Shakeel et al

Tropical Journal of Pharmaceutical Research October 2016; 15 (10): 2289-2295

ISSN: 1596-5996 (print); 1596-9827 (electronic)
© Pharmacotherapy Group, Faculty of Pharmacy, University of Benin, Benin City, 300001 Nigeria.
All rights reserved.

Available online at http://www.tjpr.org

http://dx.doi.org/10.4314/tjpr.v15i10.31
Original Research Article

Identification of clinically significant drug-drug

interactions in cardiac intensive care units of two tertiary
care hospitals in Peshawar, Pakistan
Faisal Shakeel, Jamshaid Ali Khan*, Muhammad Aamir, Rabeea Shareef and
Nazia Shah
Department of Pharmacy, University of Peshawar, Peshawar, Pakistan

*For correspondence: Email: jamshaidkhan@upesh.edu.pk; Tel: +923009592943

Received: 19 May 2016 Revised accepted: 17 September 2016

Abstract
Purpose: To identify clinically significant potential drug-drug interactions in cardiac intensive care units
of two tertiary care hospitals in Peshawar, Pakistan, and to compare the various potential drug-drug
interactions related parameters between the government and private hospitals included in the study.
Method: A prospective study was conducted in the cardiac intensive care units of the two hospitals, viz,
Lady Reading Hospital Peshawar (LRH) and Northwest General Hospital and Research Center
Peshawar (NWGH &RC), which are government and private hospitals, respectively. Samples of 260
and 250 patients from LRH and NWGH & RC, respectively, were evaluated. Patient medication charts
were evaluated for potential drug-drug interactions and clinically significant potential drug-drug
interactions using Micromedex DrugReax. The data were statistically analyzed.
Results: A high prevalence of potential drug-drug interactions was reported in both hospitals: 92 and
96.9 % in Northwest General Hospital and Research Center, and Lady Reading Hospital, respectively,
of which half were clinically significant. A total of 19 interacting drug pairs contributed to the clinically
significant potential drug-drug interactions. Independent sample t-test showed a significant difference in
the potential drug-drug interactions of both hospitals. Furthermore, a significant relationship was found
between the number of potential drug-drug interactions, on the one hand, and the number of prescribed
drugs and age, on the other.
Conclusion: A high prevalence of potential drug-drug interactions, particularly clinically significant
potential drug-drug interactions, calls for proper identification of these interactions and monitoring of
patients to minimize adverse outcomes and improve patient therapy.

Keywords: Pharmacy service, Drug interactions, Critical/intensive care, Adverse outcomes

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INTRODUCTION countries [1]. Risk factors include diseases like

hypertension, hyperlipidemia, diabetes or other
Cardiovascular diseases are a prime cause of diseases which require multiple drug therapy,
high mortality rates throughout the world. In while behavioral risk factors include unhealthy
2012, World Health Organization (WHO) diet, tobacco use, lack of physical activity and
estimated that 17.5 million people died worldwide stress [2,3]. Furthermore, treatment for these
due to cardiovascular diseases. Most of these diseases require multiple drug administration
deaths occurred in low or middle income which when combined with factors like advanced

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 Shakeel et al

age, co-morbidities and changes in hepatic and The severity and documentation of the PDDIs
renal functions, increases the risk of potential reported in Micromedex DrugReax was used to
drug-drug interactions (PDDIs) [4-6]. create a list of clinically significant PDDIs, on the
basis of which the following PDDIs were
The presence of a potential drug-drug interaction considered as clinically significant:
(PDDIs) is highly probable in critical units like
cardiac intensive care units (CCU), primarily due • PDDIs having severity of major and of
to the multiple drug therapy employed to combat excellent or good documentation
the complex disease condition of the patient
along with co-morbidities and age which further • PDDIs having severity of moderate and of
excellent or good documentation
increases the risk of PDDIs [7,8]. However, not
all the PDDIs are clinically significant and are not
Frequencies were used to summarize gender,
a predisposition of an adverse clinical event. number of prescribed drugs, diagnosis, duration
Some PDDIs are employed to benefit the patient of stay, frequency of PDDIs, interacting drug
but these are very limited, for example the use of pairs and their severity, documentation, onset
aspirin and clopidogrel in patients to prevent and clinical significance. Multiple linear
thromboembolism [9,10]. Apart for some rare regression was used to determine the
instances, PDDIs are one of the leading causes relationship between number of prescribed
of hospitalization [11,12]. drugs, duration of stay and the number of PDDIs.
P values of ˂ 0.05 was considered statistically
METHODS significant. Independent samples t test was
performed to the compare the means of clinically
This prospective cross sectional study was significant PDDIs in both hospitals. All the
carried out in CCUs of two tertiary care hospitals analysis was performed using IBM SPSS
of Peshawar, Lady Reading Hospital (LRH) and Statistics for Windows, Version 20 (Armonk, NY:
Northwest General Hospital and Research IBM Corp) [14].
Center Peshawar (NWGH & RC). LRH is a
government tertiary care hospital while NWGH is RESULTS
a private hospital. The duration of the study was
one year and was approved by the ethical General characteristics
committees of both hospitals vide letter number
010 and NWGH/Research/01, respectively.
A total of 510 patient prescriptions were
Patient demographics, duration of stay,
evaluated, of which 250 were from NWGH & RC,
diagnosis, drugs administered, dose, frequency
and duration of drugs prescribed were recorded while 260 were from LRH, representing private
from the medication chart of the patient. Names and government sector respectively. The
of the patients, their identification numbers and proportion of male patients as compared to
medical records were kept confidential. Good female patients was higher in both the hospitals,
clinical practice (GCP) guidelines were followed 59.2 % in NWGH & RC while 66.2 % in LRH. The
under the declaration of Helsinki (1964) by the mean age of the patients was 58.06 ± 12.75
International Conference on Harmonization and (range 19 - 88) and 55.24 ± 13.58 (range 12 - 95)
Nuremburg Code [26]. Patients admitted to the in NWGH & RC and LRH, respectively. The
CCU for at least 24 h and prescribed at least 2 median duration of stay was 3 days for both
drugs were included in the study. hospitals while the median number of drugs
prescribed was higher in NWGH & RC (6 drugs
Micromedex database DrugReax [13] was used per prescription) as compared to LRH (5 drugs
to analyze the potential drug-drug interactions per prescription). The general characteristics of
among prescribed drugs to the patients. This the patients are displayed in Table 1.
database provides information on the clinical
effect, severity, documentation, onset and Diagnosis
mechanism of the PDDIs. Severity may be major,
moderate or minor; documentation may be The most frequent diagnosis of patients admitted
excellent, good or fair; onset may be rapid, in both NWGH &RC and LRH was myocardial
delayed or unknown; nature of PDDIs may be infarction (MI), while acute coronary syndrome
pharmacokinetic, pharmacodynamic or unknown; (ACS) and heart failure were the other most
while mechanisms of PDDIs include absorption, frequent diagnosis of the patients. The
distribution, metabolism, elimination, synergism,
comparison of the percentage of diagnosis in
antagonism or unknown.
both hospitals is displayed in Figure 1.

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Table 1: General patient characteristics in CCU of NWGH and LRH

Variables Frequency (%) NWGH Frequency (%) LRH

Gender
Male 148 (59.2) 172 (66.2)
Female 102 (40.8) 88 (33.8)
Age (years)
Mean ± SD 58.06 (± 12.75) 55.24 (± 13.58)
≤ 18 0 2 (0.8)
19-59 127 (50.8) 144 (55.4)
≥ 60 123 (49.2) 114 (43.8)
Drugs prescribed per patient
Mean ± SD 5.81 ± (1.94) 5.70 ± (1.328)
≤4 56 (22.4) 44 (16.9)
5-6 113 (45.2) 158 (60.8)
≥7 81 (32.4) 58 (22.3)
Stay in ICU
Mean ± SD 3.62 ± (1.78) 3.73 ± (2.265)
≤2 74 (29.6) 54 (20.7)
3-5 118 (47.2) 151 (58.1)
≥6 58 (23.2) 55 (21.2)

Figure 1: Comparison of diagnosis between NWGH & RC and LRH

Prevalence of PDDIs and categories occurrence in the cardiac critical care unit. The
list of clinically significant PDDIs from both
At least one potential drug-drug interaction hospitals along with their frequencies and
(PDDI) was encountered in 92 and 96.9 % of the potential outcome is displayed as Table 3. These
patients in NWGH &RC and LRH, respectively. A PDDIs contributed to 44.6 and 51 % of the total
total of 105 interacting drug pairs contributed to PDDIs encountered in NWGH & RC and LRH
the 909 PDDIs encountered in NWGH &RC while respectively. Furthermore, it was observed that
76 interacting drug pairs contributed to the 1204 3.63 and 4.63 PDDIs were present per patient in
PDDIs encountered in LRH. The severity, NWGH & RC and LRH respectively while 2.07
documentation, onset, nature and mechanism of and 2.54 clinically significant PDDIs were present
the PDDIs encountered in both hospitals are per patient in the hospitals respectively.
displayed in Table 2.
Independent sample t-test
Clinically significant PDDIs
An independent sample t-test was performed to
Clinically significant PDDIs were identified using compare the means of clinically significant PDDIs
the predetermined criteria. Using this criteria between NWGH and LRH. The t-test showed a
along with the frequency of PDDIs, a list of 19 significant difference (t = 3.435, p = 0.001) in the
interacting drug pairs was prepared from both the number of clinically significant PDDIs between
hospitals which were considered to be significant NWGH and LRH.
clinically, because of the associated high risk and

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Table 2: Categories of Potential drug-drug interactions in NWGH and LRH

Variable Frequency (%) NWGH Frequency (%) LRH

Severity of PDDIs
Major 377 (41.4) 639 (53.1)
Moderate 496 (54.6) 563 (46.8)
Minor 36 (4.0) 2 (0.1)
Documentation of PDDIs
Excellent 79 (8.7) 72 (6.0)
Good 479 (52.7) 614 (51.0)
Fair 351 (38.6) 518 (43.0)
Onset of PDDIs
Rapid 135 (14.8) 194 (16.1)
Delayed 267 (29.4) 255 (21.2)
Unkonwn 507 (55.8) 755 (62.7)
Type of interaction
Pharmacodynamic 675 (74.3) 946 (78.6)
Pharmacokinetic 211 (23.2) 252 (20.9)
Unknown 23 (2.5) 6 (0.5)
Mechanism of interaction
Synergism 383 (42.1) 645 (53.6)
Antagonism 292 (32.2) 301 (25.0)
Absorpiton 29 (3.2) 4 (0.3)
Metabolism 69 (7.6) 48 (4.0)
Elimination 111 (12.2) 200 (16.6)
Absorption/metabolism 2 (0.2) 0
Unknown 23 (2.5) 6 (0.5)

Table 3: Clinically significant PDDIs in NWGH and LRH

Interacting drug pair Frequency Frequency Potential outcome

NWGH LRH
Aspirin-enoxaparin 64 161 Increased risk of bleeding.
Clopidogrel-omeprazole 7 10 Reduction in clinical efficacy of clopidogrel and increased
risk for thrombosis.
Ramipril-spironolactone 10 11 May result in hyperkalemia.
Digoxin-spironolactone 2 15 May result in increased digoxin exposure.
Aspirin-metoprolol 31 32 May result in decreased antihypertensive effect.
Aspirin-nitroglycerin 14 68 May result in an increase in nitroglycerin concentrations and
additive platelet function depression.
Furosemide-ramipril 22 18 May result in postural hypotension (first dose).
Aspirin-furosemide 57 51 May result in decreased diuretic and antihypertensive
efficacy.
Aspirin-spironolactone 23 35 May result in reduced diuretic effectiveness, hyperkalemia,
or possible nephrotoxicity.
Aspirin-carvedilol 20 7 May result in decreased antihypertensive effect.
Aspirin-bisoprolol 58 87 May result in decreased antihypertensive effect.
Aspirin-losartan 11 5 May result in decreased antihypertensive effects and an
increased risk of renal impairment.
Aspirin-valsartan 16 6 May result in decreased antihypertensive effects and an
increased risk of renal impairment.
May result in decreased antihypertensive effects and an
Aspirin-candesartan 1 16
increased risk of renal impairment.
Decreased diuretic and antihypertensive efficacy.
Aspirin-hydrochlorothiazide 11 3
May result in digoxin toxicity (nausea, vomiting, cardiac
Digoxin-furosemide 11 20
arrhythmias).
May result in decreased lisinopril effectiveness.
Aspirin-lisinopril 4 47
Increased risk of hypoglycemia.
Aspirin-glimepiride 18 4
Decreased formation of clopidogrel active metabolite
Atorvastatin-clopidogrel 25 18 resulting in high on-treatment platelet reactivity.

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Table 4: Prediction of clinically significant PDDIs

No. of clinically significant Coefficient Standard error t P-value

PDDIs
Constant -0.091 0.379 -0.241 0.810
No. of prescribed drugs 0.580 0.041 13.795 0.000
Duration of stay 0.001 0.034 0.020 0.984
Age -0.16 0.005 -3.196 0.001

Prediction of clinically significant PDDIs and 59.1 %) and most of were of

pharmacodynamic in nature at 120 h (45.2 %)
Multiple linear regression model was fitted to [22]. To our knowledge no previous study has
predict the number of clinically significant PDDIs focused on the clinically significant interaction in
based on number of prescribed drugs, duration cardiac intensive care units. Our study shows
of stay and age. The effect of number of that 3.63 and 4.63 PDDIs were present per
prescribed drugs on number of clinically patient in NWGH & RC and LRH respectively
significant PDDIs, controlling for the effect of while 2.07 and 2.54 clinically significant PDDIs
duration of stay and age, was found to be were present per patient in the hospitals
significant. (t = 13.795, p < 0.0001). The effect of respectively. This is of great concern because
age on number of clinically significant PDDIs, more than half of the PDDIs encountered were
clinically significant and can have a significant
controlling for the effect of duration of stay and
impact on the advanced disease condition of the
number of prescribed drugs, was also found to
patient.
be significant. (t = -3.196, p = 0.001). The effect
of duration of stay on number of clinically
A significant association was found between
significant PDDIs, controlling for the effect of clinically significant PDDIs and number of
number of prescribed drugs and age, was found prescribed drugs and age of the patient. This
to be insignificant (t = 0.020, p = 0.984) (Table association was similar to that of reported in
4). other studies [4,18,23-25]. A Nepalese study
reported a significant linear association between
DISCUSSION length of stay and occurrence of PDDIs [20].
Another study conducted in cardiology
This study reported a high prevalence of PDDIs department of Pakistan also reported a
which corresponds to other studies reporting a significant association between PDDIs and
similar higher prevalence in cardiology. prescribed drugs and age [4].
University of Pittsburg conducted a study in
cardiac and cardiothoracic ICU patients, found Proper PDDIs identification and management
87.7 % patients having at least a single PDDI system are lacking in these hospitals which
[15]. Cross sectional studies conducted in contribute to this high prevalence of PDDIs.
Pakistan also reported a prevalence of 91.1 and Pharmacists should update themselves
77.5 % cardiology patients having a PDDI [4,16]. regarding the knowledge of clinically significant
It was also reported that 72.5 % of ICU patients PDDIs and timely interventions implemented.
had PDDIs in the ICU of a Brazilian hospital [17].
While another Brazilian study reported 87.2 % Limitations of the study
patients in cardiology encountered a PDDI [18].
Monitoring of the adverse outcomes due to the
A Brazilian study evaluated 1785 prescriptions PDDIs and lack of interventions were some of
and recorded similar trends as seen in this study the limitations of this study. This study identified
with the severity of most PDDIs being moderate clinically significant PDDIs on the basis of
(78.6 %), documentation of most PDDIs was literature and drug interaction database, while
good (29.5 %) and most (42.5 %) were clinical studies can be conducted in the future to
pharmacodynamics in nature [19] Another study monitor the actual clinically notable adverse
reported PDDIs of moderate severity to be the outcomes of these PDDIs and their effect on the
most common (62.5 %) [20]. In 203 patients, patient disease.
75.03 % of PDDIs were in Category C which
corresponds to moderate severity [21]. A record CONCLUSION
of 1124 patients were evaluated for PDDIs at 24
h and 120 h after admission to the hospital. The This study identified not only a high prevalence
severity of most interactions was moderate in of PDDIs but also clinically significant PDDIs
both the time frames (50.1 and 51.4 %), most of which have greater potential for significant
the interactions were good documentation (63.9

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 Shakeel et al

changes in patients’ condition. Also notable was of Potential Drug‐Drug Interactions in Medical Intensive
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