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INTRODUCTION
Heart-related illnesses are often referred to as Cardiovascular Disease (CVD). Heart attacks and heart failure are caused by the high levels of fatty tissue blocking the coronary arteries.1
The World Health Organization (WHO) estimates that approximately 17.3 million people worldwide die each year from cardiovascular disease, and that number will rise to 23 million by the year 2030.2 The underlying blood vessel illness frequently has no symptoms. A heart attack or stroke could be the initial symptom of a hidden illness. Heart attack signs and symptoms include Chest pain or discomfort in the middle; and/or arm, left shoulder, elbow, jaw, or back pain or discomfort. Sudden weakness of the face, arm, or leg, usually on one side of the body, is the most typical sign of a stroke. Other signs include severe headache with no apparent cause, numbness of the face, arm, or leg, particularly on one side of the body; confusion; difficulty speaking or understanding speech; difficulty seeing with one or both eyes; difficulty walking; dizziness and/or loss of balance or coordination; and/or fainting or unconsciousness.3
Drug Related Problems (DRPs) is a situations involving pharmacological therapy that interferes with expected health outcomes either directly or indirectly. DRPs are the results of unmet needs. DRPs can happen for a variety of reasons, including improper drug choice, improper drug interaction, or the use of unproven medication in place of proven therapy. A fundamental component of pharmacological treatment has been described as the discovery, resolution, and prevention of DRPs.4,5 The PCNE classification system is the most widely used and, because it is regularly updated and changed, offers higher practicability and internal consistency. V9.1 is the most recent version. PCNE has a number of domains, including issue domains, drug-related problem causes, planned intervention domains, and problem status domains. Hospitalized patients are more likely to experience DRPs, which can raise expenses and patient morbidity and death. Hospitalized patients had DRPs almost three times more frequently than outpatients with CVD.6
According to the World Health Organization (WHO) Health Related Quality of Life (HRQoL) is described as “a wide notion affected in a complicated way by the person’s physical condition, psychological state, level of independence, and social relationships. Among CVDs, quality of life can be regarded as the most crucial healthcare outcome. In every disease management strategy, Quality of Life is seen as a significant result, according to the definition of health. One of the key goals of the health care system is to enhance and sustain health-related quality of life.7
MATERIALS AND MATERIALS
Study Site
The study was conducted in cardiac inpatients of the cardiology department at Vivekananda General Hospital, Hubballi.
Study Participants
Patients of either gender with an age of more than 18 years diagnosed with CVD and admitted to the Department of Cardiology at Vivekananda General Hospital were included in the study. We have excluded pregnant women with CVD from this study.
Study tool
A suitable data collection form was designed, and necessary data were collected from the patient’s case notes. DRP’s in cardiac patients were evaluated by using the PCNE tool 9.1 version. The health-related quality of life was measured by using SF-36 questionnaire in cardiac patients was documented in the data collection form and analyzed systematically.
RESULTS
Distribution of study subjects based on demographic details
Total of 210 subjects enrolled in the study of which 128 were male (61.0%) and 82 were female (39.0%). The subjects were categorized into age groups. Age group 61-70 years were in majority accounting for 60 (28.57%) and age group 21-30 years were minimal in number 5 (2.38%). Among subjects, 43 (20.48%) were smokers, 56 (26.67%) were alcoholics, 24 (11.43%) engaged in both drinking and smoking and 59 (28.09%) subjects were involved in chewing gutka. In our study most commonly seen co-morbidities were HTN 65 (40.123%), and Diabetic mellitus 58 (35.802%). The study subjects were categorised based on employment status, Employed were 153 and Unemployed were 57.
In this study 116 (55.23%) belong to Rural residences and 94 (44.76%) belong to Urban residences. Subjects were categorized based on marital status and were divided according to their BMI. 76 subjects stayed for longer periods and 37 were for shorter periods stayed in hospital. And in this study subjects were classified based on socioeconomic status such as Upper class, upper middle class, lower class and lower middle class, as shown in the Table 1.
| Demographic Details | Frequency (N) | Percentage (%) |
|---|---|---|
| Gender | ||
| Male | 128 | 61.0% |
| Female | 82 | 39.0% |
| Age | ||
| 21-30 | 5 | 2.38% |
| 31-40 | 23 | 10.95% |
| 41-50 | 44 | 20.95% |
| 51-60 | 45 | 21.43% |
| 61-70 | 60 | 28.57% |
| 71-80 | 27 | 12.86% |
| 81-90 | 6 | 2.86% |
| Social habits | ||
| Alcoholic | 56 | 26.67% |
| Smoking | 43 | 20.48% |
| Alcoholic+Smoking | 24 | 11.43% |
| Chewing gutka | 59 | 28.09% |
| No social habits | 28 | 13.33% |
| Comorbidities (162) | ||
| Hypertension (HTN) | 65 | 40.12% |
| Diabetes mellitus (DM) | 58 | 35.80% |
| Ischemic heart disease (IHD) | 6 | 3.70% |
| Rheumatic heart disease (RHD) | 1 | 0.61% |
| Tuberculosis (TB) | 1 | 0.61% |
| Appendicitis | 1 | 0.61% |
| Hypothyroidism | 10 | 6.17% |
| Chronic obstructive pulmonary disease (COPD) | 15 | 9.25% |
| Pulmonary edema | 5 | 3.08% |
| Residence | ||
| Rural | 116 | 55.23% |
| Urban | 94 | 44.76% |
| Marital status | ||
| Married | 156 | 74.3% |
| Unmarried | 25 | 11.9% |
| Widow | 29 | 13.8% |
| Body Mass Index | ||
| Normal weight (18.5-24.9) | 70 | 33.33% |
| Obesity-class 1(30.0-34.9) | 80 | 38.09% |
| Obesity-class 2(35.0-39.9) | 34 | 16.19% |
| Pre-obesity(25.0-29.9) | 10 | 4.76% |
| Under weight (below 18.5) | 16 | 7.61% |
| Socioeconomic status | ||
| Upper class | 8 | 3.80% |
| Upper middle class | 37 | 17.61% |
| Lower class | 76 | 36.19% |
| Lower middle class | 89 | 42.38% |
| Duration of hospital stay | ||
| 1-4 days | 37 | 17.61% |
| 5-10 days | 53 | 25.23% |
| 10-15 days | 76 | 36.19% |
| >15 days | 44 | 20.95% |
Drug related problems in the study population
Among 210 subjects, 520 DRPs were identified in the 205 patients. Out of 520 DRP’s, 89 (17.1%) were Problem-Related, 257 (49.4%) Cause-Related, 85 (16.3%) Interventions, 53 (10.1%) Acceptance of Interventions, and 36 (6.9%) Outcomes of intervention results, Table 2.
| Code | Primary domain | Frequency | |
|---|---|---|---|
| Problem | P | 89(17.1%) | |
| P1.3 | Untreated symptoms or indication. | 66 | |
| P2.1 | Adverse drug events (side effects). | 23 | |
| Causes | C | 257 (49.4%) | |
| C2 | Drug Selection. | 32 | |
| C4 | Treatment duration. | 22 | |
| C5 | Dispensing | 30 | |
| C6 | Drug use process. | 26 | |
| C7 | Patient Related | 42 | |
| C9.2 | Drug interaction | 105 | |
| Planned intervention | I | 85 (16.3%) | |
| I1.1 | Prescriber informed only. | 10 | |
| I1.2 | Prescriber asked for information. | 8 | |
| I2.1 | Patient counselling | 30 | |
| I2.4 | Spoken to family member | 12 | |
| I3.2 | Dosage changed to | 10 | |
| I3.5 | Drug paused/stopped | 7 | |
| I3.6 | Drug started | 8 | |
| Intervention acceptance | A | 53 (10.1%) | |
| A1.1 | Intervention accepted and fully implemented. | 10 | |
| A1.2 | Intervention accepted partially implemented. | 5 | |
| A1.3 | Intervention accepted but not implemented. | 20 | |
| A1.4 | Intervention accepted implementation unknown. | 18 | |
| Outcome of Intervention | O | 36(6.9%) | |
| O0.1 | Problem status unknown. | 7 | |
| O1.1 | Problem totally solved. | 4 | |
| O2.1 | Problem partially solved. | 5 | |
| O3.1 | Problem not solved lack of cooperation of patients. | 7 | |
| O3.2 | Problem not solved lack of cooperation of prescriber. | 5 | |
| O3.3 | Problem not solved intervention not effective. | 8 | |
| Total | 520 |
Drug interactions in the study population
It was observed that 105 Drug interactions were more common among 520 DRPs, which includes 29 (27.61%) major drug interactions, 65 (61.90%) moderate drug interactions and 11 (10.47%) minor drug interactions as shown in Table 3.
| Sl. No. | Interacting drugs | Effect | Severity | No. of patients (N) | Monitoring parameters |
|---|---|---|---|---|---|
| 1 | Aspirin+clopidogrel | Increased bleeding. | Major | 9 (8.57%) | Monitor bleeding closely. |
| 2 | Aspirin+prasugrel | Increased bleeding. | Major | 10 (9.52%) | Monitor bleeding closely. |
| 3 | Amlo dipine+clopidogrel | Decreased anti- platelet effect. | Major | 10 (9.52%) | Monitor clopidogrel efficacy. |
| 4 | Digoxin+metoprolol | Increased risk of bradycardia. | Moderate | 20 (19.04%) | Monitor HR, bradycardia. |
| 5 | Digoxin+ furosemide | Increased risk of digoxin toxicity (nausea, vomiting). | Moderate | 30 (28.57%) | Monitor potassium levels. |
| 6 | Enalapril+metformin | Increase hypoglycemia. | Moderate | 15(14.28%) | Dose adjustment needed. |
| 7 | Aspirin+hydrocortisone | Increased risk of GI ulceration. | Minor | 11(10.47%) | Monitor the patients. |
Untreated symptoms or indications in the study population
The untreated symptoms or indications in the study population were diarrhoea 17 (25.7%), cough 10 (15.15%), fever 8 (12.12%), abdominal pain 10 (15.15%), pain 11 (10.47%) and vomiting/ nausea 10 (15.15%). As shown in the Table 4.
| Sl. No. | Indication | No. of patients (N) |
|---|---|---|
| 1 | Diarrhea | 17 (25.7%) |
| 2 | Vomiting/Nausea | 10 (15.15%) |
| 3 | Fever | 8 (12.12%) |
| 4 | Abdominal pain | 10 (15.15%) |
| 5 | Cough | 10 (15.15%) |
| 6 | Pain | 11 (10.47%) |
| Total | 66 |
Adverse drug reaction in the study population
In our study population, we identified total of 23 ADRs in which a combination of Digoxin and Spironolactone induces gynecomastia 4 (17.39%), Amlodipine induced bilateral pitting oedema 5 (21.73%), Cephalosporin induced erythematous patch 2 (8.69%) and Atorvastatin induced myalgia 12 (52.17%), as shown in the Table 5.
| Sl. No. | ADR occurred | No. of ADR in patients | Percentage of ADR (%) | Drug causing ADR |
|---|---|---|---|---|
| 1 | Gynecomastia | 4 | 17.39% | Spironolactone+ Digoxin |
| 2 | Bilateral pitting edema | 5 | 21.73% | Amlodipine |
| 3 | Erythematous | 2 | 8.69% | Cephalosporin |
| 4 | Myalgia | 12 | 52.17% | Atorvastatin |
| Total | 23 |
Treatment duration in the study population
In our study population we identified 15 DRPs that were associated with treatment duration. Short duration were Levofloxacin 2 (13.3%), enoxaparin 9 (60%), and PCT 4 (26.6%), And long duration drugs were, Tramadol 4 (57.14%) and Meropenem 3 (42.85%) were recommended the treatment duration for more than 10 days, as shown in the Table 6.
| Sl. No. | Duration of treatment too short | No. of patients (%) | Prescribed duration (days) | Duration of treatment according to standard guidelines |
|---|---|---|---|---|
| 1 | Levofloxacin | 2(13.3%) | 3-5 | >7 |
| 2 | Enoxaparin | 9(60%) | 3-5 | >7 |
| 3 | PCT | 4(26.6%) | 3-5 | >7 |
| Total | 15 | |||
| Duration of treatment too short | ||||
| 1 | Tramadol | 4(50%) | 11-14 | <7 |
| 2 | Meropenem | 3(50%) | 14-15 | ≥7 |
| Total | 7 |
DRPs in Drug Dispensing
In our study, we analysed that a total number of 30 DRPs were related to the Drug Dispensing occurred, as shown in Table 7.
| Sl. No. | Causes | Number (%) |
|---|---|---|
| 1 | Prescribed drug not available | 22 (73.33%) |
| 2 | Necessary drug information not provided | 3 (10%) |
| 3 | Wrong drug prescribed | 5 (16.66%) |
| Total | 30 |
DRPs in Patient Related Domain
A total of 42 DRPs were found in Patient-Related Domain, which were either consciously or mistakenly carried out by patients as seen in the Table 8, 12 (28.57%) patients received their dosages at the incorrect times, 20 (47.61%) patients used their medications incorrectly, and 10 (23.08%) patients improperly stored their medications, as shown in the Table 8.
| Sl. No. | Patient related problem | Number (%) |
|---|---|---|
| 1 | Drug taken inappropriately | 12 (28.57%) |
| 2 | Drug taken in wrong way | 20 47.61%) |
| 3 | Drug stored inappropriately | 10 (23.80%) |
| Total | 42 |
DRPs in Intervention Domain
Distribution of planned intervention based on PCNE classification, as shown in Table 9.
| Code | Intervention | Number (%) |
|---|---|---|
| I1.1 | Prescriber informed only | 10 (11.76%) |
| I1.2 | Prescriber asked for information | 8 (9.41%) |
| I2.1 | Patient counseling | 30 (35.29%) |
| I2.4 | Spoken to family member | 12 (14.11%) |
| I3.2 | Dosage changed to | 10 (11.76%) |
| I3.5 | Drug paused/stopped | 7 (8.23%) |
| I3.6 | Drug started | 8 (9.41%) |
| Total | 85 |
DRPs in the Intervention Acceptance Domain
In this study, DRPs in the Intervention Acceptance Domain according to PCNE classification have a proportion of 50% acceptance. Our study showed the results as 18.86% of Interventions accepted and fully implemented (N=10), 9.43% Intervention accepted partially implemented (N=5), 37.73% (N=20) of Intervention accepted but not implemented and 33.96% (N=18) Intervention accepted but implementation is unknown, as shown in the Table 10.
| Code | Acceptance | Number (%) |
|---|---|---|
| A1.1 | Intervention accepted and fully implemented. | 10 (18.86%) |
| A1.2 | Intervention accepted partially implemented. | 5 (9.43%) |
| A1.3 | Intervention accepted but not implemented. | 20 (37.73%) |
| A1.4 | Intervention accepted implementation unknown. | 18 (33.96%) |
| Total | 53 |
DRPs in Intervention Outcome Domain
By evaluating the Intervention outcome domain of PCNE classification, 11.11% (N=4) problem totally solved, 13.88% (N=5) problem was not solved due to the lack of cooperation of prescriber, 13.88% (N=5) Problem partially solved, 27.77% (N=10) problem not solved due to lack of cooperation of patients, 13.88% (N=5) problem not solved in patients as the intervention provided was not effective and 19.44% (N=7) problem status, as shown in the Table 11.
| Code | Outcome of intervention | Number (%) |
|---|---|---|
| O0.1 | Problem status unknown. | 7 (19.44%) |
| O1.1 | Problem totally solved. | 4 (11.11%) |
| O2.1 | Problem partially solved. | 5 (13.88%) |
| O3.1 | Problem not solved lack of cooperation of patients. | 10 (27.77%) |
| O3.2 | Problem not solved, lack of cooperation of Prescriber. | 5 (13.88%) |
| O3.3 | Problem not solved intervention not effective. | 5 (13.88%) |
| Total | 36 |
Health related quality of life
Correlation of Age with Health-Related Quality of Life in the study population
Correlation of Age with PCS
The test revealed significant correlation between age in Physical functioning (p=0.000), Role limitation due to physical health (p=0.000), General Health (p=0.000) and Pain (p=0.08) as shown in Table 12.
| PF | RLPF | GH | Pain | Energy/fatigue | EW-B | SF | RLEP | |
|---|---|---|---|---|---|---|---|---|
| Kruskal-Wallis H | 32.304 | 29.3 | 33.763 | 17.426 | 18.209 | 24.492 | 8.328 | 26.882 |
| Df | 6 | 6 | 6 | 6 | 6 | 6 | 6 | 6 |
| Asymp. Sig. | 0.000* | 0.000* | 0.000* | 0.008* | 0.006* | 0.000* | 0.215 | 0.000* |
Correlation of Age with MCS
The test revealed a significant correlation between age in Energy/fatigue (p=0.006), Emotional well-being (p=0.000), Role limitation due to emotional problems (p=0.000) and an insignificant correlation of age in functioning (p=0.215) as shown in Table 12.
Correlation of Gender with MCS HRQoL employing Mann-Whitney U test in the study population
Physical Component Summary (PCS)
Comparing each domain and demographic factors using Mann Whitney U-Test.
There was a negative correlation between gender and Role limitation due to physical function, General health and pain component of HRQoL but there was a significant correlation in the physical function domain of HRQoL.
Mental Component Summary
Comparing each domain of MCS and demographic factors by using Mann Whitney U-Test.
There was an insignificant correlation between the gender and MCS of HRQoL.
DISCUSSION
The prospective study was conducted for 6 months attending inpatients Department of Cardiology Vivekananda General Hospital which is a 500-bed multispecialty tertiary care teaching hospital in Hubballi. A total of 210 patients were enrolled in this study based on inclusion and exclusion criteria of which 128 were male and 82 were female.
The mean age of the study population was found to be 58.62±26.02. Subjects with age group of 61-70 years were in the majority accounting for 28.57% (N=60) of the total population and the age group 21-30 years were minimal accounting for 2.38% (N=5). Contrary to the study conducted by M. Reshma et al.,8 subjects with age group of 41-50 years and 51-60 years were in the majority and subjects greater than 80years were minimal in number
In this study out of 210 subjects, 43 were engaged in habits such as smoking, 56 were alcoholics, 59 were involved chewing gutka and 24 were indulged in both drinking alcohol and smoking. A similar study was conducted by Bibirsa Sefera et al.,9 where 31 were alcoholic, 38 were smokers and 62 were involved in khat chewing.
In this study, the most commonly seen comorbidities were HTN (65) and DM (58) whereas the least found comorbidities were RHD (1), TB (1), Appendicitis (1). The other comorbidities found in the subjects were COPD (15), Hypothyroidism (10), Pulmonary edema (5). A similar study by conducted by Asmita et al., which revealed the similar results.
In our study, we classified the subjects based on the employment status such as employed and unemployed. Out of 210 subjects, employed category included 43 subjects and unemployed category included 67 subjects. A study by Bibirsa Sefera et al.,9 showed contradictory results that is unemployed category included 34 subjects and employed category included 203 subjects.
In our study 118 (56.2%) subjects were from rural area and 92 (44%) subjects were from urban area. Similar results were revealed by Bibirsa Sefera et al.,9 Whereas the study conducted by Aikaterini et al., revealed, 62 (77.5%) subjects were from urban area and 18(22.5%) were from rural area.
Among 210 study subjects 156 (74.3%) were married, 25 (11.9%) were unmarried and 29 (13.8%) were widows. Similar result was shown by Bibirsa Sefera et al. study.9
In the current study out of 210 study subjects, 16 belongs to under-weight, 70 had normal weight, 80 belonged to the obesity class-1, 34 belongs to obesity class-2 and 10 belongs to pre-obesity class. A study Francisco Lopez-Jimenez et al.,10 revealed the similar results
Out of 210 study subjects, 53 stayed up to 5-10 days, 76 stayed up-to 10-15 days, 37 stayed 1-4 days and 44 stayed for more than 15 days. A study conducted by M. Reshma et al.,8 showed 81 stayed for 1-3 days, 51 stayed for 4-6 days and 18 stayed for more than 6 days.
Among 210 subjects, 205 subject profile were identified with 519 DRP’s, which included 166 drug interaction, 36 problem related, 147 causes related, a total of 50 interventions were found and accepted, so the outcome of the intervention is 50. A study by Bibirsa Sefera et al.,9 revealed that out of 237 study subjects, 157 were problem-related, 327 were causes related, a total of 408 interventions were found and 158 were accepted.
Overall 520 DRP’s were identified and the most commonly reported were drug interactions 105, followed by ADRs 23, incomplete drug treatment despite existing indication 66 and DRP’s associated with treatment duration i.e. treatment duration too short 15, treatment duration too long 7, our findings were similar to the findings reported by Biradar S.M et al.11
The significances levels of DRP’s were analysed based on three severity criteria; major, moderate, minor. DRP’s with major severity is considered as serious problems which requires interventions (prevent or address), while moderate severity are those problems which necessitate adjustment and improve the effectiveness of the drug therapy, whereas minor is considered as problems requiring small adjustments.
In the current study 105 drug interactions were most common among 520 DRP’s, which accounts 29 (27.61%) major drug interactions, 65 (61.90%) moderate drug interactions, 11(10.47%) minor interactions. A study by Biradar S.M et al.,11 reported 140 drug interactions among 208 DRP’s, which included 70 (50%) major drug interaction, 54(38.5%) moderate drug interactions and 16 (11.4%) minor drug interactions.
In our study, we observed that the subjects with Cardiovascular disease (CVD) are more prone to DRP’s followed by different types of cancers, DM and respiratory tract infection. This may be because CVD needs long term treatments and is frequently associated with co-morbidities and complications which ultimately lead to multiple drug administration and thus predispose to DRP’s. A similar study was conducted by Biradar S.M et al.,11 which showed that CVD patients are at high risk of developing DRP’s.
The current study demonstrated the negative correlation between gender and role limitation due to physical function, General health and pain component of HRQoL, but there is significant correlation in physical function domain of HRQoL. There is insignificant correlation between the gender and MCS of HRQoL. Our findings were similar to the findings of Chatzinikolaou A et al.7
In our study to evaluated the difference across domains of HRQoL with preference to age grouping in CVD subjects using Kruskal Wallis Test. The test revealed significant correlation of age in Physical functioning, Role limitation due to physical health, General health. The test also revealed significant correlation of age in Energy/fatigue, Emotional well-being and Role limitation due to emotional problems, whereas insignificant correlation between age in Social functioning. A similar study was conducted by Chatzinikolaou A et al.,7 which reported the significant main effects of age on physical limitation, emotional limitation and pain.
CONCLUSION
We found 520 DRP’s among 210 study subjects which included 17.1% problem-related, 49.4% cause-related, 16.3% related to planned intervention, 10.1% related to acceptance of intervention and 6.9% were outcome of intervention. Thus the therapeutic outcome of the patient can be improved by early detection and documentation of DRP’s.
Through statistical analysis, we identified a correlation between demographics and HRQoL, where we found a significant correlation between the genders in PF but there was insignificant correlation between gender and other domains of the PCS such as RLPH, GH and Pain. Also insignificant difference was observed between genders with MCS of HRQoL. Whereas PF, RLPF, Pain and GH, EW-B and RLEP show significant differences between the age but insignificant in social functioning. While comparing age and final diagnosis we found that patients of above 60 years of age were seen with chronic cardiovascular disease.