Introduction
Coronavirus disease-19 (COVID-19) is a viral infection causing severe acute respiratory syndrome in humans. Suspicion of COVID-19 is firstly reported as pneumonia with unknown etiology on December 31th in China (1). An increase in the number of patients with pneumonia was identified on 31 December 2019 and then it was identified as the new Coronavirus on January 7th, 2020 which was not detected in humans before. After this date, the number of patients including infected health care professionals increased rapidly. The first case with COVID-19 in Turkey was confirmed on March, 11th, 2020 (2,3). Current situation in Turkey on January 13rd, 2022 involved more than 9.4 million confirmed cases and 82,361 deaths. The numbers are increasing each day (3). The rapid global spread of COVID-19 continues, which remains a danger throughout the world however, an accurate and certain treatment is still being investigated by the scientists.
The treatment of COVID-19 is complex and requires different groups of drugs and combinations. However, despite all effort and clinical studies, a conclusive consensus on treatment is still lacking (4). Individualized treatment measures were preferred according to to clinical severity and conditions. In many cases, multiple medication use was inevitable. The most prescribed drugs for the treatment of COVID-19 were antivirals, antibiotics, analgesics and antipyretics, corticosteroids, tocilizumab, anakinra, and convalescent plasma, etc. (4).
Since the concept of pharmaceutical care has emerged, one of the primary services of pharmacists is to ensuring optimal drug use and minimize adverse events occuring as a result of medications (5). The pharmacist-led cognitive services, which are defined as “the use of specialized knowledge by the pharmacist for the patient or health professionals for the purpose of promoting effective and safe drug therapy” aims to optimize pharmacotherapy (6).
The pharmacist should evaluate the medication therapies using their skills about pharmacotherapy as their daily routine (7). As an expert on drug use and pharmacotherapy pharmacist has an essential role in identifying and resolving the Drug-Related Problems (DRPs). The term DRPs could be defined as any events or circumstances related to pharmacotherapy that could interfere with the health outcomes (8). According to the definition of the Pharmaceutical Care Network Europe, DRP is “An event or circumstance involving drug therapy that actually or potentially interferes with desired health outcomes” (9). Potential or actual DRPs may be harmful for the patient and increase the healthcare costs (10). In a recent study held by Liew et al. (11), up to 60 % potentially inappropriate prescribing observed in patients above the age of 65 years.
The prevention and resolving of DRPs requires a professional experience and collaboration among the healthcare professionals. The pharmacists are one of the most qualified healthcare professionals to identify and prevent DRPs due to their pharmacotherapy knowledge, and regular communication with patients (5). During the medication review process, DRPs should be identified and classified by a clinical pharmacist. To optimize the drug therapy, an evaluation of the indications, dosage, adherence, adverse events, and therapeutic effects of all drugs should be assessed and recorded (7). Despite increased attention and identification of DRPs, management and prevention of this issue is still a challenge.
Aim of the Study
The main objective of this study is to investigate the pharmaceutical care need of patients with COVID-19 in hospital settings. The primary outcomes of the present study were the identification of DRPs and influencing factors.
Methods
Study Design and Sample Size
A prospective observational was study conducted on patients with COVID-19 who were admitted to pulmonology service at a tertiary-care university hospital in Istanbul, Turkey between September 2020, and May 2021. The patients in need of intensive care were excluded. The patients with COVID-19 indication enrolled in this study were diagnosed according to the World Health Organization and Turkish Ministry of Health Interim Guidance (12). A sample size of 85 was required within a 5% margin of error and confidence intervals (CI) of 95% (13).
Data Collection
The patients’ demographic factors (age, gender, body weight etc.), comorbid diseases, prescribed medicine (dosing, frequency, and treatment duration) and duration of hospital stay were recorded. In addition, blood pressure, heart rate, oxygen saturation, respiratory rate, and laboratory findings (e.g., creatinine, uric acid, fasting blood glucose, hemogram, LACE index, Quick COVID-19 severity index, COVID-GRAM Critical Illness Risk Score) on admission were recorded (14-16). Meanwhile, the number of prescribed medicine or over-the-counter medications during hospital stay were collected. The identification of DRPs was made by the clinical pharmacist according to recent guidelines, UpToDate® and Medscape® clinical decision support system, and evidence-based medicine. Potential drug-drug interactions (pDDI) were determined by using UpToDate®. Among detected pDDIs, only X (avoid combination), D (consider therapy modification) and C (monitor therapy) categories were taken into consideration.
All assessments about DRPs which had clinical significance were performed by clinical pharmacists. The DRPs and clinical significance were evaluated using the Hepler and Strand DRPs classification system (17). Data were collected using convenience sampling methods. This study were reported according to recommendation of Strengthening the Reporting of Observational Studies in Epidemiology standards (Figure 1) (18).
Statistical Analysis
Descriptive statistics, mean, median, standard deviation, and interquartile range (IQR) or counts and percentages were given for continuous variables. The frequency, percentage were given for categorical variables. The normality of continuous variables was tested using the Kolmogorov-Smirnov test. The difference among groups was analyzed with an independent t-test or Mann-Whitney U test. Chi-square tests were used to investigate the relationship between categorical variables. The univariate logistic regression analysis was used to determine which variables were significant by using p<0.20. The significant variables were included in the binary logistic regression analysis. The missing data were excluded from the analysis. All the data were analyzed by using SPSS version 26® and Jamovi version 1.6.
Ethical Approval
The study protocol was approved by the Ministry of Health and the Local Ethics Committee of Bezmialem Vakıf University’s clinical research ethics committee (approval number of 5/42, 06.05.2020). Informed consent was obtained from all individual participants included in the study.
Results
Demographics, Medications, and Drug-Related Problems (DRPs)
The total number of patients were 107, the median (IQR) age of patients was 64 (54.5-76.0) and 50.46% of them were male (Table 1). The median (IQR) score of body mass index was 25.4 (23.7-27.7). The median number of comorbidities (IQR) was 3 (2-4) per patient. The majority of the patients had at least one comorbidity (88.79%) other than COVID-19. The median (IQR) number of medicines prescribed, and the median number of days of hospital stay were 12.8 (8-16) and 9 (6-15) days, respectively (Table 1). The most frequently prescribed medicines were favipiravir, enoxaparin, pantoprazole, paracetamol, and dexamethasone (Figure 2). The total number of DRP was recorded as 201, and at least one DRP was seen in 75 out of 107 patients (Table 2). The baseline vital signs of the patients were given in Table 3. The mean and median (IQR) numbers of DRPs were 1.93±1.91/patient and 2 (0-8), respectively (Table 4). According to our results, 140 of the DRPs consisted of pDDIs. One the most abundant pDDIs was increased bleeding due to concomitant use of dexamethasone and enoxaparin.
Medical conditions of the participants are summarized in Table 1. Among 107 patients, nearly half of them were diagnosed with hypertension (HT) (n=54, 50.47%). The second and the third most common comorbidities were Diabetes Mellitus (DM) (n=30, 28.47%) and coronary artery diseases (CAD) (n=25, 23,365), respectively (Table 1). Among 75 patients with detected DRP, 44 patients had HT, 25 patients had DM and 24 patients had CAD (Table 1).
Vital Signs and Biochemical Findings
Baseline clinical and vital findings of the participants were recorded and presented in Table 3 and 4. The median (IQR) of body temperature of patients was recorded as 37 (36.4-37.5). Among our sample, median (IQR) values of heart beats per minute and oxygen saturation (spO2) were 87 (78-96.5) and 93 (88-95), respectively. The median (IQR) systolic and diastolic blood pressure values were 131 (119-145) and 76 (65-82), respectively. The median (IQR) respiratory rate of the participants was 20/min (16-22). Participants’ basal biochemical values are given in Table 4.
Factors associated with the Drug-Related Problems
Univariate analysis exploring the factors associated with DRP are presented in Table 5. The number of comorbidities [odds ratio (OR)=2.097, 95% confidence interval (CI)=1.43-3.08; p<0.001)], number of medications (OR=1.32, 95% CI=1.17-1.49; p<0.001), serum urea mg/dL levels (OR=1.035, 95% CI=1.01-1.06; p<0.05), serum blood urea nitrogen levels (OR=1.00, 95% CI=1.00-1.00; p<0.05), serum potassium levels (OR=2.409, 95% CI=1.16-5.00; p<0.05), serum lymphocyte ratio (OR=0.967, 95% CI=0.936-1.00; p<0.05), Quick COVID severity index score (OR=1.23, 95% CI=1.01-1.353; p<0.05), and LACE index score (OR=1.23, 95% CI=1.07-1.42; p<0.001) were associated with the DRPs. Binary logistic regression analysis for DRPs is presented in Table 5.
A binomial logistic regression was performed to ascertain the effects of the number of medications, the number of comorbidities, BUN, serum potassium levels, lymphocytes ratio, LACE index, score, Quick COVID severity Index, serum urea level, on the likelihood that participants had a DRP. The logistic regression model was statistically significant, c2(8)=57.842, p<0.0001. The model explained 59.7% (Nagelkerke R2) of the variance in DRPs and correctly classified 84.1% of cases. Sensitivity was 92.1%, specificity was 64.52%, positive predictive value was 61.5% and negative predictive value was 74.3%. Of the 8 predictor variables, only 4 were statistically significant: number of comorbidities, number of medications, serum potassium levels and lymphocyte ratio (Table 5). Increased number of comorbidities (OR=1.952; 95% CI=1.07-3.54, p<0.05), number of medications (OR=1.344; 95% CI=1.12-1.61, p<0.001), and serum potassium levels (OR=5.252; 95% CI=1.57-17.56, p<0.001) were associated with an increased likelihood of exhibiting DRP. But, increasing lymphocyte ratio (OR=0.953; 95% CI=0.91-0.99, p<0.05) was associated with a reduction in the likelihood of exhibiting DRPs.
Discussion
In this study, we investigated the DPRs in patients with COVID-19 and related factors in hospital settings. Hospitalized patients with COVID-19 have multiple comorbidities and need multiple medications (4). Currently, many scientists are investigating alternative medicine for COVID-19. However, there is no exact treatment alternative for COVID-19 approved by different authorities. On the other hand, the ethical aspects of these options are still questionable (19).
In this study, many of the participants were prescribed with antivirals, antibiotics, analgesics, antipyretics, and anti-thrombotic drugs. Based on the primary findings, the number of comorbidities, serum potassium levels, lymphocyte ratio, and the number of medications were associated with the number of DRPs. The identified risk factors should be assessed by pharmacist to prevent DRPs in patients with COVID-19.
According to Pradhan and Olsson (20) and Imam et al. (21), HT and DM were the most common comorbid diseases among patients with COVID-19. Another study held in Turkey pointed out that DM, HT, and CAD were the most frequent comorbidities among patients with COVID-19 (22). Our findings showed a correlation with their statements. The most common comorbid disease was recorded as HT (50.47%), which was followed by DM (28.04%), and CAD (23.36%) (Table 1). Therefore, detailed medical history should be taken and preventive measures for DRPs should be underlined by the clinical pharmacist.
A retrospective cohort study held by Imam et al. (21) pointed out that older age and increased number of comorbidities were associated with mortality. Older age (>60 years) (OR=3.66, 95% CI=2.57-5.20) and increased number of comorbidities (>3) (OR=4.11, 95% CI=3.00-5.62) were independent predictors of mortality (21). Similarly, our investigation pointed out that increased number of comorbidities (OR=1.952; 95% CI=1.07-3.54, p<0.05) were associated with the increased number of the DRPs. However, in terms of age, there was not statistically difference between the groups (Table 5). Many patients, especially elders, have multiple comorbidities. Knowledge of pharmacist should be implemented into practice to improve healthcare services for patients with COVID-19. A detailed medication review process might be useful to detect and prevent DRPs. Hence, clinical pharmacists could provide pharmaceutical care for patients with COVID-19 in the hospital setting (7,23).
Previous studies held in either in community pharmacy settings or hospital setting detected different number of DRPs per patient (7,24,25). In our study, the mean number of DRP per patient was recorded as 1.93±1.91/patient. Our results were similar with the studies by Stafford et al. (24) and Rhalimi et al. (25) study. On the other hand, Wang et al. (7) recorded higher number of DRPs per patients than our findings. This difference could be explained by the settings of different studies. For instance, the study by Stafford et al. (24) and our data were obtained from hospital settings. However, the studies by Wang et al. (7) and Rahlimi et al. (25) were conducted in a community pharmacy settings.
Multivariate analysis showed that the number of medication used was associated as independent risk factor for the number of DRPs, which was consistent with previous studies (7,26-28). Polypharmacy is a strong risk factor for DRPs. As a result, the number of used medications increased number of DRPs increased simultaneously. The presented finding extended the understanding that a higher number of medications was also an important predictor of DRP in patients with COVID-19 (OR=1.344; 95% CI=1.12-1.61, p<0.001), that was not studied extensively in the literature before (27,28). Multiple medication use is inevitable with comorbidities. However, many of the DRPs may be prevented with well-planned pharmaceutical care services.
Another significant finding of our study was that serum potassium level was associated with DRPs. Compromised kidney functions are directly related with potassium levels. Many of our participants suffered from HT and DM both of which might compromise the kidney functions. Patient with kidney diseases is more prone to drug related problems (29,30). On the other hand, one of the most used antihypertensive drugs is diuretics which can either spare potassium or prevent potassium secretion in kidneys. Also, hypokalemia or hyperkalemia may be directly related with the pharmacokinetic parameters of drugs. As in our findings, the level of serum potassium was related with DRPs which was consistent with literature (29,30). Pharmacists should take into consideration that fluctuation of serum potassium level may result as adverse events.
Study Limitations
This study had some limitations such as the generalizability of the results was limited as the sample was taken from only one center. Future multicentered studies with larger sample size are required to investigate the pharmaceutical care needs of patients with COVID-19. The sample size was rather small. Finally, the lack of a control group was a limitation of the present study, which was worth noting.
Conclusion
To the best of our knowledge, presented study was the first to investigate the incidence, type, and related factors of DRPs detected by clinical pharmacists in patients with COVID-19 in hospital settings. This study showed that a considerable proportion of patients had DRPs and the most common category was the potential drug-drug interactions. In the multivariate model, the number of medications, number of comorbidities, serum potassium levels and lymphocytes ratio were the significant related factors with the number of DRPs.
COVID-19 pandemic is still an important healthcare problem all around the world. Pharmacists and pharmacist-led cognitive services will detect, prevent, and decrease unfavorable drug-related events. To improve healthcare services, pharmacists should take responsibility and should become an indispensable component of the COVID-19 healthcare team.
Acknowledgement
The authors of this study are grateful to Bezmialem Vakif University. We are also grateful to Hümeyra Şahin-Bektay for her valuable contribution to our research. The presented study was conducted within the scope of the thesis of a Clinical Pharmacy PhD Program at the Institute of Health Sciences of Marmara University. This study was not funded by any organizations.
Ethics
Ethics Committee Approval: The study protocol was approved by the Ministry of Health and the Local Ethics Committee of Bezmialem Vakıf University’s clinical research ethics committee (approval number of 5/42, 06.05.2020).
Informed Consent: Informed consent was obtained from all individual participants included in the study.
Peer-review: Externally peer reviewed.
Authorship Contributions
Concept: M.Y.B., M.S., F.V.İ., Design: M.Y.B., M.S., F.V.İ., Data Collection or Processing: M.Y.B., M.S., Analysis or Interpretation: M.Y.B., M.S., Literature Search: M.Y.B., F.K.O., B.D., Writing: M.Y.B., M.S., F.K.O., B.D., F.V.İ.
Conflict of Interest: No conflict of interest was declared by the authors.
Financial Disclosure: The authors declared that this study received no financial support.