Potential Drug-Drug Interactions among Geriatric Patients in Medicine Department at a Tertiary Care Teaching Hospital - A Prospective Observational Study

Introduction

Drug-drug interaction (DDI) is usually described as a clinically unintended modification in the exposure and / or response to a medication (objective) that occurs with co-administration of another medication (precipitator). The potential DDI refers to co prescription of two medications known to interact that may occur in an exposed patient.¹ This can result in qualitative or quantitative changes in drug action. These changes may alter diagnostic, preventive and therapeutic activity of any drug, resulting in treatment failure, toxicity and alteration in drug efficacy. DDIs are categorised based on severity of mechanism by which drugs interact with each other.²

Potential drug-drug interactions are classified according to severity as, Contraindicated, Major, Moderate, Minor. Based on mechanism, they are categorised into pharmaceutical, pharmacokinetics, pharmacodynamics. Pharmacokinetic interactions occur due to effect of one drug on the dissemination of another drug through the body and these interactions are modulated in response to body which normally processes a drug towards elimination.³ For example, calcium and magnesium complexes interfere with absorption of tetracycline and prednisolone, sucralfate reduces the bioavailability of phenytoin, and the altered gastric pH due to sodium bicarbonate reduces the absorption of tetracycline.

Based on pharmacological activity, they are categorized as pharmacodynamic and pharmacokinetic. Pharmacodynamic DDI occur when pharmacological effect of one or more drug is altered by another drug in a combination therapy. Pharmacodynamic DDIs are categorised as, synergistic or additive effect, antagonism or negative effect. Synergism is overall effect caused by a drug combination. It occurs when overall effect of the drug combination is greater than additive. Antagonism occurs when activity of one drug is diminished by another drug. Examples:

• Pharmacokinetic interactions: Inhibition of absorption - Ciprofloxacin.

• Pharmacodynamic interactions: Antagonistic effect-NSAIDs inhibit the antihypertensive effect of drugs as ACE inhibitors.

Pharmaceutical interaction also refers to incompatibility, which occurs when drugs mixed in IV infusion leads to precipitation or inactivation of active principles. Example: Ceftriaxone with calcium containing solution forms precipitates. Treatment with drugs is an essential tool of modern healthcare; but it can also lead to illness and death posing a huge economic burden to the society. Over the past few decades, the use of drugs have increased among older adults. Approximately nine in ten older adults take medications indicating that the usage of drugs increase with advancing age.⁴ The drugs most commonly implicated in major potential interactions are those used in day to day clinical management of elderly patients with chronic diseases,⁵ requiring constant and continuous treatment with medications.⁶ The elderly might suffer from multiple illnesses at a given point of time, technically referred as ‘comorbidities’ necessitating multiple and complex treatment regimens,⁷ which can lead to drug-drug interactions. Pharmacists play a crucial role in identifying and overcoming the drug related problems like Adverse drug reactions (ADRs), adverse drug events (ADEs) and DDIs, especially for drugs with narrow therapeutic index, by regular review of medications in the prescriptions.

Materials and Methods

A prospective observational study was conducted among 350 patients admitted to Medicine department of Chigateri District Hospital, Davangere, over six months duration. The Institutional Ethical Committee of SCS College of Pharmacy approved conducting the study and written informed consent was obtained from all the residents in the hospital.

A specially designed proforma was used for collecting the data which included patient demographics, personal history, comorbidities, diagnosis, and medications prescribed for each patient. The data were obtained by interviewing the patients and/or caretakers and from patient profiles. The study was carried out by considering specific inclusion criteria, such as individuals admitted in the Medicine ward, prescriptions with more than four drugs, patients with at least three days of hospital stay, and patients aged above 60 years, while the exclusion criteria considered were outpatients, poisoning related cases, patients with missing and insufficient data, and illegible prescriptions.

Results

A total of 350 prescriptions for elderly patients that fulfilled the selection criteria were included in the study. The minimum length of stay in the hospital considered was three days. All the quantitative variables like age were expressed as variable proportion and percentage. A total of 194 (55%) males and 156 (45%) females were included in the study.

• The total elderly patients admitted were classified into three age groups: 60-69, 70-79, 80-89, above 90 years. Most common elderly patients admitted during the study period were between age groups 60-69 years, followed by 70-79 years, representing 213 (61%) and 101 (29%) of total study population, respectively.

• On analyses of prescriptions of patients, a total of 145 (41%) were prescribed with more than 10 drugs, and nearly 178 (51%) were prescribed with 6-9 drugs.

• Potential drug interactions were detected with the help of Drug.com interaction checker. All the drugs prescribed in a prescription were entered into online system for assessing the potential drug-drug interactions (PDDI) in a particular prescription. It was found that 159 prescription have no PDDI, while 137 (40%), 42 (12%) prescriptions and 12 (3%) prescription showed 1-2 PDDI, 3-5 PDDI and ≥6 PDDI, respectively, with a total 191 prescription having one PDDI.

In a total of 350 prescriptions, 465 PDDI were identified and were classified based on the severity (Table 1).

• Among the total 405 interactions identified, 294 (72.5%) were pharmacodynamic and 111 (27.5%) were pharmacokinetic interactions.

• About 173 (58%) patients had synergistic action and 121 (42%) had antagonistic action.

• Out of 405 PDDI, 27.5% were pharmacokinetic interactions. About 18 (16%) were known to affect absorption, 32 (29%) distribution, 22 (20%) metabolism, and 39 (35%) were known to affect elimination (Figure 1). 

Out of 171 drugs enrolled in the study, the commonly prescribed drugs involved in the drug interactions are mentioned in Table 2 and PDI based on body systems are mentioned in Table 3.

Discussion

In the present study, 350 subjects were reviewed, and a total of 405 DDIs were identified. The DDIs were classified as minor, moderate and severe/ major, according to severity of interaction. Critical interactions are those that pose a potential threat to life or could result in permanent harm, necessitating medical intervention to mitigate or prevent severe adverse effects. In the case of moderate drug-drug interactions (DDI), the patient's health may worsen due to the interactions, necessitating additional care or an extended hospital stay. Minor interactions are usually not medically detrimental, but can occasionally be bothersome. Minor interactions does not require change in the treatment plan.

For the current investigation, information was gathered from 350 patients who were hospitalized in the Medical ward of a tertiary care teaching hospital in Davangere. The study encompassed the prescriptions of 350 elderly patients, with 194 (55%) being males and 156 (45%) females, aligning closely with a study conducted in Saudi Arabia by Al Suwaidan A et al. In the study, the prescriptions involved a minimum four drugs to a maximum 16 drugs. The prescriptions studied included 171 different types of drugs from different classes like anti-hypertensives, antibiotics, corticosteroids, cardiovascular, antiepileptic, antipsychotic medications and others. In total of 350 prescriptions, 191 (54%) prescriptions showed at least one PDDI. These results are in contrast with the study conducted in Gujarat by Vegada B et al. which reported a minimum of one DDI to a maximum of six interactions. A total of 405 interactions were identified among 171 drugs, with combinations of 166 pairs of drugs. The 191 (54%) prescriptions included had at least one PDDI, 42 (12%) prescriptions had 3-5 PDDI, while 12 (3%) prescriptions had ≥ 6 PDDI in accordance to the study conducted in Gujarat by Vegada B et al.⁸

The severity assessment of DDIs in our study showed that most interactions (257 (64%)) were moderate, followed by minor (104 (25%)) and major interactions (44 (11%)). Similar findings were observed in comparison to the research carried out in Ooty by Kulkarni V et al. ⁹ When prescriptions were categorized based on polypharmacy status, non-polypharmacy was identified in 27 (8%) prescriptions, whereas polypharmacy and hyper-polypharmacy were evident in 175 (51%) and 145 (41%) prescriptions, respectively. Similar observations were made in the study conducted in Saudi Arabia by Al Suwaidan A et al.

Patients were classified into four different age groups - 213 (61%) were in the age group of 60 to 69 years, 101 (29%) were in the age group of 70-79 years, 28 (8%) were in 80-89 years age group, while 8 (2%) were aged above 90 years. A similar trend was observed in the study conducted by Salwe K et al. in Puducherry. DDIs affecting pharmacokinetics were as follows: DDIs affecting absorption were found in 18 (16%) prescriptions, those affecting distribution were found in 32 (29%), DDIs affecting metabolism were observed in 22 (20%) prescriptions and while interactions affecting excretion were noted in 39 (35%) prescriptions. These results are in contradiction to the reports of Kulkarni V et al. ⁹

In the present study, among 405 interactions observed, 27.5% were pharmacokinetic DDIs and 72.5% were pharmacodynamic interactions. Among the pharmacodynamic DDIs observed, 173 (58%) were synergistic and 121 (42%) were antagonistic. Similar results were observed in the study conducted in Maharashtra by Nishandar T et al. ¹⁰ Out of 191 patients exposed to PDDI, 101 (53%) had comorbidities and the most frequent comorbidity noted was hypertension 49 (48%), followed by diabetes mellitus 24 (24%). The results were 228 (37%) antihypertensive, 113 (18%) antibiotics, cardiovascular and corticosteroids were 46 (7.5%). Each of these results is similar to the findings of the study conducted in Saudi Arabia by Al Suwaiden A et al. The most frequently involved drugs in PDDIs were hydrocortisone (70), furosemide (60), amlodipine (42), metronidazole (42), theophylline (41), tramadol (26) and metaprolol (25). (Table 2)These results could be related to the findings of a study conducted in Indonesia by Rahmawati F et al. ¹¹ 

Conclusion

The findings of the study revealed that geriatric patients are at a high risk for polypharmacy because of multiple comorbid conditions. The overall incidence of PDDI observed was 54%. Most of the interactions were pharmacodynamic and antagonistic in nature.

Intensive monitoring during therapy was deemed necessary for drug interactions involving hydrocortisone and furosemide, which were the most prevalent drugs in such interactions. The primary aim of the study was to investigate the association between polypharmacy and co-morbidity. Investigators provided evidence for association of polypharmacy with co-morbidities. Understanding the frequency and factors predicting clinically significant potential drug-drug interactions (PDDI) can assist clinicians and pharmacists in recognizing patients at elevated risk of PDDI. This awareness is crucial for exercising caution when prescribing or dispensing medications to prevent adverse outcomes.

Additional research conducted across diverse medical centers is essential to gather data on potential drug-drug interactions in the geriatric population. Pharmacists should actively engage in the management of medication therapy by collaborating with healthcare professionals to prevent and address issues related to drug-drug interactions.

Conflict of Interest

Nil

Acknowledgement

The authors are thankful to Dr. Nagendra Rao, principal, SCS College of Pharmacy, Harapanahalli, for the encouragement and the valuable support throughout the study.