Prevalence of drug-drug interactions in older people before and after hospital admission: analysis from the OPERAM trial

The OPERAM trial included older (≥70 years) patients with multimorbidity (≥3 chronic medical conditions) and polypharmacy (≥5 chronic medications) [19]. In this trial, 2008 hospitalized patients were enrolled between December 2016 and October 2018 in four medical centers in Bern (Switzerland), Brussels (Belgium), Cork (Ireland) and Utrecht (The Netherlands) [19]. The date of study inclusion (baseline, t₀) was the first day of the index hospitalization. Follow-up data were collected at the end of the index hospitalization (discharge, t₁) and via telephone interviews at 2 (t₂), 6 (t₆) and 12 (t₁₂) months after baseline. A blinded trial team member evaluated and reported all medications taken on those dates, as well as hospitalizations and deaths. Details of the protocol and intervention have been published previously [19‐23]. The OPERAM trial received approval from ethics committees at each site. All methods were performed in accordance with the relevant guidelines and regulations.

All the patients included in the OPERAM trial who were alive, had not withdrawn and were not lost to follow-up at hospital discharge, and had full medication data during the index hospitalization were included in this substudy (to be able to measure our main criterion) [19]. Patients with medication data at time t, but with no medication data at t_− 1, were censored at t_− 1. For example, a few patients had medication data at 6 months but not at 2 months; these patients were censored at 2 months.

DDIs were identified using recently defined the list of 66 potentially clinically significant DDIs [11]. Throughout the rest of the manuscript, the term “DDI” is used to refer to these potentially clinically significant DDIs.

The drugs most frequently involved in DDIs are cardiovascular, antithrombotic and central nervous system drugs. The expert panel list provides details on the type and mechanism of the DDI (i.e., pharmacodynamic, pharmacokinetic or both), potential harmful effect(s), and management (Additional file 1). An algorithm based on the Anatomical Therapeutic Chemical (ATC) codes of the 66 DDIs was developed (available via https://github.com/agapiospanos/DDI). This algorithm was used to identify DDIs in our patients at the different time points.

In the present study, potential harm resulting from the DDI was evaluated by allocating each DDI to one of the following categories: serious cardiovascular adverse effects; serious neurological adverse effects; bleeding; deterioration of renal function and/or hyperkalemia (including severe myopathy and rhabdomyolysis, which may lead to acute renal failure); hematologic toxicity; and miscellaneous others (Additional file 2).

The prevalence of DDIs at 2 months post-randomization compared to that at baseline was defined as having increased if there was a new prescription giving rise to one or more new DDIs or decreased if deprescription had resulted in removal of one or more DDIs. The 2-month time point was chosen to assess the effect of treatment changes considered during hospitalization, including the weeks following hospital discharge when prescriptions may be adjusted by the general practitioner, for example. This was also the time point selected for several secondary outcomes of the original OPERAM study and therefore all the data were available at this time point [19, 20].

The point-prevalence of DDIs at the different time points (baseline, discharge, 2, 6 and 12 months post-randomization) was evaluated in total (at least one DDI) and for each DDI separately, and then according to the type of interaction (i.e., pharmacokinetic, pharmacodynamic), the potential harm, the randomization arm, and the trial site. The most common DDIs in this population were defined using the 3rd quartile of the most frequent DDIs. McNemar’s test was used to assess differences in prevalence between baseline and discharge. The chi-squared test for trend was used to assess the trend in prevalence between discharge and 1 year after trial enrollment.

Data are presented as median (25–75% interquartile range [IQR]) for continuous variables, and numbers (percentages) for categorical variables. A Mann-Whitney U test or Kruskall-Wallis test was used to compare continuous variables between groups and Pearson’s chi-squared test or Fisher’s exact test to compare categorical variables between groups.

A total of 2008 patients were enrolled in the OPERAM trial, of whom 1950 were alive and had medication data available at discharge and were included in this substudy (Fig. 1). The median age [IQR] was 79 [74–84] years; 1080 patients (55%) were male; the median [IQR] number of drugs per day was 12 [9‐16]. Baseline characteristics are given in Table 1 (Additional file 3). [Place of Table 1] The median length of stay [IQR] was 7 [3‐10] days.

At baseline, 1045 (54%) patients had at least one DDI (Table 1) [median number of DDIs per person [IQR] with at least one DDI: 1[1–2]). Certain medical conditions (depression, coronary artery disease, heart failure, atrial fibrillation, chronic obstructive pulmonary disease [COPD]) and polypharmacy were risk factors for the presence of at least one DDI at baseline, with ORs varying between 1.25 [1.02–1.54] and 2.88 [1.99–4.26] (Table 2). Age over 80 years (80–89 years: 0.79 [0.64–0.97], ≥90 years: 0.65 [0.44–0.96]) and a history of chronic hepatic failure (0.49 [0.31–0.77]) were associated with a lower prevalence of DDIs (Table 2).

The point-prevalence rates for at least one DDI were 54, 58, 57, 56 and 57% at baseline, hospital discharge and at 2, 6 and 12 months from the index hospitalization, respectively (Fig. 2A, Additional file 4). The prevalence of DDIs increased significantly during the index hospitalization (McNemar test, P < .001), then remained stable over time (Chi-squared test for trend, P = .31). The observed increase from baseline to discharge was notable for pharmacodynamic DDIs (but not for pharmacokinetic DDIs) (Fig. 2B), and for DDIs potentially associated with cardiovascular adverse events (Fig. 2C).

The five most prevalent DDIs in our cohort were: DDI 65 (prescription of ≥2 drugs that reduce potassium), DDI 36 (prescription of ≥3 centrally-acting drugs), DDI 21 (prescription of ≥2 potassium-sparing drugs), DDI 12 (oral anticoagulant and antiplatelet) and DDI 39 (oral non-steroidal anti-inflammatory drug and selective serotonin reuptake inhibitor or serotonin-norepinephrine reuptake inhibitor) (Fig. 2A, Additional file 4). These five DDIs accounted for 78% of all DDIs at baseline, 80% at discharge and 83% thereafter. They were all classified as pharmacodynamic interactions (Additional file 1).

The main drug classes involved in the three most frequent DDIs are listed in Additional file 5 (DDI 65: high ceiling diuretics, inhaled beta2 agonists, systemic corticosteroids and contact laxatives; DDI 36: antipsychotics, anxiolytics, hypnotics and sedatives, opioids, antidepressants and antiepileptics; DDI 21: agents acting on the renin-angiotensin system and spironolactone).

As described in Fig. 2D and Additional files 6–7, the prevalence of DDIs during the index hospitalization only increased in patients randomized to the control arm, as compared to the intervention arm, and hospitalized in Bern, as compared to other sites. Patients’ baseline characteristics and types of admission were different across the sites (Additional file 8). Patients in Bern, compared to other sites, had more comorbidities, more polypharmacy, and were generally hospitalized for non-elective reasons (Additional file 8).

At 2 months, DDIs had increased in 459 (27%) patients and decreased in 331 (19%) patients compared to at baseline (Additional files 9 and 10). Female sex, hyperpolypharmacy (≥10 drugs per day at baseline), history of depression and heart failure were significantly associated with a decrease in DDIs at 2 months (Table 3). History of atrial fibrillation, coronary heart disease, or cardiac failure and hyperpolypharmacy were significantly associated with an increase in DDIs at 2 months (Table 3).

In a European cohort of older patients with multimorbidity and polypharmacy, the prevalence of potentially clinically significant DDIs was high (54%) at hospital admission. Patients with certain medical conditions, such as depression, coronary artery disease, heart failure, atrial fibrillation and COPD, and those with polypharmacy were more likely to have at least one DDI at baseline. The top five most frequent potentially clinically significant DDIs (drugs that reduce potassium [diuretics, inhaled beta2 agonists, systemic corticosteroids], centrally-acting drugs [psychotropics, antidepressants, opioids, antiepileptics], potassium-sparing drugs [angiotensin-converting enzyme, angiotensin II type 1 receptor blockers, spironolactone] and antithrombotics] comprised 80% of all potentially clinically significant DDIs. These five potentially clinically significant DDIs were all classified as pharmacodynamic interactions mainly causing cardiovascular adverse events. The prevalence of potentially clinically significant DDIs increased significantly at discharge and then remained stable over the subsequent 12 months (i.e., did not return to the baseline prevalence level).

The high prevalence of DDIs in our cohort aligns with the in-patient and out-patient prevalences reported in the literature for comparable populations (geriatric outpatient cohort: 44.5% [24] and 58.3% [25]; geriatric inpatient cohort: 60.5% [26]). The drug classes most frequently involved in DDIs in our cohort were also the same as those previously reported [1, 4, 16, 17, 26‐29]. These drugs are often prescribed to older patients to treat common age-related conditions, particularly cardiovascular and neurological conditions. Consistent with our results, Vonbach et al. reported that more than 70% of all major and moderately severe potential DDIs were pharmacodynamic interactions [30].

In line with our results, two studies reported that hospitalization was associated with an increase in DDIs in older patients, [26, 30] one of which reported that almost half of the DDIs at hospital discharge were incurred during hospitalization [30]. However, and this is the originality of our study, none of the published studies assessed DDIs over time to describe trends after discharge in older patients. Changes in the prevalence of DDIs over time, with a higher prevalence at discharge than at baseline, and a decrease after hospital discharge but not to baseline levels, were noted particularly for DDI 65 (concomitant prescription of ≥2 drugs that reduce potassium), which includes cardiovascular and respiratory drugs (high ceiling diuretics and inhaled beta2 agonists). This trend has already been described in patients with coronary heart disease and COPD, [31] conditions for which these drugs are indicated. In addition, factors associated with an increase in DDIs at 2 months were similar to those previously reported in the literature, especially polypharmacy [2‐4, 7, 32]. The fact that the patients included in Bern had more comorbidities, were more likely to have polypharmacy, and were generally hospitalised for non-elective reasons, may explain the differences in trends across trial sites.

DDIs are often classified according to their potentially harmful effects, but no study has reported the prevalence of DDIs according to whether or not they may be appropriate. Evaluation of appropriateness of a DDI often requires an individual, case-by-case assessment, which is not possible on a large database. However, from the list of 66 DDIs, some can be considered inappropriate in many cases (“avoid concurrent use”), such as DDI 32, “beta-blocker and verapamil or diltiazem” (potentially serious cardiovascular adverse effects in particular in patients predisposed to heart failure); DDI 36, “concomitant use of ≥3 centrally-acting drugs” (increased risk of falls, fracture, impaired cognition); and DDI 63, “tamoxifen and paroxetine or fluoxetine or bupropion” (risk of sudden death – ventricular arrhythmias, torsade de pointes). Most drugs in these DDI categories were rarely prescribed in our cohort with the exception of DDI 36. Other DDIs may be appropriate, or even intentional, in some cases if preventive measures are taken (e.g., dose adaptation, close monitoring, patient education), for example, for DDI 12, “oral anticoagulant and antiplatelet drug”; DDI 65, “concomitant prescription of ≥ 2 drugs that reduce potassium”; and DDI 66: “selective serotonin reuptake inhibitor and loop or thiazide diuretic”. DDI 65 prescribed in acute clinical situations, such as cardiac failure or COPD exacerbation, may, for example, be appropriate if serum potassium concentrations are monitored closely. Similarly, DDI 12 is only appropriate in certain specific clinical situations (e.g., atrial fibrillation and recent acute coronary syndrome) and for a fixed duration [33]. The fact that 57% of patients in the experimental arm (i.e., patients for whom medication review was performed by a physician and pharmacist) had at least one DDI at hospital discharge suggests that most of these DDIs were considered appropriate in these patients and thus did not require drug discontinuation or modification after the medication review. Only the patients in the control arm had an increase in the prevalence of DDI 36 from baseline to discharge, which may explain why there was a significant increase in the prevalence of DDIs during hospitalization only in patients in the control arm. These data suggest that frequent medication reviews for those admitted to hospital, not only during hospital admission, but also after discharge, can contribute to reducing the risk of inappropriate DDIs.

To our knowledge, this is the first international, multicenter study to report data on the prevalence of DDIs at hospital admission and at different time points over a one-year follow-up period in an older population with multimorbidity. To identify the DDIs, we used for the first time a new list of 66 potentially clinically significant DDIs developed by an international consensus panel [11].

This study has some limitations. First, we were unable to distinguish between appropriate and inappropriate DDIs (which would require detailed information on, for example, dose adaptations, indications, monitoring, patient specifics). Second, because of a lack of statistical power, we did not assess ADEs and drug-related hospital admissions associated with DDIs. This information would have enabled us to evaluate actual DDIs resulting from potential DDIs. As reported in the literature, it is therefore likely that we have overestimated the true clinical significance of the DDIs [3]. Indeed, studies that focused on actual DDIs reported lower prevalences in ambulatory settings (9.5 and 25.5%) [24, 34] as well as for in-patients (8.8%) [35]. Nevertheless, the presence of a potentially clinically significant DDI remains a strong signal that should alert the prescriber to the need for greater patient monitoring and education.

It seems important to help clinicians identify potentially harmful DDIs more effectively, in particular the five most prevalent, to improve their assessment of risk-benefit ratios in individual patients. Risk minimization measures for prescription of psychotropic drugs, antithrombotics and drugs that reduce or increase potassium concentrations should be deployed.

The next logical step would be to assess the clinical impact of these DDIs, especially of the most common ones. To this end, a large scale cohort study from healthcare databases could be carried out. Better identification of the impact of DDIs is important for clinicians, researchers and health policy decision-makers to plan for safer healthcare in ageing societies.