ChatGPT: First Glance from a Perspective of Clinical PharmacologyAuthors: Julie Rudbech Krumborg1,2, Nicolaj Mikkelsen1,2, Per Damkier1,2, Zandra Nymand Ennis1,2, Daniel Pilsgaard Henriksen1,2, Mads Lillevang-Johansen1,2, Sidsel Arnspang Pedersen1,2, Troels K Bergmann1,31. Department of Clinical Pharmacology, Odense University Hospital, Denmark2. Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Denmark3. Department of Regional Health Research, University of Southern Denmark, Esbjerg, DenmarkCorresponding author: Julie Rudbech Krumborg: Julie.Rudbech.Krumborg@rsyd.dkKeywords : Artificial intelligence, Clinical Pharmacology, Drug Information Services, evidence-based medicine, Medical WritingConflict of interest statement: The authors state no conflicts of interest
Background: Serotonin syndrome is a potentially life-threatening syndrome with manifestations spanning from mild adverse effects to life-threatening toxicity. The syndrome is caused by overstimulation of serotonin receptors by serotonergic drugs. Since the use of serotonergic drugs is increasing, primarily due to the widespread use of selective serotonin reuptake inhibitors, cases of serotonin syndrome have likely seen a parallel increase. The true incidence of serotonin syndrome remains unknown due to its diffuse clinical presentation. Objectives: This review aims to provide a clinically focused overview of serotonin syndrome, covering its pathophysiology, epidemiology, clinical manifestations, diagnostic criteria, differential diagnosis, and treatment as well as classifying serotonergic drugs and their mechanism of action. The pharmacological context is emphasized, as it is crucial for detection and management of serotonin syndrome. Methods: Focused review based on a literature search using the PubMed database. Findings and conclusion: Serotonin syndrome can occur through therapeutic use or overdose of a single serotonergic drug, or as a drug interaction between two or more serotonergic drugs. Central clinical features consist of neuromuscular excitation, autonomic dysfunction and altered mental status, occurring in a patient undergoing new or altered serotonergic therapy. Early clinically recognition and treatment are crucial to prevent significant morbidity.
Interventions to promote deprescribing are an important focus of research. Key decisions for such interventions are whether to target one or multiple medicines, and whether the intervention scope is deprescribing, or also extends to other aspects of medicines optimisation. This article reflects on how these decisions impact on developing interventions and measuring outcomes. Many behavioural strategies are common to deprescribing and medicines optimisation, however operationalisation may differ. Aspects to consider include the burden of multiple simple interventions versus one complex intervention, the extent to which the approach to deprescribing can be specified as part of the intervention, and variability in how the intervention is delivered across patients and providers. Outcomes should be selected based on the intervention target and scope and the audience for whom evidence is being produced. These may include medication changes, and process outcomes to assess intervention delivery. Targeting single medications may allow for a focus on specific clinical or symptom-related outcomes, rather than more general outcomes such as adverse drug reactions. Cost-related outcomes are also important to inform implementation decisions, and modelling approaches may be more feasible for interventions targeting single medications.
Background: A quasi-experimental study investigated a pharmacist-led intervention aimed at deprescribing among patients with type 2 diabetes at risk of hypoglycaemia. Objective: To evaluate the process of implementing the intervention in primary care in order to understand variations in implementation and outcomes. Methods: Mixed-methods study based on the Grant-framework, with 10 domains, including recruitment of patients, delivery of the intervention, and response of pharmacists and patients. Data collected were: administrative logs, semi-structured observations of patient consultations (n=8), interviews with pharmacists (n=16), and patient-reported experience measure (PREM) questionnaires (n=66; response 73%). Results: Ninety patients from 14 pharmacies were included. Although the selection of patients based on high hypoglycaemia-risk was considered useful, pharmacists experienced barriers to proposing deprescribing in patients with recent medication changes, patients without current health problems or hypoglycaemic events, and patients treated in secondary care. The consultation aid and deprescribing tool provided were evaluated positively by the pharmacists. The majority of patients were satisfied with the service and information that the pharmacists provided. Conclusion: Pharmacists and patients were positive about the intervention. Both groups valued the consultation on deprescribing, supported by tools. To optimise the effect, improvements can be made to patient selection and local agreements on proactive deprescribing.
Deprescribing search filters aiming at maximizing sensitivity for MEDLINE and for Embase were recently developed. Simultaneously, The US Deprescribing Network (USden) developed a deprescribing search strategy that included a deprescribing search filter for MEDLINE. The aim of this case study was to implement these deprescribing search filters in original search strategies from deprescribing related systematic reviews (SRs) and to calculate their performances. Two deprescribing SRs were included. Authors were asked to repeat the selection process described in SRs original methods. Performances of search strategies implemented with deprescribing search filters (ISS) were calculated and compared to original search strategies (OSS). In MEDLINE, sensitivity for SR 1 was 50% for OSS (Precision: 2.8%), 58% for ISS with maximised sensitivity filter (Precision: 1.7%) and 42% for ISS with USden filter (Precision: 5.1%). Sensitivity for SR 2 was 25% for all search strategies (Precision: 0.1%, 0.2% and 1,2% respectively). In Embase, sensitivity for SR 1 was 33% (Precision: 4,1%) for OSS and 58% for ISS (Precision 2.1%). No articles were included through Embase search strategies for SR 2. Using maximized sensitivity deprescribing filters may increase the exhaustivity of deprescribing SRs. Precision offered by the USDeN deprescribing filter is a convenient alternative for non-systematic reviews.
Medication reviews focusing on deprescribing can reduce potentially inappropriate medication; however, evidence regarding the effects on health-related outcomes is scares. In a real-life, quality improvement project, we aimed to investigate how a general practitioner-led medication review intervention with focus on deprescribing affected health-related outcomes. We performed a before-after intervention study including care home residents and community-dwelling patients affiliated with a large Danish general practice. The primary outcomes were changes in self-reported health status, general condition, and functional level from baseline to 3-4 months follow-up. Of 105 included patients, 87 completed follow-up. From baseline to follow-up, 255 medication changes were made, of which 83% were deprescribing. Mean self-reported health status increased from 7.3 to 7.9 (0.6 [95% CI: 0.2 to 0.9]); the proportion of patients with general condition rated as “average or above” was stable (74.7% to 80.5% (5.7% [95% CI: -3.4 to 14.9]); and the proportion of patients with functional level “without any disability” was stable (58.6% to 54.0% (-4.6% [95% CI: -10.1 to 1.0]). In conclusion, this general practitioner-led medication review intervention led to deprescribing and increased self-reported health status without deterioration of general condition or functional level in real-life primary care patients.
Background: Deprescribing is a complex process requiring a patient-centred approach. One frequently expressed deprescribing barrier is patients’ attitudes and beliefs toward reducing or stopping a medication. This study aims to identify the willingness to deprescribe predictors in a sample of Portuguese older patients. Methods: Cross-sectional study with community-dwelling patients aged ≥ 65 and taking at least one regular medication. Data collection included patients’ demographic and clinical characteristics and the Portuguese Revised Patients’ Attitudes Towards Deprescribing (rPATD) Questionnaire. Descriptive statistics were used to present patients’ characteristics and attitudes towards deprescribing. A multiple binary logistic regression analysis was performed to identify willingness to desprescribe predictors. Results: 192 participants (median age 72 years; 65.6% female) were included. A large majority (83.33%) were willing to deprescribe if recommended by their doctor. The willingness to desprescribe predictors were age (adjusted odds ratio (aOR)= 1.136), female sex (aOR= 3.036), and the rPATD concerns about stopping (aOR= 0.391). Conclusions: Most patients were willing to deprescribe if recommended by their doctor. Older age and female sex increase the odds of willingness to deprescribe; conversely, higher concerns about stopping medications decrease the odds. These findings suggest that addressing patients’ concerns about stopping their medicines may contribute to deprescribing success.
Adhesion G protein-coupled receptors (aGPCRs) possess a unique topology including the presence of a GPCR proteolysis site (GPS) which upon autoproteolysis generates two functionally distinct fragments that remain non-covalently associated at the plasma membrane. A proposed activation mechanism for aGPCRs involves the release of a tethered agonist which depends on cleavage at the GPS. However, this hypothesis has been challenged by the observation that non-cleavable aGPCRs exhibit constitutive activity, thus making the function of GPS cleavage widely enigmatic. In this study, we sought to elucidate the function of GPS-mediated cleavage through the study of G protein coupling with Latrophilin-3/ADGRL3, a prototypical aGPCR involved in synapse formation and function. Using BRET-based G protein biosensors, we reveal that an autoproteolysis-deficient mutant of ADGRL3 retains constitutive activity. Surprisingly, we uncover that cleavage deficiency leads to a signaling bias directed at potentiating the activity of select G proteins such as Gi2 and G12/13. These data unveil the underpinnings of biased signaling for aGPCRs defined by GPS autoproteolysis.
Deprescribing is an essential component of safe prescribing, especially for people with higher levels of polypharmacy. Identifying individuals prepared to consider medicine changes may facilitate deprescribing-orientated reviews. We aimed to explore the relationship between revised patient attitudes towards deprescribing (rPATD) scores and medication changes in older people prescribed ≥15 medicines. A secondary analysis of rPATD scores and prescription data from a cluster randomised controlled trial of a GP-delivered, deprescribing-orientated medication review was conducted. The association between number of medicines stopped, started and changed and baseline rPATD scores was assessed using Poisson regression adjusting for patient age, gender, study group allocation, baseline number of medicines and effects of clustering. Participants (n=404) had a mean age of 76.4 years and were prescribed a mean of 17.1 medicines at baseline. Willingness to stop a medicine was associated with higher rates of both deprescribing (IRR: 1.40; 95%CI: 1.06-1.84) and initiating medicines (IRR: 1.43; 95%CI: 1.09-1.88). Satisfaction with current medicines was associated with a lower rate of deprescribing (IRR: 0.69; 95%CI: 0.57-0.85). The rPATD questionnaire could be used as part of a deprescribing intervention to identify participants who may be prepared to engage in deprescribing, enabling more efficient use of clinician time during complex consultations.
The future of deprescribing research: seizing opportunities and learning from the past Michael A. Steinman, MDUniversity of California, San Francisco and the San Francisco VA Medical CenterWord count: 1549References: 10Funding: This work was supported by the National Institute on Aging (grants R24AG064025 and K24AG049057)Disclosures: Dr. Steinman receives royalties from UpToDate and honoraria from the American Geriatrics Society. This manuscript is based on a lecture given at the First International Conference on Deprescribing (ICOD), Kolding, Denmark, September 2022.
Objective: Combining different drugs increases the potential for drug-drug interactions en-hancing the risk of adverse drug reactions. We aimed to unravel potential pharma-cokinetic interactions between aripiprazole and duloxetine. Methods: Plasma concentrations of aripiprazole of two groups of 78 patients each, receiving aripiprazole as a monotherapy, or combined with duloxetine, were compared. A po-tential impact of duloxetine on the metabolism of aripiprazole was expected in high-er plasma concentrations of aripiprazole and higher dose-adjusted plasma concen-trations. Results: Patients co-medicated with duloxetine showed significantly higher plasma concen-trations of aripiprazole (p=0.019) by 54.2%. Dose-adjusted plasma concentrations were 45.6% higher (p=0.001). 65.4 % of these patients exhibited aripiprazole plasma concentrations above the upper limit of the therapeutic reference range, in the con-trol group this was only the case for 43.6% of the patients (p=0.006). A positive rela-tionship was found between the daily dose of duloxetine and dose-adjusted plasma concentrations of aripiprazole (p=0.034). Conclusions: Combining duloxetine and aripiprazole leads to significantly higher drug concentra-tions of aripiprazole, most likely via an inhibition of cytochrome P450 CYP2D6 and to a lesser extent of CYP3A4 by duloxetine. Clinicians have to consider increasing aripiprazole concentrations when adding duloxetine to a treatment regimen with ari-piprazole.
GPR56/ADGRG1 is an adhesion GPCR and mutations on this receptor cause cortical malformation due to the over-migration of neural progenitor cells on the brain surface. At the pial surface, GPR56 interacts with collagen III, induces Rho dependent activation through Gα12/13 and inhibits the neuronal migration. In human glioma cells, GPR56 inhibits cell migration through Gαq/11 dependent Rho pathway. GPR56-tetraspanin complex is known to couple with Gαq/11. GPR56 is an aGPCR that couples with various G proteins and signals through different downstream pathways. In this study, BFPP mutants disrupting GPR56 function but remain to be expressed on plasma membrane were used to study receptor signaling through Gα12, Gα13 and Gα11 with BRET biosensors. GPR56 showed coupling with all three G proteins and activated heterotrimeric G protein signaling upon stimulation with Stachel peptide. However, BFPP mutants showed different signaling defects for each G protein indicative of distinct activation and signaling properties of GPR56 for Gα12, Gα13 or Gα11. β-arrestin recruitment was also investigated following the activation of GPR56 with Stachel peptide using BRET biosensors. N-terminally truncated GPR56 showed enhanced β-arrestin recruitment, however neither wild-type receptor nor BFPP mutants gave any measurable recruitment upon Stachel stimulation, pointing different activation mechanisms for β-arrestin involvement.
VLGR1/ADGRV1 (very large G protein-coupled receptor-1) is the largest known adhesion G protein-coupled receptor. Mutations in VLGR1/ADGRV1 cause Usher syndrome (USH), the most common form of hereditary deaf-blindness, and have been additionally linked to epilepsy. Although VLGR1/ADGRV1 is almost ubiquitously expressed, little is known about the subcellular function and signalling of the VLGR1 protein and thus about mechanisms underlying the development of diseases. Using affinity proteomics, we have identified key components of autophagosomes as putative interacting proteins of VLGR1. In addition, whole transcriptome sequencing of the retinae of the Vlgr1/del7TM mouse model revealed altered expression profiles of gene-related autophagy. Monitoring autophagy by immunoblotting and immunocytochemistry of the LC3 and p62 as autophagy marker proteins revealed evoked autophagy in VLGR1-deficient hTERT-RPE1 cells and USH2C patient-derived fibroblasts. Our data demonstrate the molecular and functional interaction of VLGR1 with key components of the autophagy process and point to an essential role of VLGR1 in the regulation of autophagy at internal membranes. The close association of VLGR1 with autophagy helps to explain the pathomechanisms underlying human USH and epilepsy-related to VLGR1 defects.
VLGR1/ADGRV1 (very large G protein-coupled receptor-1) is the largest adhesion G protein-coupled receptor aGPCRs. Mutations in VLGR1/ADGRV1 are associated with human Usher syndrome (USH), the most common form of deaf-blindness, and also with epilepsy in humans and in mice. Although VLGR1 is almost ubiquitously expressed in CNS and ocular and inner ear sensory cells. Little is known about the pathogenesis of the diseases related to VLGR1. We previously identified VLGR1 as a vital component of focal adhesions (FA) serving as a metabotropic mechanoreceptor that controls cell spreading and migration. FAs are highly dynamic and turnover frequently in response to internal and external signals. Here, we aimed to elucidate how VLGR1 participates in FA turnover. Nocodazole washout assays and live-cell imaging of RFP-paxillin consistently demonstrated that FA disassembly was not altered, de novo assembly of FA was significantly delayed in Vlgr1-deficient astrocytes indicating that VLGR1 is enrolled in the assembly of FAs. In FRAP experiments recovery rates were significantly reduced in Vlgr1-deficient FAs, indicating reduced turnover kinetics in VLGR1-deficient FAs. We showed that VLGR1 regulates cell migration by controlling the FA turnover during their assembly. From this, we expect novel insights into pathomechanisms related to pathogenic dysfunctions of VLGR1.
The present study evaluates the influence of type 2 diabetes (T2D) on important CYP450 isoforms and P-glycoprotein (P-gp) transporter activities before and 3 months after intensifying treatment regimen of 40 patients. Results have been compared with 21 non-T2D healthy participants (control group). CYPs and P-gp activities were assessed after administration of Geneva cocktail. Mean metabolic ratios (MR) for CYP2B6 (1.81±0.93 vs. 2.68±0.87), CYP2C19 (0.420 ± 0.360 vs. 0.687 ± 0.558), and CYP3A4/5 (0.487 ± 0.226 vs. 0.633 ± 0.254) significantly decreased in T2D subjects compared to control group (p<0.05). CYP2C9 (0.089±0.037 vs. 0.069±0.017) activities slightly increased in diabetic subjects and no difference was observed for CYP1A2 (0.154±0.085 vs. 0.136±0.065), CYP2D6 (1.17 ± 0.56 vs. 1.24 ± 0.83) and P-gp activities in comparison with control group. Three months after intensifying treatment regimen, MRs of CYP2C9 (0.080 ± 0.030) and CYP3A4/5 (0.592 ± 0.268) have shown a significant improvement and were not statistically different compared to control group (P>0.05). Several covariables such as inflammatory markers (IL-1β and IL-6), genotypes, diabetes- and demographic-related factors were considered in our analyses. Our results indicate that low chronic inflammatory status associated with T2D modulates CYP450 activities in an isoform specific manner.
4-Methylbenzylidene camphor (4-MBC) is a photo-absorbing UV filter, which can be absorbed into the circulation and cause systemic effects. 4-MBC is found extensively in the environment and measurements suggest bioaccumulation in human tissues. 4-MBC is continued to be released in the environment despite the growing knowledge about its potential endocrine and reproductive disrupting effects. 4-MBC interfers with various processes, such as placental development, spermatogenesis, and inflammatory cascades. Previous reviews mention 4-MBC as one of the several UV filters but here we focus on 4-MBC only. We cover the potential effects on human health regarding systemic and molecular effects, with the focus on reproduction. We also cover the potential bioaccumulation and interactions with receptor systems, such as the estrogen receptors β and α, and progesterone receptor, and analyze 4-MBC´s effects on mRNA expression and protein expression. Furthermore, 4-MBC is reported to act with inflammatory pathways by activating p38 MAPK and NF-κB, leading to the production of inflammatory TNF-α and IL-6. In conclusion, 4-MBC has wide ranging effects in different models while there is more research warranted to detail the mechanism of action, long-term effects at low doses and the potential interaction with many pathways and other pollutants.