analytical decisions when deriving exposure from dispensing data affect replicability. Detailed analytical protocols, such as HARPER, are critical for transparency of operational definitions and interpretations of key study parameters.

Transitions to polysubstance use: Prospective cohort study of adolescents in Australia.

BACKGROUND AND AIMS: Adolescent polysubstance use has been associated with adverse social and health outcomes. Our aim was to measure rates and transitions to polysubstance use during adolescence and identify factors associated with initiation and discontinuation of polysubstance use. DESIGN: Prospective cohort study. Multistate Markov modelling was used to estimate rates and identify correlates of transitions between substance use states. SETTING AND PARTICIPANTS: Adolescent-parent dyads (n = 1927; adolescents in grade 7, age ≈13 years) were recruited from Australian schools during 2010/11 (Wave 1). Adolescents were surveyed annually until 2016/17 (n = 1503; age ≈19 years; Wave 7) and parents were surveyed annually until 2014/15 (Wave 5). MEASUREMENTS: Alcohol, tobacco, cannabis and 3,4-methylenedioxymethamphetamine (MDMA) use outcomes were collected at Waves 3-7. Potential confounders were collected at Waves 1-6 and consisted of sex, anxiety and depression symptoms and externalizing problems, parental monitoring, family conflict and cohesion, parental substance use and peer substance use. Covariates were age and family socioeconomic status. FINDINGS: Few adolescents engaged in polysubstance use at earlier waves (Wave 3: 5%; Wave 4: 8%), but proportions increased sharply across adolescence (Waves 5-7: 17%, 24%, 36%). Rates of transitioning to polysubstance use increased with age, with few (<9%) adolescents transitioning out. More externalizing problems (odds ratio [OR] = 1.10; 99.6% confidence interval [CI] = 1.07-1.14), parental heavy episodic drinking (OR = 1.22; 99.6% CI = 1.07-1.40), parental illicit substance use (OR = 3.56; 99.6% CI = 1.43-8.86), peer alcohol use (OR = 5.68; 99.6% CI = 1.59-20.50) and peer smoking (OR = 4.18; 99.6% CI = 1.95-8.81) were associated with transitioning to polysubstance use. CONCLUSIONS: Polysubstance use in Australia appears to be rare during early adolescence but more common in later adolescence with low rates of transitioning out. Externalizing problems and greater parental and peer substance use are risk factors for adolescent polysubstance use that may be suitable intervention targets.

Has the rescheduling of modified-release paracetamol in Australia affected the frequency of overdoses?

OBJECTIVES: In June 2020, modified-release paracetamol (paracetamol-MR) preparations were up-scheduled from schedule-2 (available in pharmacy) to schedule-3 (available by request to a pharmacist only). The present study aims to ascertain whether up-scheduling affected the frequency of paracetamol-MR overdoses. METHODS: This is a retrospective cohort study of two data sets from 1 June 2017 to 31 May 2022. Monash Health data were extracted using the diagnosis of paracetamol overdose coding and electronic medical records data. Calls regarding paracetamol-MR overdoses to Victorian Poisons Information Centre (VPIC) were extracted from the Poisons centre call database. We used a quasi-experimental research design with interrupted time series analysis to evaluate the immediate impact and change in trend of poisoning-related calls and ED presentations before and after June 2020. The change in proportion of paracetamol-MR cases in both databases was analysed using the Χ2 test. RESULTS: The proportion of paracetamol-MR cases in both data sets did not change. From Monash Health, there was no level change in monthly paracetamol-MR overdose-related presentations following re-scheduling (rate ratio [RR] = 1.08, 95% confidence interval [CI] = 0.57-2.01). There was no change in monthly paracetamol-MR overdose-related calls to VPIC following re-scheduling (RR = 1.05, 95% CI = 0.96-1.14). CONCLUSION: The proportion of paracetamol-MR overdoses did not decrease after the up-scheduling to S3. Similarly, the frequency of overdoses by month remained similar. Further limitations on access to paracetamol products may need to be considered.

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

INTRODUCTION: Paracetamol is one of the most used medicines worldwide and is the most common important poisoning in high-income countries. In overdose, paracetamol causes dose-dependent hepatotoxicity. Acetylcysteine is an effective antidote, however despite its use hepatotoxicity and many deaths still occur. AREAS COVERED: This review summarizes paracetamol overdose and toxicity (including mechanisms, risk factors, risk assessment, and treatment). In addition, we summarize the epidemiology of paracetamol overdose worldwide. A literature search on PubMed for poisoning epidemiology and mortality from 1 January 2017 to 26 October 2022 was performed to estimate rates of paracetamol overdose, liver injury, and deaths worldwide. EXPERT OPINION: Paracetamol is widely available and yet is substantially more toxic than other analgesics available without prescription. Where data were available, we estimate that paracetamol is involved in 6% of poisonings, 56% of severe acute liver injury and acute liver failure, and 7% of drug-induced liver injury. These estimates are limited by lack of available data from many countries, particularly in Asia, South America, and Africa. Harm reduction from paracetamol is possible through better identification of high-risk overdoses, and better treatment regimens. Large overdoses and those involving modified-release paracetamol are high-risk and can be targeted through legislative change.

Hospital admissions for paracetamol poisoning declined following codeine re-scheduling in Australia.

BACKGROUND: Codeine was restricted to prescription only in Australia in 2018. This intervention aimed to reduce harms from codeine dependance and use, including toxicity from co-formulated paracetamol. We aimed to quantify the impact of this intervention on paracetamol poisoning hospital admissions in a national hospital admissions database. METHODS: We analyzed the number of paracetamol overdoses resulting in hospital admissions from the Australian Institute of Health and Welfare National Hospital Morbidity Database, January 2011 to June 2020. We used interrupted time series analysis to quantify the effect of codeine re-scheduling on the monthly number of paracetamol poisoning-related hospital admissions in Australia. We compared paracetamol poisonings with no opioid combinations, and poisonings with probable paracetamol-codeine combinations. RESULTS: There was an immediate and sustained decrease (level shift) in the number of paracetamol poisoning-related hospital admissions following codeine re-scheduling (RR=0.85; 95% CI 0.80-0.89). This reduction was due to the decrease in poisonings with likely paracetamol-codeine combinations (RR=0.62; 95% CI 0.57-0.67) while there was no change in other paracetamol poisonings (RR=0.91; 95% CI 0.96-1.01). CONCLUSION: Codeine re-scheduling in Australia appears to have reduced paracetamol poisoning-related hospital admissions.

Hospitalised poisonings in Australian children: a 10-year retrospective study.

INTRODUCTION: Paediatric poisoning is a major cause of childhood injury, and most poisonings are preventable. We aimed to describe hospitalisations resulting from poisoning and envenomation in Australian children, including demographics, cause of the exposure, hospital length of stay, rates of intensive care unit admission and in-hospital deaths. We also aimed to describe risk factors for increased length of stay and intensive care unit admission. METHODS: A retrospective analysis was performed of hospitalised poisoning and envenomation cases of children (<15 years) in Australia from 1 July 2009 to 30 June 2019. A nationwide hospital admissions database was used for this study. RESULTS: During the 10-year study period 33,438 children were admitted to hospital due to a pharmaceutical or non-pharmaceutical poisoning/envenomation; an average of 74.8 cases per 100,000 population per year. Approximately 10 children were admitted to hospital each day for poisoning. Over 70% of these cases were due to pharmaceuticals (n = 23,628), most frequently non-opioid analgesics, anti-pyretics and anti-rheumatics (n = 8759, 37.1% of pharmaceutical exposures). The most common non-pharmaceutical exposure was contact with venomous animals and toxic plants (n = 4578, 46.7% of non-pharmaceuticals). Intentional self-harm occurred in 7833 (23.4%) of cases. Intensive care unit admission was required in 519 cases (2.5% of the 20,739 cases where this information was available), while 200 (0.96% of 20,739) needed ventilator support. Ten children (0.03%) died. Older age, female sex, poisoning with pharmaceuticals and metropolitan hospital location were associated with increased length of stay. Older age and poisoning with pharmaceuticals were also associated with intensive care unit admission. CONCLUSION: Approximately 10 children were admitted to hospital with poisoning every day in Australia. Most poisonings were due to pharmaceuticals, particularly simple analgesics that are found in most Australian homes. Severe outcomes (intensive care unit admissions and deaths) were rare.

Hospital-treated intentional self-poisoning events and in-hospital mortality in Tehran before and during the COVID-19 pandemic.

Hospital-treated intentional self-poisoning is common. The possibility of changed (increased) suicidal behaviors during the COVID-19 pandemic has been raised. To compare frequencies in self-poisoning events (SPEs) and the proportions with in-hospital mortality, in the year prior to and following the official onset of the COVID-19 pandemic, in a population of hospital-treated self-poisoning patients in Iran. All self-poisoned patients admitted to Loghman-Hakim Hospital, a clinical toxicology specialty hospital in Tehran, were included. The frequency of SPEs was compared between the one-year periods immediately before and after the onset of COVID-19 pandemic using Poisson regression. Differences in proportions of in-hospital mortality were also compared using logistic regression. A total of 14,478 patients with 15,391 SPEs (8,863 [61.2%] females) were evaluated in the study. There was no difference in the overall frequency of SPEs (relative risk [RR] of 0.99 [CI95% 0.96-1.03]), but a small increase in males (RR 1.07; 1.02-1.13) and a minor decrease in females (RR 0.95; 0.91-0.99). In total, 330 patients died (2.3% of all SPEs). There was no difference in overall in-hospital mortality odds ratio (OR: 0.98 [0.79-1.22]), in females (OR = 1.14 [0.80-1.60]) or males (OR = 0.92 [0.69-1.23]). There was no change in the frequency of SPEs and no difference in the in-hospital mortality proportions, suggesting that the COVID-19 pandemic had little or no effect on these aspects of suicidal behavior in Iran. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-03248-y.

Role of age-sex as underlying risk factors for death in acute pesticide self-poisoning: a prospective cohort study.

BACKGROUND: There is growing evidence in the literature that patients' age is associated with increased risk of death in acute pesticide poisoning. However, few studies have investigated whether the age effect differs between males and females. We aimed to examine the association between age-sex and risk of death in acute pesticide self-poisoning. METHODS: A prospective cohort of deliberate pesticide-poisoned patients admitted to ten rural Sri Lankan hospitals between March 2002 and December 2019. The pesticide ingested was identified based on identification of container or history. A mixed effects logistic regression was fitted to investigate the effect of age-sex on death in acute pesticide self-poisoning adjusting for clinical symptoms on admission, measured by Glasgow Coma Scale and Poison Severity Score, and controlling for clustering among hospital sites. RESULTS: In total, 201 different pesticides were ingested by patients. 6,643 patients ingested an unknown pesticide. A single pesticide was co-ingested with alcohol by 4,603 patients. Of the 28,303 patients enrolled, 2,028 patients died, resulting in case fatality of 7.2% (95% CI 6.9-7.5). The effect of age on case fatality was stronger for males after 21 years of age. The odds of dying for each 5 years increase in age was 1.26 (95% CI 1.23-1.28) times higher for males versus 1.14 (95% CI 1.10-1.19) times higher for females. Missing data were handled by multiple imputation. CONCLUSION: Patient's age-sex are important risk factors for death in acute pesticide self-poisoning even after controlling for clinical effects. The age effect on the odds of dying was significantly different for males and females, with this effect being stronger for males. Given that patient's age and sex are very easy to collect on admission, our study highlights the need for incorporating these risk factors in policy and clinical decisions.

Alcohol-related suicide across Australia: a geospatial analysis.

BACKGROUND: The acute effects of alcohol consumption are a major risk factor for suicide. Positive blood alcohol concentrations are present in almost one-third of all suicides at time of death. These suicides are defined as alcohol-related suicides. This cross-sectional study examines the geospatial distribution/clustering of high proportions of alcohol-related suicides and reports on socioeconomic and demographic risk factors. METHODS: National Coronial Information System (NCIS) data were used to calculate proportions of suicides with alcohol present at the time of death for each level 3 statistical areas (SA3) in Australia. A density analysis and hotspot cluster analysis were used to visualise and establish statistically significant clustering of areas with higher (hotspots) and lower (coldspots) proportions. Subsequently, socioeconomic and demographic risk factors for alcohol use and suicide were reported on for hot and cold spots. RESULTS: Significant clustering of areas with higher proportions of alcohol-related suicide occurred in northern Western Australia, the Northern Territory and Queensland, as well as inland New South Wales and inland Queensland. Clustering of SA3s with significantly lower proportions occurred in major city and inner regional Sydney and Melbourne. Conclusion and implications for public health: Results from this study identify areas in which prevention strategies should target alcohol use and can be used to inform prevention strategy design. Additionally, hotspots and coldspots identified in this study can be used for further analysis to better understand contextual risk factors for alcohol-related suicide.

Selecting the model for multiple imputation of missing data: Just use an IC!

Multiple imputation and maximum likelihood estimation (via the expectation-maximization algorithm) are two well-known methods readily used for analyzing data with missing values. While these two methods are often considered as being distinct from one another, multiple imputation (when using improper imputation) is actually equivalent to a stochastic expectation-maximization approximation to the likelihood. In this article, we exploit this key result to show that familiar likelihood-based approaches to model selection, such as Akaike's information criterion (AIC) and the Bayesian information criterion (BIC), can be used to choose the imputation model that best fits the observed data. Poor choice of imputation model is known to bias inference, and while sensitivity analysis has often been used to explore the implications of different imputation models, we show that the data can be used to choose an appropriate imputation model via conventional model selection tools. We show that BIC can be consistent for selecting the correct imputation model in the presence of missing data. We verify these results empirically through simulation studies, and demonstrate their practicality on two classical missing data examples. An interesting result we saw in simulations was that not only can parameter estimates be biased by misspecifying the imputation model, but also by overfitting the imputation model. This emphasizes the importance of using model selection not just to choose the appropriate type of imputation model, but also to decide on the appropriate level of imputation model complexity.

Risk factors for indicators of opioid-related harms amongst people living with chronic non-cancer pain: Findings from a 5-year prospective cohort study.

BACKGROUND: The literature suggests patient characteristics and higher opioid doses and long-term duration are associated with problematic opioid behaviours but no one study has examined the role of all these factors simultaneously in a long-term prospective cohort study. METHODS: Five-year, community-based, prospective cohort of people prescribed opioids for chronic non-cancer pain (CNCP). Logistic mixed effect models with multiple imputation were used to address missing data. Oral morphine equivalent (OME) mg per day was categorised as: 0 mg OME/day, 1-49 mg OME/day (reference), 50-89 mg OME/day, 90-199 mg OME/day and 200mg+ OME/day. Patient risk factors included: age, gender, substance use, mental health history and pain-related factors. Main outcomes included: Prescribed Opioids Difficulties Scale (PODS), Opioid-Related Behaviours In Treatment (ORBIT) scale, and ICD-10 opioid dependence. Multiple confounders for problematic opioid behaviours were assessed. FINDINGS: Of 1,514 participants 44.4% were male (95%CI 41.9-46.9) and their mean age was 58 years (IQR 48-67). Participants had a mean duration of pain of 10 years (IQR 4.5-20.0) and had been taking strong opioids for a median of four years (IQR 1.0-10.0). At baseline, median OME/day was 73 (IQR 35-148). At 5-years, 85% were still taking strong opioids. PODS moderate-high scores reduced from 59.9% (95%CI 58.8-61.0) at baseline to 51.5% (95%CI 50.0-53.0) at 5-years. Around 9% met criteria for ICD-10 opioid dependence at each wave. In adjusted mixed effect models, the risk factors most consistently associated with problematic opioid use were: younger age, substance dependence, mental health histories and higher opioid doses. INTERPRETATION: Both patient risk factors and opioid dose are associated with problematic opioid use behaviours.