{"id":40556,"date":"2021-09-30T11:42:19","date_gmt":"2021-09-30T11:42:19","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=40556"},"modified":"2021-10-11T07:28:08","modified_gmt":"2021-10-11T07:28:08","slug":"frequency-and-predictors-of-potential-drug-interactions-among-psychiatry-outpatients-on-treatment-with-antidepressant-medications","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol14no3\/frequency-and-predictors-of-potential-drug-interactions-among-psychiatry-outpatients-on-treatment-with-antidepressant-medications\/","title":{"rendered":"Frequency and Predictors of Potential Drug Interactions among Psychiatry Outpatients on Treatment with Antidepressant Medications"},"content":{"rendered":"

Introduction<\/strong><\/p>\n

Antidepressants are commonly used drugs in the management of depression and various anxiety disorders1<\/sup>. Placebo-controlled trial reveals that different categories of antidepressants demonstrate equal efficacy when administered in comparable doses2<\/sup>. The treatment duration of\u00a0antidepressants may vary from months to years, during which apatient may be prescribeddifferent categories of drugs to treat other clinical conditions or comorbidities. Hence, it is clinically significant to evaluate the occurrence of potential drug interactions in such\u00a0patients. Many clinical studies provide instances of potential drug interactions between antidepressants and co-prescribed medications. An interaction between citalopram and diclofenac was reported in a prospective, observational study3<\/sup>. The incidence rate ratio (IRR) for\u00a0selective serotonin reuptake inhibitors (SSRIs) was 1.2, which increased to 12.4 whenSSRIs and non-steroidal anti-inflammatory drugs (NSAIDs) were co-administered. On the other hand, when Tricyclic antidepressants (TCAs) and NSAIDs were co-administered, the IRR increased by\u00a02.54<\/sup>.In another study, co-medication of SSRIs with anticoagulation during acenocoumarol maintenance treatment was found to increase the anticoagulation risk when combined with fluvoxamine (HR 2.63) and venlafaxine (HR 2.19)5<\/sup>.<\/p>\n

DDIs are a common cause of concern in psychiatry since most psychiatric\u00a0illnesses\u00a0need multiple medications to manage them6<\/sup>. The presence of additional non-psychiatric comorbidities, the pharmacokinetics nature\u00a0of the prescription medicines, and the length of treatment render this group even more sensitive to DDIs6,7<\/sup>.<\/p>\n

Apart from medications, alcohol is known to interact with many drugs as both getmetabolized by the same liver enzymes resulting in pharmacokinetic interactions8<\/sup>. A study documented an increase in the risk of falling in community-dwelling older adults, possibly due to\u00a0alcohol and tricyclic and tetracyclic antidepressants combination9<\/sup>.The research concluded that the combination of alcohol with tricyclic and tetracyclic antidepressants increased the risk of falling in community-dwelling older persons10<\/sup>.Smoking can also interact with antidepressant\u00a0treatment. Systematic review research found evidence of a drop in the concentration of blood levels of fluvoxamine, duloxetine, mirtazapine, and trazodone among smokers compared to nonsmokers11<\/sup>. Some antidepressants’ blood levels are known to be lowered in smokers due to the\u00a0induction of metabolism mediated by CYP1A2 and CYP2B6 enzymes12<\/sup>.<\/p>\n

A review of our literature on antidepressant-related DDIs suggests that pDDIs are frequent in outpatient and inpatient settings. However, the majority of these DDIs were mild to moderate in severity. However, there is a scarcity of data in our research setting on the\u00a0prevalence and character of antidepressant-related DDIs. Further more, not many studies evaluated the type and nature of potential drug-drug interactions(pDDIs) related to antidepressants in psychiatry outpatients in the UAE. In our study, we attempt to identify and\u00a0document any significant drug interactions associated with antidepressant medications administered to the outpatients of the psychiatry department. The study also attempts to identify variables predicting potential drug interactions. Our study data is anticipated to strengthen the\u00a0interventional strategies and promote rational therapy with antidepressants.<\/p>\n

Materials and Methods<\/strong><\/p>\n

This was cross-sectionalresearch undertaken atthe Psychiatry outpatient department (OPD) of Ibrahim Bin Hamad Obaidallah Hospital (IBHOH), Ras Al-Khaimah, UAE.Patients of all age groups and both the gender, who fulfilled the mental and behavioral diagnostic criteria of\u00a0the International classification of disease (ICD-10) and were prescribed with at least one antidepressant medication irrespective of the clinical indication and registered in the psychiatry OPD of IBHOH, were included in the study.<\/p>\n

Ethics approval<\/strong><\/p>\n

The study was approved by the institutional Research and Ethics committee and the Ras Al Khaimah Research and Ethics committee (RAK REC) [Reg No. 44\/2016-PG-P].All methods in studies involving human subjects were carried out in compliance with the institutional\u00a0research committee’s ethical standards, the 1964 Helsinki statement, and its subsequent revisions or similar ethical standards.<\/p>\n

Assessment of Drug Interactions <\/strong><\/p>\n

The patient\u2019s prescriptions were reviewed and analyzed with referral to Micromedex database 2.0 for the presence of potential drug interactions. This database has been widely adopted to identify & analyze potential drug interactions. The drug interactions identified were\u00a0assessed based on the severity and documentation criteria of the Micromedex database 2.0.<\/p>\n

Data analysis<\/strong><\/p>\n

The obtained data were incorporated into a Microsoft Excel spreadsheet and analyzed using SPSS version 24.0, statistical software for the social sciences.The continuous data were presented as mean SD, while the categorical data were presented as percentages.The Chi-square\u00a0test was used to examine the relationship between the dependent and independent categorical variables.By calculating relative risk (RR), the predisposing factors for potential drug-drug reactions were identified. In the presence of all of the variables studied, RR greater than one suggests an increased risk of potential drug-drug reactions. The variables tested are gender,\u00a0nationality, age, general medical conditions, number of drugs prescribed, presence of total polypharmacy, and psychiatric polypharmacy. The predictors of pDDIs were detected using multiple regression analysis. A probability value of less than 0.05 was deemed statistically\u00a0significant, and any value less than 0.01 was deemed highly significant.<\/p>\n

Results <\/strong><\/p>\n

Patient demography<\/strong><\/p>\n

The research included 131 patients who met the inclusion criteria.The majority of the study population were females (62%). The mean age of the study population was 44.8 \u00b1 16.6 years). A sizable proportion of the study population were UAE nationals (67%) compared to\u00a0expatriates (33%). Based on the patients\u2019 medical history,51.1% of patients had other comorbidities\/medical illnesses besides psychiatric conditions. Psychotropic drugs were prescribed in 42% of the patients.<\/p>\n

Positive family history of psychiatric illnesses was observed in 32.1% of patients, and 55% of the patients were not known\/aware if they had a family history of psychiatric illnesses. Around8.4% of study patients had a history of suicidal attempts recently or in previous years. Only a tiny proportion of patients had a habit of alcohol consumption (5%), drug abuse (8%), and tobacco smoking (13%).<\/p>\n

Three hundred forty-three drugs were prescribed to the study patients (average drugs prescribed per patient 2.62\u00b1 1.01).The majority of study patients(69.4%) received monotherapy, 29% received two antidepressants, and 1.6% received three antidepressants.The majority of the study patients (36.6%) received SSRIs, followed by serotonin-norepinephrine reuptake\u00a0inhibitors [SNRIs] (13.7%), Serotonin, and \u03b12-adrenergic antagonist (8.4%),and tricyclic antidepressants [TCAs] (6.9%) as monotherapy.<\/p>\n

Frequency of pDDIs between antidepressants and other psychotropic medications<\/strong><\/p>\n

A total of 88 potential drug-drug interactions (pDDIs) involving forty-one drug pairs were identified in 63 patients taking antidepressant medications. The frequency of pDDIs among the psychiatric outpatients receiving antidepressant medications was 48.1%.The mean age of these\u00a0patients was 44.9\u00b1 13.7 years. The majority of these patients received three (41.3%), followed by two (28.6%), four (25.4), five (3.1%), and six (1.5%) medications. The psychiatric diagnosis associated with the identified pDDIs in these patients is shown in Table 1. The majority of the\u00a0detected potential drug interactions were significant in severity (83%), followed by moderate severity (16%),and 1% was contraindicated. Escitalopram with mirtazapine(7%) was the most commonly documented pDDI. The most frequently interacting drug pairs, their level of severity, and pharmacological consequences are listed in Table 2.<\/p>\n

Table 1:\u00a0<\/strong>Psychiatric Disorders Associated with The Identified pDDIs in Patients Taking Antidepressants and Other Psychotropic Medications.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Diagnosis<\/strong><\/td>\nICD-10-CM-Codes<\/strong><\/td>\nNo.\u00a0 ofthe patients with pDDI, (%)<\/strong><\/td>\n<\/tr>\n
Major Depressive Disorder<\/td>\nF32.9<\/td>\n14 (22.2)<\/td>\n<\/tr>\n
\n

Generalized Anxiety Disorder<\/p>\n<\/td>\n

\n

F41.1<\/p>\n<\/td>\n

\n

9 (14.3)<\/p>\n<\/td>\n<\/tr>\n

\n

Obsessive-Compulsive Disorder<\/p>\n<\/td>\n

\n

F42.9<\/p>\n<\/td>\n

\n

7 (11)<\/p>\n<\/td>\n<\/tr>\n

\n

Bipolar Disorder, Depressed Episode<\/p>\n<\/td>\n

\n

F31.30<\/p>\n<\/td>\n

\n

7 (11)<\/p>\n<\/td>\n<\/tr>\n

\n

Major Depressive Disorder with Psychotic Features<\/p>\n<\/td>\n

\n

F33.3<\/p>\n<\/td>\n

\n

6 (9.5)<\/p>\n<\/td>\n<\/tr>\n

\n

Adjustment Disorder with Mixed Anxiety and Depressed Mood<\/p>\n<\/td>\n

\n

F43.23<\/p>\n<\/td>\n

\n

2 (3.2)<\/p>\n<\/td>\n<\/tr>\n

\n

Anxious Depression<\/p>\n<\/td>\n

\n

F41.8<\/p>\n<\/td>\n

\n

2 (3.2)<\/p>\n<\/td>\n<\/tr>\n

\n

Panic Disorder<\/p>\n<\/td>\n

\n

F41.0<\/p>\n<\/td>\n

\n

2 (3.2)<\/p>\n<\/td>\n<\/tr>\n

\n

Schizophrenia<\/p>\n<\/td>\n

\n

F20.0<\/p>\n<\/td>\n

\n

2 (3.2)<\/p>\n<\/td>\n<\/tr>\n

\n

Substance Abuse<\/p>\n<\/td>\n

\n

F19.10<\/p>\n<\/td>\n

\n

2 (3.2)<\/p>\n<\/td>\n<\/tr>\n

\n

Post-Traumatic Stress Disorder<\/p>\n<\/td>\n

\n

F43.10<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Social Phobia<\/p>\n<\/td>\n

\n

F40.10<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Premenstrual Tension Syndromes<\/p>\n<\/td>\n

\n

N94.3<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Adjustment Disorder with Depressed Mood<\/p>\n<\/td>\n

\n

F43.21<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Borderline Personality Disorder<\/p>\n<\/td>\n

\n

F60.3<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Adjustment Disorder with Anxiety<\/p>\n<\/td>\n

\n

F43.22<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Schizoaffective Disorder<\/p>\n<\/td>\n

\n

F25.9<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Psychosis, Paranoid<\/p>\n<\/td>\n

\n

F22.0<\/p>\n<\/td>\n

\n

1 (16)<\/p>\n<\/td>\n<\/tr>\n

\n

Somatization Disorder<\/p>\n<\/td>\n

\n

F45.0<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n

\n

Intellectual Disability<\/p>\n<\/td>\n

\n

F79.0<\/p>\n<\/td>\n

\n

1 (1.6)<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Table 2: Most Frequently Interacting Antidepressants and Other Psychotropic Drug Pairs.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Type of pDDIs<\/strong><\/td>\nn ( %)<\/strong><\/td>\nSeverity<\/strong><\/td>\nDocumentation<\/strong><\/td>\nPharmacological Consequences: May result in Increased Risk of<\/strong><\/td>\n<\/tr>\n
Escitalopram + Mirtazapine<\/td>\n6 (7)<\/td>\nMajor<\/td>\nFair<\/td>\nSerotonin syndrome<\/td>\n<\/tr>\n
Fluoxetine +<\/p>\n

Propranolol<\/td>\n

6 (7)<\/td>\nMajor<\/td>\nGood<\/td>\nPropranolol toxicity<\/td>\n<\/tr>\n
Fluoxetine +<\/p>\n

Olanzapine<\/td>\n

5 (5.9)<\/td>\nMajor<\/td>\nFair<\/td>\nQT-interval prolongation<\/td>\n<\/tr>\n
Mirtazapine +<\/p>\n

Bromazepam<\/td>\n

4 (4.6)<\/td>\nMajor<\/td>\nFair<\/td>\nCNS depression<\/td>\n<\/tr>\n
Venlafaxine +<\/p>\n

Quetiapine<\/td>\n

4 (4.6)<\/td>\nMajor<\/td>\nFair<\/td>\nQT-interval prolongation<\/td>\n<\/tr>\n
Mirtazapine +<\/p>\n

Duloxetine<\/td>\n

4 (4.6)<\/td>\nMajor<\/td>\nFair<\/td>\nSerotonin syndrome<\/td>\n<\/tr>\n
Mirtazapine + Carbamazepine<\/td>\n3 (3.5)<\/td>\nMajor<\/td>\nFair<\/td>\nSerotonin syndrome<\/td>\n<\/tr>\n
Mirtazapine +<\/p>\n

Venlafaxine<\/td>\n

3 (3.5)<\/td>\nMajor<\/td>\nFair<\/td>\nSerotonin syndrome<\/td>\n<\/tr>\n
Clomipramine + Olanzapine<\/td>\n3 (3.5)<\/td>\nMajor<\/td>\nGood<\/td>\nIncreased risk of seizures<\/td>\n<\/tr>\n
Escitalopram +<\/p>\n

Olanzapine<\/td>\n

3 (3.5)<\/td>\nMajor<\/td>\nFair<\/td>\nQT-interval prolongation<\/td>\n<\/tr>\n
Fluoxetine + Carbamazepine<\/td>\n2 (2.2)<\/td>\nMajor<\/td>\nGood<\/td>\nCarbamazepine toxicity<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Note: The identified pDDIs were graded based on the severity and documentation as specified by Micromedex database 2.0.<\/p>\n

Frequency of pDDIs between antidepressants and non-psychotropic medications<\/strong><\/p>\n

Twenty-one pDDIs involving sixteen drug pairs were identified among twelve patients who received antidepressant medications along with non-psychotropic medications.The frequency of pDDIs in these patients was 9.2%. The mean age of these patients\u00a0was 59.1 \u00b1<\/u> 12.2 years. Table 3 represents the psychiatric diagnosis associated with the identified pDDIs in these patients.Among twenty-one identified pDDIs, 71.4% were of major severity, and the remaining were moderate (28.6%) in severity. Escitalopram with levothyroxine (14%) and\u00a0escitalopram with aspirin (14%) were the most commonly documented pDDIs. Table 4 provides the details of the most frequently interacting drug-pairs, their level of severity, and pharmacological consequences.<\/p>\n

Table 3:\u00a0<\/strong>Psychiatric Disorders Associated with The Identified pDDIs in Patients Taking Antidepressants and non-psychotropic Medications.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n
Diagnosis<\/strong><\/td>\nICD-10-CM-Codes<\/strong><\/td>\nNo.\u00a0 ofthe patients with pDDI(%)<\/strong><\/td>\n<\/tr>\n
Major Depressive Disorder<\/td>\nF32.9<\/td>\n5 (42)<\/td>\n<\/tr>\n
Generalized Anxiety Disorder<\/td>\nF41.1<\/td>\n2 (17)<\/td>\n<\/tr>\n
Obsessive-Compulsive Disorder<\/td>\nF42.9<\/td>\n2 (17)<\/td>\n<\/tr>\n
Anxious Depression<\/td>\nF41.8<\/td>\n1 (8)<\/td>\n<\/tr>\n
Premenstrual Tension Syndromes<\/td>\nN94.3<\/td>\n1 (8)<\/td>\n<\/tr>\n
Bipolar Disorder, Depressed Episode<\/td>\nF31.30<\/td>\n1 (8)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Table 4: Most Frequently Interacting Antidepressants and non-psychotropic drug pairs.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Type of pDDIs<\/strong><\/td>\nn ( %)<\/strong><\/td>\nSeverity<\/strong><\/td>\nDocumentation<\/strong><\/td>\nPharmacological Consequences: May result in Increased Risk of<\/strong><\/td>\n<\/tr>\n
Escitalopram +<\/p>\n

Aspirin<\/td>\n

3 (14)<\/td>\nMajor<\/td>\nExcellent<\/td>\nRisk of bleeding<\/td>\n<\/tr>\n
Escitalopram + Levothyroxine<\/td>\n3 (14)<\/td>\nModerate<\/td>\nFair<\/td>\nLevothyroxine requirements<\/td>\n<\/tr>\n
Mirtazapine +<\/p>\n

Levothyroxine<\/td>\n

2 (10)<\/td>\nMajor<\/td>\nFair<\/td>\nTherapeutic and toxic effects of both drugs<\/td>\n<\/tr>\n
Fluoxetine +<\/p>\n

Aspirin<\/td>\n

1 (5)<\/td>\nMajor<\/td>\nExcellent<\/td>\nBleeding<\/td>\n<\/tr>\n
Fluoxetine +<\/p>\n

Diclofenac<\/td>\n

1 (5)<\/td>\nMajor<\/td>\nExcellent<\/td>\nBleeding<\/td>\n<\/tr>\n
Clomipramine +<\/p>\n

Diclofenac<\/td>\n

1 (5)<\/td>\nMajor<\/td>\nExcellent<\/td>\nBleeding<\/td>\n<\/tr>\n
Duloxetine +<\/p>\n

Diclofenac<\/td>\n

1 (5)<\/td>\nMajor<\/td>\nExcellent<\/td>\nBleeding<\/td>\n<\/tr>\n
Mirtazapine +<\/p>\n

Warfarin<\/td>\n

1 (5)<\/td>\nMajor<\/td>\nExcellent<\/td>\nInternational Normalised Ratio<\/td>\n<\/tr>\n
Venlafaxine +<\/p>\n

Clopidogrel<\/td>\n

1 (5)<\/td>\nMajor<\/td>\nGood<\/td>\nBleeding<\/td>\n<\/tr>\n
Venlafaxine +<\/p>\n

Aspirin<\/td>\n

1 (5)<\/td>\nMajor<\/td>\nGood<\/td>\nBleeding<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Note: The identified pDDIs were graded based on the severity and documentation as specified by Micromedex database 2.0<\/p>\n

Frequency of potential drug-tobacco interactions (pDTIs)<\/strong><\/p>\n

In our study, seventeen patients smoked tobacco cigarettes,among which pDTIs were identified in ten patients.\u00a0 The average age of these individuals was 31.08 +<\/u> 11.08 years.\u00a0 The psychiatric diagnosis among these patients wasgeneralized anxiety disorder (30%), major\u00a0depressive disorder (20%), substance abuse (20%), borderline personality disorder (10%), adjustment disorder with mixed anxiety and depressed mood (10%) and anxious depression (10%). In addition, we observed distinct types of pDTIs, the severities of which are described in Table 5.<\/p>\n

 <\/p>\n

Frequency of potential drug-ethanol interactions (pDEIs)<\/strong><\/p>\n

Among the six patients who consumed alcohol in our study, the pDEIswere identified in five patients as they continued to consume alcohol during the treatment with antidepressants. The mean age of these patients was 44.6 \u00b1 9.54 years.Major depressive disorder (40%), borderline\u00a0personality disorder (20%), generalized anxiety disorder (20%), and substance abuse (20%) were the psychiatric diagnoses in these patients. Three types of pDEIswere detected; their severity is compiled in Table 5.<\/p>\n

Table 5: Types of pDTIs and pDEIs associated with antidepressants.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n
Type of pDTIs&pDEIs<\/strong><\/td>\nn ( %)<\/strong><\/td>\nSeverity<\/strong><\/td>\nDocumentation<\/strong><\/td>\nPharmacological Consequences: May result in Increased Risk of<\/strong><\/td>\n<\/tr>\n
Mirtazapine + Tobacco<\/td>\n5 (38.5)<\/td>\nMajor<\/td>\nFair<\/td>\nCYP1A2 substrates<\/td>\n<\/tr>\n
\n

Agomelatine +<\/p>\n

Tobacco<\/p>\n<\/td>\n

4 (30.8)<\/td>\nMajor<\/td>\nFair<\/td>\nCYP1A2 substrates<\/td>\n<\/tr>\n
uloxetine +<\/p>\n

TobaccDo<\/td>\n

3 (23)<\/td>\nMajor<\/td>\nFair<\/td>\nCYP1A2 substrates<\/td>\n<\/tr>\n
Fluvoxamine +<\/p>\n

Tobacco<\/td>\n

1 (7.7)<\/td>\nMajor<\/td>\nFair<\/td>\nCYP1A2 substrates<\/td>\n<\/tr>\n
Mirtazapine + Ethanol<\/td>\n3(60)<\/td>\nModerate<\/td>\nGood<\/td>\nPsychomotor impairment<\/td>\n<\/tr>\n
Escitalopram + Ethanol<\/td>\n1(20)<\/td>\nModerate<\/td>\nFair<\/td>\n\n

Potentiation of the cognitive and motor effects of alcohol<\/p>\n<\/td>\n<\/tr>\n

Venlafaxine + Ethanol<\/td>\n1(20)<\/td>\nMinor<\/td>\nFair<\/td>\nIncreased risk of CNS effects<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Predictors of pDDIs<\/strong><\/p>\n

Among the various parameters analyzed in the study, a significant association was observed between potential drug interactions and the number of drugs prescribed (X2 <\/sup>= 6.582; p=0.014), while an even more significant association was observed for the presence of total polypharmacy (X2 <\/sup>= 12.146; p<0.01) and presence of psychiatric polypharmacy (X2 <\/sup>= 16.983;\u00a0p<0.01). The analysis is highlighted in Table 6.Further, the estimation of relative risk revealed that patients using more than three medications are at one and half times more risk of pDDIs; similarly,patients with total polypharmacy and psychiatric polypharmacy are almost eight times and five times more risk of pDDIs respectively (p<0.01).The detailsare presented in Table 7.<\/p>\n

Table 6: Association between demographic, disease, and treatment-related variables and presence of pDDIs.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n
\n

Variable<\/strong><\/p>\n<\/td>\n

Total number of patients (n=131)<\/strong><\/td>\nChi-square<\/strong><\/td>\n<\/tr>\n
Interaction present (n=67)<\/strong><\/td>\nInteraction absent (n=64)<\/strong><\/td>\nX2<\/sup><\/strong><\/td>\np-value<\/strong><\/td>\n<\/tr>\n
Gender <\/strong><\/td>\nMale<\/p>\n

Female<\/td>\n

27 (40.3)<\/p>\n

40 (59.7)<\/td>\n

23 (35.9)<\/p>\n

41 (64.1)<\/td>\n

0.264<\/td>\n\n

0.719<\/p>\n<\/td>\n<\/tr>\n

Nationality<\/strong><\/p>\n

\u00a0<\/strong><\/td>\n

Emirati<\/p>\n

Expatriate<\/td>\n

43 (64.2)<\/p>\n

24 (35.8)<\/td>\n

45 (70.3)<\/p>\n

19 (29.7)<\/td>\n

0.558<\/td>\n0.464<\/td>\n<\/tr>\n
Age <\/strong><\/p>\n

\u00a0<\/strong><\/td>\n

< 65 years<\/p>\n

><\/u> 65 years<\/td>\n

61 (91)<\/p>\n

06 (09)<\/td>\n

55 (85.9)<\/p>\n

09 (14.1)<\/td>\n

0.842<\/td>\n0.418<\/td>\n<\/tr>\n
Presence of General Medical conditions<\/strong><\/td>\nYes<\/p>\n

No<\/p>\n

Unknown<\/td>\n

35 (52.2)<\/p>\n

32 (51.6)<\/p>\n

00 (0.0)<\/td>\n

32 (47.8)<\/p>\n

30 (48.4)<\/p>\n

02 (100)<\/td>\n

 <\/p>\n

2.131<\/td>\n

 <\/p>\n

0.564<\/td>\n<\/tr>\n

Number of Drugs Prescribed<\/strong><\/td>\n<<\/u>3 drugs<\/p>\n

> 3 drugs<\/td>\n

29 (40.8)<\/p>\n

38 (63.3)<\/td>\n

42 (59.2)<\/p>\n

22 (36.7)<\/td>\n

6.582<\/td>\n0.014*<\/td>\n<\/tr>\n
Presence of Total Polypharmacy<\/strong><\/td>\nYes<\/p>\n

No<\/td>\n

66 (98.5)<\/p>\n

01 (1.5)<\/td>\n

51 (79.7)<\/p>\n

13 (20.3)<\/td>\n

12.146<\/td>\n0.000**<\/td>\n<\/tr>\n
Presence of Psychiatric Polypharmacy<\/strong><\/td>\nYes<\/p>\n

No<\/td>\n

65 (97)<\/p>\n

02 (1.8)<\/p>\n

 <\/td>\n

49 (76.6)<\/p>\n

15 (23.4)<\/p>\n

 <\/td>\n

 <\/p>\n

16.983<\/td>\n

\u00a0<\/strong><\/p>\n

0.000**<\/p>\n

 <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

*p<0.05 is statistically significant; **p<0.01 is statistically highly significant<\/em><\/p>\n

Multiple regression was carried out to investigate whether the presence of psychiatric polypharmacy, total polypharmacy, and a total number of drugs could significantly predict pDDIs. The results of the regression indicated that the model explained 13.1% of the variance\u00a0 and that the model was a significant predictor of pDDIs (F[3, 127]= 6.368, p< 0.01, R2<\/sup> = 0.13). Onlythe presence of psychiatric polypharmacy contributed significantly to the model (B = -0.423, p<0.05). While presence of\u00a0 total polypharmacy (B = 0.122, p=0.52) and total number of drugs did not (B= -0.147, p=0.08).<\/p>\n

Table 7: Predictors of Potential Drug-Drug Interaction<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n
Variable<\/strong><\/td>\nTotal number of patients (n=131)<\/strong><\/td>\nRelative Risk<\/strong><\/td>\n<\/tr>\n
Interaction present (n=67)<\/strong><\/td>\nInteraction absent (n=64)<\/strong><\/td>\nRR (95% CI)<\/strong><\/td>\np-value<\/strong><\/td>\n<\/tr>\n
Number of Drugs Prescribed<\/strong><\/td>\n<\/tr>\n
<<\/u><\/strong>3 drugs<\/strong><\/p>\n

> 3 drugs<\/strong><\/td>\n

29 (40.8)<\/p>\n

38 (63.3)<\/td>\n

42 (59.2)<\/p>\n

22 (36.7)<\/td>\n

1.5 [1.1-2.1]<\/td>\n0.01*<\/td>\n<\/tr>\n
Presence of Total Polypharmacy<\/strong><\/td>\n<\/tr>\n
No<\/strong><\/p>\n

Yes<\/strong><\/td>\n

01 (1.5)<\/p>\n

66 (98.5)<\/td>\n

13 (20.3)<\/p>\n

51 (79.7)<\/td>\n

7.9 [1.1-52.5]<\/td>\n0.02*<\/td>\n<\/tr>\n
Presence of Psychiatric Polypharmacy<\/strong><\/td>\n<\/tr>\n
No<\/strong><\/p>\n

Yes<\/strong><\/td>\n

02 (1.8)<\/p>\n

65 (97)<\/td>\n

15 (23.4)<\/p>\n

49 (76.6)<\/td>\n

4.8 [1.3-17.9]<\/td>\n0.01*<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

*p<0.05 is statistically significant.<\/em><\/p>\n

Discussion<\/strong><\/p>\n

Eighty-eight potential interactions were observed in 48.1% of study patients. As a result, the total frequency of pDDIs in the antidepressant-treated study population was67.2%, of which 83% of patients had pDDIs of major severity. Our study findings were in accordance with a\u00a0previous study which reported a pDDI prevalence of 57.5%. However, most patients (42.5%) in that study experienced pDDIs of moderate severity3<\/sup>. The most common pDDIs documented werewith escitalopram and mirtazapine and fluoxetine with propranolol combinations. The\u00a0commonly prescribed interacting pair were citalopram and diclofenac (11.6%), followed by imipramine and labetalol (10.5%) and fluoxetine and propranolol (9.39%)3<\/sup>.Imipramine and methylphenidate were the most commonly interacting pair in a studyto determine and evaluate\u00a0the prevalence and significance of pDDIs in children and adolescents aged \u2264 18 yearsreceiving antidepressants13<\/sup>.<\/p>\n

Most of the pDDIs documented in our studywere significant. However, the prescribed medications’ benefitsseemed to be greater than the possible risks caused by the pDDIs. Most of the pDDIs were associated with psychotropic medications rather than other\u00a0medications, but they did not cause any severe clinical outcome. All the documented interactions were in accordance with the recent clinical trials except for one pDDI, which was contraindicated. The contraindications documented in our study are lower than reported earlier3<\/sup>.<\/p>\n

Interactions between Antidepressants and non-psychiatric prescription<\/strong><\/p>\n

\u00a0<\/strong>Twenty-one pDDIs were identified in 9.1% of the study patients who were prescribed psychiatric and non-psychiatric medications, with an overall frequency of pDDIs in 16% of psychiatric outpatients receiving antidepressants. The most commonly documented pDDIs\u00a0 , levothyroxine (14.3%), escitalopram, and aspirin (14.3%) combinations. The interaction between escitalopram and levothyroxine is moderate but may increase the requirement of levothyroxine. The interaction between escitalopram and aspirin is major and can\u00a0cause an increased risk of bleeding. The pDDI was commonly observed in patients with major depressive disorder.<\/p>\n

Increased risk of bleeding<\/strong><\/p>\n

In our study, interactionswere observedwith concomitant use of antidepressants and anticoagulants or antiplatelets, resulting in an increased risk of bleeding. Since depressive syndrome is common after stroke, due consideration should be given for potential interactions\u00a0between antidepressants and anticoagulants or antiplatelets medications. Hence, before selecting an antidepressant in patients on other medications, it is beneficial to refer to an updated drug information database14<\/sup>.<\/p>\n

Concomitant use of some antidepressants and NSAIDs may also increase the risk of bleeding. The bleeding risk is attributed to an SSRI-induced increase in gastric secretion or depletion in platelet serotonin. The use of a proton pump inhibitor can reduce the risk of\u00a0gastrointestinal bleeding15<\/sup>. Concurrent use of SSRIs and NSAIDs increases the risk of gastrointestinal side effects tenfold over SSRIs alone and fourfold over NSAIDs alone. However, concomitant administration of TCAs with NSAIDs does not have this effect4\u00a0<\/sup><\/p>\n

Drug- tobacco interactions <\/strong><\/p>\n

Among the study population, 12.9% were regular tobacco cigarette smokers. A previous study reported a 20.3% prevalence of smoking among schizophrenic patients in psychiatry outpatient clinics16<\/sup>. Drug-tobacco interactions (DTIs) between antidepressant\u00a0prescription and tobacco smoking were observed in 7.6% of patients. In our study, generalized anxiety disorder was the most common psychiatric disorder associated with DTIs. A higher likelihood of agoraphobia, generalized anger, and panic disorders are caused by increased\u00a0cigarette smoking in adolescents17<\/sup>. Decrease in the plasma concentration of mirtazapine and agomelatine most commonly observed in interaction with tobacco smoking. Smokers using imipramine might require higher doses, while no dose adjustments are required for other tricyclic\u00a0antidepressants such as amitriptyline or clomipramine18<\/sup>. Smokers may require doses higher than the recommended dose in clinical trial data.Dose adjustments may be required in patients who decide to quit or reduce smoking19<\/sup>.In patients who decide to quit, US Food and Drug Administration approved bupropion is an excellent choice for patients who want to stop smoking as it can reduce the desire for nicotine and doubles rates of smoking cessation14<\/sup>.<\/p>\n

Drug-ethanol interactions <\/strong><\/p>\n

Six individuals in the research group had a pre-existing habit of taking alcohol, and of them, five (3.8%) were exposed to the medication-alcohol interaction.Major depressive disorder was the most common psychiatric condition associated with drug-ethanol interaction\u00a0(DEIs). Alcohol consumption is associated with slightly higher rates of major depression20<\/sup>. In our study, three types of DEIs were detected. The most common was ethanol interactions with mirtazapine resulting in psychomotor impairment. They were followed by ethanol and\u00a0escitalopram to potentiateethanol\u2019s cognitive and motor effects. Both interactions were moderate in severity. Another interaction was ethanol with venlafaxine, which may result in an increased risk of CNS effects. This interaction was of minor severity. Acute or chronic ethanol drinking\u00a0combined with psychiatric medicines may result in several clinically important toxicological interactions.<\/p>\n

Ethanol use, both acute and chronic, may alter the pharmacodynamics and pharmacokinetics of such medicines.\u00a0 Pharmacodynamics interaction, such as altering drug action,is more significant than kinetic interaction like enhancing drug metabolism8<\/sup>.Ethanol pharmacodynamic\u00a0 interactions involve enhancing the drug’s effects, particularly in the CNS (e.g., sedation). Pharmacokinetics interactions result in faster metabolism of the drugs. Chronic ingestion of ethanol may increase microsomal protein and P450,reducingthe plasma half-life of many psychiatric medications8<\/sup>.It can interfere with the first-pass metabolism of amitriptyline,\u00a0leading to increased amitriptyline levels in the blood. On the other hand, no severe interactions appear to occur between SSRIs and Ethanol21<\/sup>.<\/p>\n

Predictors of pDDIs<\/strong><\/p>\n

We observed that the study population using more than three medications, total polypharmacy, and psychiatric polypharmacy, hadan increased risk of pDDIs. In comparison, research conducted in the same study setting reported the number of drugs and polypharmacy as the predictors of\u00a0pDDIs among psychiatric inpatients receiving antipsychotic medications22<\/sup>. Polypharmacy is a crucial contributing factor associated with increased risk of pDDIs23<\/sup>.\u00a0 Research revealed that forecasting polypharmacy and DDI at the time of admission in psychiatric hospitals is critical for\u00a0effective management, such as pharmaceutical supervision24<\/sup>.<\/p>\n

Limitations of the study <\/strong><\/p>\n

As the prescription analysis was carried out only three days of the week, the study sample was small and may not represent all the psychiatric cases treated in the same setting.Furthermore, in some cases, the patient’s electronic medical records did not include information on social and\u00a0medical histories and the counter drugs prescribed. Additionally, as this study was conducted in a government hospital, the choice of antidepressants was limited.<\/p>\n

Conclusion <\/strong><\/p>\n

Almost fifty percent of the patients receiving antidepressants were at risk of potential drug interactions. Escitalopram and mirtazapine, followed by mirtazapine and duloxetine, were the most frequent interacting drugpairs.More than three medications, total polypharmacy, and\u00a0psychiatric polypharmacy increase the risk of pDDIs in patients prescribed with antidepressants. This study contributes to updating the knowledge of the severity of different pDDIs, which benefits clinicians in maintaining patient safety and aids in selecting appropriate antidepressants for relevant groups of patients.<\/p>\n

Acknowledgement<\/strong><\/p>\n

Our heartfelt appreciation goes out to the whole health care team in the study setting\u00a0and the hospital director for their constant support. The authors express their gratitude to all the RAK Medical and Health Sciences University authorities, Ras Al Khaimah, for their kind support duringthe research period.<\/p>\n

Conflict of Interest <\/strong><\/p>\n

The authors declare no conflict of interest<\/p>\n

Funding Source<\/strong><\/p>\n

Nil<\/p>\n

References<\/strong><\/p>\n

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