Serotoninsyndrom und medikamentöse Schmerztherapie

Individual Pharmacotherapy Management (IPM-II) for Patient and Drug Safety in Polypharmacy via Clinical Electronic Health Record Is Associated with Significant Fall Prevention

BACKGROUND/OBJECTIVES

Falls and fractures are emerging as a near-pandemic and major global health concern, placing an enormous burden on ageing patients and public health economies. Despite the high risk of polypharmacy in the elderly patients, falls are usually attributed to age-related changes. For the "Individual Pharmacotherapy Management (IPM)" established at the University Hospital Halle, the IPM medication adjustments and their association with in-hospital fall prevention were analysed.

METHODS

On the basis of the most updated digital overall patient view via his inpatient electronic health record (EHR), IPM adapts each drug's Summary of Product Characteristics to the patient's condition. A retrospective pre-post intervention study in geriatric traumatology on ≥70 years old patients compared 200 patients before IPM implementation (CG) with 204 patients from the IPM intervention period (IG) for the entire medication list, organ, cardiovascular and vital functions and fall risk parameters.

RESULTS

Statistically similar baseline data allowed a comparison of the average 80-year-old patient with a mean of 11.1 ± 4.9 (CG) versus 10.4 ± 3.6 (IG) medications. The IPM adjusted for drug-drug interactions, drug-disease interactions, overdoses, anticholinergic burden, adverse drug reactions, esp. from opioids inducing increased intrasynaptic serotonin, psychotropic drugs, benzodiazepines, contraindications and missing prescriptions. IPM was associated with a significant reduction in in-hospital falls from 18 (9%) in CG to 3 (1.5%) in IG, a number needed to treat of 14, relative risk reduction 83%, OR 0.17 [95% CI 0.04; 0.76], p = 0.021 in multivariable regression analysis. Factors associated with falls were antipsychotics, digitoxin, corticosteroids, Würzburg pain drip (combination of tramadol, metamizole, metoclopramide), head injury, cognitive impairment and aspects of the Huhn Fall Risk Scale including urinary catheter.

CONCLUSION

The results indicate medication risks constitute a major iatrogenic cause of falls in this population and support the use of EHR-based IPM in standard care for the prevention of falls in the elderly and for patient and drug safety. In terms of global efforts, IPM contributes to the running WHO and United Nations Decade of Healthy Ageing (2021-2030).

Polypharmacy and drug interactions in older patients with cancer receiving chemotherapy: associated factors

BACKGROUND

Polypharmacy in older adults with cancer receiving chemotherapy leads to increased risks of drug interactions, translating in potential hazardous health outcomes. This study aims to assess the prevalence of polypharmacy, drug-drug interactions (DDIs), and severe-drug interactions (SDIs) in older patients with cancer. Antineoplastic agents (ANAs) involvement and possible risk contexts (comorbidities with cardiac risk, and high-risk medications) were also analysed.

METHODS

Observational study with older adults (≥ 65 years) diagnosed with cancer, who were treated with antineoplastic agents (ANAs); it was conducted in three hospitals from the north of Portugal. Data collection was obtained using self-reports and medical records. DDIs were identified and classified using Micromedex® software. Descriptive and association analyze statistics were performed. Statistical hypothesis tests with p value less than 0.05 were considered significant. All statistical procedures and analysis were performed with R version 4.1.3.

RESULTS

We enrolled 552 patients. Polypharmacy prevalence was 88.40%; 76.45% and 56.16% of the patients presented with DDIs and SDIs, respectively. SDIs with ANAs were found in 21.20% of the patients. High-risk medications were associated with a higher risk of polypharmacy, DDIs, and SDIs. Polypharmacy and DDIs were higher in patients with hypertension or diabetes. SDIs were higher in patients with diabetes.

CONCLUSION

Polypharmacy, potential DDIs and SDIs were highly prevalent in older adults with cancer. A careful review of the medication administered is necessary to decrease it. These findings warrant further research to optimize medication in this population and decrease problems related to medication, which may lead to emergency room visits and hospitalisations, compromising patient safety and/or ongoing treatments.

Serotonin Syndrome in an Infant Associated With Linezolid and Opioid Use

Most reported cases of serotonin syndrome involve either a selective serotonin reuptake inhibitor (SSRI) or monoamine oxidase inhibitors (MAOI) and at least 1 other serotonergic medication or exposure to a single serotonin-augmenting drug. This case report describes serotonin syndrome occurring in association with the concomitant use of the antibiotic linezolid and opioids, specifically methadone, in a pediatric intensive care unit patient. The patient developed hyperpyrexia, muscle rigidity, clonus, and multiorgan dysfunction within 48 hours of receiving linezolid while concurrently on methadone. This drug-drug interaction is a rare cause of serotonin syndrome that has only been described 1 other time in the adult literature. This report raises awareness of this rare but serious and potentially lethal complication of serotonin syndrome associated with concomitant linezolid and opioid use. Timely consideration of the diagnosis in the setting of hyperpyrexia can facilitate prompt initiation of targeted therapies to prevent sequela.

Trends in MDMA-related mortality across four countries

AIMS

To determine trends in 3,4 methylenedioxymethamphetamine (MDMA)-related death rates across Australia, Finland, Portugal and Turkey and to analyse the toxicology and causes of death across countries.

DESIGN

Analysis of MDMA-related deaths extracted from a national coronial database in Australia (2001-19) and national forensic toxicology databases in Finland (2001-17), Portugal (2008-19) and Turkey (2007-17). Presentation of MDMA use and seizure data (market indicators).

SETTING

Australia, Finland, Portugal and Turkey.

CASES

All deaths in which MDMA was considered by the forensic pathologist to be contributory to death.

MEASUREMENTS

Information collected on cause and circumstances of death, demographics and toxicology.

FINDINGS

A total of 1400 MDMA-related deaths were identified in Turkey, 507 in Australia, 100 in Finland and 45 in Portugal. The median age ranged from 24 to 27.5 years, and males represented between 81 and 94% of the deaths across countries. Standardized mortality rates significantly increased across all four countries from 2011 to 2017 during a period of increased purity and availability of MDMA. The underlying cause of death was predominantly due to drug toxicity in Australia (n = 309, 61%), Finland (n = 70, 70%) and Turkey (n = 840, 60%) and other causes in Portugal (n = 25, 56%). Minorities of all deaths across the countries were due to MDMA toxicity alone (13-25%). These deaths had a significantly higher blood MDMA concentration than multiple drug toxicity deaths in Australia, Finland and Turkey. Drugs other than MDMA commonly detected were stimulants (including cocaine, amphetamine and methamphetamine) (Australia 52% and Finland 61%) and alcohol (Australia 46% and Portugal 49%). In addition to MDMA toxicity, benzodiazepines (81%) and opioids (64%) were commonly identified in these deaths in Finland. In comparison, synthetic cannabinoids (15%) and cannabis (33%) were present in a minority of deaths in Turkey.

CONCLUSIONS

Deaths related to 3,4 methylenedioxymethamphetamine (MDMA) increased in Australia, Finland, Portugal and Turkey between 2011 and 2017. Findings show MDMA toxicity alone can be fatal, but multiple drug toxicity remains more prevalent.

Construction of a Virtual Opioid Bioprofile: A Data-Driven QSAR Modeling Study to Identify New Analgesic Opioids

Compared to traditional experimental approaches, computational modeling is a promising strategy to efficiently prioritize new candidates with low cost. In this study, we developed a novel data mining and computational modeling workflow proven to be applicable by screening new analgesic opioids. To this end, a large opioid data set was used as the probe to automatically obtain bioassay data from the PubChem portal. There were 114 PubChem bioassays selected to build quantitative structure-activity relationship (QSAR) models based on the testing results across the probe compounds. The compounds tested in each bioassay were used to develop 12 models using the combination of three machine learning approaches and four types of chemical descriptors. The model performance was evaluated by the coefficient of determination (R ²) obtained from 5-fold cross-validation. In total, 49 models developed for 14 bioassays were selected based on the criteria and were identified to be mainly associated with binding affinities to different opioid receptors. The models for these 14 bioassays were further used to fill data gaps in the probe opioids data set and to predict general drug compounds in the DrugBank data set. This study provides a universal modeling strategy that can take advantage of large public data sets for computer-aided drug design (CADD).

Drug Interaction and Serotonin Toxicity with Opioid Use: Another Reason to Avoid Opioids in Headache and Migraine Treatment

Treatment of headache, specifically migraine attacks, has always been a challenging subject, especially for neurologist and pain specialists. Triptans are generally underutilized, despite being the gold standard abortive medication for migraine attacks. On the other hand, opioid analgesics are overused as a treatment for headache. One reason for this could be physician unfamiliarity with drug interactions between opioids and other medications, especially the possibility of serotonin toxicity. The general awareness of potential serotonin toxicity with using opioid analgesics is low. In this review, we will conduct a theoretic and evidence-based review of the potential for developing serotonin syndrome in patients who are using opioids analgesics, especially in combination with antidepressants, a common co-prescribed combination. We also review the current diagnostic criteria for serotonin syndrome and identify possible shortcomings of those criteria. Our aim is to increase the awareness of health care providers about potential drug interaction of opioid analgesics with other classes of medication. We place particular emphasis on tramadol since this drug is one of the most commonly used opioid analgesics for headache. The potential for developing serotonin syndrome is relatively high in the patients who are using opioid for pain control. The use of opioids in migraine headache is already discouraged due to the high risk of medication overuse headache and also an increase in headache-related disability (Katsarava et al. Neurology 62:788-790, 2004; Bigal and Lipton. Neurology 71:1821-8, 2008; Casucci and Cevoli. Neurol Sci. 34 Suppl 1:S125-8, 2013). This is another reason that physicians and health care providers should avoid using this class of medication for pain, specifically headache and migraine treatment.

[Drug interactions in pain therapy]

BACKGROUND

Pain is one of the most common reasons for consulting a physician. Chronic pain patients often suffer from a variety of comorbidities, such as depression and anxiety and they are therefore often simultaneously treated with more than one drug. The probability of drug interactions increases with every additional drug.

MATERIAL AND METHODS

A systematic internet and literature search up to February 2015 was carried out. Systematic lists were included. In addition, the drug prescription information sheets were used and an internet search via Pubmed and google.com was carried out for drugs alone and in combination in order to find substance-specific interactions.

RESULTS

A differentiation is made between pharmaceutical, pharmacodynamic and pharmacokinetic drug interactions. Pharmaceutical interactions are caused by chemical, physical or physicochemical incompatibility of drugs or adjuvants used. These can even occur outside the body and during concomitant administration via the same route. A pharmacodynamic interaction in pain management is for example the additive sedative effect of opioids and benzodiazepines when taken together. Pharmacokinetic interactions occur during the absorption, distribution, metabolism and in the elimination phases.

CONCLUSION

Many drug interactions can be avoided by careful and continuous evaluation of pharmacotherapy and if necessary its adaptation; however, a sound knowledge of the underlying pharmacological mechanisms and the properties of currently used analgesics is necessary.