Are drug-drug interactions a real clinical concern?

Assessment of co-ingestion effects on poisoning patterns, drug-drug interactions, and adverse outcomes in acute toxic exposure

Multiple toxic exposures are increasing nowadays. In cases of acute poisoning involving multiple agents, there is a potential for additional toxicity that goes beyond the effects and toxicity of each drug. Very scarce studies have investigated the problem of multiple toxic exposures where the information on drug-drug interactions (DDIs) originates from clinical experience, which is inconclusive and cannot be generalized to patients. Therefore, the current study aimed to explore the influence of co-ingestion on the clinical presentation of exposed patients and to identify the common associated DDIs and their effect on poisoning outcomes, including the need for mechanical ventilation (MV), intensive care unit (ICU) utilization, and prolonged hospital stay. The current study is a retrospective cross-sectional study that was conducted using medical records of 169 adult patients admitted to a poison control center and diagnosed with acute drug poisoning. Of them, 40.8 % were exposed to multiple drugs. The total number of drugs reported in the current study was 320 preparations, with an average of 1.9 drugs per patient. There were about 726 potential DDIs; more than half of these interactions were significant (n = 486). Antidepressants and psychotropics showed the highest total number of DDIs. Patients with multiple ingestion were significantly older and this pattern of exposure was more frequent among suicidal attempters, substance abusers, cardiac patients, and patients diagnosed with neurological and psychological problems. Moreover, patients with multiple ingestions showed severe presentations indicated by higher grades of Poison Severity Score and lower Glasgow Coma Scale. Multiple ingestion was associated with higher liability for MV, ICU admission, and prolonged length of hospital stay (p < 0.001). There was a significant moderate direct correlation between the number of drugs consumed and the number of resulting DDIs (r = 0.542, p < 0.001). There was a significant direct correlation between the occurrence of significant chronic/chronic drug interactions from one side and the history of substance abuse (r = 0.596, p = 0.041) and psychological illness (r = 0.662, p = 0.019) from the other side. Moreover, significant acute/acute drug interactions were correlated with being male (r = 0.969, p < 0.001) of older age (r = 0.672, p = 0.024). Similarly, significant acute/chronic drug interactions were moderately correlated with being a male (r = 0.692, p = 0.013). The presence of epilepsy and psychological problems were the main significant predictors of multiple acute toxic exposures. Among the patients exposed acutely to more than one agent who were on long-term treatment, exposure to three drugs or more could significantly predict the need for MV with excellent area under the curve (AUC) of 0.896 and 77.0 % accuracy. Moreover, and it was a fair predictor of ICU admission (AUC = 0.625), with an 88.9 % ability to exclude patients unlikely to need ICU admission. Particular attention should be paid to the patients at risk of potential DDIs. When prescribing drugs, the minimum number of drugs with the lowest effective doses, and minimal potential DDIs should be prioritized.

Cognitive task analysis of clinicians' drug-drug interaction management during patient care and implications for alert design

BACKGROUND

Drug-drug interactions (DDIs) are common and can result in patient harm. Electronic health records warn clinicians about DDIs via alerts, but the clinical decision support they provide is inadequate. Little is known about clinicians' real-world DDI decision-making process to inform more effective alerts.

OBJECTIVE

Apply cognitive task analysis techniques to determine informational cues used by clinicians to manage DDIs and identify opportunities to improve alerts.

DESIGN

Clinicians submitted incident forms involving DDIs, which were eligible for inclusion if there was potential for serious patient harm. For selected incidents, we met with the clinician for a 60 min interview. Each interview transcript was analysed to identify decision requirements and delineate clinicians' decision-making process. We then performed an inductive, qualitative analysis across incidents.

SETTING

Inpatient and outpatient care at a major, tertiary Veterans Affairs medical centre.

PARTICIPANTS

Physicians, pharmacists and nurse practitioners.

OUTCOMES

Themes to identify informational cues that clinicians used to manage DDIs.

RESULTS

We conducted qualitative analyses of 20 incidents. Data informed a descriptive model of clinicians' decision-making process, consisting of four main steps: (1) detect a potential DDI; (2) DDI problem-solving, sensemaking and planning; (3) prescribing decision and (4) resolving actions. Within steps (1) and (2), we identified 19 information cues that clinicians used to manage DDIs for patients. These cues informed their subsequent decisions in steps (3) and (4). Our findings inform DDI alert recommendations to improve clinicians' decision-making efficiency, confidence and effectiveness.

CONCLUSIONS

Our study provides three key contributions. Our study is the first to present an illustrative model of clinicians' real-world decision making for managing DDIs. Second, our findings add to scientific knowledge by identifying 19 cognitive cues that clinicians rely on for DDI management in clinical practice. Third, our results provide essential, foundational knowledge to inform more robust DDI clinical decision support in the future.

Drug-drug interactions of protein kinase inhibitors in chronic myeloid leukaemia patients: A study using the French health insurance database

The introduction of protein kinase inhibitors (PKIs) for chronic myeloid leukaemia (CML) has considerably improved prognosis of the disease but has also demonstrated a great potential for drug-drug interactions. Using the French health insurance databases, we aim to investigate the frequency, identify the associated factors and describe the potential consequences of potential drug-drug interactions (pPKI-DIs) between PKIs and concurrent medications in CML. A retrospective cohort study has been performed among patients with CML identified in the French healthcare database from 2011 to 2014. A pPKI-DI is defined as the presence of drugs listed as 'interacting' on the same day as PKI dispensing (co-dispensing) or in its coverage period (co-medication) during the first year of follow-up. The list of interacting drugs is based on the summary of products characteristics (SPCs) and Thesaurus of interactions. We performed specific nested case-control comparisons to investigate the association between PKI-DI and each of the three potential outcomes (death, hospitalisation for adverse drug reactions and switch to another PKI). We included 3480 patients; 1429 (41%) had a co-dispensing pPKI-DI, and 2153 (62%) had a co-medication pPKI-DI; 50% of the pPKI-DIs were 'to be taken into account', and 17% were 'not recommended'. The PKI with the most interactions was imatinib, and additional common drug classes included statins, benzodiazepines and proton pump inhibitors. Multivariate analysis demonstrated that the use of a higher number of additional drugs, comorbidities at baseline, high number of prescribers and higher ages were potential risk factors. Nilotinib and dasatinib showed a tendency towards a higher risk of pPKI-DI compared to imatinib. Despite the fact that some PKI-DIs were potentially clinically relevant, we did not find any significant association with death, hospitalisation for adverse drug reactions and switching. These findings should increase awareness to help reduce the prevalence of PKI-drug interactions and thereby ensure better management of CML patients.

Efficacy of Short-Term High Dose Pulsed Dapsone Combination Therapy in the Treatment of Chronic Lyme Disease/Post-Treatment Lyme Disease Syndrome (PTLDS) and Associated Co-Infections: A Report of Three Cases and Literature Review

Lyme disease and associated co-infections are increasing worldwide and approximately 20% of individuals develop chronic Lyme disease (CLD)/Post-Treatment Lyme Disease Syndrome (PTLDS) despite early antibiotics. A seven- to eight-week protocol of double dose dapsone combination therapy (DDDCT) for CLD/PTLDS results in symptom remission in approximately 50% of patients for one year or longer, with published culture studies indicating higher doses of dapsone demonstrate efficacy against resistant biofilm forms of Borrelia burgdorferi. The purpose of this study was, therefore, to evaluate higher doses of dapsone in the treatment of resistant CLD/PTLDS and associated co-infections. A total of 25 patients with a history of Lyme and associated co-infections, most of whom had ongoing symptoms despite several courses of DDDCT, took one or more courses of high dose pulsed dapsone combination therapy (200 mg dapsone × 3-4 days and/or 200 mg BID × 4 days), depending on persistent symptoms. The majority of patients noticed sustained improvement in eight major Lyme symptoms, including fatigue, pain, headaches, neuropathy, insomnia, cognition, and sweating, where dapsone dosage, not just the treatment length, positively affected outcomes. High dose pulsed dapsone combination therapy may represent a novel therapeutic approach for the treatment of resistant CLD/PTLDS, and should be confirmed in randomized, controlled clinical trials.

Prevalence and factors associated with polypharmacy and potential drug interactions in adults in Manaus, Amazonas state, Brazil: a cross-sectional population-based study, 2019

OBJECTIVE

To assess the prevalence and factors associated with polypharmacy and the presence of potential drug interactions in Manaus, Amazonas state, Brazil, in 2019.

METHODS

This was a population-based cross-sectional study conducted with adults aged ≥ 18 years. The presence of drug interactions among people on a polypharmacy regimen (≥ 5 drugs) was investigated on the Micromedex database. Prevalence ratios (PR) with 95% confidence intervals (95%CI) were calculated using Poisson regression model with robust variance, following hierarchical analysis and considering the complex sample design.

RESULTS

Of the 2,321 participants, 2.8% (95%CI 2.1;3.6) were on polypharmacy regimen, of whom, 74.0% presented drug interactions, usually with four or more drug interactions per person (40.4%) and high severity (59.5%). Polypharmacy was higher among older adults (PR = 3.24; 95%CI 1.25;8.42), people with poor health (PR = 2.54; 95%CI 1.14;5.67), previous hospitalization (PR = 1.90; 95%CI 1.09;3.32) and multimorbidity (PR = 3.20; 95%CI 1.53;6.67).

CONCLUSION

Polypharmacy was more frequent among older adults and people with medical problems, who presented more drug interactions.

Basic principles of combination therapy: focus on drug-drug interaction

The article is devoted to the issue of drug interactions in the combination regimens. Today, when drug therapy is the first-line approach for patients with noncommunicable diseases, and the world population ageing leads to an increase in the number of patients with severe comorbidity and polypharmacy, the problem of drug-drug interaction is especially relevant. The article discusses the main types of drug interactions  — pharmacokinetic (related to absorption, distribution, metabolism and excretion of drugs) and pharmacodynamic ones, leading to synergy or antagonism of the pharmacological effects. The consequences of drug interactions can be desirable and undesirable, while the latter are much more common. Attention should be directed precisely to preventing such interactions. Also, using data from special scales and lists (Beers criteria, STOPP/START criteria), the options for various adverse drugdrug interactions are briefly described. In addition, the article provides a number of Internet resources that allow assessing the drug interaction risk when prescribing combination therapy.