Drug-drug interaction, adverse drug reaction and their determinants among adult hypertensive patients; Multicenter study in Ethiopia

Drug-drug interaction, adverse drug reaction and their determinants among adult hypertensive patients; Multicenter study in Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Drug-drug interaction, adverse drug reaction and their determinants among adult hypertensive patients; Multicenter study in Ethiopia Gosaye Mekonen Tefera, Beshadu Bedada Feyisa, Tesemma Sileshi Chala, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8527897/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Hypertensive patients are at high risk of adverse drug interaction (ADR) and drug-drug interaction (DDI) because of high tendency to use multiple drugs; this can undermine the quality of patients’ care. The aim of the study was to assess the magnitude of ADR, DDI, and their determinants among adult hypertensive patients at selected hospitals in Ethiopia. Methods A hospital-based cross-sectional study was conducted using chart reviews and patient interviews. DDIs were identified and classified using the Medscape online DDI checker. Written informed consent was obtained, and multivariate logistic regression was performed with statistical significance at p ≤ 0.05. Results Among a total of 543 hypertensive patients ADR was reported in 32.2%, with the most common being weakness (33.7%), followed by gastric irritation (33.1%), and headache (30.3%). Nearly half of the patients (47.9%) experienced at least one DDI. A total of 789 DDIs with mean of 3.03 ± 2.22 was identified in the study participants. Enalapril plus metformin was found as the most common contributing for DDI. Multivariable logistic regression analysis showed that patients with comorbid conditions, (AOR = 2.42; 95%CI: 1.25–4.67; p = 0.008), increasing number of concurrent medications use (AOR = 6.93; 95%CI: 4.50–10.69; p < 0.001), use of furosemide (AOR = 14.42; 95%CI: 4.38–47.48; p < 0.001), metformin (AOR = 23.57; 95%CI: 7.53–73.72; p < 0.001), and propranolol (AOR = 7.56; 95%CI: 1.12–50.61; p = 0.037) were significantly associated with higher odds of DDI. Increasing age (AOR = 1.017; 95%CI: 1.000–1.034; p = 0.044) and presence of comorbid conditions (AOR = 1.506; 95%CI: 1.001–2.264; p = 0.049) as well as, the use of enalapril (AOR = 1.751; 95%CI: 1.143–2.683; p = 0.010), nifedipine (AOR = 2.359; 95%CI: 1.013–5.492; p = 0.047), hydrochlorothiazide (AOR = 1.712; 95%CI: 1.112–2.635; p = 0.015) and increased number of concurrent medications (AOR = 1.287; 95%CI: 1.091–1.519; p = 0.003) were significantly associated with higher odds of ADRs. Conclusion This study found a high prevalence of DDI and ADR; with nearly half experiencing DDIs and about one-third reporting ADRs with different independent predictors. These findings highlight the need for regular medication review and close clinical monitoring to improve medication safety and optimize hypertension management. Hypertension Drug-drug interaction adverse drug reaction Polypharmacy predictors Medscape Ethiopia Introduction World Health Organization (WHO) report shows hypertension affects 1 in 3 adults worldwide. Globally 56%( 1 ), in the USA (per the new definition of hypertension) 49.64% ( 2 ), in Africa 36% ( 1 ), and in Ethiopia 30% ( 3 ) of adult population has hypertension. Hypertension is, a deadly condition which leads to 10.8 million avoidable deaths every year out of 41 million death from non-communicable disease (NCD) and different morbidities (stroke, heart attack, heart failure, kidney damage) and enormous economic costs( 1 ). Appropriate hypertension management will save lives and improve wellbeing ( 1 ). In-appropriately treated hypertension has worst health outcomes( 4 ), which is higher in Africa ( 5 ). Appropriate hypertension management through ensuring that people receive appropriate ant-hypertensive therapy and free from drug-drug interaction (DDI) and adverse drug reaction (ADR) to BP goal achievement has been highly recommended ( 6 – 10 ). Thus, by improving BP control alone, the global health care savings have been estimated at $ 100 billion per year ( 11 ), and it can assure the achievement of Sustainable Development Goal (SDG) target 3.4; one third reduction in premature mortality by 2030 from NCD ( 1 , 11 ). DDI is defined as the qualitative or quantitative modification of the effect of a drug by the simultaneous or successive administration of a different drugs. This may result in the alteration of therapeutic effect and safety of either or both drugs. It is a great concern among hypertensive patients due to the tendency of receiving multidrug therapy( 12 ). However, it is important to remember that DDI may be beneficial or harmful. Thus, WHO recommends that the problem can be significantly minimized by implementing careful attention to the identification and resolution of DDIs ( 13 , 14 ). DDI studies among hypertensive patients out of Ethiopia showed that the prevalence is as high as 47.6% to 89.06% ( 13 , 15 , 16 ), where majority of them were significant in severity (85.36%) to 95.42%. A lots of antihypertensive medication have been contributing for DDI ( 13 , 15 – 17 ). Even though it is highly recommended to have surveillance on DDI among hypertension patients to take appropriate intervention, the available data in Ethiopia is limited( 12 ) (to our knowledge only one study before 10 years in single hospital ( 18 ) and no study in West Shoa Zone. The other studies on DDI were not specific to antihypertensive (it is general or related with cardiovascular disease)( 19 – 22 ). In fact, those data showed high prevalence of DDI in Ethiopia among patients with cardiovascular disease (CVD) ( 19 – 22 ); Addis Ababa 90.1% ( 19 ) and at Dessie Referral Hospital, Ethiopia 1.63 DDI per patient ( 23 ). Therefore, investigating adverse drug reactions (ADRs), drug–drug interactions (DDIs), and their determinants is essential to quantify the magnitude of the problem and enable early intervention to optimize antihypertensive therapy. These findings provide valuable evidence to support healthcare providers in improving patient care and minimizing ADRs and DDIs during clinical management. Methods and Participants Study area, period and design: A hospital-based cross-sectional study was conducted in 5 selected public hospitals (multi-center study) in the West Shoa Zone, Oromia, Ethiopia, from January 01 2024 to April 30, 2024. West Shoa Zone has ten public hospitals in general which serves around 3.6 million populations. From the 10 hospitals, by lottery method 5 hospitals, namely, Guder Primary Hospital, Ambo University Referral Hospital, Ambo General Hospital, Ginchi Primary Hospital and Bako Primary Hospital were included to the study. The selected hospitals have separate outpatient departments for the treatment and follow-up of chronic diseases including hypertension. So the data for this study was collected from the outpatient department of chronic diseases follow up. Study Participants Recruitment, Sampling and Data Collection Procedure Adult hypertensive patients (≥ 18 years) on pharmacologic treatment for at least 6 months and on follow up during data collection period were included by systematic random sampling methods from selected hospitals with inclusion criteria (proportional allocation was made for each hospitals). Pregnant mothers, refuse to participate in the study, patients with cognitive impairment, seriously ill patients (admission) that made it impossible to conduct a reliable interview and patients with incomplete medical records were excluded. Study variables: Dependent variables were, DDI and ADR, while independent variables were: sociodemographic, disease related factors, presence of metabolic syndrome (BMI or WHR), drug related factors (number and type of drug used), and behavioral factors (alcohol, khat, and tobacco use habit). Sample size and sampling procedure Sample size was calculated for different objectives and/ or predictor variables and then the largest sample size (588) was selected as a final sample size. For determinant factor double population formula was used with 95% C.I and 80% powers from study at Nekemte, Ethiopia ( 8 ). Determinant factor p-value AOR %outcome exposed %outcome un-exposed Power (%) 95%c.I Sample size Sex 0.005 1.89 44% 31.5 80 95 233 Age 0.030 0.38 37 63.9 80 95 51 Adherence to drug 0.032 3.14 66.3 41.1 80 95 58 Physical exercise 0.02 2.8 37.9 24.2 80 95 176 A single population formula was used to calculate the sample size for BP control rate. The assumptions considered during the calculation of the sample size were 95% confidence level, 5% margin of error, and p = 36.4%; prevalence of uncontrolled hypertension from the study carried out in Nekemte, Ethiopia( 8 ). Where ; N is the size of the population that the sample is to represent = 13748 hypertensive patients in West Shoa in 2015 E.C from DHIS 2. Design effect= 1.5, thus 1.5*356= 534 (2 stage sampling) 10% for non-response rate = 54 +534 = 588 The sample size for each hospital was proportionally allocated with the ratio of 588/11360= 0.052. Systematic random sampling method (every K th ) was used to select the study participants from each selected hospitals. Data Collection Tool, Process and Quality Control The data collection tool used for this study was annexed as supplementary material (data collection tool). Data was collected with semi-structured questionnaire through patient interviews and medical record reviews. A medical chart review and a data abstraction tool was filled for each eligible patient to get relevant information like co-morbid condition/s, BP and laboratory values, medication/s. Patients were interviewed to obtain socio-demographic, disease-related, behavioral/ lifestyle and compliance to medication/salt related information. The pretest was done on 5% of the total sample to ensure the quality and agreement of the data abstraction format with the objective of the study and adjustments were done accordingly. The identification of DDI was done based on the ‘Medscape online drug interaction checker’( 24 ). All concurrent medications were entered into Medscape, which classifies DDIs by severity: ( 1 ) Contraindicated – risks outweigh benefits; ( 2 ) Serious – avoid or modify therapy; ( 3 ) Significant – monitor for adverse effects or reduced efficacy; ( 4 ) Minor – minimal or unknown clinical impact. Polypharmacy was defined as the use of ≥ 5 medications concurrently( 25 ). ADRs were defined as any harmful or unintended drug response perceived by the patient to be caused by their medications( 24 ). ADR is considered based on patient report after probing that the compliant was started after the use of the offending drug (any drug used by patient). Data Processing and Analysis: The data was entered, cleaned and analyzed using Statistical Package for the Social Sciences (SPSS) version 20.0. Descriptive statistics including frequency, percentages, mean and standard deviation (SD) were used to summarize study variables. Multivariate logistic regression was done for variables with p-value less than 0.25 and known predictors from previous study to determine factors associated with DDI with p-values ≤ 0.05 for statistical significance. Results Socio-demographic and clinical characteristics of study participants The details of the socio demographic characteristics of the study participants was available elsewhere in other document ‘Psychometric property of Hill bone high blood pressure therapy compliance scale’ because it was done simultaneously. A total of 543 hypertensive patients were included in the study with response rate of 92.3%. The mean (± SD) age of the participants was 56.5 ± 12.3 years. Based on the age-adjusted Charlson comorbidity index (CCI), patients were almost equally distributed between the low-risk (42.7%) and moderate-risk (42.9%) categories, with fewer in the high-risk group. About half (50.8%) had at least one chronic comorbid condition, most commonly a single condition (83%). Diabetes mellitus was the leading comorbidity (50.4%), followed by heart failure (19.6%) and asthma/Chronic Obstructive Pulmonary Disease (COPD) (14.1%) ( Table 1 ) . Table 1 clinical characteristics of study participants at selected hospitals of West Shoa Zone, January to April 30/2024, Ethiopia (N = 543) Variables Categories Frequency % Age based Charlson CI risk classification score (N = 543) low risk (0–2 score) 232 42.7 moderate risk (3–4 score) 233 42.9 high risk ( > = 5 score) 78 14.4 Median (IQR), min-max 3[2–4], 1–10 Chronic Co-morbid condition based on CCI (N = 543) No 267 49.2 Yes 276 50.8 Number of comorbid condition (N = 276) 1 229 83.0 2 37 13.4 ≥ 3 10 3.6 List of chronic common co-morbid condition based on CCI (top 10)(N = 276) DM 139 50.4 Heart failure 54 19.6 Asthma/COPD 39 14.1 Gastritis/PUD 22 8.0 Stroke/TIA 21 7.6 CKD 13 4.7 Rheumatic/connective tissue disease 13 4.7 IHD 10 3.6 PVD 8 2.9 HIV/AIDS 7 2.5 Others# 15 5.4 Note : other #- (hemiplegia, Cancer, Dementia/Alzheimer, Depression); COPD-chronic obstructive pulmonary disease; DM-diabetes mellitus; PUD-peptic ulcer disease; TIA-transient ischemic attack; CKD-chronic kidney disease, IHD-ischemic heart disease; PVD-peripheral vascular disease; HIV/AIDS-Human immune virus/ Acquired immune deficiency syndrome; Prevalence of Drug-drug interaction and Adverse Drug Reaction Among 543 patients, 16.0% were identified to have polypharmacy. Nearly half of the patients (47.9%) experienced at least one drug-drug interaction (DDI), regarding the severity of DDI, significant interactions being the most common (85.4%), and 17.3% experiencing serious interactions. There was no contra-indicated type of DDI identified. The mean number of DDIs per patient with interactions (among 260 patients) was 3.03 ± 2.22 (range 1–12), with a total of 789 DDIs identified in the study participants. Regarding adverse effects, 32.2% of patients reported at least one adverse drug reaction, with the most common being weakness (33.7%), gastric irritation (33.1%), headache (30.3%), and ankle swelling (10.3%) (Table 2 ). Table 2 Drug-drug interaction and patient reported ADR among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N = 543) Variables Category Frequency Percentages Poly pharmacy (N = 543) No 456 84.0 Yes 87 16.0 Overall drug-drug interaction (N = 543) No 283 52.1 yes 260 47.9 Severity of drug-drug interaction (N = 260) Minor 83 31.9% Significant 222 85.4% Serious 45 17.3% Number of drug-drug interaction per patient (N = 260) 1 73 28.1% 2 58 22.3% 3 52 20.0% 4 31 11.9% ≥ 5 46 17.7% Mean ± SD (min. to maximum) 3.03 ± 2.22 ( 1 – 12 ) Summary of drug-drug interaction Sum (total DDI) 789 DDI identified Average per patients with DDI (260) 3.04 DDI Average per sample (543) 1.45 DDI Total number of DDI by level of severity (N = 260) Minor 153 0.6 DDI* Significant 584 2.3 DDI* Serious 52 0.2 DDI* Adverse drug reaction (self-report) (N = 543) No 368 67.8 Yes 175 32.2 Type of adverse drug reaction reported by patients (N = 175)- Multiple response Weakness 59 33.7% Headache 53 30.3% Erectile dysfunction 5 2.9% Gastric irritation (GI compliant) 58 33.1% Dry cough 9 5.1% Ankle swelling 18 10.3% Generalized body edema 10 5.7% Skin itching/ allergic reaction 11 6.3% Hypotension 3 1.7% Dizziness 5 2.9% Pain/tingling of extremities 3 1.7% Others $ 11 6.2% Note: DDI *- average drug-drug interaction per 260 patients; DDI- drug-drug interaction; Other$ - (chest pain, urinary retention, shortness of breath, constipation, hyperkalemia, synchro/seizure, liver toxicity, dry mouth) Common drugs contributing for DDI and it clinical consequence Among the identified drug–drug interactions (DDIs), the most frequently observed combination was enalapril plus metformin, accounting for 89 cases (34.2%), which was associated with increased metformin toxicity and a heightened risk of hypoglycemia and lactic acidosis. This was followed by amlodipine plus metformin in 69 cases (26.5%), where amlodipine reduced the therapeutic effect of metformin through pharmacodynamics antagonism, potentially leading to hyperglycemia. The combination of aspirin and enalapril was observed in 38 patients (14.6%) and was linked to pharmacodynamics antagonism with possible acute kidney injury, classified as significant to serious in severity. Similarly, glyburide plus atorvastatin occurred in 37 cases (14.2%) and increased the risk of atorvastatin-induced myopathy. Interactions involving antihypertensive and diuretic agents were also common. Enalapril plus furosemide was identified in 31 cases (11.9%), posing a risk of acute hypotension and renal insufficiency due to synergistic effects. Enalapril plus glyburide, reported in 27 cases (10.4%), increased the risk of hypoglycemia, while enalapril plus insulin was seen in 16 cases (6.2%) with a similar synergistic hypoglycemic effect. Antidiabetic drug combinations contributed substantially to DDIs; metformin plus insulin was identified in 18 cases (6.9%), significantly increasing hypoglycemia risk. Cardiovascular drug combinations such as aspirin plus metoprolol (17 cases; 6.5%) and metoprolol plus furosemide (11 cases; 4.2%) were associated with alterations in serum potassium levels. Less frequent but clinically relevant interactions included propranolol or bisoprolol plus amlodipine (9 cases; 3.5%), which may synergistically lower blood pressure and cause hypotension; nifedipine plus metformin (7 cases; 2.7%), associated with reduced glycemic control; and atorvastatin plus amitriptyline (10 cases; 3.8%), which increased amitriptyline exposure. In addition, combinations involving aspirin or spironolactone with furosemide were noted in 16 cases (6.2%), potentially affecting serum potassium levels. Overall, the majority of identified DDIs were classified as significant in severity, underscoring the need for careful medication review and close clinical monitoring in patients receiving multiple chronic therapies ( Table 3 ). Table 3 List of top-15 drugs contributed to DDI, their Prevalence, and Expected Negative Effects among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N = 543) List of common drugs contributed to DDI Prevalence of DDI (%) Clinical consequence of DDI Severity of DDI per Medscape checker Enalapril + metformin 89 (34.2) Increased metformin toxicity: Increases risk for hypoglycemia and lactic acidosis. Significant Amlodipine + metformin 69 (26.5) Amlodipine decreases effects of metformin by pharmacodynamics antagonism-hyperglycemia. Significant Aspirin + enalapril 38 (14.6) Increase risk of acute renal insufficiency, pharmacodynamics antagonism Significant-serious Glyburide + atorvastatin 37 (14.2) Increase risk of atorvastatin myopathy Significant Enalapril + furosemide 31 (11.9) Increase risk of acute renal insufficiency & hypotension (synergism) Significant Enalapril + glyburide 27 (10.4) Enalapril increase risk of hypoglycemia (synergism ) Significant Metformin + insulin 18 (6.9) Increased risk of hypoglycemia (synergism ) Significant Aspirin + metoprolol 17 (6.5) Increased serum potassium(synergism ) Significant Enalapril + insulin 16 (6.2) Increases risk for hypoglycemia(synergism ) Significant Aspirin/ Spironolactone + Furosemide 16 (6.2) Affect serum potassium (Unclear effect) Significant Atenolol/Propranolol/bisoprolol + amlodipine 13 (5.0) Synergize BP reduction / hypotension Significant Metoprolol + furosemide 11 (4.2) Affect serum potassium (Unclear effect) Significant Atorvastatin + amitriptyline 10 (3.8) Atorvastatin will increase the level or effect of amitriptyline Significant Nifedipine + metformin 7 (2.7) Amlodipine decreases effects of metformin by pharmacodynamic antagonism-hyperglycemia. Significant Digoxin + furosemide 6 (2.3) Hypokalemia increases digoxin effects & Affect serum potassium (Unclear effect) Significant Aspirin + spironolactone 5 (1.9) Both increase serum potassium Significant Others# 92 (35.4) Note : Others#- (folic acid + methotrexate, amitriptyline + metformin, amitriptyline + metformin, hydrochlorothiazide + metoprolol, indomethacin + albuterol, amitriptyline + tramadol, amlodipine + phenytoin, valproic acid + phenytoin, amoxicillin + hydrochlorothiazide, artemether/lumefantrine + primaquine, aspirin + hydrochlorthiazide. aspirin + albuterol/propranolol/bisoprolol, phenytoin + amlodipine/atorvastatin/valproate, prednisolone + HCT, propranolol + insulin), Amitriptyline + albuterol, Diclofenac/dexamethasone + enalapril, CBZ + atorvastatin, Beclomethasone + HCT, Beclomethasone + furosemide, Gabapentine + amitriptyline, Tramadol + albuterol, Indomethacin + enalapril, CBZ + amlodipine, Albuterol + furosemide, Indomethacin + HCT, Furosemide + HCT, Nifedipine + atorvastatin, carbamazepine + HCT/enalapril, phenobarbito + amlodipine/carbamazepine, Metoprolol + albuterol, Metformin + HCT). Common drugs contributing for DDI and its potential effect on Blood pressure Among the study participants (N = 260), most DDIs had no potential effect on blood pressure (188; 72.3%), while 16.9% (44 cases) decreased BP and 10.8% (28 cases) increased BP. Interactions between CVD and non-CVD drugs were the most frequent (100; 38.5%), followed by within-CVD interactions (71; 27.3%) and all-class interactions (70; 26.9%); non-CVD interactions were least common (19; 7.3%). Among DDIs affecting BP (N = 72), significant severity predominated (41; 56.9%), with minor (29; 40.3%) and serious (2; 2.8%) interactions occurring less frequently (Table 4 ). Table 4 clinical effect of DDI on BP and common class of drugs contributing for DDI among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N = 260) Variables Categories Frequency Percentages DDI effect on BP (N = 260) No effect 188 72.3 Decreased 44 16.9 Increased 28 10.8 Type of DDI by therapeutic class (N = 260) All type 70 26.9 CVD with Non-CVD 100 38.5 non CVD 19 7.3 Within-CVD 71 27.3 Level of DDI effect on BP (N = 72) Serious 2 2.8 Significant 41 56.9 Minor 29 40.3 Predictors of Drug-drug interaction (DDI) Binary logistic regression was performed to screen candidate variables for multivariable logistic regression. Variables with a p-value ≤ 0.25 in the bivariable analysis, as well as variables identified as significant predictors in previous studies (including polypharmacy and overall number of medications used), were entered into the multivariable model to identify independent predictors of drug–drug interactions (DDIs). Multivariable logistic regression analysis showed that patients with comorbid conditions (AOR = 2.42; 95% CI: 1.25–4.67; p = 0.008), an increasing number of medications (AOR = 6.93; 95% CI: 4.50–10.69; p < 0.001), use of furosemide (AOR = 14.42; 95% CI: 4.38–47.48; p < 0.001), metformin (AOR = 23.57; 95% CI: 7.53–73.72; p < 0.001), and propranolol (AOR = 7.56; 95% CI: 1.12–50.61; p = 0.037) were significantly associated with higher odds of DDI. In contrast, use of enalapril (AOR = 0.28; 95% CI: 0.13–0.60; p = 0.001), amlodipine (AOR = 0.27; 95% CI: 0.13–0.57; p = 0.001), hydrochlorothiazide (AOR = 0.49; 95% CI: 0.24–0.98; p = 0.044), and beclomethasone (AOR = 0.18; 95% CI: 0.03–0.89; p = 0.036) were associated with reduced odds of DDI ( Table 5 ). Table 5 Predictors of DDI among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N = 543) Variables Category Drug interaction COR AOR 95% CI P-value# No (%) Yes (%) Comorbid condition No 200(75.2) 66(24.8) 1 1 - Yes 83(30.0) 194(70.0) 2.96 2.42 1.25–4.67 0.008 Overall Number of drugs used Median ± SD 2 ± 0.92 4 ± 1.31 9.65* 6.93 4.50-10.69 0.000 Enalapril No 176(64.5) 97(35.5) 1 1 - Yes 107(39.6) 163(60.4) 0.24* 0.28 0.13–0.60 0.001 Propranolol No 281(52.4) 255(47.6) 1 1 - Yes 2 (28.6) 5(71.4) 5.36 7.56 1.12–50.61 0.037 Amlodipine No 97(43.9) 124(56.1) 1 1 - Yes 186(57.8) 4 (2.2%) 0.26* 0.268 0.13–0.57 0.001 HCT No 169(45.4) 203(54.6) 1 1 - Yes 114(66.7) 57(33.3) 0.31* 0.49 0.24–0.98 0.044 Furosemide No 278(55.7) 221(44.3) 1 1 - Yes 5(11.4) 39(88.6) 9.08* 14.42 4.38–47.48 0.000 Metformin No 278(68.3) 129(31.7) 1 1 - Yes 5(3.7) 131(96.3) 55.40* 23.57 7.53–73.72 0.000 Aspirin No 277(56.6) 212(43.4) 1 1 - Yes 6(11.1) 48(88.9) 3.12 3.13 0.85–11.52 0.080 Beclomethasone No 278(53.2) 245(46.8) 1 1 - Yes 5(25.0) 15 (75.0) 0.10 0.18 0.03–0.89 0.036 Note: * -p-value is < 0.05, #- p-value for multivariate logistic regression Predictors of patient reported adverse drug reaction (ADR) After running bivariate logistic analysis, the variables with p-value ≤ 0.25 were entered into multivariate logistic regression analysis. Hence, being male (AOR = 0.626; 95% CI: 0.413–0.948; p = 0.027), lack of physical exercise (AOR = 0.615; 95% CI: 0.403–0.940; p = 0.025), the use of glyburide (AOR = 0.370; 95% CI: 0.189–0.726; p = 0.004), and use of beclomethasone (AOR = 0.177; 95% CI: 0.045–0.693; p = 0.013) were associated with a significantly lower likelihood of ADRs. Increasing age, with each one-year increase in age increasing the odds of ADRs by approximately 2% (AOR = 1.017; 95% CI: 1.000–1.034; p = 0.044) and an increase in the number of concurrent medications, with each additional medication increasing the odds by about 29% (AOR = 1.287; 95% CI: 1.091–1.519; p = 0.003). The presence of comorbid conditions (AOR = 1.506; 95% CI: 1.001–2.264; p = 0.049), the use of enalapril (AOR = 1.751; 95% CI: 1.143–2.683; p = 0.010), the use of nifedipine (AOR = 2.359; 95% CI: 1.013–5.492; p = 0.047) and hydrochlorothiazide (AOR = 1.712; 95% CI: 1.112–2.635; p = 0.015) were significantly increased the odds of ADRs ( Table 6 ). Table 6 Predictors of ADR among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N = 543) Variables Categories ADR AOR 95% CI p-value No (%) Yes (%) Sex Female 196 (66.0) 101 (34.0) 1 Male 172 (69.9) 74(30.1) 0.626 0.413–0.948 0.027 Age Mean ± SD 55.86 ± 12.34 57.93 ± 12.25 1.017 1.000-1.034 0.044 Physical exercise Yes 226 (65.9) 117 (34.1) 1 No 142 (71.0) 58 (29.0) 0.615 0.403–0.940 0.025 Comorbid condition No 193 (72.6) 73 (27.4) 1 Yes 175 (63.2) 102 (36.8) 1.506 1.001–2.264 0.049 Enalapril No 197 (72.2) 76 (27.8) 1 Yes 171 (63.3) 99 (36.7) 1.751 1.143–2.683 0.010 Amlodipine No 149 (67.4) 72 (32.6) 1 Yes 219 (68.0) 103 (32.0) 1.506 0.956–2.373 0.078 Nifedipine No 348 (68.2) 162 (31.8) Yes 20 (60.6) 13 (39.4) 2.359 1.013–5.492 0.047 Hydrochlorothiazide No 257 (69.1) 115 (30.9) 1 Yes 111 (64.9) 60 (35.1) 1.712 1.112–2.635 0.015 Number of concurrent medication Mean ± SD 1.23 ± 0.42 1.40 ± 0.49 1.287 1.091–1.519 0.003 Glyburide No 323 (67.2) 158 (32.8) 1 Yes 45 (72.6) 17 (27.4) 0.370 0.189–0.726 0.004 Beclomethasone No 351 (67.1) 172 (32.9) 1 Yes 17 (85.0) 3 (150) 0.177 0.045–0.693 0.013 Discussion This is a first study in its nature of assessing DDI and patient reported ADR among HTN patients in Ethiopian context. This study provides valuable insights into the patient safety related to medication therapy, highlighting its influence on blood pressure (BP) control. The study revealed that, based on the age-adjusted Charlson comorbidity index (CCI), majority were in low-risk and moderate-risk categories. Low high risk CCI distribution suggests that while many hypertensive patients have comorbidity, most do not have multiple or severe conditions that would substantially increase their mortality risk. Yet, using tools such as the CCI can help clinicians identify high-risk patients who may require more intensive monitoring and tailored interventions to optimize outcomes ( 26 ). Diabetes mellitus (DM) was the leading comorbid condition (50.4%), followed by heart failure (19.6%). This finding was consistent with others studies: a study conducted in Puducherry, India, identified diabetes mellitus (DM) as the most common comorbidity among hypertensive patients, accounting for 19.2% ( 13 ), Similarly, a multicenter study in China reported DM as the leading comorbidity, followed by other cardiovascular diseases among hypertensive patients ( 27 , 28 ). Consistent findings were also observed in a multicenter study in Ethiopia, where DM was the most prevalent comorbidity, affecting 26.7% of hypertensive patients ( 29 ). Conversely, when examining comorbidities among patients with DM, hypertension was identified as the most common condition ( 28 , 30 ). These findings strongly indicate the need for strict clinical attention in hypertensive patients, as the coexistence of hypertension and DM substantially increases cardiovascular risk and premature mortality ( 28 ). Furthermore, previous studies have demonstrated that comorbid conditions, particularly DM significantly affect blood pressure control and overall health outcomes among hypertensive patients ( 28 , 29 , 31 ). It is a challenge for achieving guideline-recommended blood pressure targets. Hypertensive patients with comorbidities and concurrent medication use have a high likelihood of experiencing clinically significant drug–drug interactions (DDIs). Therefore, clinicians and pharmacists must remain vigilant in identifying potential DDIs to minimize their adverse effects ( 13 , 14 ). In the current study, nearly half of the patients (47.9%) experienced at least one DDI. This prevalence is comparable to findings from studies conducted in South-West Nigeria (47.6%) ( 17 ) and Puducherry, India (48%) DDI( 13 ). However, higher prevalence were reported in studies from Universitas Airlangga Teaching Hospital, Surabaya, Indonesia (89.06%) ( 16 ), Addis Ababa, Ethiopia (90.1%) ( 19 ), and central Gujarat, India (71.5%) ( 15 ). These discrepancies may be attributed to differences in DDI identification tools (Medscape versus Lexicomp Drug Interaction Checker) ( 16 , 32 ), study populations, and clinical settings particularly studies focusing on elderly patients (> 60 years) or those with cardiovascular diseases ( 19 ). In the present study, significant-severity DDIs were the most frequently observed, accounting for 85.4% of all identified interactions. Among patients who experienced at least one DDI (n = 260), the mean number of DDIs per patient was 3.03. This average number of DDIs per patient is considerably higher than reports from South-West Nigeria (1.3 DDIs per patient) ( 17 ), and Dessie, Ethiopia (1.6 DDIs per patient) ( 23 ). The observed variation may be attributed to differences in study populations and, more importantly, methodological differences in DDI assessment. For instance, the Nigerian study evaluated interactions only among antihypertensive and antiplatelet medications ( 17 ), whereas the current study assessed all medications used by patients, thereby increasing the likelihood of detecting DDIs. With respect to DDI severity, the predominance of significant interactions in the current study is consistent with findings from studies conducted in Indonesia ( 32 ), and Dessie, Ethiopia( 23 ), where moderate/significant-severity DDIs were also most common (89.4%). In contrast, studies from central Gujarat, India( 15 ) and Puducherry, India ( 13 ), reported a higher proportion of clinically significant DDIs (85.36%). Similarly, a study from Addis Ababa, Ethiopia, conducted among elderly patients with cardiovascular diseases, reported a higher burden of DDI, with 75%, and 83.3% notable proportions of moderate/significant and minor DDIs, respectively ( 19 ). These differences may reflect variations in patient age, comorbidity burden, medication complexity, and clinical settings. The present study identified enalapril plus metformin as the most frequently observed drug combination associated with DDIs, accounting for 34.2% of all interactions. This combination is known to increase metformin toxicity and elevate the risk of hypoglycemia and lactic acidosis. The second most common interacting pair was amlodipine plus metformin (26.5%), in which amlodipine may reduce the therapeutic effectiveness of metformin through pharmacodynamic antagonism, potentially resulting in poor glycemic control and hyperglycemia. Similarly, studies conducted in central Gujarat ( 15 ) and Puducherry, India ( 13 ) reported atenolol, aspirin, and amlodipine as the most common medications implicated in DDIs among hypertensive patients. Overall, the majority of identified DDIs in the current study were classified as clinically significant, highlighting the importance of systematic medication review and close clinical monitoring in patients receiving multiple long-term therapies. Among participants who experienced DDIs (N = 260), most interactions had no apparent effect on BP (72.3%); however, 16.9% were associated with a decrease in BP, while 10.8% were associated with an increase in BP. Consistent with previous studies, DDIs in hypertensive patients have been linked to a range of clinically relevant complications, including electrolyte disturbances particularly potassium imbalance ( 13 , 15 , 17 , 19 , 32 ), increased risk of acute kidney injury ( 13 , 17 ), interference with blood pressure control (either elevation or reduction of BP) ( 13 – 15 , 17 , 19 , 32 ), and an increased risk of myopathy ( 13 , 19 ). These findings further emphasize the critical role of clinicians and pharmacists in proactive DDI screening and individualized patient management. The present study demonstrated that the presence of comorbid conditions, a higher number of concurrent medications, and the use of furosemide, metformin, and propranolol were significantly associated with increased odds of drug–drug interactions (DDIs). In contrast, the use of enalapril, amlodipine, hydrochlorothiazide, and beclomethasone was associated with reduced odds of DDIs. This apparent protective effect may be attributed to the frequent prescription of these agents as monotherapy or in standardized treatment combinations, which limits exposure to complex multidrug regimens and consequently reduces the likelihood of clinically significant interactions. These findings are consistent with reports from studies conducted in Nigeria and India ( 13 , 17 ), Indonesia ( 32 ), and Dessie, Ethiopia ( 23 ), all of which identified the number of prescribed medications as a significant predictor of DDIs. Similarly, the presence of comorbidities has been consistently associated with an increased risk of DDIs ( 13 ). Evidence from previous studies further indicates that polypharmacy markedly elevates the risk of adverse drug reactions (ADRs) and DDIs ( 17 ). Moreover, the occurrence of ADRs in 32.2% of patients underscores the importance of careful regimen optimization and continuous clinical monitoring to ensure treatment safety and effectiveness. The most frequently reported adverse effects were weakness (33.7%), gastric irritation (33.1%), and headache (30.3%). Prior studies have shown that ADRs are a major contributor to non-compliance to antihypertensive therapy, which in turn leads to poor blood pressure control ( 29 , 33 , 34 ). In line with the present findings, a study conducted in Gondar, Ethiopia, reported that approximately 20% to 31.1% of patients experienced ADRs, with tiredness, dizziness, and headache being the most common complaints ( 33 , 35 ). In the current study, several factors were independently associated with the occurrence of ADRs. These were; increasing age, comorbid conditions, number of concurrent medications, the use of enalapril, nifedipine, and hydrochlorothiazide were significantly associated with a higher risk of ADRs. Increasing age, comorbidities, and a higher number of concurrent medications were significantly associated with an increased risk of ADRs, likely due to age-related pharmacokinetic and pharmacodynamic changes, cumulative drug burden, and a higher likelihood of DDIs( 36 ). Additionally, the use of enalapril, nifedipine, and hydrochlorothiazide was linked to a higher ADR risk, possibly reflecting their known adverse effect profiles, including hypotension, dizziness, electrolyte disturbances, and renal impairment, particularly in older patients with multiple comorbidities( 35 – 37 ). Strength and limitation of the study: This study is done at multicenter which improves generalizability and robustness of its findings. However, the cross-sectional design limits the ability to establish causal relationships, and the reliance on self-reported data may introduce social desirability bias. Conclusions This study demonstrates a high burden of DDI and ADR among hypertensive patients. Amlodipine and enalapril were the most commonly prescribed antihypertensive, with clinically important DDIs mainly involving metformin. DDIs were significantly associated with comorbidities, polypharmacy, and use of furosemide, metformin, and propranolol, while enalapril, amlodipine, hydrochlorothiazide. The most common ADR were weakness, gastric irritation and headache. ADRs were significantly associated with age, sex, comorbidities, polypharmacy, and use of enalapril, nifedipine, and hydrochlorothiazide. Overall, these findings underscore the critical need for regular medication review, and close clinical monitoring particularly in patients with multiple comorbidities and concurrent medications to minimize the DDIs and ADRs and improve the safety and quality of hypertension management. Declarations Authors' contributions Conceptualization and fund acquisition: Tefera, GM. Supervising, project administration, study design and formal analysis, investigation, methodology: Tefera, GM, Feyisa, BB, Chala, TS & Beressa, TB. Writing–original draft: Tefera GM. Writing review & editing: Tefera GM, Feyisa BB, Chala, TS & Beressa TB. All authors read and approved the final manuscript. Acknowledgment First of all, our greatest and an endless gratitude go to our almighty GOD and Ambo University for funding this study. Finally we would like to express our sincere thanks to study participants and all individual who had contributed for realization of this research. Funding The source of funding for this study was Ambo University, with funding code of CHSRH/R-Phar/03/16. The funder has no role in study design, manuscript preparation and any influence on the result of the study. Competing interest: The authors report no conflicts of interest in this work. The authors used ChatGPT only for language improvement. Clinical trial number: Not applicable. Human Ethics and Consent to Participate declarations: The ethical approval was received from Ambo University Institutional Research and ethics review committee (AU IRERC) with a letter number of AU/C/H/S/RH/M771/2/17/2024. This study adhered to the principles outlined in the Declaration of Helsinki. The study participants were informed of the study purpose, procedures, benefits potential and risks, confidentiality protections, and their right to withdraw at any time. For the data collected from medical records, no patient identifiers such as names or card numbers were used. Then informed written consent was taken. Consent for publication: Not applicable. Availability of data and materials: All the data used for this manuscript writing was available within the document and its supplementary materials. Authors' contributions: Conceptualization and fund acquisition: Tefera, GM. Supervising, project administration, study design and formal analysis, investigation, methodology: Tefera, GM, Feyisa, BB, Chala TS & Beressa, TB. Writing–original draft: Tefera GM. Writing review & editing: GM, BB, Chala TS & TB. All authors read and approved the final manuscript. References Organization WH. Global report on hypertension: the race against a silent killer. 2023. Chobufo MD, Gayam V, Soluny J, Rahman EU, Enoru S, Foryoung JB, et al. Prevalence and control rates of hypertension in the USA: 2017–2018. International Journal of Cardiology Hypertension. 2020;6:100044. Amare F, Hagos B, Sisay M, Molla B. Uncontrolled hypertension in Ethiopia: a systematic review and meta-analysis of institution-based observational studies. BMC Cardiovascular Disorders. 2020;20(1):129. Babirye M, Yadesa TM, Tamukong R, Obwoya PS. Prevalence and factors associated with drug therapy problems among hypertensive patients at hypertension clinic of Mbarara Regional Referral Hospital, Uganda: a| cross-sectional study. Therapeutic Advances in Cardiovascular Disease. 2023;17:17539447231160319. Jeemon P, Séverin T, Amodeo C, Balabanova D, Campbell NRC, Gaita D, et al. World Heart Federation Roadmap for Hypertension - A 2021 Update. Glob Heart. 2021;16(1). Samaila A, Biambo AA, Usman N, Aliyu HH. Drug related problems and implications for pharmaceutical care interventions in hypertensive outpatients in a Nigerian hospital. J Sci Pract Pharm. 2019;5(2):281-6. Hussen A, Daba FB. Drug therapy problems and their predictors among hypertensive patients on follow up in Dil-Chora Referral Hospital, Dire-Dawa, Ethiopia. hypertension. 2017;5(7). Fekadu G, Adamu A, Gebre M, Gamachu B, Bekele F, Abadiga M, et al. Magnitude and determinants of uncontrolled blood pressure among adult hypertensive patients on follow-up at Nekemte Referral Hospital, Western Ethiopia. Integrated blood pressure control. 2020:49-61. Cipolle RJ, Strand LM, Morley PC. Pharmaceutical care practice: the patient-centered approach to medication management services. (No Title). 2012. Carey RM, Whelton PK, Committee* AAHGW. Prevention, detection, evaluation, and management of high blood pressure in adults: synopsis of the 2017 American College of Cardiology/American Heart Association Hypertension Guideline. Annals of internal medicine. 2018;168(5):351-8. Jeemon P, Séverin T, Amodeo C, Balabanova D, Campbell NR, Gaita D, et al. World heart federation roadmap for hypertension–A 2021 update. Global Heart. 2021;16(1). Alemayehu TT, Wassie YA, Bekalu AF, Tegegne AA, Ayenew W, Tadesse G, et al. Prevalence of potential drug‒drug interactions and associated factors among elderly patients in Ethiopia: a systematic review and meta-analysis. Global Health Research and Policy. 2024;9(1):46. Subramanian A, Adhimoolam M, Kannan S. Study of drug–Drug interactions among the hypertensive patients in a tertiary care teaching hospital. Perspectives in Clinical Research. 2018;9(1):9-14. Fravel MA, Ernst M. Drug interactions with antihypertensives. Current hypertension reports. 2021;23(3):14. Kothari N, Ganguly B. Potential drug-drug interactions among medications prescribed to hypertensive patients. Journal of clinical and diagnostic research: JCDR. 2014;8(11):HC01. Saraswati MD, Ardiana SM, Suprapti B, Assegaf MY, Hamidah KF. Potential Drug-Drug Interactions in Ambulatory Patients with Hypertension: a Retrospective Study. Pharmacy & Pharmaceutical Sciences Journal/Jurnal Farmasi Dan Ilmu Kefarmasian Indonesia. 2022;9(1). Fadare JO, Ajayi AE, Adeoti AO, Desalu OO, Obimakinde AM, Agboola SM. Potential drug-drug interactions among elderly patients on anti-hypertensive medications in two tertiary healthcare facilities in Ekiti State, South-West Nigeria. Sahel Medical Journal. 2016;19(1):32-7. Fufa F, Mirkano D, Tipathi R. Prescription pattern and potential drug-drug interactions of antihypertensive drugs in a general hospital, South Ethiopia. Cukurova Medical Journal. 2015;40(4):698-706. Adem L, Tegegne GT. Medication appropriateness, polypharmacy, and drug-drug interactions in ambulatory elderly patients with cardiovascular diseases at Tikur Anbessa Specialized Hospital, Ethiopia. Clinical interventions in aging. 2022:509-17. Assefa YA, Kedir A, Kahaliw W. Survey on polypharmacy and drug-drug interactions among elderly people with cardiovascular diseases at Yekatit 12 Hospital, Addis Ababa, Ethiopia. Integrated Pharmacy Research and Practice. 2020:1-9. Chelkeba L, Alemseged F, Bedada W. Assessment of potential drug-drug interactions among outpatients receiving cardiovascular medications at Jimma University specialized hospital, South West Ethiopia. Int J Basic Clin Pharmacol. 2013;2(2):144-52. Diksis N, Melaku T, Assefa D, Tesfaye A. Potential drug–drug interactions and associated factors among hospitalized cardiac patients at Jimma University Medical Center, Southwest Ethiopia. SAGE open medicine. 2019;7:2050312119857353. Gobezie MY, Bitew HB, Tuha A, Hailu HG. Assessment of Potential Drug–Drug Interactions and Their Predictors in Chronic Outpatient Department of Dessie Referral Hospital, Dessie, Northeast Ethiopia. Drug, healthcare and patient safety. 2021:29-35. Medscape. Drug-drug interaction. Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC geriatrics. 2017;17(1):230. Drosdowsky A, Gough K. The Charlson Comorbidity Index: problems with use in epidemiological research. Journal of Clinical Epidemiology. 2022;148:174-7. Wang J, Ma JJ, Liu J, Zeng DD, Song C, Cao Z. Prevalence and Risk Factors of Comorbidities among Hypertensive Patients in China. Int J Med Sci. 2017;14(3):201-12. Lauder L, Mahfoud F, Azizi M, Bhatt DL, Ewen S, Kario K, et al. Hypertension management in patients with cardiovascular comorbidities. European Heart Journal. 2023;44(23):2066-77. Abdisa L, Girma S, Lami M, Hiko A, Yadeta E, Geneti Y, et al. Uncontrolled hypertension and associated factors among adult hypertensive patients on follow-up at public hospitals, Eastern Ethiopia: A multicenter study. SAGE open medicine. 2022;10:20503121221104442. Naseri MW, Esmat HA, Bahee MD. Prevalence of hypertension in Type-2 diabetes mellitus. Annals of Medicine and Surgery. 2022;78. Gobezie MY, Hassen M, Tesfaye NA, Solomon T, Demessie MB, Fentie Wendie T, et al. Prevalence of uncontrolled hypertension and contributing factors in Ethiopia: a systematic review and meta-analysis. Frontiers in Cardiovascular Medicine. 2024;Volume 11 - 2024. Alkhalid Z, Birand N. Determination and comparison of potential drug–drug interactions using three different databases in northern cyprus community pharmacies. Nigerian Journal of Clinical Practice. 2022;25(12):2005-9. Gebreyohannes EA, Bhagavathula AS, Abebe TB, Tefera YG, Abegaz TM. Adverse effects and non-adherence to antihypertensive medications in University of Gondar Comprehensive Specialized Hospital. Clinical hypertension. 2019;25(1):1. Habtegiorgis A, Edin A, Lemma K, Utura T, Girma D, Getachew D, et al. Determinants of uncontrolled blood pressure among adult hypertensive patients on follow-up at Negelle and Adola General Hospital, Guji Zone, Southern Ethiopia: facility-based case control study. BMC Public Health. 2024;24(1):2971. Dagnew SB, Moges TA, Ayele TM, Wondm SA, Yazie TS, Dagnew FN. Adverse drug reactions and its associated factors among geriatric hospitalized patients at selected comprehensive specialized hospitals of the Amhara Region, Ethiopia: a multicenter prospective cohort study. BMC geriatrics. 2024;24(1):955. Rodriguez-Espeso EA, Verdejo-Bravo C, Cruz-Jentoft AJ. [Adverse drug reactions in older adults: A review of epidemiology, risk factors and prevention strategies]. Rev Esp Geriatr Gerontol. 2025;60(5):29. Alhawassi TM, Krass I, Pont LG. Antihypertensive-related adverse drug reactions among older hospitalized adults. Int J Clin Pharm. 2018;40(2):428-35. Additional Declarations No competing interests reported. Supplementary Files DataabstructiontoolDDIADR.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8527897","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585857575,"identity":"1970272b-b511-4c0f-9e87-158e82a50542","order_by":0,"name":"Gosaye Mekonen Tefera","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYBAC/gYGhgMfDCR4GCTAfBsgZmw8gE+LBFD24IwKCzmoljSQlga8WgyAmJnnTIUxVMthMIlfC3v7wwO8bRKJ26Wbn326UXPebm37YaAtNTbROLXwnDE4IAnUsnPOMePZOcduJ287kwjUciwttwGHFsMbOQwHDIFaNtxIMGbOYbudbHYAqIWx4TBOLQY30h8cSARrSf/MnPPvXLLZ+YeEtCQYHDhwRsLY4EaOMXNu2wE7sxsEbJE4c8bgYEOFhJzljJxi5ty+5ASzG0BbEvD4hb+9/fHnPwZ1POYS6ZuZc77Z2ZudT3/44EONDU4tCBdC6USwygRCypG12BOjeBSMglEwCkYWAABr6muKTZcR7gAAAABJRU5ErkJggg==","orcid":"","institution":"CHSRH, Ambo University","correspondingAuthor":true,"prefix":"","firstName":"Gosaye","middleName":"Mekonen","lastName":"Tefera","suffix":""},{"id":585857576,"identity":"abcc7e8f-4213-4317-967a-0a144b31bd3b","order_by":1,"name":"Beshadu Bedada Feyisa","email":"","orcid":"","institution":"CHSRH, Ambo University","correspondingAuthor":false,"prefix":"","firstName":"Beshadu","middleName":"Bedada","lastName":"Feyisa","suffix":""},{"id":585857577,"identity":"0e8dc167-8d46-48c3-aef2-da425978856a","order_by":2,"name":"Tesemma Sileshi Chala","email":"","orcid":"","institution":"CHSRH, Ambo University","correspondingAuthor":false,"prefix":"","firstName":"Tesemma","middleName":"Sileshi","lastName":"Chala","suffix":""},{"id":585857578,"identity":"1ae507f9-f5ec-4e5c-9cfa-6eeac9450a24","order_by":3,"name":"Tamirat Bekele Beressa","email":"","orcid":"","institution":"CHSRH, Ambo University","correspondingAuthor":false,"prefix":"","firstName":"Tamirat","middleName":"Bekele","lastName":"Beressa","suffix":""}],"badges":[],"createdAt":"2026-01-06 07:23:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8527897/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8527897/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108976433,"identity":"8d9d5347-5dc3-4d0b-9af1-8826a92ac888","added_by":"auto","created_at":"2026-05-11 11:19:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":634778,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8527897/v1/7716a432-211e-4b71-bef4-ebaebae90993.pdf"},{"id":102061403,"identity":"f07a392b-fd4b-4e6c-a327-1d00c73d9d9e","added_by":"auto","created_at":"2026-02-06 17:05:55","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":26179,"visible":true,"origin":"","legend":"","description":"","filename":"DataabstructiontoolDDIADR.docx","url":"https://assets-eu.researchsquare.com/files/rs-8527897/v1/fb1842bcc63def0bf5f83966.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Drug-drug interaction, adverse drug reaction and their determinants among adult hypertensive patients; Multicenter study in Ethiopia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWorld Health Organization (WHO) report shows hypertension affects 1 in 3 adults worldwide. Globally 56%(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), in the USA (per the new definition of hypertension) 49.64% (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), in Africa 36% (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), and in Ethiopia 30% (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) of adult population has hypertension. Hypertension is, a deadly condition which leads to 10.8\u0026nbsp;million avoidable deaths every year out of 41\u0026nbsp;million death from non-communicable disease (NCD) and different morbidities (stroke, heart attack, heart failure, kidney damage) and enormous economic costs(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Appropriate hypertension management will save lives and improve wellbeing (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In-appropriately treated hypertension has worst health outcomes(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), which is higher in Africa (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAppropriate hypertension management through ensuring that people receive appropriate ant-hypertensive therapy and free from drug-drug interaction (DDI) and adverse drug reaction (ADR) to BP goal achievement has been highly recommended (\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Thus, by improving BP control alone, the global health care savings have been estimated at \u003cspan\u003e$\u003c/span\u003e100\u0026nbsp;billion per year (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), and it can assure the achievement of Sustainable Development Goal (SDG) target 3.4; one third reduction in premature mortality by 2030 from NCD (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDDI is defined as the qualitative or quantitative modification of the effect of a drug by the simultaneous or successive administration of a different drugs. This may result in the alteration of therapeutic effect and safety of either or both drugs. It is a great concern among hypertensive patients due to the tendency of receiving multidrug therapy(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, it is important to remember that DDI may be beneficial or harmful. Thus, WHO recommends that the problem can be significantly minimized by implementing careful attention to the identification and resolution of DDIs (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). DDI studies among hypertensive patients out of Ethiopia showed that the prevalence is as high as 47.6% to 89.06% (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), where majority of them were significant in severity (85.36%) to 95.42%. A lots of antihypertensive medication have been contributing for DDI (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEven though it is highly recommended to have surveillance on DDI among hypertension patients to take appropriate intervention, the available data in Ethiopia is limited(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) (to our knowledge only one study before 10 years in single hospital (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) and no study in West Shoa Zone. The other studies on DDI were not specific to antihypertensive (it is general or related with cardiovascular disease)(\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In fact, those data showed high prevalence of DDI in Ethiopia among patients with cardiovascular disease (CVD) (\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e); Addis Ababa 90.1% (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and at Dessie Referral Hospital, Ethiopia 1.63 DDI per patient (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, investigating adverse drug reactions (ADRs), drug\u0026ndash;drug interactions (DDIs), and their determinants is essential to quantify the magnitude of the problem and enable early intervention to optimize antihypertensive therapy. These findings provide valuable evidence to support healthcare providers in improving patient care and minimizing ADRs and DDIs during clinical management.\u003c/p\u003e"},{"header":"Methods and Participants","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area, period and design:\u003c/h2\u003e \u003cp\u003eA hospital-based cross-sectional study was conducted in 5 selected public hospitals (multi-center study) in the West Shoa Zone, Oromia, Ethiopia, from January 01 2024 to April 30, 2024. West Shoa Zone has ten public hospitals in general which serves around 3.6\u0026nbsp;million populations. From the 10 hospitals, by lottery method 5 hospitals, namely, Guder Primary Hospital, Ambo University Referral Hospital, Ambo General Hospital, Ginchi Primary Hospital and Bako Primary Hospital were included to the study. The selected hospitals have separate outpatient departments for the treatment and follow-up of chronic diseases including hypertension. So the data for this study was collected from the outpatient department of chronic diseases follow up.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Participants Recruitment, Sampling and Data Collection Procedure\u003c/h3\u003e\n\u003cp\u003eAdult hypertensive patients (\u0026ge;\u0026thinsp;18 years) on pharmacologic treatment for at least 6 months and on follow up during data collection period were included by systematic random sampling methods from selected hospitals with inclusion criteria (proportional allocation was made for each hospitals). Pregnant mothers, refuse to participate in the study, patients with cognitive impairment, seriously ill patients (admission) that made it impossible to conduct a reliable interview and patients with incomplete medical records were excluded.\u003c/p\u003e\n\u003ch3\u003eStudy variables:\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003eDependent variables\u003c/b\u003e were, DDI and ADR, while independent variables were: sociodemographic, disease related factors, presence of metabolic syndrome (BMI or WHR), drug related factors (number and type of drug used), and behavioral factors (alcohol, khat, and tobacco use habit).\u003c/p\u003e\n\u003ch3\u003eSample size and sampling procedure\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSample size was calculated for different objectives and/ or predictor variables and then the largest sample size (588) was selected as a final sample size. For determinant factor double population formula was used with 95% C.I and 80% powers from study at Nekemte, Ethiopia (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeterminant factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%outcome exposed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%outcome un-exposed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePower (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95%c.I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdherence to drug\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA single population formula was used to calculate the sample size for BP control rate. The assumptions considered during the calculation of the sample size were 95% confidence level, 5% margin of error, and p\u0026thinsp;=\u0026thinsp;36.4%; prevalence of uncontrolled hypertension from the study carried out in Nekemte, Ethiopia(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"510\" height=\"88\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhere\u003c/strong\u003e;\u0026nbsp;\u003c/p\u003e\n\u003col class=\"decimal_type\" style=\"list-style-type: lower-alpha;\"\u003e\n \u003cli\u003eN is the size of the population that the sample is to represent = 13748 hypertensive patients in West Shoa in 2015 E.C from DHIS 2.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDesign effect= 1.5, thus 1.5*356= 534 (2 stage sampling)\u003c/li\u003e\n \u003cli\u003e10% for non-response rate = 54 +534 = 588\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe sample size for each hospital was proportionally allocated with the ratio of 588/11360= 0.052. \u0026nbsp;Systematic random sampling method (every K\u003csup\u003eth\u003c/sup\u003e) was used to select the study participants from each selected hospitals.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eData Collection Tool, Process and Quality Control\u003c/h3\u003e\n\u003cp\u003eThe data collection tool used for this study was annexed as supplementary material (data collection tool). Data was collected with semi-structured questionnaire through patient interviews and medical record reviews. A medical chart review and a data abstraction tool was filled for each eligible patient to get relevant information like co-morbid condition/s, BP and laboratory values, medication/s. Patients were interviewed to obtain socio-demographic, disease-related, behavioral/ lifestyle and compliance to medication/salt related information. The pretest was done on 5% of the total sample to ensure the quality and agreement of the data abstraction format with the objective of the study and adjustments were done accordingly.\u003c/p\u003e \u003cp\u003eThe identification of DDI was done based on the \u0026lsquo;Medscape online drug interaction checker\u0026rsquo;(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). All concurrent medications were entered into Medscape, which classifies DDIs by severity: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Contraindicated \u0026ndash; risks outweigh benefits; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Serious \u0026ndash; avoid or modify therapy; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Significant \u0026ndash; monitor for adverse effects or reduced efficacy; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Minor \u0026ndash; minimal or unknown clinical impact. Polypharmacy was defined as the use of \u0026ge;\u0026thinsp;5 medications concurrently(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). ADRs were defined as any harmful or unintended drug response perceived by the patient to be caused by their medications(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). ADR is considered based on patient report after probing that the compliant was started after the use of the offending drug (any drug used by patient).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Processing and Analysis:\u003c/h2\u003e \u003cp\u003eThe data was entered, cleaned and analyzed using Statistical Package for the Social Sciences (SPSS) version 20.0. Descriptive statistics including frequency, percentages, mean and standard deviation (SD) were used to summarize study variables. Multivariate logistic regression was done for variables with p-value less than 0.25 and known predictors from previous study to determine factors associated with DDI with p-values\u0026thinsp;\u0026le;\u0026thinsp;0.05 for statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic and clinical characteristics of study participants\u003c/h2\u003e \u003cp\u003e The details of the socio demographic characteristics of the study participants was available elsewhere in other document \u0026lsquo;Psychometric property of Hill bone high blood pressure therapy compliance scale\u0026rsquo; because it was done simultaneously. A total of 543 hypertensive patients were included in the study with response rate of 92.3%. The mean (\u0026plusmn;\u0026thinsp;SD) age of the participants was 56.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3 years.\u003c/p\u003e \u003cp\u003eBased on the age-adjusted Charlson comorbidity index (CCI), patients were almost equally distributed between the low-risk (42.7%) and moderate-risk (42.9%) categories, with fewer in the high-risk group. About half (50.8%) had at least one chronic comorbid condition, most commonly a single condition (83%). Diabetes mellitus was the leading comorbidity (50.4%), followed by heart failure (19.6%) and asthma/Chronic Obstructive Pulmonary Disease (COPD) (14.1%) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eclinical characteristics of study participants at selected hospitals of West Shoa Zone, January to April 30/2024, Ethiopia (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables Categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge based Charlson CI risk classification score (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow risk (0\u0026ndash;2 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emoderate risk (3\u0026ndash;4 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehigh risk (\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;5 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian (IQR), min-max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3[2\u0026ndash;4], 1\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChronic Co-morbid condition based on CCI (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNumber of comorbid condition (N\u0026thinsp;=\u0026thinsp;276)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003eList of chronic common co-morbid condition based on CCI (top 10)(N\u0026thinsp;=\u0026thinsp;276)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsthma/COPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGastritis/PUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStroke/TIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRheumatic/connective tissue disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIV/AIDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003cb\u003eother\u003c/b\u003e#- (hemiplegia, Cancer, Dementia/Alzheimer, Depression); COPD-chronic obstructive pulmonary disease; DM-diabetes mellitus; PUD-peptic ulcer disease; TIA-transient ischemic attack; CKD-chronic kidney disease, IHD-ischemic heart disease; PVD-peripheral vascular disease; HIV/AIDS-Human immune virus/ Acquired immune deficiency syndrome;\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Drug-drug interaction and Adverse Drug Reaction\u003c/h2\u003e \u003cp\u003eAmong 543 patients, 16.0% were identified to have polypharmacy. Nearly half of the patients (47.9%) experienced at least one drug-drug interaction (DDI), regarding the severity of DDI, significant interactions being the most common (85.4%), and 17.3% experiencing serious interactions. There was no contra-indicated type of DDI identified. The mean number of DDIs per patient with interactions (among 260 patients) was 3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22 (range 1\u0026ndash;12), with a total of 789 DDIs identified in the study participants.\u003c/p\u003e \u003cp\u003eRegarding adverse effects, 32.2% of patients reported at least one adverse drug reaction, with the most common being weakness (33.7%), gastric irritation (33.1%), headache (30.3%), and ankle swelling (10.3%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDrug-drug interaction and patient reported ADR among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentages\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePoly pharmacy (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall drug-drug interaction (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSeverity of drug-drug interaction (N\u0026thinsp;=\u0026thinsp;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eNumber of drug-drug interaction per patient (N\u0026thinsp;=\u0026thinsp;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (min. to maximum)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22 (\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSummary of drug-drug interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSum (total DDI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e789 DDI identified\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage per patients with DDI (260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3.04 DDI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage per sample (543)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.45 DDI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal number of DDI by level of severity (N\u0026thinsp;=\u0026thinsp;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 DDI*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3 DDI*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2 DDI*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAdverse drug reaction (self-report) (N\u0026thinsp;=\u0026thinsp;543)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e \u003cp\u003eType of adverse drug reaction reported by patients (N\u0026thinsp;=\u0026thinsp;175)- Multiple response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeakness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeadache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErectile dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGastric irritation (GI compliant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDry cough\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnkle swelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneralized body edema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSkin itching/ allergic reaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypotension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDizziness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePain/tingling of extremities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003cspan\u003e$\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: \u003cb\u003eDDI\u003c/b\u003e*- average drug-drug interaction per 260 patients; DDI- drug-drug interaction; \u003cb\u003eOther$\u003c/b\u003e- (chest pain, urinary retention, shortness of breath, constipation, hyperkalemia, synchro/seizure, liver toxicity, dry mouth)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCommon drugs contributing for DDI and it clinical consequence\u003c/h2\u003e \u003cp\u003eAmong the identified drug\u0026ndash;drug interactions (DDIs), the most frequently observed combination was enalapril plus metformin, accounting for 89 cases (34.2%), which was associated with increased metformin toxicity and a heightened risk of hypoglycemia and lactic acidosis. This was followed by amlodipine plus metformin in 69 cases (26.5%), where amlodipine reduced the therapeutic effect of metformin through pharmacodynamics antagonism, potentially leading to hyperglycemia.\u003c/p\u003e \u003cp\u003eThe combination of aspirin and enalapril was observed in 38 patients (14.6%) and was linked to pharmacodynamics antagonism with possible acute kidney injury, classified as significant to serious in severity. Similarly, glyburide plus atorvastatin occurred in 37 cases (14.2%) and increased the risk of atorvastatin-induced myopathy.\u003c/p\u003e \u003cp\u003eInteractions involving antihypertensive and diuretic agents were also common. Enalapril plus furosemide was identified in 31 cases (11.9%), posing a risk of acute hypotension and renal insufficiency due to synergistic effects. Enalapril plus glyburide, reported in 27 cases (10.4%), increased the risk of hypoglycemia, while enalapril plus insulin was seen in 16 cases (6.2%) with a similar synergistic hypoglycemic effect.\u003c/p\u003e \u003cp\u003eAntidiabetic drug combinations contributed substantially to DDIs; metformin plus insulin was identified in 18 cases (6.9%), significantly increasing hypoglycemia risk. Cardiovascular drug combinations such as aspirin plus metoprolol (17 cases; 6.5%) and metoprolol plus furosemide (11 cases; 4.2%) were associated with alterations in serum potassium levels.\u003c/p\u003e \u003cp\u003eLess frequent but clinically relevant interactions included propranolol or bisoprolol plus amlodipine (9 cases; 3.5%), which may synergistically lower blood pressure and cause hypotension; nifedipine plus metformin (7 cases; 2.7%), associated with reduced glycemic control; and atorvastatin plus amitriptyline (10 cases; 3.8%), which increased amitriptyline exposure. In addition, combinations involving aspirin or spironolactone with furosemide were noted in 16 cases (6.2%), potentially affecting serum potassium levels.\u003c/p\u003e \u003cp\u003eOverall, the majority of identified DDIs were classified as significant in severity, underscoring the need for careful medication review and close clinical monitoring in patients receiving multiple chronic therapies \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of top-15 drugs contributed to DDI, their Prevalence, and Expected Negative Effects among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eList of common drugs contributed to DDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrevalence of DDI (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClinical consequence of DDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeverity of DDI per Medscape checker\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnalapril\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89 (34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreased metformin toxicity: Increases risk for hypoglycemia and lactic acidosis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmlodipine\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmlodipine decreases effects of metformin by pharmacodynamics antagonism-hyperglycemia.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u0026thinsp;+\u0026thinsp;enalapril\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncrease risk of acute renal insufficiency, pharmacodynamics antagonism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant-serious\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlyburide\u0026thinsp;+\u0026thinsp;atorvastatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncrease risk of atorvastatin myopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnalapril\u0026thinsp;+\u0026thinsp;furosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncrease risk of acute renal insufficiency \u0026amp; hypotension (synergism)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnalapril\u0026thinsp;+\u0026thinsp;glyburide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnalapril increase risk of hypoglycemia (synergism )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin\u0026thinsp;+\u0026thinsp;insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreased risk of hypoglycemia (synergism )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u0026thinsp;+\u0026thinsp;metoprolol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreased serum potassium(synergism )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnalapril\u0026thinsp;+\u0026thinsp;insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases risk for hypoglycemia(synergism )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin/ Spironolactone\u0026thinsp;+\u0026thinsp;Furosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAffect serum potassium (Unclear effect)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtenolol/Propranolol/bisoprolol\u0026thinsp;+\u0026thinsp;amlodipine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSynergize BP reduction / hypotension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetoprolol\u0026thinsp;+\u0026thinsp;furosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAffect serum potassium (Unclear effect)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtorvastatin\u0026thinsp;+\u0026thinsp;amitriptyline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAtorvastatin will increase the level or effect of amitriptyline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNifedipine\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmlodipine decreases effects of metformin by pharmacodynamic antagonism-hyperglycemia.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigoxin\u0026thinsp;+\u0026thinsp;furosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHypokalemia increases digoxin effects \u0026amp; Affect serum potassium (Unclear effect)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u0026thinsp;+\u0026thinsp;spironolactone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBoth increase serum potassium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOthers#\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92 (35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eNote\u003c/span\u003e: \u003cb\u003eOthers#-\u003c/b\u003e (folic acid\u0026thinsp;+\u0026thinsp;methotrexate, amitriptyline\u0026thinsp;+\u0026thinsp;metformin, amitriptyline\u0026thinsp;+\u0026thinsp;metformin, hydrochlorothiazide\u0026thinsp;+\u0026thinsp;metoprolol, indomethacin\u0026thinsp;+\u0026thinsp;albuterol, amitriptyline\u0026thinsp;+\u0026thinsp;tramadol, amlodipine\u0026thinsp;+\u0026thinsp;phenytoin, valproic acid\u0026thinsp;+\u0026thinsp;phenytoin, amoxicillin\u0026thinsp;+\u0026thinsp;hydrochlorothiazide, artemether/lumefantrine\u0026thinsp;+\u0026thinsp;primaquine, aspirin\u0026thinsp;+\u0026thinsp;hydrochlorthiazide. aspirin\u0026thinsp;+\u0026thinsp;albuterol/propranolol/bisoprolol, phenytoin\u0026thinsp;+\u0026thinsp;amlodipine/atorvastatin/valproate, prednisolone\u0026thinsp;+\u0026thinsp;HCT, propranolol\u0026thinsp;+\u0026thinsp;insulin), Amitriptyline\u0026thinsp;+\u0026thinsp;albuterol, Diclofenac/dexamethasone\u0026thinsp;+\u0026thinsp;enalapril, CBZ\u0026thinsp;+\u0026thinsp;atorvastatin, Beclomethasone\u0026thinsp;+\u0026thinsp;HCT, Beclomethasone\u0026thinsp;+\u0026thinsp;furosemide, Gabapentine\u0026thinsp;+\u0026thinsp;amitriptyline, Tramadol\u0026thinsp;+\u0026thinsp;albuterol, Indomethacin\u0026thinsp;+\u0026thinsp;enalapril, CBZ\u0026thinsp;+\u0026thinsp;amlodipine, Albuterol\u0026thinsp;+\u0026thinsp;furosemide, Indomethacin\u0026thinsp;+\u0026thinsp;HCT, Furosemide\u0026thinsp;+\u0026thinsp;HCT, Nifedipine\u0026thinsp;+\u0026thinsp;atorvastatin, carbamazepine\u0026thinsp;+\u0026thinsp;HCT/enalapril, phenobarbito\u0026thinsp;+\u0026thinsp;amlodipine/carbamazepine, Metoprolol\u0026thinsp;+\u0026thinsp;albuterol, Metformin\u0026thinsp;+\u0026thinsp;HCT).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCommon drugs contributing for DDI and its potential effect on Blood pressure\u003c/h2\u003e \u003cp\u003eAmong the study participants (N\u0026thinsp;=\u0026thinsp;260), most DDIs had no potential effect on blood pressure (188; 72.3%), while 16.9% (44 cases) decreased BP and 10.8% (28 cases) increased BP. Interactions between CVD and non-CVD drugs were the most frequent (100; 38.5%), followed by within-CVD interactions (71; 27.3%) and all-class interactions (70; 26.9%); non-CVD interactions were least common (19; 7.3%). Among DDIs affecting BP (N\u0026thinsp;=\u0026thinsp;72), significant severity predominated (41; 56.9%), with minor (29; 40.3%) and serious (2; 2.8%) interactions occurring less frequently (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eclinical effect of DDI on BP and common class of drugs contributing for DDI among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N\u0026thinsp;=\u0026thinsp;260)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentages\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDDI effect on BP (N\u0026thinsp;=\u0026thinsp;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eType of DDI by therapeutic class (N\u0026thinsp;=\u0026thinsp;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVD with Non-CVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enon CVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithin-CVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLevel of DDI effect on BP (N\u0026thinsp;=\u0026thinsp;72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of Drug-drug interaction (DDI)\u003c/h2\u003e \u003cp\u003eBinary logistic regression was performed to screen candidate variables for multivariable logistic regression. Variables with a p-value\u0026thinsp;\u0026le;\u0026thinsp;0.25 in the bivariable analysis, as well as variables identified as significant predictors in previous studies (including polypharmacy and overall number of medications used), were entered into the multivariable model to identify independent predictors of drug\u0026ndash;drug interactions (DDIs).\u003c/p\u003e \u003cp\u003eMultivariable logistic regression analysis showed that patients with comorbid conditions (AOR\u0026thinsp;=\u0026thinsp;2.42; 95% CI: 1.25\u0026ndash;4.67; p\u0026thinsp;=\u0026thinsp;0.008), an increasing number of medications (AOR\u0026thinsp;=\u0026thinsp;6.93; 95% CI: 4.50\u0026ndash;10.69; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), use of furosemide (AOR\u0026thinsp;=\u0026thinsp;14.42; 95% CI: 4.38\u0026ndash;47.48; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), metformin (AOR\u0026thinsp;=\u0026thinsp;23.57; 95% CI: 7.53\u0026ndash;73.72; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and propranolol (AOR\u0026thinsp;=\u0026thinsp;7.56; 95% CI: 1.12\u0026ndash;50.61; p\u0026thinsp;=\u0026thinsp;0.037) were significantly associated with higher odds of DDI. In contrast, use of enalapril (AOR\u0026thinsp;=\u0026thinsp;0.28; 95% CI: 0.13\u0026ndash;0.60; p\u0026thinsp;=\u0026thinsp;0.001), amlodipine (AOR\u0026thinsp;=\u0026thinsp;0.27; 95% CI: 0.13\u0026ndash;0.57; p\u0026thinsp;=\u0026thinsp;0.001), hydrochlorothiazide (AOR\u0026thinsp;=\u0026thinsp;0.49; 95% CI: 0.24\u0026ndash;0.98; p\u0026thinsp;=\u0026thinsp;0.044), and beclomethasone (AOR\u0026thinsp;=\u0026thinsp;0.18; 95% CI: 0.03\u0026ndash;0.89; p\u0026thinsp;=\u0026thinsp;0.036) were associated with reduced odds of DDI \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictors of DDI among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eDrug interaction\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value#\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eComorbid condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e200(75.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66(24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e194(70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25\u0026ndash;4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Number of drugs used\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.65*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.50-10.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEnalapril\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e176(64.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e97(35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e107(39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e163(60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u0026ndash;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePropranolol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e281(52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e255(47.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5(71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.12\u0026ndash;50.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAmlodipine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97(43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e124(56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e186(57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u0026ndash;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169(45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e203(54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114(66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u0026ndash;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFurosemide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e278(55.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e221(44.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5(11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39(88.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.08*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.38\u0026ndash;47.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetformin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e278(68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e129(31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5(3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e131(96.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.40*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.53\u0026ndash;73.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e277(56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e212(43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6(11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48(88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.85\u0026ndash;11.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBeclomethasone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e278(53.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e245(46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5(25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026ndash;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eNote: * -p-value is \u0026lt;\u0026thinsp;0.05, #- p-value for multivariate logistic regression\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003ePredictors of patient reported adverse drug reaction (ADR)\u003c/h2\u003e \u003cp\u003eAfter running bivariate logistic analysis, the variables with p-value\u0026thinsp;\u0026le;\u0026thinsp;0.25 were entered into multivariate logistic regression analysis. Hence, being male (AOR\u0026thinsp;=\u0026thinsp;0.626; 95% CI: 0.413\u0026ndash;0.948; p\u0026thinsp;=\u0026thinsp;0.027), lack of physical exercise (AOR\u0026thinsp;=\u0026thinsp;0.615; 95% CI: 0.403\u0026ndash;0.940; p\u0026thinsp;=\u0026thinsp;0.025), the use of glyburide (AOR\u0026thinsp;=\u0026thinsp;0.370; 95% CI: 0.189\u0026ndash;0.726; p\u0026thinsp;=\u0026thinsp;0.004), and use of beclomethasone (AOR\u0026thinsp;=\u0026thinsp;0.177; 95% CI: 0.045\u0026ndash;0.693; p\u0026thinsp;=\u0026thinsp;0.013) were associated with a significantly lower likelihood of ADRs. Increasing age, with each one-year increase in age increasing the odds of ADRs by approximately 2% (AOR\u0026thinsp;=\u0026thinsp;1.017; 95% CI: 1.000\u0026ndash;1.034; p\u0026thinsp;=\u0026thinsp;0.044) and an increase in the number of concurrent medications, with each additional medication increasing the odds by about 29% (AOR\u0026thinsp;=\u0026thinsp;1.287; 95% CI: 1.091\u0026ndash;1.519; p\u0026thinsp;=\u0026thinsp;0.003). The presence of comorbid conditions (AOR\u0026thinsp;=\u0026thinsp;1.506; 95% CI: 1.001\u0026ndash;2.264; p\u0026thinsp;=\u0026thinsp;0.049), the use of enalapril (AOR\u0026thinsp;=\u0026thinsp;1.751; 95% CI: 1.143\u0026ndash;2.683; p\u0026thinsp;=\u0026thinsp;0.010), the use of nifedipine (AOR\u0026thinsp;=\u0026thinsp;2.359; 95% CI: 1.013\u0026ndash;5.492; p\u0026thinsp;=\u0026thinsp;0.047) and hydrochlorothiazide (AOR\u0026thinsp;=\u0026thinsp;1.712; 95% CI: 1.112\u0026ndash;2.635; p\u0026thinsp;=\u0026thinsp;0.015) were significantly increased the odds of ADRs \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictors of ADR among hypertensive patients at selected hospitals of West Shoa Zone, Ethiopia (N\u0026thinsp;=\u0026thinsp;543)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eADR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e196 (66.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e172 (69.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74(30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.413\u0026ndash;0.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.86\u0026thinsp;\u0026plusmn;\u0026thinsp;12.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.93\u0026thinsp;\u0026plusmn;\u0026thinsp;12.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000-1.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhysical exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142 (71.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.403\u0026ndash;0.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eComorbid condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193 (72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73 (27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.001\u0026ndash;2.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEnalapril\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e197 (72.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76 (27.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e171 (63.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.143\u0026ndash;2.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAmlodipine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149 (67.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e219 (68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.956\u0026ndash;2.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNifedipine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e348 (68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (60.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.013\u0026ndash;5.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHydrochlorothiazide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e257 (69.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111 (64.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (35.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.112\u0026ndash;2.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of concurrent medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.091\u0026ndash;1.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGlyburide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e323 (67.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45 (72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.189\u0026ndash;0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBeclomethasone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e351 (67.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17 (85.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.045\u0026ndash;0.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is a first study in its nature of assessing DDI and patient reported ADR among HTN patients in Ethiopian context. This study provides valuable insights into the patient safety related to medication therapy, highlighting its influence on blood pressure (BP) control.\u003c/p\u003e \u003cp\u003eThe study revealed that, based on the age-adjusted Charlson comorbidity index (CCI), majority were in low-risk and moderate-risk categories. Low high risk CCI distribution suggests that while many hypertensive patients have comorbidity, most do not have multiple or severe conditions that would substantially increase their mortality risk. Yet, using tools such as the CCI can help clinicians identify high-risk patients who may require more intensive monitoring and tailored interventions to optimize outcomes (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDiabetes mellitus (DM) was the leading comorbid condition (50.4%), followed by heart failure (19.6%). This finding was consistent with others studies: a study conducted in Puducherry, India, identified diabetes mellitus (DM) as the most common comorbidity among hypertensive patients, accounting for 19.2% (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), Similarly, a multicenter study in China reported DM as the leading comorbidity, followed by other cardiovascular diseases among hypertensive patients (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Consistent findings were also observed in a multicenter study in Ethiopia, where DM was the most prevalent comorbidity, affecting 26.7% of hypertensive patients (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Conversely, when examining comorbidities among patients with DM, hypertension was identified as the most common condition (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). These findings strongly indicate the need for strict clinical attention in hypertensive patients, as the coexistence of hypertension and DM substantially increases cardiovascular risk and premature mortality (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Furthermore, previous studies have demonstrated that comorbid conditions, particularly DM significantly affect blood pressure control and overall health outcomes among hypertensive patients (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). It is a challenge for achieving guideline-recommended blood pressure targets.\u003c/p\u003e \u003cp\u003eHypertensive patients with comorbidities and concurrent medication use have a high likelihood of experiencing clinically significant drug\u0026ndash;drug interactions (DDIs). Therefore, clinicians and pharmacists must remain vigilant in identifying potential DDIs to minimize their adverse effects (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In the current study, nearly half of the patients (47.9%) experienced at least one DDI. This prevalence is comparable to findings from studies conducted in South-West Nigeria (47.6%) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and Puducherry, India (48%) DDI(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, higher prevalence were reported in studies from Universitas Airlangga Teaching Hospital, Surabaya, Indonesia (89.06%) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), Addis Ababa, Ethiopia (90.1%) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), and central Gujarat, India (71.5%) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These discrepancies may be attributed to differences in DDI identification tools (Medscape versus Lexicomp Drug Interaction Checker) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), study populations, and clinical settings particularly studies focusing on elderly patients (\u0026gt;\u0026thinsp;60 years) or those with cardiovascular diseases (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, significant-severity DDIs were the most frequently observed, accounting for 85.4% of all identified interactions. Among patients who experienced at least one DDI (n\u0026thinsp;=\u0026thinsp;260), the mean number of DDIs per patient was 3.03. This average number of DDIs per patient is considerably higher than reports from South-West Nigeria (1.3 DDIs per patient) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), and Dessie, Ethiopia (1.6 DDIs per patient) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The observed variation may be attributed to differences in study populations and, more importantly, methodological differences in DDI assessment. For instance, the Nigerian study evaluated interactions only among antihypertensive and antiplatelet medications (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), whereas the current study assessed all medications used by patients, thereby increasing the likelihood of detecting DDIs. With respect to DDI severity, the predominance of significant interactions in the current study is consistent with findings from studies conducted in Indonesia (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), and Dessie, Ethiopia(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), where moderate/significant-severity DDIs were also most common (89.4%). In contrast, studies from central Gujarat, India(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) and Puducherry, India (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), reported a higher proportion of clinically significant DDIs (85.36%). Similarly, a study from Addis Ababa, Ethiopia, conducted among elderly patients with cardiovascular diseases, reported a higher burden of DDI, with 75%, and 83.3% notable proportions of moderate/significant and minor DDIs, respectively (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). These differences may reflect variations in patient age, comorbidity burden, medication complexity, and clinical settings.\u003c/p\u003e \u003cp\u003eThe present study identified enalapril plus metformin as the most frequently observed drug combination associated with DDIs, accounting for 34.2% of all interactions. This combination is known to increase metformin toxicity and elevate the risk of hypoglycemia and lactic acidosis. The second most common interacting pair was amlodipine plus metformin (26.5%), in which amlodipine may reduce the therapeutic effectiveness of metformin through pharmacodynamic antagonism, potentially resulting in poor glycemic control and hyperglycemia. Similarly, studies conducted in central Gujarat (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) and Puducherry, India (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) reported atenolol, aspirin, and amlodipine as the most common medications implicated in DDIs among hypertensive patients.\u003c/p\u003e \u003cp\u003eOverall, the majority of identified DDIs in the current study were classified as clinically significant, highlighting the importance of systematic medication review and close clinical monitoring in patients receiving multiple long-term therapies. Among participants who experienced DDIs (N\u0026thinsp;=\u0026thinsp;260), most interactions had no apparent effect on BP (72.3%); however, 16.9% were associated with a decrease in BP, while 10.8% were associated with an increase in BP. Consistent with previous studies, DDIs in hypertensive patients have been linked to a range of clinically relevant complications, including electrolyte disturbances particularly potassium imbalance (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), increased risk of acute kidney injury (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), interference with blood pressure control (either elevation or reduction of BP) (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), and an increased risk of myopathy (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). These findings further emphasize the critical role of clinicians and pharmacists in proactive DDI screening and individualized patient management.\u003c/p\u003e \u003cp\u003eThe present study demonstrated that the presence of comorbid conditions, a higher number of concurrent medications, and the use of furosemide, metformin, and propranolol were significantly associated with increased odds of drug\u0026ndash;drug interactions (DDIs). In contrast, the use of enalapril, amlodipine, hydrochlorothiazide, and beclomethasone was associated with reduced odds of DDIs. This apparent protective effect may be attributed to the frequent prescription of these agents as monotherapy or in standardized treatment combinations, which limits exposure to complex multidrug regimens and consequently reduces the likelihood of clinically significant interactions. These findings are consistent with reports from studies conducted in Nigeria and India (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), Indonesia (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), and Dessie, Ethiopia (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), all of which identified the number of prescribed medications as a significant predictor of DDIs. Similarly, the presence of comorbidities has been consistently associated with an increased risk of DDIs (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Evidence from previous studies further indicates that polypharmacy markedly elevates the risk of adverse drug reactions (ADRs) and DDIs (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, the occurrence of ADRs in 32.2% of patients underscores the importance of careful regimen optimization and continuous clinical monitoring to ensure treatment safety and effectiveness. The most frequently reported adverse effects were weakness (33.7%), gastric irritation (33.1%), and headache (30.3%). Prior studies have shown that ADRs are a major contributor to non-compliance to antihypertensive therapy, which in turn leads to poor blood pressure control (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In line with the present findings, a study conducted in Gondar, Ethiopia, reported that approximately 20% to 31.1% of patients experienced ADRs, with tiredness, dizziness, and headache being the most common complaints (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the current study, several factors were independently associated with the occurrence of ADRs. These were; increasing age, comorbid conditions, number of concurrent medications, the use of enalapril, nifedipine, and hydrochlorothiazide were significantly associated with a higher risk of ADRs. Increasing age, comorbidities, and a higher number of concurrent medications were significantly associated with an increased risk of ADRs, likely due to age-related pharmacokinetic and pharmacodynamic changes, cumulative drug burden, and a higher likelihood of DDIs(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Additionally, the use of enalapril, nifedipine, and hydrochlorothiazide was linked to a higher ADR risk, possibly reflecting their known adverse effect profiles, including hypotension, dizziness, electrolyte disturbances, and renal impairment, particularly in older patients with multiple comorbidities(\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrength and limitation of the study:\u003c/h2\u003e \u003cp\u003eThis study is done at multicenter which improves generalizability and robustness of its findings. However, the cross-sectional design limits the ability to establish causal relationships, and the reliance on self-reported data may introduce social desirability bias.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates a high burden of DDI and ADR among hypertensive patients. Amlodipine and enalapril were the most commonly prescribed antihypertensive, with clinically important DDIs mainly involving metformin. DDIs were significantly associated with comorbidities, polypharmacy, and use of furosemide, metformin, and propranolol, while enalapril, amlodipine, hydrochlorothiazide. The most common ADR were weakness, gastric irritation and headache. ADRs were significantly associated with age, sex, comorbidities, polypharmacy, and use of enalapril, nifedipine, and hydrochlorothiazide. Overall, these findings underscore the critical need for regular medication review, and close clinical monitoring particularly in patients with multiple comorbidities and concurrent medications to minimize the DDIs and ADRs and improve the safety and quality of hypertension management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization and fund acquisition: Tefera, GM. Supervising, project administration, study design and formal analysis, investigation, methodology: Tefera, GM, Feyisa, BB, Chala, TS \u0026amp; Beressa, TB. Writing\u0026ndash;original draft: Tefera GM. Writing review \u0026amp; editing: Tefera GM, Feyisa BB, Chala, TS \u0026amp; Beressa TB. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst of all, our greatest and an endless gratitude go to our almighty GOD and Ambo University for funding this study. Finally we would like to express our sincere thanks to study participants and all individual who had contributed for realization of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe source of funding for this study was Ambo University, with funding code of CHSRH/R-Phar/03/16. The funder has no role in study design, manuscript preparation and any influence on the result of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflicts of interest in this work. The authors used ChatGPT only for language improvement.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethical approval was received from Ambo University Institutional Research and ethics review committee (AU IRERC) with a letter number of AU/C/H/S/RH/M771/2/17/2024. This study adhered to the principles outlined in the Declaration of Helsinki. The study participants were informed of the study purpose, procedures, benefits potential and risks, confidentiality protections, and their right to withdraw at any time. For the data collected from medical records, no patient identifiers such as names or card numbers were used. Then informed written consent was taken.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data used for this manuscript writing was available within the document and its supplementary materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization and fund acquisition: Tefera, GM. Supervising, project administration, study design and formal analysis, investigation, methodology: Tefera, GM, Feyisa, BB, Chala TS \u0026amp; Beressa, TB. Writing\u0026ndash;original draft: Tefera GM. Writing review \u0026amp; editing: GM, BB, Chala TS \u0026amp; TB. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOrganization WH. Global report on hypertension: the race against a silent killer. 2023.\u003c/li\u003e\n\u003cli\u003eChobufo MD, Gayam V, Soluny J, Rahman EU, Enoru S, Foryoung JB, et al. Prevalence and control rates of hypertension in the USA: 2017\u0026ndash;2018. International Journal of Cardiology Hypertension. 2020;6:100044.\u003c/li\u003e\n\u003cli\u003eAmare F, Hagos B, Sisay M, Molla B. Uncontrolled hypertension in Ethiopia: a systematic review and meta-analysis of institution-based observational studies. BMC Cardiovascular Disorders. 2020;20(1):129.\u003c/li\u003e\n\u003cli\u003eBabirye M, Yadesa TM, Tamukong R, Obwoya PS. Prevalence and factors associated with drug therapy problems among hypertensive patients at hypertension clinic of Mbarara Regional Referral Hospital, Uganda: a| cross-sectional study. Therapeutic Advances in Cardiovascular Disease. 2023;17:17539447231160319.\u003c/li\u003e\n\u003cli\u003eJeemon P, S\u0026eacute;verin T, Amodeo C, Balabanova D, Campbell NRC, Gaita D, et al. World Heart Federation Roadmap for Hypertension - A 2021 Update. Glob Heart. 2021;16(1).\u003c/li\u003e\n\u003cli\u003eSamaila A, Biambo AA, Usman N, Aliyu HH. Drug related problems and implications for pharmaceutical care interventions in hypertensive outpatients in a Nigerian hospital. J Sci Pract Pharm. 2019;5(2):281-6.\u003c/li\u003e\n\u003cli\u003eHussen A, Daba FB. Drug therapy problems and their predictors among hypertensive patients on follow up in Dil-Chora Referral Hospital, Dire-Dawa, Ethiopia. hypertension. 2017;5(7).\u003c/li\u003e\n\u003cli\u003eFekadu G, Adamu A, Gebre M, Gamachu B, Bekele F, Abadiga M, et al. Magnitude and determinants of uncontrolled blood pressure among adult hypertensive patients on follow-up at Nekemte Referral Hospital, Western Ethiopia. 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Global Health Research and Policy. 2024;9(1):46.\u003c/li\u003e\n\u003cli\u003eSubramanian A, Adhimoolam M, Kannan S. Study of drug\u0026ndash;Drug interactions among the hypertensive patients in a tertiary care teaching hospital. Perspectives in Clinical Research. 2018;9(1):9-14.\u003c/li\u003e\n\u003cli\u003eFravel MA, Ernst M. Drug interactions with antihypertensives. Current hypertension reports. 2021;23(3):14.\u003c/li\u003e\n\u003cli\u003eKothari N, Ganguly B. Potential drug-drug interactions among medications prescribed to hypertensive patients. Journal of clinical and diagnostic research: JCDR. 2014;8(11):HC01.\u003c/li\u003e\n\u003cli\u003eSaraswati MD, Ardiana SM, Suprapti B, Assegaf MY, Hamidah KF. Potential Drug-Drug Interactions in Ambulatory Patients with Hypertension: a Retrospective Study. Pharmacy \u0026amp; Pharmaceutical Sciences Journal/Jurnal Farmasi Dan Ilmu Kefarmasian Indonesia. 2022;9(1).\u003c/li\u003e\n\u003cli\u003eFadare JO, Ajayi AE, Adeoti AO, Desalu OO, Obimakinde AM, Agboola SM. Potential drug-drug interactions among elderly patients on anti-hypertensive medications in two tertiary healthcare facilities in Ekiti State, South-West Nigeria. Sahel Medical Journal. 2016;19(1):32-7.\u003c/li\u003e\n\u003cli\u003eFufa F, Mirkano D, Tipathi R. Prescription pattern and potential drug-drug interactions of antihypertensive drugs in a general hospital, South Ethiopia. Cukurova Medical Journal. 2015;40(4):698-706.\u003c/li\u003e\n\u003cli\u003eAdem L, Tegegne GT. Medication appropriateness, polypharmacy, and drug-drug interactions in ambulatory elderly patients with cardiovascular diseases at Tikur Anbessa Specialized Hospital, Ethiopia. Clinical interventions in aging. 2022:509-17.\u003c/li\u003e\n\u003cli\u003eAssefa YA, Kedir A, Kahaliw W. Survey on polypharmacy and drug-drug interactions among elderly people with cardiovascular diseases at Yekatit 12 Hospital, Addis Ababa, Ethiopia. Integrated Pharmacy Research and Practice. 2020:1-9.\u003c/li\u003e\n\u003cli\u003eChelkeba L, Alemseged F, Bedada W. Assessment of potential drug-drug interactions among outpatients receiving cardiovascular medications at Jimma University specialized hospital, South West Ethiopia. Int J Basic Clin Pharmacol. 2013;2(2):144-52.\u003c/li\u003e\n\u003cli\u003eDiksis N, Melaku T, Assefa D, Tesfaye A. Potential drug\u0026ndash;drug interactions and associated factors among hospitalized cardiac patients at Jimma University Medical Center, Southwest Ethiopia. SAGE open medicine. 2019;7:2050312119857353.\u003c/li\u003e\n\u003cli\u003eGobezie MY, Bitew HB, Tuha A, Hailu HG. Assessment of Potential Drug\u0026ndash;Drug Interactions and Their Predictors in Chronic Outpatient Department of Dessie Referral Hospital, Dessie, Northeast Ethiopia. Drug, healthcare and patient safety. 2021:29-35.\u003c/li\u003e\n\u003cli\u003eMedscape. Drug-drug interaction.\u003c/li\u003e\n\u003cli\u003eMasnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC geriatrics. 2017;17(1):230.\u003c/li\u003e\n\u003cli\u003eDrosdowsky A, Gough K. The Charlson Comorbidity Index: problems with use in epidemiological research. Journal of Clinical Epidemiology. 2022;148:174-7.\u003c/li\u003e\n\u003cli\u003eWang J, Ma JJ, Liu J, Zeng DD, Song C, Cao Z. Prevalence and Risk Factors of Comorbidities among Hypertensive Patients in China. Int J Med Sci. 2017;14(3):201-12.\u003c/li\u003e\n\u003cli\u003eLauder L, Mahfoud F, Azizi M, Bhatt DL, Ewen S, Kario K, et al. Hypertension management in patients with cardiovascular comorbidities. European Heart Journal. 2023;44(23):2066-77.\u003c/li\u003e\n\u003cli\u003eAbdisa L, Girma S, Lami M, Hiko A, Yadeta E, Geneti Y, et al. Uncontrolled hypertension and associated factors among adult hypertensive patients on follow-up at public hospitals, Eastern Ethiopia: A multicenter study. SAGE open medicine. 2022;10:20503121221104442.\u003c/li\u003e\n\u003cli\u003eNaseri MW, Esmat HA, Bahee MD. Prevalence of hypertension in Type-2 diabetes mellitus. Annals of Medicine and Surgery. 2022;78.\u003c/li\u003e\n\u003cli\u003eGobezie MY, Hassen M, Tesfaye NA, Solomon T, Demessie MB, Fentie Wendie T, et al. Prevalence of uncontrolled hypertension and contributing factors in Ethiopia: a systematic review and meta-analysis. Frontiers in Cardiovascular Medicine. 2024;Volume 11 - 2024.\u003c/li\u003e\n\u003cli\u003eAlkhalid Z, Birand N. Determination and comparison of potential drug\u0026ndash;drug interactions using three different databases in northern cyprus community pharmacies. Nigerian Journal of Clinical Practice. 2022;25(12):2005-9.\u003c/li\u003e\n\u003cli\u003eGebreyohannes EA, Bhagavathula AS, Abebe TB, Tefera YG, Abegaz TM. Adverse effects and non-adherence to antihypertensive medications in University of Gondar Comprehensive Specialized Hospital. Clinical hypertension. 2019;25(1):1.\u003c/li\u003e\n\u003cli\u003eHabtegiorgis A, Edin A, Lemma K, Utura T, Girma D, Getachew D, et al. Determinants of uncontrolled blood pressure among adult hypertensive patients on follow-up at Negelle and Adola General Hospital, Guji Zone, Southern Ethiopia: facility-based case control study. BMC Public Health. 2024;24(1):2971.\u003c/li\u003e\n\u003cli\u003eDagnew SB, Moges TA, Ayele TM, Wondm SA, Yazie TS, Dagnew FN. Adverse drug reactions and its associated factors among geriatric hospitalized patients at selected comprehensive specialized hospitals of the Amhara Region, Ethiopia: a multicenter prospective cohort study. BMC geriatrics. 2024;24(1):955.\u003c/li\u003e\n\u003cli\u003eRodriguez-Espeso EA, Verdejo-Bravo C, Cruz-Jentoft AJ. [Adverse drug reactions in older adults: A review of epidemiology, risk factors and prevention strategies]. Rev Esp Geriatr Gerontol. 2025;60(5):29.\u003c/li\u003e\n\u003cli\u003eAlhawassi TM, Krass I, Pont LG. Antihypertensive-related adverse drug reactions among older hospitalized adults. Int J Clin Pharm. 2018;40(2):428-35.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hypertension, Drug-drug interaction, adverse drug reaction, Polypharmacy, predictors, Medscape, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-8527897/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8527897/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHypertensive patients are at high risk of adverse drug interaction (ADR) and drug-drug interaction (DDI) because of high tendency to use multiple drugs; this can undermine the quality of patients\u0026rsquo; care. The aim of the study was to assess the magnitude of ADR, DDI, and their determinants among adult hypertensive patients at selected hospitals in Ethiopia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA hospital-based cross-sectional study was conducted using chart reviews and patient interviews. DDIs were identified and classified using the Medscape online DDI checker. Written informed consent was obtained, and multivariate logistic regression was performed with statistical significance at p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong a total of 543 hypertensive patients ADR was reported in 32.2%, with the most common being weakness (33.7%), followed by gastric irritation (33.1%), and headache (30.3%). Nearly half of the patients (47.9%) experienced at least one DDI. A total of 789 DDIs with mean of 3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22 was identified in the study participants. Enalapril plus metformin was found as the most common contributing for DDI. Multivariable logistic regression analysis showed that patients with comorbid conditions, (AOR\u0026thinsp;=\u0026thinsp;2.42; 95%CI: 1.25\u0026ndash;4.67; p\u0026thinsp;=\u0026thinsp;0.008), increasing number of concurrent medications use (AOR\u0026thinsp;=\u0026thinsp;6.93; 95%CI: 4.50\u0026ndash;10.69; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), use of furosemide (AOR\u0026thinsp;=\u0026thinsp;14.42; 95%CI: 4.38\u0026ndash;47.48; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), metformin (AOR\u0026thinsp;=\u0026thinsp;23.57; 95%CI: 7.53\u0026ndash;73.72; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and propranolol (AOR\u0026thinsp;=\u0026thinsp;7.56; 95%CI: 1.12\u0026ndash;50.61; p\u0026thinsp;=\u0026thinsp;0.037) were significantly associated with higher odds of DDI. Increasing age (AOR\u0026thinsp;=\u0026thinsp;1.017; 95%CI: 1.000\u0026ndash;1.034; p\u0026thinsp;=\u0026thinsp;0.044) and presence of comorbid conditions (AOR\u0026thinsp;=\u0026thinsp;1.506; 95%CI: 1.001\u0026ndash;2.264; p\u0026thinsp;=\u0026thinsp;0.049) as well as, the use of enalapril (AOR\u0026thinsp;=\u0026thinsp;1.751; 95%CI: 1.143\u0026ndash;2.683; p\u0026thinsp;=\u0026thinsp;0.010), nifedipine (AOR\u0026thinsp;=\u0026thinsp;2.359; 95%CI: 1.013\u0026ndash;5.492; p\u0026thinsp;=\u0026thinsp;0.047), hydrochlorothiazide (AOR\u0026thinsp;=\u0026thinsp;1.712; 95%CI: 1.112\u0026ndash;2.635; p\u0026thinsp;=\u0026thinsp;0.015) and increased number of concurrent medications (AOR\u0026thinsp;=\u0026thinsp;1.287; 95%CI: 1.091\u0026ndash;1.519; p\u0026thinsp;=\u0026thinsp;0.003) were significantly associated with higher odds of ADRs.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study found a high prevalence of DDI and ADR; with nearly half experiencing DDIs and about one-third reporting ADRs with different independent predictors. These findings highlight the need for regular medication review and close clinical monitoring to improve medication safety and optimize hypertension management.\u003c/p\u003e","manuscriptTitle":"Drug-drug interaction, adverse drug reaction and their determinants among adult hypertensive patients; Multicenter study in Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-06 17:05:50","doi":"10.21203/rs.3.rs-8527897/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"94082145-1e3b-4669-9bfd-2140dbd7107f","owner":[],"postedDate":"February 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T13:25:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-06 17:05:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8527897","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8527897","identity":"rs-8527897","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}