The study analyzed data from a total of 310 elderly patients who were admitted to the Inpatient and attended the Outpatient departments of Yenepoya Medical College and Hospital. The demographic characteristics of the study population are summarized in Table 1: The mean age of the study participants was 70.25 years, with a standard deviation of 5.56 years. The age of the patients ranged from 31 to 92 years, indicating a wide age distribution within the sample. Out of the 310 participants, 122 (39.4%) were female, and 188 (60.6%) were male. The study had a higher representation of male participants compared to females. The majority of the participants fell within the age group of 66–70 years, comprising 35.8% of the total sample. This was followed by the age groups of 71–75 years (24.2%), 60–65 years (22.3%), 76–80 years (13.9%), and 81 years and above (3.9%), respectively. The distribution indicates a predominance of participants in the middle to older age brackets. A significant proportion of the study participants (86.1%) were admitted to the Inpatient ward, while the remaining 13.9% sought medical care from the Outpatient department. This suggests a higher prevalence of polypharmacy and associated conditions among hospitalized elderly patients compared to those receiving outpatient care.
Figure 1 illustrates the distribution of drug interactions observed among the elderly patients included in the study. The majority of patients experienced varying degrees of drug interactions, with the most common occurrences being 6 drug interactions (52), followed by 3 drug interactions (42) and 4 drug interactions (34). Smaller proportions of patients experienced 1, 2, 5, 7, 8, 9, and 10 drug interactions, with frequencies ranging from 1 to 52 cases. Overall, the findings highlight the prevalence of polypharmacy-related drug interactions among the elderly population, underscoring the need for careful medication management and monitoring to mitigate potential adverse effects and optimize therapeutic outcomes.
Table 1 Demographic characteristics of study participants
Variables
|
Frequency (n)
|
Percentage (%)
|
Age group
60-65 years
66-70 years
71-75 years
76-80 years
81 and above
|
69
111
75
43
12
|
22.3
35.8
24.2
13.9
3.9
|
Gender
Male
Female
|
188
122
|
60.6
39.4
|
In-Patient
|
267
|
86.1
|
Out-Patients
|
43
|
13.9
|
Figure 2 illustrates the distribution of drug interactions among the study participants based on severity levels. Among the study participants, 67 (21.6%) patients experienced mild drug interactions. Mild drug interactions are typically characterized by minor symptoms or discomfort that do not significantly impact the patient's health or require medical intervention. The majority of patients, comprising 155 (50.0%) individuals, experienced moderate drug interactions. Moderate drug interactions are characterized by symptoms that may require medical attention or intervention but are not life-threatening. A subset of patients, totaling 88 (28.4%) individuals, experienced severe drug interactions. Severe drug interactions are characterized by significant symptoms or complications that may pose a threat to the patient's health and require immediate medical intervention or discontinuation of the offending medication. Overall, the results provide insights into the distribution of drug interactions among the study participants, highlighting the varying severity levels of drug interactions experienced within the elderly population. These findings underscore the importance of vigilant monitoring and management of medication-related adverse events to ensure patient safety and optimize therapeutic outcomes.
Figure 3 illustrates the distribution of drug interactions among patients with polypharmacy, categorized by less than 5 drugs prescribed. The bar chart visually demonstrates the comparison between instances of drug interactions among patients with polypharmacy of less than 5 drugs and those with polypharmacy of greater than 5 drugs. The red bar indicating cases of lesser polypharmacy and the yellow bar representing cases of greater polypharmacy. The red bar represents instances where patients were prescribed less than 5 drugs. According to the data, 11 patients fell into this category. The green bar represents instances where patients were prescribed greater than 5 drugs.
Figure 4 visualizes the distribution of drug interactions among patients with polypharmacy, categorized by greater than or equal to 5 drugs prescribed. The yellow bar corresponds to cases of greater polypharmacy (greater than or equal to 5 drugs). According to the data, 281 patients fell into this category and the red bar corresponds to cases of lesser polypharmacy (less than 5 drugs).
Figure 5 illustrates the distribution of drug interactions among patients with polypharmacy, categorized by less than 9 drugs prescribed. The red bar corresponds to cases of lesser polypharmacy (less than 9 drugs). According to data, 39 patients fell into this category; while the pink bar corresponds to cases of greater polypharmacy (greater than 9 drugs).
Figure 6 depicts the distribution of drug interactions among patients with polypharmacy, categorized by greater than 9 drugs prescribed. The brown bar corresponds to cases of greater polypharmacy (greater than 9 drugs). According to data, 214 patients fell into this category. while the green bar corresponds to cases of lesser polypharmacy (less than 9 drugs).
Figure 7 illustrates the distribution of Specific drugs prescribed for the management of various co-morbidities. Most frequently prescribed drugs were pantoprazole (222), aspirin (96), metformin (85), frusemide (85), and atorvastatin (81).
Table 2 Age and the number of drugs prescribed at treatment.
Correlation coefficient
|
Chi-squared
|
Degrees of freedom (df)
|
p-value
|
0.8978203
|
536.2
|
486
|
0.05718
|
Significant value <0.05; Correlation test; Chi-square test
Table 3 shows the age and number of drugs prescribed at treatment. The correlation coefficient between age and the number of drugs prescribed at treatment is approximately 0.8978203. This indicates a strong positive correlation between these two variables. A correlation coefficient of 1 represents a perfect positive correlation, and a coefficient of -1 represents a perfect negative correlation. In this case, a coefficient close to 1 suggests that as age increases, the number of drugs prescribed at treatment tends to increase as well. Based on the chi-squared test results, the p-value is 0.05718, which is slightly below the typical significance level of 0.05. This suggests that there is a borderline association between age and the number of drugs prescribed at treatment. While the association is not statistically significant at the conventional threshold, it indicates a potential relationship between age and the number of drugs prescribed, warranting further investigation.
Table 3 Age and the number of drugs prescribed at discharge.
chi-squared
|
Degrees of freedom (df)
|
p-value
|
447.88
|
486
|
0.8915
|
Significant value <0.05; Chi-square test
Table 3 illustrates the age and the number of drugs prescribed at discharge. The p-value (0.8915) is significantly greater than the typical significance level of 0.05. This suggests that there is no statistically significant association between age categories and the number of drugs prescribed at discharge. In other words, based on the chi-squared test, there is no evidence to suggest an association between age categories and the number of drugs prescribed at discharge.
Table 4 Gender vs. number of drugs prescribed at treatment.
t
|
95% CI
|
Degrees of freedom (df)
|
p-value
|
2.1083
|
0.0696 - 2.1339
|
156.99
|
0.03659
|
Significant value <0.05; t-statistic test
Table 4 shows gender vs. number of drugs prescribed at treatment. There is a statistically significant difference in the number of drugs prescribed at treatment between females and males. The mean number of drugs prescribed for females is approximately 13.1087, while the mean number of drugs prescribed for males is approximately 12.0070. The 95 percent confidence interval suggests that the true difference in means between the two groups is likely to fall between 0.0696 and 2.1339. The p-value of 0.03659 is less than the typical significance level of 0.05, indicating the statistical significance of the difference.
Table 5 Drug interactions vs. number of drugs prescribed at treatment.
Source
|
Degrees of freedom (df)
|
Sum of Squares
(Sum Sq)
|
Mean Square
(Mean Sq)
|
F value
|
p-value
(Pr (>F))
|
Drug Interactions
|
9
|
461
|
51.22
|
4.205
|
4.77e-05
|
Residual sum of squares
|
229
|
2790
|
12.18
|
|
|
Significant value <0.05; ANOVA test
Table 5 shows drug interactions vs. number of drugs prescribed at treatment. There is a highly significant difference in the means of "Number of drugs prescribed at treatment" among different levels of "Drug Interactions." The small p-value (4.77e-05) associated with the F-statistic suggests that the observed differences in means are highly unlikely to occur by chance. This indicates that the number of drug interactions significantly affects the number of drugs prescribed at treatment, as evidenced by the ANOVA test results.
Table 6 Age vs drug interactions
chi-squared
|
Degrees of freedom (df)
|
p-value
|
207.22
|
243
|
0.9535
|
Significant value <0.05; Chi-square test
Table 6 shows age vs drug interactions. The p-value (0.9535) is greater than the typical significance level of 0.05. This suggests that there is no statistically significant association between age categories and drug interactions.
Table 7 Age vs mild drug interactions
|
Degrees of freedom (df)
|
Sum of Squares
(Sum Sq)
|
Mean Square
(Mean Sq)
|
F value
|
p-value
(Pr (>F))
|
Mild
|
1
|
0.99
|
0.994
|
0.046
|
0.839
|
Residuals
|
5
|
108.43
|
21.687
|
|
|
Significant value <0.05; ANOVA test
Table 7 shows age vs mild drug interactions. The results of the one-way ANOVA test for the "mild" variable suggest that there is no statistically significant difference in the mean age based on the presence or absence of mild drug interactions. The p-value associated with the "mild" factor is 0.839, which is much greater than the typical significance level of 0.05. A p-value greater than 0.05 indicates that we fail to reject the null hypothesis. In other words, age does not appear to be significantly associated with the presence of mild drug interactions in this study population. This suggests that age alone may not be a determining factor for the occurrence of mild drug interactions. Other factors such as medication regimen, comorbidities, and individual pharmacokinetics may play a more substantial role in influencing the presence of mild drug interactions.
Table 8 Age vs moderate drug interactions
|
Degrees of freedom (df)
|
Sum of Squares
(Sum Sq)
|
Mean Square
(Mean Sq)
|
F value
|
p-value
(Pr (>F))
|
Moderate
|
8
|
262
|
32.72
|
1.064
|
0.39
|
Residuals
|
195
|
5994
|
21.687
|
|
|
Significant value <0.05; ANOVA test
Table 8 shows age vs moderate drug interactions. Based on the results of the one-way ANOVA test, there is no statistically significant difference in the mean age among the different levels of the "moderate" variable. The p-value for the "moderate" factor is 0.39, which is greater than the typical significance level of 0.05. Therefore, we fail to reject the null hypothesis.
Table 9 Age vs severe drug interactions
|
Degrees of freedom (df)
|
Sum of Squares
(Sum Sq)
|
Mean Square
(Mean Sq)
|
F value
|
p-value
(Pr (>F))
|
Severe
|
6
|
121
|
20.18
|
0.417
|
0.828
|
Residuals
|
95
|
4070
|
42.85
|
|
|
Significant value <0.05; ANOVA test
Table 9 illustrates age vs severe drug interactions. The results of the one-way ANOVA test for the "severe" variable suggest that there is no statistically significant difference in the mean age based on the "severe" categories. The p-value for the "severe" factor is 0.828, which is much greater than the typical significance level of 0.05. Therefore, we fail to reject the null hypothesis.
Table 10 Gender vs drug interactions
t
|
Degrees of freedom (df)
|
p-value
|
2.1083
|
156.99
|
0.03659
|
Significant value <0.05; Two sample t-test
Table 10 shows gender vs drug interactions. The p-value (0.03659) is less than the significance level of 0.05, suggesting that there is evidence to reject the null hypothesis. This indicates a statistically significant difference in the mean number of drugs prescribed at treatment between genders. Furthermore, the confidence interval for the difference in means does not include zero, further supporting the conclusion of a significant difference. Therefore, based on the results of the t-test, gender appears to have a significant effect on the number of drugs prescribed at treatment, with one gender receiving a significantly different number of drugs compared to the other.
Table 11 Gender vs mild drug interactions
t
|
95% CI
|
Degrees of freedom (df)
|
p-value
|
1.3147
|
-0.0501 - 0.2515
|
235.37
|
0.1899
|
Significant value <0.05; Two sample t test
Table 11 shows gender vs mild drug interactions. The Two Sample t-test comparing the "mild" variable between males and females resulted in a p-value of 0.1899. Since the p-value is greater than the typical significance level of 0.05, we fail to reject the null hypothesis. This suggests that there is no statistically significant difference in the "mild" variable between males and females in the dataset. Thus, based on the t-test results, gender does not appear to have a significant effect on the occurrence of mild drug interactions in the study population. Other factors may be influencing the presence of mild drug interactions, such as specific medications, underlying health conditions, or genetic factors.
Table 12 Gender vs moderate drug interactions
t
|
95% CI
|
Degrees of freedom (df)
|
p-value
|
-0.17263
|
-0.6423 - 0.5388
|
232.3
|
0.8631
|
Significant value <0.05; Two sample t test
Table 12 illustrates gender vs moderate drug interactions. The Two-Sample t-test comparing the "moderate" variable between males and females resulted in a p-value of 0.8631. With a p-value greater than the typical significance level of 0.05, we fail to reject the null hypothesis. This means that there is insufficient evidence to suggest a significant difference in the "moderate" variable between males and females. Therefore, based on the t-test results, gender does not appear to have a significant effect on the occurrence of moderate drug interactions in the study population.
Table 13 Gender vs severe drug interactions
t
|
95% CI
|
Degrees of freedom (df)
|
p-value
|
-1.1092
|
-0.4821 - 0.1352
|
165.02
|
0.269
|
Significant value <0.05; Two sample t test
Table 13 shows gender vs severe drug interactions. The Welch Two Sample t-test comparing the "severe" variable between males and females resulted in a p-value of 0.269. Since the p-value is greater than the typical significance level of 0.05, we fail to reject the null hypothesis. This suggests that there is no statistically significant difference in the "severe" variable between males and females in the dataset. Therefore, based on the t-test results, gender does not appear to have a significant effect on the occurrence of severe drug interactions in the study population.
Table 14 Common Potential Drug-drug interactions:
Drug combinations
|
PDDIs (%)
|
Clinical types of PDDIs
|
Mechanism of PDDIs
|
Potential risk
|
Metoprolol + Timolol
|
35 (11.29%)
|
Severe
|
PK
|
Both increase anti-hypertensive blocking channel
|
Nifedipine + Tolvaptan
|
29 (9.35%)
|
Severe
|
PK
|
Increases the level of tolvaptan by affecting hepatic enzyme metabolism
|
Nifedipine + Amlodipine
|
25 (8.06%)
|
Severe
|
PD
|
Increases the level of amlodipine by affecting hepatic enzyme metabolism
|
Sodium Bicarbonate + Levofloxacin
|
17 (5.48%)
|
Severe
|
PD
|
Decreases the level of levofloxacin by inhibition of GI absorption
|
Levofloxacin + Ondansetron
|
16 (5.16%)
|
Severe
|
PK and PD
|
Increases Qtc interval
|
Fludrocortisone + Tolvaptan
|
14 (5.41%)
|
Severe
|
|
Fludrocortisone decreases the level of tolvaptan by p-glycoprotein efflux transporter
|
Azithromycin + Heparin
|
12 (3.87%)
|
Severe
|
PD, Synergism
|
Increases the effect of heparin by decreasing metabolism
|
Dexamethasone + Ivabradine
|
11 (3.54%)
|
Severe
|
PD, Antagonism
|
Decreases the effect of ivabradine by affecting hepatic enzyme metabolism
|
Sodium Bicarbonate + Levofloxacin
|
11 (3.54%)
|
Severe
|
PD, Antagonism
|
Sodium bicarbonate decreases the level of levofloxacin by inhibition of GI absorption
|
Ceftriaxone + Calcium Acetate
|
9 (2.90%)
|
Severe
|
PD, Antagonism
|
Calcium salts enhance toxic effect of ceftriaxone
|
Quetiapine + Pramipexole
|
9 (2.90%)
|
Severe
|
PD, Synergism
|
Pharmacodynamic synergism
|
Ceftriaxone + Enoxaparin
|
7 (2.25)
|
Severe
|
PD, Antagonism
|
Increases the effect of enoxaparin by anticoagulation
|
Tramadol + Gabapentin
|
6 (1.93%)
|
Moderate
|
PD
|
enhances CNS depressant effect of tramadol
|
Tramadol + Desloratadine
|
6 (1.93%)
|
Moderate
|
PK
|
Enhances CNS depressant effect of tramadol
|
Pantoprazole + Digoxin
|
6 (1.93%)
|
Moderate
|
PK
|
Increases the level of digoxin by increasing gastric pH
|
Clopidogrel And Aspirin + Pantoprazole
|
5 (1.61%)
|
Moderate
|
PD
|
Decreases serum conc. Of active metabolite of clopidogrel
|
Dexamethasone + Disulfiram
|
5 (1.61%)
|
Moderate
|
PK
|
Disulfiram may enhance the toxic effect of dexamethasone
|
Clonidine + Metoprolol
|
5 (1.61%)
|
Moderate
|
PD, Synergism
|
Pharmacodynamic synergism
|
Ramipril+ Pregabalin
|
4 (1.29%)
|
Moderate
|
PD, Synergism
|
Pharmacodynamic synergism
|
Spironolactone + Potassium Chloride
|
4 (1.29%)
|
Moderate
|
PD
|
Increases serum potassium
|
Escitalopram + Quetiapine
|
4 (1.29%)
|
Moderate
|
PK
|
Increases toxicity of quetiapine by QTc interval
|
Haloperidol + Pramipexole
|
4 (1.29%)
|
Moderate
|
PD, Antagonism
|
Pharmacodynamic antagonism
|
Quetiapine + Pramipexole
|
5 (1.61%)
|
Moderate
|
PD, Antagonism
|
Pharmacodynamic antagonism
|
Quetiapine + Levodopa
|
5 (1.61%)
|
Moderate
|
PD, Antagonism
|
Pharmacodynamic antagonism
|
Haloperidol + Ivabradine
|
4 (1.29%)
|
Moderate
|
PK
|
Increases the level of ivabradine by affecting hepatic enzyme metabolism
|
Ranolazine + Metformin
|
4 (1.29%)
|
Moderate
|
PD, Antagonism
|
Increases the effect of metformin by decreasing the elimination
|
Diltiazem + Ivabradine
|
4 (1.29%)
|
Moderate
|
PD, Synergism
|
Increases the level of ivabradine by affecting hepatic enzyme metabolism
|
Hydrocortisone + Ranolazine
|
4 (1.29%)
|
Moderate
|
PK
|
Decreases the level of ranolazine by affecting hepatic enzyme metabolism
|
Diltiazem + Budesonide
|
4 (1.29%)
|
Moderate
|
PD
|
Increases the level of budesonide by affecting hepatic enzyme metabolism
|
Budesonide + Spironolactone
|
4 (1.29%)
|
Moderate
|
PK and PD
|
Decreases the level of spironolactone affecting hepatic enzyme metabolism
|
Calcium Gluconate + Gentamycin
|
4 (1.29%)
|
Moderate
|
PD, Synergism
|
Pharmacodynamic synergism
|
Torsemide + Gentamycin
|
3 (0.96%)
|
Moderate
|
PD, Synergism
|
Pharmacodynamic synergism
|
Calcium Gluconate + Doxycycline
|
3 (0.96%)
|
Moderate
|
PD, Antagonism
|
either decreases the level of other by inhibition of GI absorption
|
Ceftriaxone + Heparin
|
3 (0.96%)
|
Moderate
|
PK and PD
|
Ceftriaxone increases the level of heparin by anticoagulation
|
Piperacillin + Heparin
|
3 (0.96%)
|
Moderate
|
PD, Antagonism
|
Piperacillin increases the level of heparin by anticoagulation
|
Doxycycline + Ivabradine
|
2 (0.64%)
|
Mild
|
PK and PD
|
Doxycycline increases the level of ivabradine by affecting hepatic enzyme metabolism
|
Zolpidem + Pregabalin
|
2 (0.64%)
|
Mild
|
PD, Antagonism
|
Pregabalin enhances CNS depressant effect of zolpidem
|
Spironolactone + Potassium Chloride
|
1 (0.32%)
|
Mild
|
PD, Antagonism
|
Both increases serum potassium
|
Tramadol + Linezolid
|
1 (0.32%)
|
Mild
|
PD, Antagonism
|
Linezolid enhances the serotonergic effect of tramadol, which results in serotonin syndrome
|
Tramadol + Morphine
|
1 (0.32%)
|
Mild
|
|
Morphine increases CNS depressant effect of tramadol
|
Levofloxacin + Aceclofenac
|
1 (0.32%)
|
Mild
|
PD, Antagonism
|
Aceclofenac increases the neuroexcitatory effect of levofloxacin
|
Mirtazapine + Azithromycin
|
1 (0.32%)
|
Mild
|
PD, Antagonism
|
Both increases QTc interval
|
Magnesium Hydroxide + Doxycycline
|
1 (0.32%)
|
Mild
|
PK and PD
|
Magnesium hydroxide decreases the level of doxycycline by inhibition of GI absorption
|
Doxycycline + Amoxicillin
|
1 (0.32%)
|
Mild
|
PK and PD
|
Pharmacodynamic antagonism
|
Acenocoumarol + Aspirin
|
1 (0.32%)
|
Mild
|
PD, Antagonism
|
Aspirin enhances the anticoagulant effect of acenocoumarol
|
Clopidogrel + Pantoprazole
|
1 (0.32%)
|
Mild
|
PK and PD
|
Pantoprazole decreases serum conc. Of active metabolite of clopidogrel
|
Levofloxacin + Etodolac
|
1 (0.32%)
|
Mild
|
PD, Antagonism
|
Etodolac enhaces neuroexcitatory effect of levofloxacin
|
Amitriptyline + Ondansetron
|
1 (0.32%)
|
Mild
|
PD, Antagonism
|
Both increase sedation/ either increases toxicity of other by serotonin level
|
Ticagrelor + Aspirin
|
1 (0.32%)
|
Mild
|
PK and PD
|
Aspirin increases antiplatelet effect of ticagrelor
|
Table 14 shows the most commonly occurring drug drug interactions