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Dagnewetal.
BMC Pharmacology and Toxicology (2022) 23:88
https://doi.org/10.1186/s40360-022-00630-1
RESEARCH
Potential drug-drug interactions
andassociated factors amongadmitted patients
withpsychiatric disorders atselected hospitals
inNorthwest Ethiopia
Ephrem Mebratu Dagnew1, Asrat Elias Ergena2, Samuel Agegnew Wondm1 and Ashenafi Kibret Sendekie3*
Abstract
Background: Prescribing medications without potential drug-drug interactions (pDDIs) is one of the components of
the rational use of medications. However, taking combined medications has resulted in life-threatening pDDIs, which
are causing severe clinical outcomes for patients. This study was aimed at assessing the prevalence of pDDIs and
associated factors in admitted patients with psychiatric disorders.
Methods: An institution-based multicenter cross-sectional study was conducted among patients with psychiatric
disorders admitted to a selected hospital in Northwest Ethiopia. Samples were approached through a systematic
sampling method. The Statistical Package for the Social Sciences (SPSS) version 26 was used to analyze the data.
Logistic regression was applied to determine the association of variables with pDDIs. A p-value of < 0.05 was statisti-
cally significant.
Results: Out of 325 study participants, more than half (52.9%) were females, with a median age of 61 years. Overall,
more than two-thirds (68.9%) were exposed to at least one clinically significant, either significant or serious level of
pDDIs. Nearly one-fourth (23.2%) of participants had at least one serious level of pDDIs. Older patients were found
more likely to have pDDIs compared to younger patients (p = 0.043). Similarly, patients with a higher number of pre-
scribed medications (p = 0.035) and patients with longer hospital admissions (p = 0.004) were found more likely to be
exposed to pDDIs than their counterparts.
Conclusion: In this study, a significant number of admitted patients with psychiatric problems encountered clinically
significant pDDIs. As a result, healthcare providers could assess and follow patients with a combination of medications
that potentially have a drug-drug interaction outcome.
Keywords: Drug-drug interactions, Psychiatric disorders, Severity, Northwest Ethiopia
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Introduction
Medications have a potential contribution to negative
treatment outcomes unless appropriately used. us,
the morbidity and mortality of patients with a series of
medical illnesses has been significantly affected by inap-
propriate medication use [1]. Drug-drug interaction,
among different medication-related problems, can occur
when the effect of one drug is altered by another drug,
Open Access
*Correspondence: ashukib02@yahoo.com; Ashenafi.kibret@uog.edu.et
3 Depatment of Clinical Pharmacy, School of Pharmacy, College of Medicine
and Health Sciences, University of Gondar, Gondar, Ethiopia
Full list of author information is available at the end of the article
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Page 2 of 9
Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
including a concomitant treatment, over-the-counter
medication, food, or substance, like alcohol or tobacco
[2]. As a result, a drug-drug interaction can be defined
as the pharmacological response to the administra-
tion or co-exposure of one drug with another drug that
modifies the response of patients to the drug effect [3].
e consequences of clinically significant pDDIs have a
negative impact on the morbidity, mortality, duration of
hospitalization, quality of life, and healthcare costs of the
patients [4].
A clinically relevant drug-drug interaction occurs when
the effectiveness or toxicity of one medication is altered
by the administration of another medication or a sub-
stance that is administered for medical purposes (to be
distinguished from drug-food interactions). Adverse
consequences of drug-drug interactions may result
from either diminished therapeutic effect or toxicity [5].
Drug-drug interactions (DDIs) are becoming an increas-
ingly important cause of adverse drug reactions. It has
been reported that 20 − 30% of all adverse reactions to
drugs are caused by drug-drug interactions, which can be
prevented through appropriate monitoring and follow-
up. But this incidence increases among the elderly and
patients who take two or more medications [2].
Drugs for psychiatric disorders that result in serum
concentration changes are generally most relevant for
drugs with a narrow therapeutic index. ese drugs
include lithium and clozapine, where increases or
decreases play a role in worsening clinical conditions or
increasing the risk of serious adverse effects [6].
e most serious interactions with psychotropics result
in profound sedation, central nervous system toxicity,
large changes in blood pressure, ventricular arrhyth-
mias, and an increased risk of dangerous side-effects or
a decreased therapeutic effect of one of the interacting
drugs [7, 8]. It is difficult to completely prevent drug-drug
interactions, especially in patients with psychiatric prob-
lems, due to the lifelong treatment use of multidrug reg-
imens and the fact that most patients are elderly. Close
monitoring of highly at-risk patients may prevent life-
threatening outcomes. Nowadays, drug-drug interactions
are among the major challenges in patients with psychi-
atric disorders. Monitoring and reporting of these DDIs
in medications used for psychiatric problems is neces-
sary due to the pharmacokinetic and pharmacodynamic
nature of the drugs. However, in Ethiopia, the investiga-
tions regarding the prevalence and nature of pDDIs in
admitted patients with psychiatric disorders are limited.
Even though there is a single study that demonstrated
drug-drug interactions in patients with psychiatric dis-
orders, it was a single-center study with a retrospective
cross-sectional design [8]. e current multicenter study
was part of a project initially published regarding the
prevalence of drug-related problems (DRPs) [9]. e ini-
tial study couldn’t address a detailed investigation of the
extent of drug-drug interactions and its determinants.
erefore, this study assessed the prevalence of poten-
tial drug-drug interactions and associated factors among
admitted patients with psychiatric disorders in selected
hospitals in Northwest Ethiopia. e study also analyzed
the severity of existing drug-drug interactions.
Methods
Study design andsetting
An institutional-based multicenter cross-sectional study
was conducted from April to July 2021 at five compre-
hensive and specialized hospitals in Northwest Ethio-
pia. ese hospitals include the University of Gondar
Comprehensive and Specialized Hospital (UoGCSH),
Felege-Hiwot Comprehensive and Specialized Hospital
(FHCSH), Tibebe-Ghion Comprehensive and Specialized
Hospital (TGCSH), Debre-Markos Comprehensive and
Specialized Hospital (DMCSH), and Debre-Tabor Com-
prehensive and Specialized Hospital (DTCSH). ese
hospitals have provided healthcare services for over
26.5million people in their total catchment areas.
Study participants andinclusion criteria
All adult patients with a psychiatric problem who were
admitted to the psychiatric wards of selected hospitals in
Northwest Ethiopia were included in the study popula-
tion. Patients aged 18 years or older, diagnosed with any
psychiatric disorder and received a combination of medi-
cations were included in the study. Pregnant and lactat-
ing mothers, critically ill patients who couldn’t respond
to self-response interview questions, and patients with
incomplete medical records during the study period did
not participate in this study.
Sample size determination andsampling techniques
e single population proportion formula was used to
calculate the required sample size by considering the
following assumptions: the proportion of drug–drug
interactions to be 81.8% (P = 0.82) [8], the reliability coef-
ficient for 95% confidence level (Z = 1.96) and 5% margin
of error (d = 0.05); n = z2pq/d2.
After adding a 10% contingency of non-response, the
total sample size of participants to be selected was 325.
Participants from the selected hospitals were included
based on a proportional allocation formula: ni = n*Ni/N,
where, ni = sample size from each hospital, n = total sam-
ple size to be selected, N = total population, Ni = total
population from each selected hospital. Consequently,
the total population from all selected study areas was
984 per year (264 from UoGCSH, 192 from FHCSH, 180
from TGCSH, 192 from DMCSH, and 156 from DTCSH)
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Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
based on the previous admission. Considering this, 87,
63, 60, 63, and 52 study participants were included from
the respective hospitals in the final study.
e participants were included in the final study using
a consecutive sampling technique, and all eligible partici-
pants from respective sites were enrolled consecutively
until the required sample size was obtained.
Denition ofterms
Psychiatric disorders:according to the DSM-5 definition,
“a syndrome characterized by clinically significant distur-
bance in an individual’s cognition, emotion regulation,
or behavior reflecting a dysfunction in the psychological,
biological, or developmental processes underlying mental
function.”[10].
Drug-drug interactions:defined as the pharmacological
or clinical response to the administration or co-exposure
of a drug with another drug that modifies the patient’s
response to the drug index [3].
Potential drug-drug interactions: According to Con-
sensus recommendations for systematic evaluation of
drug-drug interaction evidence for clinical decision sup-
port “a potential DDI is defined as the co-prescription of
two drugs known to interact, and therefore a DDI could
occur in the exposed patient” [11].
e severity of drug-drug interactions:it is the level of
evidence of the severity of the outcome from interactive
medications. It can either be contraindicated, the drug-
pair is contraindicated in the patient for current use, seri-
ous; such an interaction may have a risk of death and/or
may result in some serious negative outcome, and recom-
mended to use an alternative, significant; it may have a
harmful effect on the patient’s condition and can require
close monitoring, or minor (no change required); it may
have an increase in frequency or severity of side effects,
but would not require therapeutic change and, they are
self-limited effects on patients [12].
Comorbidity: is the presence of one or more addi-
tional conditions, often co-occurring with the primary
condition.
Duration of treatment:refers to how long (in years) a
patient was treated with a manual method for any given
problem.
Data collection instruments, procedures andquality
management
e data was collected using a structured English
questionnaire developed after reviewing various lit-
erature [13–21]. It was collected by both patient inter-
views and retrospective medical recording methods
for primary and secondary data, respectively. Patient
socio-demographic characteristics include: age, gen-
der, monthly income, alcohol drinking habit, sub-
stance use (Khat and cigarettes), educational level,
occupations, residency, etc. Whereas medications and
clinical characteristics like history of allergy, type of
medication, number of medications, the duration of
treatment, presence of comorbidities, type of psychiat-
ric disorders, and number of hospitalizations were also
extracted from the medical records of the participants.
Data were collected by five trained clinical pharmacists
and five trained psychiatric nurses, who were overseen
by two clinical pharmacy lecturers. e chart num-
bers were entered into Microsoft Office Excel 2016 and
checked for duplication.
To ensure the quality of the data, data collectors were
trained for two days, and orientation was also provided
by the principal investigator. e principal investiga-
tor (PI) closely supervised the data collection process,
and the collected data was checked daily for complete-
ness during the data collection period. e data collec-
tion tool was pretested on 5% of the calculated sample
size of patients admitted to the psychiatric ward of
Dessie comprehensive specialized hospital to check
the acceptability and consistency of the data collec-
tion tool two weeks before the actual data collection.
e data from the pretest was excluded in the analysis.
e questionnaire was sent to senior clinical pharma-
cists and senior physicians, who were academicians and
researchers, for face validity and approval.
Data entry andstatistical analysis
The data was coded, cleared, and checked for com-
pleteness before being entered into EPI-data version
4.6 and exported to the statistical software package for
social sciences (SPSS) version 26 for analysis. Then, it
was reviewed and cleaned manually for its complete-
ness and consistency. The results were summarized
using descriptive statistics including frequency and
percentage for categorical and mean and standard
division for continuous variables. The Medscape drug-
interaction checker was used to check for pDDIs. To
make the assessment of the existing pDDIs consist-
ent, the severity of identified drug-drug interactions
was also characterized using evidence from Medscape.
Finally, we analyzed only clinically significant drug-
drug interactions with most of the pDDIs resulting
in significant and serious levels of drug-drug interac-
tions. Independent variables having a p-value < 0.25 in
the univariate logistic regression analysis entered into
the multivariable logistic regression analysis to control
the confounding effect. The odds ratio (OR) with a 95%
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Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
confidence interval was also computed. In the final
model, a p-value < 0.05 was statistically significant.
Results
Socio‑demographic characteristics ofthestudy
participants
More than half (172, or 52.9%) of the study partici-
pants were females, with a median age of 61 (24–85)
years. The majority of the participants were rural resi-
dents; 215(66.2%). More than half, 173 (53.2%), of the
participants had no regular monthly income and the
majority of the respondents were substance non-users,
319 (98.2%) (Table1).
Clinical characteristics ofthestudy participants
Regarding the types of psychiatric disorders, schizo-
phrenia 140 (30.8%) was responsible for the admission
of a greater proportion of patients. More than half of
the participants, 182 (56%), had comorbid conditions
in addition to psychiatric disorders. The majority of
the study participants, 290 (89.2%), were admitted for
more than a week. The study participants received
an average of 3 (ranges 1–8) medications per patient
(Table2).
Prevalence ofpotential drug‑drug interaction
anddistribution based onseverity
A higher proportion of study participants (107, 33%) had
1 to 3 pDDIs. is study showed that the overall preva-
lence of the pDDIs was found to be 68.9%, which revealed
that a total of 224 participants were encountered with
at least one serious or significant pDDIs, with a median
(range) of 3 (1–7) pDDIs per patient. Regarding the
severity of pDDIs near one-fourth, 52 (23.2%) of the par-
ticipants had serious drug-drug interactions (Table3).
Common interacting medications, their level ofinteraction
andadverse outcomes
Patients on a combination of fluoxetine and amitripty-
line accounted for a higher proportion of serious pDDIs,
10(4.5%), while a combination of chlorpromazine and
trihexyphenidyl was responsible for a higher propor-
tion of patients, 45(20.1%) exposed to significant pDDIs
(Table4).
Factors associated withtheoccurrence ofpotential
drug‑drug interactions
Logistic regression analysis was performed to examine
the relationship between existing pDDIs and the num-
ber of predictor variables. Multivariable logistic regres-
sion revealed that age, number of drugs, and hospital
Table 1 Socio-demographic characteristics among patients with psychiatric disorders admitted in selected hospitals of Northwest
Ethiopia from April –July, 2021 (N = 325)
Variables Category Frequency (%) Median (range)
Sex Male 153(47.1)
Female 172(52.9)
Age in years 18–30 89(27.4) 61(24–85)
31–45 115(35.4)
46–60 71(21.8)
≥ 61 50(15.4)
Residency Rural 215(66.2)
Urban 110(33.8)
Educational status Non-formal education 108(33.2)
Primary education 106(32.6)
Secondary 61(18.8)
College and university 50(15.4)
Monthly income (Eth birr) < 1500 27(8.3)
1500–2499 38(11.7)
2500–3499 35(10.8)
≥ 3500 52(16)
No regular income 173(53.2)
Substance use (Khat, cigarette) Yes 6(1.8)
No 319(98.2)
Alcohol drinking habit Yes 33(10.2)
No 292(89.8)
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Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
stay were independently associated with the occurrence
of pDDIs in admitted patients with psychiatric disor-
ders. Consequently, it has been found that, holding all
other predictor variables constant, the odds of pDDIs
in elderly patients with an age greater than or equal to
61 is about 1.5 times [AOR = 1.47, 95% CI (1.13–2.56);
p = 0.043] compared with patients aged 18–30 years
old. Similarly, patients with a higher number of pre-
scribed medications and those who stayed longer at the
hospital were found more likely to be exposed to pDDIs
than their counterparts, [AOR = 2.75, 95% CI (1.56–
7.31); p = 0.035] and [AOR = 2.13, 95% CI (1.34–3.64);
p = 0.004], respectively (Table5).
Discussion
Prescribing medications without potential drug-drug
interactions is a component of the rational use of medi-
cations. Drug-drug interactions continue to be a major
cause of morbidity and mortality of admitted patients
[22]. Administration of more than or equal to two drugs
for an admitted patient repeatedly leads to pDDIs, which
may further compromise the patient’s health-related out-
come. To the best of the authors’ literature search, the
prevalence and extent of potential drug-drug interactions
in admitted patients with psychiatric disorders have not
been investigated in the study areas. erefore, this facil-
ity-based multicenter study was conducted to determine
the prevalence of potential drug-drug interactions and
the severity of the existing drug-drug interactions using
the Medscape drug-drug interaction checker in admitted
patients with psychiatric disorders.
Overall, nearly two-thirds (68.9%) of the study partici-
pants had clinically significant pDDIs, which is consist-
ent with the previous studies [21, 23, 24]. e finding
suggests that a higher proportion of patients have at least
one significant potential drug-drug interaction. ere-
fore, patients taking a combination of potentially inter-
active medications need close follow-up. In contrast,
the current finding is lower than studies demonstrated
in Mekelle, Ethiopia [8]. e discrepancy in the preva-
lence of pDDIs among different studies might be related
to differences in healthcare approach with pharmacist
Table 2 Clinical characteristics of the study participants
Othersa, substance-related disorders, anxiety disorders, post-traumatic disorders
Variables Category Frequency, n (%) Median (range)
Types of psychiatric disorders at admission Schizophrenia 140(30.8)
Brief-psychotic feature 117(25.7)
Bipolar disorder 67(14.7)
Major mood disorder 55(12.1)
Othera8(2.5)
Presence of comorbidities No 143(44)
Yes 182(56)
Types of comorbidities Heart failure 6(1.8)
Substance use 6(1.6)
Peptic ulcer disease 5(1.5)
Retroviral infection (HIV) 3(0.9)
Tuberculosis (TB) 2(0.6)
Hospital stays (days) < 7 35(10.8) 14(3–35)
≥ 7 290(89.2)
Number of prescribed medications < 5 184(56.6) 3 (1–8)
≥ 5 141(43.4)
Duration of treatment ≤ 1 year 176 (54.1)
2–3 years 86 (26.5)
≥ 4 years 63 (19.4)
Table 3 Prevalence and severity of potential drug-drug
interactions among the study participants
Variables Category Frequency, n (%) Median (range)
Prevalence of pDDIs 1–3 107(33%) 3 (1–7)
4–5 84(25.8%)
≥ 6 33(10.2%)
Total 224 (68.9%)
Level (severity) of
pDDIs Serious 52(23.2%)
Significant 172(76.8%)
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Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
Table 4 Level of pDDIs and potential adverse outcome with respective combined prescribed medications (N = 224)
Paired medications Frequency (%) Leve of interaction Adverse outcome
Fluoxetine -Amitriptyline 10(4.5) Serious Fluoxetine increases the effect of amitriptyline by affecting CYP2C19.
Fluoxetine and amitriptyline both increase serotonin levels. Avoid
use in combination.
Carbamazepine-diazepam 8(3.6) Serious Carbamazepine will decrease the level or effect of diazepam by
affecting hepatic/intestinal enzyme CYP3A4 metabolism. Avoid or
Use Alternate Drug.
Carbamazepine-haloperidol 7(3.1) Serious Carbamazepine will decrease the level or effect of haloperidol by
affecting hepatic/intestinal enzyme CYP3A4 metabolism. Avoid or
Use Alternate Drug.
Fluoxetine-Risperidone 6(2.7) Serious Fluoxetine will increase the level or effect of risperidone by affecting
hepatic enzyme CYP2D6 metabolism. Avoid or Use Alternate Drug.
Fluoxetine-Haloperidol 5(2.2) Serious Fluoxetine will increase the level or effect of haloperidol by affecting
hepatic enzyme CYP2D6 metabolism. Avoid or Use Alternate Drug.
Chlorpromazine-Amitriptyline 5(2.2) Serious Chlorpromazine and amitriptyline both increase QTc interval. Avoid
or Use Alternate Drug.
Chlorpromazine-Haloperidol 4(1.8) Serious chlorpromazine and haloperidol both increase QTc interval. Avoid or
Use Alternate Drug.
Fluoxetine-cimetidine 4(1.8) Serious Fluoxetine will increase the level or effect of cimetidine by affecting
hepatic enzyme CYP2C19 metabolism. Avoid or Use Alternate Drug.
Fluphenazine deaconate-haloperidol 3(1.3) Serious fluphenazine and haloperidol both increase QTc interval. Avoid or
Use Alternate Drug.
Chlorpromazine-Trihexyphenidyl 45(20.1) Significant Chlorpromazine increases effects of trihexyphenidyl by pharma-
codynamic synergism. Use Caution/Monitor. Potential for additive
anticholinergic effects.
Haloperidol-Trihexyphenidyl 32(14.3) Significant haloperidol increases effects of trihexyphenidyl by pharmaco-
dynamic synergism. Use Caution/Monitor. Potential for additive
anticholinergic effects.
Trifluoperazine-trihexyphenidyl 25(11.2) Significant trifluoperazine increases effects of trihexyphenidyl by pharmaco-
dynamic synergism. Use Caution/Monitor. Potential for additive
anticholinergic effects.
Fluphenazine decanoate-trihexyphenidyl 22(9.8) Significant Fluphenazine increases effects of trihexyphenidyl by pharmaco-
dynamic synergism. Use Caution/Monitor. Potential for additive
anticholinergic effects.
Fluoxetine- Amitriptyline 10(4.5) Amitriptyline and fluoxetine both increase QTc interval. Modify
Therapy/Monitor Closely.
Carbamazepine-diazepam 8(3.6) Significant Carbamazepine decreases levels of diazepam by increasing metabo-
lism. Use Caution/Monitor.
Carbamazepine-haloperidol 7 (3.6) Significant Carbamazepine decreases levels of haloperidol by increasing
metabolism. Use Caution/Monitor.
Fluoxetine-Risperidone 6(2.7) Significant Fluoxetine and risperidone both increase QTc interval. Use Caution/
Monitor.
Fluoxetine-Haloperidol 5(2.2) Significant Fluoxetine and haloperidol both increase QTc interval. Modify
Therapy/Monitor Closely.
Chlorpromazine-Amitriptyline 5(2.2) Significant Chlorpromazine and amitriptyline both increase sedation. Use Cau-
tion/Monitor.
Chlorpromazine-Haloperidol 4(1.8) Significant -Chlorpromazine and haloperidol both increase sedation. Use Cau-
tion/Monitor.
-chlorpromazine and haloperidol both increase antidopaminergic
effects, including extrapyramidal symptoms and neuroleptic malig-
nant syndrome. Use Caution/Monitor.
Fluphenazine-haloperidol 3(1.3)) Significant Fluphenazine and haloperidol both increase sedation. Use Caution/
Monitor.
-Fluphenazine and haloperidol both increase antidopaminergic
effects, including extrapyramidal symptoms and neuroleptic malig-
nant syndrome. Use Caution/Monitor.
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Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
involvement, differences in alternative medication avail-
ability, and differences in the use of software or tools to
identify pDDIs in these patients taking interactive medi-
cations. Additionally, the current study is a multicenter
study that may differ from a single study due to differ-
ences in pharmaceutical care across the settings.
Based on the severity of consequence outcomes result-
ing from interactive medications, the level of pDDIs
is commonly classified as contraindicated, major, sig-
nificant, and minor. In this study, we analyzed potential
drug-drug interactions, which were relevant in terms of
clinical outcome and quality of life of the patients. Con-
sistent with the previous studies [8, 21, 23, 24], most
study participants were exposed to clinically significant
pDDIs, either with serious or significant drug-drug inter-
actions, which needed interventions. Interactive medica-
tions may be prescribed because of the non-availability
of alternative medications with less interaction poten-
tial or due to the knowledge and skill gap of healthcare
practitioners about the pharmacokinetics and dynamics
properties of the medications. erefore, healthcare pro-
viders, particularly prescribers, could be vigilant about
the combination of medications, which can lead to life-
threatening treatment and clinically significant inter-
actions. e use of alternative medications with a low
potential for interaction could be recommended. Close
monitoring and follow-up of patients who received inter-
active medication is also strongly advised.
e occurrence of drug-drug interactions may have
many contributing factors. e current findings from
multivariate logistic regression revealed that being
elderly, being treated with a higher number of drugs, and
longer hospital stays were significantly associated with
the presence of pDDIs. In line with the previous studies
[24, 25], compared with younger patients (18–30 years),
older patients with an age greater than or equal to 61
years were found more likely to be exposed to pDDIs.
is finding might be justified by the fact that patients
of advanced age may have multimorbidity and comor-
bidities with polypharmacy, which can be responsible for
potential drug-drug interactions. Age-related changes
in pharmacokinetic properties of the drug may also be
responsible for pDDIs. e elderly psychiatric population
is particularly prone to being on many drugs, including
psychotropic, which increases the potential for a harmful
drug-drug interaction [25]. ese findings suggest that
elderly patients need to be under close monitoring and
follow-up with healthcare providers.
In line with the previous studies [2, 21, 24], the current
finding also revealed that patients treated with a higher
number of medications were more likely to be exposed
to pDDIs. As a result, patients with a higher number of
Table 5 Univariable and multivariable analyzes of factors associated with pDDIs
CORCrude odds ratio, AORAdjusted odds ratio
*denotes statistically signicant at p < 0.05
Variables Category Potential Drug‑drug
interaction COR (95% CI) AOR (95% CI) P‑value
No Yes
Age (Years) 18–30 22 67 1 1
31–45 43 72 0.55(0.13–1.89) 0.39(0.17–2.65)
46–60 27 44 0.54(0.09–1.02) 0.36(0.12–1.86)
≥ 61 9 41 1.5(1.01–2.65) 1.47(1.13–2.56) 0.043*
Sex Male 49 104 1 1
Female 52 120 0.92(0.24–2.16) 1.48(0.96–2.28) 0.62
Source of medication Free
Payment 61
40 134
90 1
0.98(0.17–2.04) 1
1.24(0.72–2.11) 0.429
Presence of Comorbidities No 36 107 1 1
1–2 21 47 1.33(0.76–2.25) 1.74(0.90–3.36) 0.098
3–4 32 61 1.56(0.28–4.74) 1.12(0.74–2.47) 0.076
≥ 5 12 9 3.96(0.32–18.45) 1.16(0.98–2.13) 0.087
Number of prescribed medications < 5
≥ 5 56
45 128
96 1
1.07(1.002–1.761) 1
2.75(1.56–7.31) 0.035*
Duration of treatment ≤ 1 year
2–3 years
≥ 4 years
56
25
20
120
61
43
1
0.88(0.15–2.67)
0.99(0.25–2.61)
1
0.67(0.35–1.40)
0.83(0.35–1.78)
0.31
0.57
Length of hospital stay < 7days
≥ 7 days 85
16 205
19 1
2.03(0.56–3.12) 1
2.13(1.34–3.64) 0.004*
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Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
medications could be assessed accordingly, and health-
care providers could be highly vigilant in the prevention
of harmful drug-drug interactions with patients taking a
higher number of medications with potentially interac-
tive combinations. Patients with longer hospital stays
were also found more likely to have a higher incidence
of pDDIs compared with patients with shorter hospital
stays. is is consistent with the previous studies [21].
Patients admitted to different levels of hospitals may be
exposed to different medications, and patients with a
longer hospital stay may be repeatedly exposed to dif-
ferent medications, which may result in a drug-drug
interaction. is finding suggests that patients with a
longer hospital stay could be assessed for the potential
medication interactions and pharmacists would be bet-
ter involved to intervene and tailor recommendations
based on the available medications with a low potential
interaction.
Generally, the current study has highlighted the level
of pDDIs and potential associated factors among patients
with psychiatric disorders, which can be a benchmark
for future investigators with prospective studies in larger
populations. Drug-drug interactions may not be avoid-
able, but the existing life-threatening pDDIs may be min-
imized through close monitoring and follow-up of risky
patients. e prevention of pDDIs and achieving good
treatment outcomes for non-significant and preventable
DDIs needs multifactorial involvement, including health-
care providers and patients, starting with the prescribing
and use of prescribed medications, availing of alternative
medications with less interaction potential, and assessing
the significance of interactive medications using interac-
tion checker software and tools. Documentation of the
existing pDDIs could also be improved. erefore, assess-
ing and following patients with a combination of medi-
cations which potentially have a drug-drug interaction
could be a must to achieve a better treatment outcome.
e current study has some limitations. e first thing
is that since the study is cross-sectional, it couldn’t show a
real cause-outcome association and it did not analyze the
consequences of the pDDIs. e second thing is that the
results may not be used to generalize for the entire coun-
try. However, it may be used as a benchmark for future
studies in the country. erefore, prospective studies in a
larger sample population could be recommended.
Conclusion
e current study highlighted that a significant number of
admitted patients with psychiatric disorders were exposed
to clinically significant pDDIs. Older patients, patients with
a higher number of medications, and patients with a longer
hospital stay were more likely to have pDDIs compared
with their counterparts. erefore, healthcare providers
could assess and follow patients with such risk factors
with a combination of medications that potentially have a
drug-drug interaction outcome. Minimize the occurrence
of life-threatening and clinically significant pDDIs by using
rational medication prescription and patient monitoring
could be a role for healthcare providers.
Abbreviations
DDI: Drug-drug interactions; pDDIs: potential drug-druginteractions.
Acknowledgements
The authors want to thank the selected hospital administration for their posi-
tive cooperation during the study. We would also like to forward our gratitude
to the data collectors and study participants.
Authors’ contributions
EMD and AKS contributed to the conception, data curation, formal analysis,
investigation, methodology, project administration, resources, supervision and
writing of the original draft and reviewed the final manuscript. AEE and SAW
contributed to the data curation, formal analysis, methodology, and validation
and reviewed the final manuscript. All authors gave final approval of the
version to be published; agreed on the journal to which the article has been
submitted; and agreed to be accountable for all aspects of the work.
Funding
We did not receive funding for this study.
Availability of data and materials
The datasets generated and/or analyzed during the current study are not
publicly available to protect from unnecessary abuse of full data of the partici-
pants but are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study was ethically approved by the ethical review committee of the
University of Gondar with a reference number of Sop/123/2021. Participants
were informed with both written and verbal consent forms after the objec-
tives of the study were briefed. Participants involved in the study were in a
condition to give informed consent willingly with all proper understanding of
the study purposes. All methods were carried out in accordance with relevant
guidelines and regulations.
Consent for publication
Not applicable because confidentiality was kept and participants were suf-
ficiently anonymized.
Competing interests
The authors stated that there is no competing interest.
Author details
1 Depatment of Pharmacy, College of Health Sciences, Debre Markos Uni-
versity, Debre Markos, Ethiopia. 2 Department of Pharmaceutical Chemistry,
School of Pharmacy, College of Medicine and Health Sciences, University
of Gondar, Gondar, Ethiopia. 3 Depatment of Clinical Pharmacy, School of Phar-
macy, College of Medicine and Health Sciences, University of Gondar, Gondar,
Ethiopia.
Received: 27 July 2022 Accepted: 21 November 2022
References
1. Roy DA, Shanfar I, Shenoy P, Chand S, Up N, Kc B. Drug-related problems
among chronic kidney disease patients: a clinical pharmacist led study.
Int J Pharm Res. 2020;12(4):79–84. Available: https:// www. acade mia. edu/
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 9 of 9
Dagnewetal. BMC Pharmacology and Toxicology (2022) 23:88
•
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•
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maximum visibility for your research: over 100M website views per year
•
At BMC, research is always in progress.
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? Choose BMC and benefit from:
? Choose BMC and benefit from:
43313 197/ Drug_ relat ed_ probl ems_ among_ chron ic_ kidney_ disea se_
patie nts_a_ clini cal_ pharm acist_ led_ study.
2. K annan G, Anitha R, Rani VN, Thennarasu P, Alosh J, Vasantha J, et al. A
study of drug-drug interactions in cancer patients of a south indian
tertiary care teaching hospital. J Postgrad Med. 2011;57(3):206.
3. Malone DC, Armstrong EP, Abarca J, Grizzle AJ, Hansten PD, Van Bergen
RC, et al. Identification of serious drug–drug interactions: results of the
partnership to prevent drug–drug interactions. J Am Pharm Assoc.
2004;44(2):142–51.
4. Guthrie B, Makubate B, Hernandez-Santiago V, Dreischulte T. The rising
tide of polypharmacy and drug-drug interactions: population database
analysis 1995–2010. BMC Med. 2015;13(1):1–10.
5. van Leeuwen RW, Swart EL, Boom FA, Schuitenmaker MS, Hugtenburg JG.
Potential drug interactions and duplicate prescriptions among ambula-
tory cancer patients: a prevalence study using an advanced screening
method. BMC Cancer. 2010;10(1):1–5.
6. Demler TL. Psychiatric drug-drug interactions. US Pharm.
2012;37(11):HS16–HS19. Available: https:// www. uspha rmaci st. com/ artic
le/ psych iatric- drug- drug- inter actio ns-a- refre sher.
7. Chadwick B, Waller DG, Edwards JG. Potentially hazardous drug interac-
tions with psychotropics. Adv Psychiatr Treatment. 2005;11(6):440–9.
8. Mezgebe HB, Seid K. Prevalence of potenial drug-drug interactions
among psychitric patients in Ayder referral hospital, Mekelle, Tigray,
Ethiopia. J Sci Innov Res. 2015;4:71–5.
9. Dagnew EM, Ayalew MB, Alemnew Mekonnen G, Geremew AB, Abdela
OA. Drug-related problems and associated factors among adult psychi-
atric inpatients in Northwest Ethiopia: Multicenter cross-sectional study.
SAGE Open Med. 2022;10:20503121221112485. https:// doi. org/ 10. 1177/
20503 12122 11124 85.
10. Developmental psychopathology, define: mental disorder. Accessed
on. Jun 2021. Aavilable from: https:// www. chegg. com/ flash cards/ devel
opmen tal- psych opath ology- e1db3 e44- 1032- 4cfc- ad17- 91d66 18eb1 a0/
deck.
11. Scheife RT, Hines LE, Boyce RD, Chung SP, Momper JD, Sommer CD,
et al. Consensus recommendations for systematic evaluation of
drug-drug interaction evidence for clinical decision support. Drug Saf.
2015;38(2):197–206.
12. Medscape Reference. Drug Interactions Checker. Accessed on. June 2021.
Available from: https:// www. refer ence. medsc ape. com/ drug- inter actio
nchec ker [Ref list]).
13. Alshehri GH, Keers RN, Ashcroft DM. Frequency and nature of medication
errors and adverse drug events in mental health hospitals: a systematic
review. Drug Saf. 2017;40(10):871–86.
14. Aljadhey H, Mahmoud MA, Ahmed Y, Sultana R, Zouein S, Alshanawani S
et al. Incidence of Adverse Drug Events in Public and Private Hospitals in
Riyadh, Saudi Arabia: the (ADESA) Prospective Cohort Study. BMJ open.
2016;(67):e010831. https:// doi. org/ 10. 1136/ bmjop en- 2015- 010831.
15. Cruciol-Souza JM, Thomson JC. Prevalence of potential drug-drug inter-
actions and its associated factors in a brazilian teaching hospital. J Pharm
Pharm Sci. 2006;9(3):427–33.
16. Gonzaga de Andrade Santos TN, Mendonça da Cruz Macieira G, Cardoso
Sodré Alves BM, Onozato T, Cunha Cardoso G, Ferreira Nascimento MT,
et al. Prevalence of clinically manifested drug interactions in hospi-
talized patients: a systematic review and meta-analysis. PLoS ONE.
2020;15(7):e0235353-e.
17. Greeshma M, Lincy S, Maheswari E, Tharanath S, Viswam S. Identifica-
tion of drug related problems by clinical pharmacist in prescriptions
with polypharmacy: a prospective interventional study. J Young Pharm.
2018;10(4):460–65
18. Haddad PM, Sharma SGJCd. Adverse Eff Atyp antipsychotics.
2007;21(11):911–36.
19. Harichandran DT, Viswanathan MT, Gangadhar R. Adverse drug reactions
among hospitalized patients in psychiatry department in a tertiary care
hospital. J Health Res Rev. 2016;3(2):77.
20. Ilickovic IM, Jankovic SM, Tomcuk A, Djedovic J. Pharmaceutical care in a
long-stay psychiatric hospital. Eur J Hosp Pharm. 2016;23(3):177–81.
21. Ismail M, Iqbal Z, Khattak MB, Javaid A, Khan MI, Khan TM, et al. Potential
drug-drug interactions in psychiatric ward of a tertiary care hospital:
prevalence, levels and association with risk factors. Trop J Pharm Res.
2012;11(2):289–96.
22. Farooqui R, Hoor T, Karim N, Muneer M. Potential drug-drug interactions
among patients prescriptions collected from medicine out-patient set-
ting. Pakistan J Med Sci. 2018;34(1):144.
23. Sunny S, Prabhu S, Chand S, Nandakumar U, Chacko CS, Joel JJ. Assess-
ment of drug-drug interactions among patients with psychiatric
disorders: a clinical pharmacist-led study. Clin Epidemiol Global Health.
2022;13:100930.
24. Castilho ECD, Reis A, Borges T, Siqueira L, Miasso A. Potential drug–drug
interactions and polypharmacy in institutionalized elderly patients in a
public hospital in Brazil. J Psychiatr Ment Health Nurs. 2018;25(1):3–13.
25. Vasudev A, Harrison R. Prescribing safely in elderly psychiatric wards:
survey of possible drug interactions. Psychiatr Bull. 2008;32(11):417–8.
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