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Fundamental & Clinical Pharmacology Apr 2024The combination dextropropoxyphene/paracetamol (DXP/P) was the most prescribed opioid analgesic until its withdrawal in 2011.
BACKGROUND
The combination dextropropoxyphene/paracetamol (DXP/P) was the most prescribed opioid analgesic until its withdrawal in 2011.
OBJECTIVES
This study investigated dispensations of analgesics in chronic users of DXP/P during the 18 months following its withdrawal.
METHODS
A cross-sectional study repeated yearly was conducted by using the French reimbursement database from 2006 to 2015. Chronic DXP/P users were defined as patients who received at least 40 boxes of DXP/P in the year prior to withdrawal. Data on analgesic dispensing were analyzed at DXP/P withdrawal (T0) and then every 6 months for 18 months.
RESULTS
A total of 63 671 subjects had a DXP/P reimbursement in the year prior to its discontinuation, of whom 7.1% were identified as chronic users (mean age: 71.5 years, women: 68.7%). Among the patients taking DXP/P alone at T0 (74.6%), one fourth switched to a peripheral analgesic, one fourth to a combination of peripheral analgesic/opioid, one fourth to another opioid, and the others mainly discontinued their treatment (14.1%) or died. During the following 12 months, most of the subjects taking only peripheral analgesics continued this treatment, while half of the subjects with a combination of opioid/peripheral analgesic or taking only an analgesic remained on this type of treatment.
CONCLUSION
Eighteen months after DXP/P withdrawal, more than 10% of patients stopped taking an analgesic. Vigilance is required regarding any change in analgesics by regularly reassessing patients' pain and, in the case of opioid treatments, by monitoring the risk of use disorders.
Topics: Humans; Female; Aged; Analgesics, Opioid; Dextropropoxyphene; Cross-Sectional Studies; Analgesics; Pain
PubMed: 37864449
DOI: 10.1111/fcp.12962 -
Journal of Chemical Information and... Oct 2022The design of novel, safe, and effective drugs to treat human diseases is a challenging venture, with toxicity being one of the main sources of attrition at later stages...
The design of novel, safe, and effective drugs to treat human diseases is a challenging venture, with toxicity being one of the main sources of attrition at later stages of development. Failure due to toxicity incurs a significant increase in costs and time to market, with multiple drugs being withdrawn from the market due to their adverse effects. Cardiotoxicity, for instance, was responsible for the failure of drugs such as fenspiride, propoxyphene, and valdecoxib. While significant effort has been dedicated to mitigate this issue by developing computational approaches that aim to identify molecules likely to be toxic, including quantitative structure-activity relationship models and machine learning methods, current approaches present limited performance and interpretability. To overcome these, we propose a new web-based computational method, , which can predict six types of cardiac toxicity outcomes, including arrhythmia, cardiac failure, heart block, hERG toxicity, hypertension, and myocardial infarction, efficiently and accurately. was developed using the concept of graph-based signatures, molecular descriptors, toxicophore matchings, and molecular fingerprints, leveraging explainable machine learning, and was validated internally via different cross validation schemes and externally via low-redundancy blind sets. The models presented robust performances with areas under ROC curves of up to 0.898 on 5-fold cross-validation, consistent with metrics on blind tests. Additionally, our models provide interpretation of the predictions by identifying whether substructures that are commonly enriched in toxic compounds were present. We believe will provide valuable insight into the potential cardiotoxicity of small molecules early on drug screening efforts. The method is made freely available as a web server at https://biosig.lab.uq.edu.au/cardiotoxcsm.
Topics: Humans; Cardiotoxicity; Dextropropoxyphene; Quantitative Structure-Activity Relationship; Machine Learning; ROC Curve; Arrhythmias, Cardiac
PubMed: 36219164
DOI: 10.1021/acs.jcim.2c00822 -
Neurology India 2022There are numerous toxins that affect our nervous system, both central and peripheral. Innumerable differentials exist in patients of acute encephalopathy and the list...
BACKGROUND
There are numerous toxins that affect our nervous system, both central and peripheral. Innumerable differentials exist in patients of acute encephalopathy and the list can be narrowed down with appropriate imaging. Specific neuroradiological features point to a particular diagnosis in a substantial number of cases.
OBJECTIVE
Through this study, we aimed to demonstrate the varied imaging findings of toxic encephalopathy on MRI encountered at our institute.
MATERIAL AND METHODS
A retrospective analysis of the patients clinically diagnosed as toxic encephalopathy and referred for imaging between March 2015 and December 2019 was done. A total of 25 patients were included. Patient records were reviewed for clinical details, laboratory investigations, and treatment; the institute Picture Archiving and Communication System provided the imaging findings.
RESULTS
Patients presenting were aged between 22 and 55 years (mean-34.3 years). Four patients (16%) presented with imaging findings characteristic of Marchiafava-Bignami disease and six patients (24%) had MRI findings of Wernicke encephalopathy. Three patients (12%) had methanol poisoning sequelae while imaging findings of nitroimidazole drug toxicity were observed in another three patients (12%). Two patients (8%) each of carbon monoxide poisoning and lead toxicity were seen. We had one patient (4%) each of isoniazid, methyl iodide, dextropropoxyphene toxicity, chronic toluene abuse, and hyperglycemia-induced hemiballismus-hemichorea.
CONCLUSION
Our study illustrates the amalgamated spectrum of MRI appearances in various subgroups of toxic encephalopathies. Imaging substantiated by relevant history and clinical manifestations can accurately diagnose the possible causative agent in the majority of the cases.
Topics: Adult; Brain Diseases; Humans; Magnetic Resonance Imaging; Middle Aged; Neurotoxicity Syndromes; Retrospective Studies; Wernicke Encephalopathy; Young Adult
PubMed: 36076654
DOI: 10.4103/0028-3886.355127 -
Frontiers in Pharmacology 2022To characterize the trend of opioid use (number of users, dispensations and oral morphine milligram equivalents) in Catalonia (Spain). This population-based cohort...
To characterize the trend of opioid use (number of users, dispensations and oral morphine milligram equivalents) in Catalonia (Spain). This population-based cohort study included all individuals aged 18 years or older, registered in the Information System for Research in Primary Care (SIDIAP), which covers >75% of the population in Catalonia, Spain, from 1 January 2007, to 31 December 2019. The exposures were all commercialized opioids and their combinations (ATC-codes): codeine, tramadol, oxycodone, tapentadol, fentanyl, morphine, and other opioids (dihydrocodeine, hydromorphone, dextropropoxyphene, buprenorphine, pethidine, pentazocine). The main outcomes were the annual figures per 1,000 individuals of 1) opioid users, 2) dispensations, and 3) oral morphine milligram equivalents (MME). Results were stratified separately by opioid types, age (5-year age groups), sex (male or female), living area (rural or urban), and socioeconomic status (from least, U1, to most deprived, U5). The overall trends were quantified using the percentage change (PC) between 2007 and 2019. Among 4,656,197 and 4,798,114 residents from 2007 to 2019, the number of opioid users, dispensations and morphine milligram equivalents per 1,000 individuals increased 12% (percentage change: 95% confidence interval (CI) 11.9-12.3%), 105% (95% confidence interval 83%-126%) and 339% (95% CI 289%-390%) respectively. Tramadol represented the majority of opioid use in 2019 (61, 59, and 54% of opioid users, dispensations, and total MME, respectively). Individuals aged 80 years or over reported the sharpest increase regarding opioid users (PC: 162%), dispensations (PC: 424%), and MME (PC: 830%). Strong opioids were increasingly prescribed for non-cancer pains over the years. Despite the modest increase of opioid users, opioid dispensations and MME increased substantially, particularly in the older population. In addition, strong opioids were incrementally indicated for non-cancer pains over the years. These findings suggest a transition of opioid prescriptions from intermittent to chronic and weak to strong and call for more rigorous opioid stewardship.
PubMed: 35754470
DOI: 10.3389/fphar.2022.912361 -
Postgraduate Medicine Nov 2022Despite their poor tolerance, weak opioids are still the most commonly-prescribed medicine for osteoarthritis (OA)-related pain. The objective of this network... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Despite their poor tolerance, weak opioids are still the most commonly-prescribed medicine for osteoarthritis (OA)-related pain. The objective of this network meta-analysis was to comparatively examine the efficacy and safety of weak opioids in OA treatment.
METHODS
Databases including PubMed, Embase, Cochrane Library and Web of Science were searched from inception to 4 April 2022 to retrieve randomized controlled trials (RCTs) comparing weak opioids with placebo or between one another in OA patients. Bayesian network meta-analysis was performed on the following outcomes of interest, namely the change-from-baseline score in pain relief, gastrointestinal (GI) adverse events (AEs), central nervous system (CNS) AEs, and total number of AEs (i.e. the number of subjects experiencing any AE for at least once) during follow-up. The surface under the cumulative ranking curve (SUCRA) was used to rank the effectiveness of each treatment and identify the best treatment.
RESULTS
A total of 14 RCTs invoving four types of weak opioids were included in this meta-analysis. Compared to placebo, tramadol (standardized mean difference [SMD] = -0.34, 95% credible interval [CrI]: -0.53 to -0.18) and codeine (SMD = -0.39, 95% CrI: -0.79 to -0.04) were effective for pain relief, but involved a higher risk of GI AEs, CNS AEs and total number of AEs. Dextropropoxyphene demonstrated a significantly lower risk of GI AEs (OR = 0.28, 95%CrI: 0.17 to 0.51), CNS AEs (OR = 0.29, 95%CrI: 0.11 to 0.78) and total number of AEs (OR = 0.35, 95%CrI: 0.15 to 0.82) compared to codeine. Dihydrocodeine had a better safety profile in CNS AEs (SUCRA = 64.8%) and total number of AEs (SUCRA = 66.6%).
CONCLUSIONS
The results of the present study confirmed that tramadol and codeine were effective drugs for the treatment of OA, but involved considerable safety issues. Dextropropoxyphene and dihydrocodeine exhibited a relatively good safety profile but their efficacy still warrant further investigation.
Topics: Humans; Network Meta-Analysis; Analgesics, Opioid; Tramadol; Dextropropoxyphene; Randomized Controlled Trials as Topic; Osteoarthritis; Codeine; Pain
PubMed: 35611671
DOI: 10.1080/00325481.2022.2080360 -
Asian Journal of Psychiatry May 2022Strict adherence to pharmacological dosage regimens is a prerequisite to the success of most treatments, particularly for patients in drug abuse programs. The compliance...
BACKGROUND
Strict adherence to pharmacological dosage regimens is a prerequisite to the success of most treatments, particularly for patients in drug abuse programs. The compliance of tramadol, an atypical non-scheduled narcotic analgesic, using objective method has not been adequately studied in an Indian setting.
AIM
To evaluate the compliance and pattern of drug use among opioid-dependent subjects prescribed tramadol based on urinalysis.
METHOD
Fifty male opioid-dependent patients (ICD 10), seeking treatment at a tertiary de-addiction treatment centre of North India on tramadol prescription for atleast past four weeks were included. Self-reported substance use was recorded using semi-structured proforma. Ten ml of urine was collected for the assessment of compliance of tramadol of other substance use (morphine, buprenorphine, dextropropoxyphene, pentazocine, cannabis, benzodiazepines, pheniramine). All these drugs were analyzed using the immunoassay-based Cassette test and Gas Chromatography in human urine.
RESULT
Mean age of the participants was 42.8 years and the mean duration of opioid use was 15.9years. The urine specimen of all subjects tested positive for tramadol. Urinalysis revealed benzodiazepines, cannabis, and pheniramine to be the most common substances of use in this population. It was seen that agreement of self-reporting and urine test results was good for morphine (κ = 0.558) and cannabis (κ = 0.312) and was poor for buprenorphine, pentazocine, and pheniramine.
CONCLUSION
The study demonstrates the continued use of several illicit or non-prescribed medications in a medication-assisted opioid treatment population. The results affirm the reliability of urinalysis as an adjunct for testing compliance in such a population.
Topics: Adult; Analgesics; Analgesics, Opioid; Benzodiazepines; Buprenorphine; Cross-Sectional Studies; Humans; Male; Morphine; Opioid-Related Disorders; Pentazocine; Pheniramine; Reproducibility of Results; Tertiary Care Centers; Tramadol; Urinalysis
PubMed: 35305452
DOI: 10.1016/j.ajp.2022.103080 -
Data in Brief Apr 2021Here we describe the dataset of the first report of pharmacogenomics profiling in an outpatient spine setting with the primary aims to catalog: 1) the genes, alleles,...
Here we describe the dataset of the first report of pharmacogenomics profiling in an outpatient spine setting with the primary aims to catalog: 1) the genes, alleles, and associated rs Numbers (accession numbers for specific single-nucleotide polymorphisms) analysed and 2) the genotypes and corresponding phenotypes of the genes involved in metabolizing 37 commonly used analgesic medications. The present description applies to analgesic medication-metabolizing enzymes and may be especially valuable to investigators who are exploring strategies to optimize pharmacologic pain management (e.g., by tailoring analgesic regimens to the genetically identified sensitivities of the patient). Buccal swabs were used to acquire tissue samples of 30 adult patients who presented to an outpatient spine clinic with the chief concern of axial neck and/or back pain. Array-based assays were then used to detect the alleles of genes involved in the metabolism of pain medications, including all common (wild type) and most rare variant alleles with known clinical significance. Both CYP450 isozymes - including CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 - and the phase II enzyme UDP-glucuronosyltransferase-2B7 (UGT2B7) were examined. Genotypes/phenotypes were then used to evaluate each patient's relative ability to metabolize 37 commonly used analgesic medications. These medications included both non-opioid analgesics (i.e., aspirin, diclofenac, nabumetone, indomethacin, meloxicam, piroxicam, tenoxicam, lornoxicam, celecoxib, ibuprofen, flurbiprofen, ketoprofen, fenoprofen, naproxen, and mefenamic acid) and opioid analgesics (i.e., morphine, codeine, dihydrocodeine, ethylmorphine, hydrocodone, hydromorphone, oxycodone, oxymorphone, alfentanil, fentanyl, sufentanil, meperidine, ketobemidone, dextropropoxyphene, levacetylmethadol, loperamide, methadone, buprenorphine, dextromethorphan, tramadol, tapentadol, and tilidine). The genes, alleles, and associated rs Numbers that were analysed are provided. Also provided are: 1) the genotypes and corresponding phenotypes of the genes involved in metabolizing 37 commonly used analgesic medications and 2) the mechanisms of metabolism of the analgesic medications by primary and ancillary pathways. In supplemental spreadsheets, the raw and analysed pharmacogenomics data for all 30 patients evaluated in the primary research article are additionally provided. Collectively, the presented data offer significant reuse potential in future investigations of pharmacogenomics for pain management.
PubMed: 33644270
DOI: 10.1016/j.dib.2021.106832