62 research outputs found
Preventing opioid overdoses in Europe:a critical assessment of known risk factors and preventative measures
This report is the outcome of a project into opioid overdoses. The remit was to focus on finding practical methods of overdose prevention. In order to fulfil this remit, a critical review of existing knowledge on overdose prevention was conducted. The report adds value to existing information by developing a methodology to classify and analyse risk and protective factors stratified by those involved (drug users, observers and organisations). The report then assesses the extent to which risk and protective factors can be potentially modified at different levels, e.g. individual, treatment setting, organisational and strategic. The report therefore has the potential to be updated as new information emerges
Central nervous system (CNS) medications and polypharmacy in later life : cross-sectional analysis of the English Longitudinal Study of Ageing (ELSA)
OBJECTIVES: Many central nervous system (CNS) medications are considered potentially inappropriate for prescribing in older people; however, these medications are common in polypharmacy (≥5 medicines) regimens. This paper aims to determine the prevalence of CNS drug classes commonly taken by older people. Furthermore, this paper aims to determine whether polypharmacy and other factors, previously found to be associated with overall polypharmacy, are associated with the most common CNS drug classes. DESIGN: Cross-sectional study. SETTING: English Longitudinal Study of Ageing (wave 6). PARTICIPANTS: 7730 participants (≥50 years). MAIN OUTCOME MEASURES: Adjusted Odds Ratios (OR) and 95% confidence intervals (CI) for CNS drug classes. RESULTS: 31% of the sample were currently taking ≥5 medications (polypharmacy), of whom 58% (n=1362/2356) were taking CNS medicines as part of their regimen. The most common CNS drug classes in polypharmacy regimens were non-opioid analgesics, opioid analgesics, tricyclic and related antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs) (34.6%, 13.2%, 10.9% and 10.4%, respectively). Compared with people currently taking 1-4 prescribed medicines, polypharmacy was associated with adjusted ORs of 5.71 (95% CI: 4.29 to 7.61, p<0.01) for opioid analgesics, 3.80 (95% CI: 3.25 to 4.44, p<0.01) for non-opioid analgesics, 3.11 (95% CI: 2.43 to 3.98, p<0.01) for TCAs and 2.30 (95% CI: 1.83 to 2.89, p<0.01) for SSRIs. Lower wealth was also associated with the aforementioned CNS drug classes. CONCLUSION: Opioid and non-opioid analgesics were the most prevalent classes of CNS medicines in this study. Polypharmacy is strongly associated with the aforementioned classes of analgesics. Polypharmacy is also associated with TCAs and SSRIs, although to a lesser extent than for analgesics. For all CNS medicine classes, polypharmacy may need to be considered in relation to reducing the risk of potential adverse events. After adjustment, lower wealth is associated particularly with analgesics, highlighting that socioeconomic factors may play a role in the prescribing of CNS medicines. These findings provide a baseline for future research into this area
Validating estimates of problematic drug use in England
<p>Abstract</p> <p>Background</p> <p>UK Government expenditure on combatting drug abuse is based on estimates of illicit drug users, yet the validity of these estimates is unknown. This study aims to assess the face validity of problematic drug use (PDU) and injecting drug use (IDU) estimates for all English Drug Action Teams (DATs) in 2001. The estimates were derived from a statistical model using the Multiple Indicator Method (MIM).</p> <p>Methods</p> <p>Questionnaire study, in which the 149 English Drug Action Teams were asked to evaluate the MIM estimates for their DAT.</p> <p>Results</p> <p>The response rate was 60% and there were no indications of selection bias. Of responding DATs, 64% thought the PDU estimates were about right or did not dispute them, while 27% had estimates that were too low and 9% were too high. The figures for the IDU estimates were 52% (about right), 44% (too low) and 3% (too high).</p> <p>Conclusion</p> <p>This is the first UK study to determine the validity estimates of problematic and injecting drug misuse. The results of this paper highlight the need to consider criterion and face validity when evaluating estimates of the number of drug users.</p
Using adaptive choice based conjoint (ACBC) analysis to study patients’ preferences regarding pharmaceutical treatment for osteoarthritis (OA)
Background:
Adaptive Choice Based Conjoint (ACBC) is a technique for eliciting and quantifying people’s preferences. This is the first application of ACBC in rheumatology research. The advantage of this method is that it adapts to patients’ responses to different medication scenarios. This research is concerned with the extent to which the benefits of medication are traded-off against serious adverse effects such as kidney impairment and stroke.
Objectives:
To determine the relative importance of 8 medication attributes, using the Adaptive Choice Based Conjoint.
Methods:
11 participants were recruited from the Research User Group (RUG) at the Arthritis Research UK Primary Care Centre, Keele University, UK, to evaluate a newly developed ACBC questionnaire. Participants were over 50 years of age and suffering from OA in at least one of their joints. Participants completed an ACBC questionnaire involving 8 attributes: medication availability, frequency, route of administration, expected benefit, risk of addiction, risk of stomach side effects, risk of kidney and liver side effects, and risk of heart attacks and strokes. The relative importance of the 8 attributes, which sum to 100%, was calculated using Hierarchical Bayes (HB) estimation.
Results:
Rather than medication benefits being the top priority, the greatest impact on patients’ preference regarding medication was the risk of kidney and liver side effects (22%), followed by the risk of heart attacks and strokes (17%), then the risk of stomach side effects (16%). The route of administration, frequency, and expected benefit were the least important factors influencing patients’ preference (7%).
Conclusions:
ACBC reveals information about patients’ preferences and the precise trade-offs that patients are willing to make. For example, OA patients are willing to trade off the benefits of medication for low risks of adverse effects. The benefits that patients expect from the medication are not very important when traded-off against serious medication adverse effects such as kidney and liver side effects. This shows the importance of making patients aware of OA medication side effects within the context of other treatment options
Using Adaptive Choice Based Conjoint (ACBC) analysis to predict individual patient preferences for pharmaceutical treatment of osteoarthritis
Background:
Eliciting individual patient preferences is important alongside eliciting group preferences. Group results are used to understand general population preferences and develop guidelines, while individual patient preferences assist patient-clinician shared decision-making.
Aim:
To examine whether predicted preferences derived from individual patients through ACBC match their expressed preferences for pharmaceutical treatment of osteoarthritis.
Methods:
11 participants with osteoarthritis (over 50 years of age) were recruited from the Research Users’ Group at the Arthritis Research UK Primary Care Centre, Keele University. Participants completed a computerised interactive ACBC questionnaire involving 8 attributes: medication availability, frequency, route of administration, expected benefit, risk of addiction, risk of stomach side effects, risk of kidney and liver side effects, and risk of heart attacks and strokes. Individual data were analysed using monotone regression. Patients were individually interviewed after being shown the ACBC predicted results.
Results:
For each individual, the ACBC-predicted individual patient’s preferences were in concordance with his or her expressed preferences of different attributes. Furthermore, ACBC assisted patients to trade-off attributes-levels against each other and make decisions about their preferences.
Conclusion:
ACBC is a practical tool that can be used in primary care to analyse individual patient preference prior to consultation, without unduly consuming clinicians' time
Title: Melatonin, hypnotics and their association with fracture: a matched cohort study
Objectivesalthough melatonin prescribing in England has been increasing in recent years, there have been no large scale studies on the safety of melatonin compared to other medical treatments for insomnia. The primary aim of this study was to examine the association between exposure to melatonin, hypnotic benzodiazepines (temazepam, nitrazepam) or Z-drugs (zolpidem, zopiclone) and fracture risk.Designretrospective cohort study.Setting309 general practices contributing to The Health Improvement Network (THIN) between 2008 and 2013.Participants1,377 patients aged 45 years and older prescribed melatonin; 880 patients prescribed hypnotic benzodiazepines; 1,148 patients prescribed Z-drugs and 2,752 unexposed controls matched by age, gender and practice.Main outcomefracture following prescription of study drugs ascertained from practice records.Resultsthe unadjusted hazard ratios for fracture during the follow-up period were 1.90 (95% CI 1.41–2.57) for melatonin, 1.70 (95% CI 1.18–2.46) for hypnotic benzodiazepines and 2.03 (95% CI 1.45–2.84) for Z-drugs. After adjustment for 26 covariates, the hazard ratios were 1.44 (95% CI 1.01–2.04) for melatonin, 1.26 (95% CI 0.82–1.92) for hypnotic benzodiazepines and 1.52 (95% CI 1.04–2.23) for Z-drugs. Only patients with three or more melatonin prescriptions had elevated risk. The mean time to fracture was 1.04 years and there was no significant difference in mean time to fracture between the cohorts.Conclusionsin this large cohort of patients attending UK primary care, prescriptions for melatonin and Z-drugs were associated with a significantly increased risk of fracture. With the use of melatonin increasing steadily overtime, this study adds to the literature on the safety profile of this drug
Engagement in an e-Health Tool (ORION) predicts opioid-dependent patient likelihood of behavioural change
Background: An eHealth computer-based tool named ORION was constructed to assist patients in the clinic to appreciate the factors responsible for risks of drug overdose. The aim of this study was to investigate the associations between risk perception of overdose, engagement in the ORION tool and willingness to alter overdose risk factors. Methods: 194 opioid dependent patients participated from 4 countries (UK, N=39; Germany, N=99; Italy, N=40 and Denmark, N=16).A structural equation model was fitted (AMOS version 17) to summarise the predicted associations between perceived risk and willingness to change risks of opioid overdose. The degree of engagement with the tool (time spent and number of changes to overdose risk factors) was explored. Results: A variety of models were fitted and the most parsimonious model provided a non-significant difference between the raw data and the specified model: Chi Sq = 16.87, df10, p = .077chi sq/df = 1.688. The fit indices: CFI = .991, RMSEA = .066. Pre and post self-assessments of risk towards known factors linked with overdose were highly correlated. A significant path was found between engagement in the tool and the willingness to change one or more risk factors (stand. coeff. = 0.16, p = .04). In addition, the final assessment of the risk factors was associated with engagement (stand. coeff. = 0.18, p = .02). Conclusion: The encouragement of drug users to engage in exploring changes to their overdose risk when presented on a computer screen appears to increase willingness to change risky behaviour.Publisher PDFPeer reviewe
Evaluating associations between metabolic health, obesity and depressive symptoms : a prospective analysis of data from the English Longitudinal Study of Ageing (ELSA) with a 2-year follow-up
OBJECTIVES: Conflicting results have been reported when the associations between metabolic health, obesity and depression were examined previously. The primary aim of this study was to determine whether metabolic health or obesity are independently associated with depressive symptoms, among a representative sample of older people living in England. Independent associations between covariates and depression were also examined. DESIGN: Prospective study with a 2-year follow-up. SETTING: The English Longitudinal Study of Ageing Wave 6 (2012-2013) and Wave 7 (2014-2015). PARTICIPANTS: 6804 participants aged older than 50 years. DATA ANALYSIS: Multivariate models were used to determine whether metabolic health or obesity are independently associated with depressive symptoms at 2-year follow-up. Unadjusted and adjusted ORs with corresponding 95% CI were calculated; the adjusted ORs took account of baseline depression, gender, age, wealth, obesity and poor metabolic health. RESULTS: Before adjusting for covariates, poor metabolic health was associated with depressive symptoms at 2-year follow-up (OR 1.24; 95% CI, 1.07 to 1.44, p<0.01). After adjusting for covariates, the association was no longer statistically significant (OR 1.17; 95% CI, 0.99 to 1.38, p=0.07). Similarly, obesity was associated with depressive symptoms at 2-year follow-up before adjusting for covariates (OR 1.54; 95% CI, 1.33 to 1.79, p<0.01). However, after adjusting for covariates the association between obesity and depressive symptoms at 2-year follow-up became statistically insignificant (OR 1.19; 95% CI, 1.00 to 1.41, p=0.06). The strongest predictors for future depression were baseline depression (OR 10.59; 95% CI, 8.90 to 12.53, p<0.01) and lower wealth (OR 3.23; 95% CI, 2.44 to 4.35, p<0.01). CONCLUSION: Neither poor metabolic health nor obesity were associated with a risk of depressive symptoms at 2-year follow-up, after adjusting for covariates. As wealth inequalities continue to rise across England, the risk of depressive symptoms at 2-year follow-up is likely to be elevated in individuals living in the lower wealth quintiles
P181 Musculoskeletal pain and prognosis of acute coronary syndrome and cerebrovascular accident: a linked electronic health record cohort study
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