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Determination of Factors that Impact Adherence to Warfarin in Patients with Stroke/Inmeli Hastalarda Varfarine Uyumu Etkileyen Faktorlerin Belirlenmesi.


Stroke is one of the most important cause of disability and mortality worldwide. Among stroke subtypes, ischemic strokes comprise 87% of all strokes and have a high risk for recurrent cardioembolic events. The most common cause of recurrent cardioembolic events after stroke has been reported as atrial fibrillation (AF). The incidence of AF increases with age, and risk of AF-related stroke increases about 4-5-fold with the addition of other risk factors (hypertension, diabetes, coronary cardiac diseases, cardiac failure) in patients with stroke (1). Furthermore, prophylactic treatment should be initiated to prevent cardiovascular events because AF-related ischemic stroke is more severe, which causes a worse functional state and higher mortality than those related to other etiologies (1,2,3). Oral anticoagulant agents are the mainstay of therapy in secondary prevention. Although numerous oral non-vitamin K antagonists have been developed in recent years, they have not yet replaced warfarin (vitamin K antagonist) (4,5). The efficacy of warfarin treatment is related to many variables such as socio-demographics, genetics, the pharmacokinetics of the drug, and patient adherence to the therapy. Among these factors, the adherence of the patient to the drug is the modifiable one.

There are many studies on adherence to warfarin in patients with cardiovascular disease. However, the number of studies is lower in the case of stroke. In the literature, it has been reported that higher educational level, regular social life, being well-informed about the therapy, strong patient-health professional relationship, and the severity of the disease positively affect the adherence to warfarin therapy, whereas drug-food and drug-drug interactions, concomitant diseases, polypharmacy and psychosocial causes such as anxiety, depression, lack of knowledge or motivation or inability to arrange physician appointments negatively affect adherence (6,7). Although not being very consistent, inadequate adherence to warfarin has shown to be associated with poor anticoagulation control [international normalized ratio (INR) out of targeted therapeutic range] (8,9). Maintaining INR in the targeted therapeutic range (2.0-3.0) increases the improvement in functional outcomes by 2-fold, it reduces the risk of death after stroke by 2.8-fold (1,10). An INR value below the targeted limit increases the risk of recurrent venous thromboembolism or stroke, whereas values over the limit may lead to hemorrhagic events that result in excessive bleeding or death. Therefore, optimal management of the treatment includes a correctly prescribed dose regimen that avoids the risk of both thromboembolism and bleeds, and monitoring of the INR value and enhancing patient adherence (10,11,12).

Evaluating factors associated with adherence to warfarin treatment would have clinical importance in enhancing adherence to the drug. The aim of this study was to determine the adherence to warfarin therapy, and to evaluate factors that might affect adherence.

Materials and Methods

Study Design and Participants

This descriptive cross-sectional study was conducted on patients with stroke who were admitted to an outpatient neurology clinic of a tertiary hospital in Istanbul. A total of 99 patients with stroke who were under warfarin treatment for at least 6 months, aged over 18 years, able to communicate, and willing to participate were included in the study. Before data collection, ethical approval was obtained from the Ethics Board of the hospital (25.11.2016/892). Written informed consent was obtained from the participants.

Data Collection

To collect data, a patient information form, Adherence Scale [Morisky, Green, Levine test (MGL)], MedTake test, hospital anxiety and depression scale (HADS), mini mental state examination (MMSE), Barthel index of daily activities, modified Rankin disability scale (mRS), and the EQ-5D (EUROQOL Quality of Life Scale) were used. Data were collected through face-to-face interviews.

Adherence Scale (Morisky, Green, Levine Test): MGL was used to evaluate warfarin adherence. This scale was developed by Morisky et al. (1986) (13) in order to evaluate adherence. The scale consists of 4 questions. The scale is answered as "yes" or "no", and shows the drug adherence of the patient as "high", "moderate", and "poor". The higher the score is, the better the adherence.

MedTake Test: To evaluate the knowledge of patients regarding warfarin, the MedTake test was used. MedTake was developed by Raehl et al. (2002) (14) in order to evaluate the knowledge about prescribed oral drugs of elderly patients. Four parameters (dose of medication, indications for taking the drug, co-ingestion of the drug with food or water and drug regimen) are evaluated for each drug via this scale. For each parameter, the patients obtain scores of over 25. The composite score is 100 for each drug. The higher the score is, the better the knowledge (15).

Hospital Anxiety and Depression Scale: This scale was developed by Zigmond and Snaith (1983) (16) and adapted to Turkish by Aydemir et al. (1997) (17). It is a self-evaluation scale including 14 items, and it evaluates anxiety and depression. The answers are evaluated as quadruple likert-type. The cut-off score is 10 for anxiety and 7 for depression.

Mini Mental State Examination: The MMSE was developed by Folstein et al. (1975) (18) in order to evaluate mental dysfunction, and was adapted to Turkish by Kucukdeveci et al. (2005) (19). It is a widely-used tool in clinical studies and practice. The scale evaluates five basic mental functions (orientation, memory, attention, calculation, and language). The maximum score that can be obtained from the scale is 30; lower scores indicate worse mental function.

Barthel Index of Daily Activities: This index has been used in order to evaluate dependency in the daily activities of patients with neurologic disorders. It was adapted to Turkish by Kucukdeveci et al. (2000) (20). The score ranges between 0 and 100, where 0 indicates complete dependency and 100 indicates independence (21).

Modified Rankin Disability Scale: This scale was developed by Van Swieten et al. (1988) (22) to determine the functional state of patients. According to the score obtained in the mRS, 1 and 2 indicate independence, and 3 and higher indicate dependency.

EQ-5D Scale: The EQ-5D is a standardized instrument developed by the EuroQol Group for use as a measure of health outcome. Its EQ-5DVA S item provides a single index value for health status (23).

Statistical Analysis

The SPSS 21.0 (IBM SPSS Inc., Armonk, NY) statistics program was used for the statistical analysis. Normality analysis was performed using the Kolmogorov-Smirnov test in order to define the types of tests in comparisons. Non-parametric tests were used for comparisons because the distribution of the data did not fit to normal distribution. Descriptive statistics (percentages, mean, standard deviation) were used to display sample characteristics, and the Mann-Whitney U test was used for the comparison of factors affecting drug adherence between two groups. Spearman's correlation analysis was performed for correlational analyses of continuous variables. Stepwise logistic regression analysis was used in order to determine the predictors of adherence. The results were evaluated within the 95% confidence interval, and a p value of <0.05 was accepted as significant.


The mean age of the sample was 68.6[+ or -]8.9 (range, 46-93) years. Among the included 99 patients, 54 (54.5%) were male and half of the group was illiterate. The mean duration of diagnosis was 5.9[+ or -]3.4 years. The patients had been using the anticoagulant agent for a mean of 4.2[+ or -]3.3 (range, 0.5-13) years (Table 1).

The characteristics of drug use are presented in Table 2. Of the patients, two-thirds were taking medications without assistance (62.6%), and one-third had experienced drug-related adverse effects (33.3%). The majority of the patients (72.7%) had undergone regular INR monitoring.

Mean scores of the scales used in the study are presented in Table 3. The mean MedTake score of the patients was 78.5[+ or -]17.2 (range, 35-100). The mean adherence score was 3.3[+ or -]1.1 (0-4). Twenty percent of the patients were non-adherent.

When drug adherence was compared between subgroups according to the sociodemographic, disease-related and drug use-related characteristics, some significant differences were found (Table 4). A significant negative correlation was determined between age and drug adherence (r=-0.39, p<0.001). The drug adherence scores were lower in illiterate patients compared to the literate (3.00[+ or -]1.26 vs. 3.57[+ or -]0.95, p=0.007) and in single/divorced/widows compared to the married (3.02[+ or -]1.32 vs 3.50[+ or -]0.95, p=0.053). Drug adherence was worse in patients who had been hospitalized within the last year compared to those who had not (2.45[+ or -]1.56 vs 3.55[+ or -]0.85, p=0.001). Besides, a significant negative correlation was determined between the number of risk factors and adherence (r=-0.33, p<0.001). A significant negative correlation was observed between the duration of anticoagulant use and adherence (r=-0.52, p<0.001). The mean drug adherence scores were lower in patients receiving their drugs with the help of other people compared to self-users (2.97[+ or -]1.21 vs 3.50[+ or -]1.05, p=0.005), in those had experienced drug-related adverse effect compared to those that did not (2.93[+ or -]1.32 vs 3.49[+ or -]1.00, p=0.018).

The relationship between drug adherence and knowledge regarding drug use (MedTake), functional state (Barthel, Rankin, MMSE), anxiety and depression (HADS) and quality of life (EQ-5D) scores have been presented in Table 4. Significant correlations were determined between drug adherence and all parameters.

In order to eliminate the effects of independent variables, originated from the relationships between themselves, independent variables that were determined to be significant underwent regression analysis (Table 5). Variables that were included in the model were age, education, hospitalization, self-use of the drug, adverse effects, MedTake, HADS anxiety and depression, MMSE, Barthel, and Rankin. Backward stepwise regression analysis was performed in nine steps and revealed that predictors of the adherence were having experienced adverse effects, knowledge regarding drugs (MedTake) and depression (HADS) (R2=0.482; p=0.001; p<0.05) (Table 6).


Warfarin is still one of the most commonly used drugs in the secondary prevention of stroke, although some novel agents have been developed. In previous studies on warfarin treatment, the most commonly studied subject was the efficacy/safety of the drug (24). In this study, adherence to warfarin treatment and factors that might affect adherence were investigated.

Eighty percent of our patients reported adherence to warfarin. It is difficult to interpret this result because different methods have been employed to assess adherence in different studies and there are limited studies in patients with stroke. In real-world observational studies, adherence to warfarin has been reported lower (between 56-75%). However, the majority of these earlier studies were conducted on patients with AF or thromboembolism (25,26,27,28,29). There is also a nationwide study conducted in Turkey on adherence to warfarin (30), but because this study was conducted in a mixed patient group and "time in therapeutic range method" was used in this study to assess adherence, it may not be appropriate to compare our results. There are only a few studies on stroke patients presenting self-report adherence rates. These studies reported varying rates for high adherence (between 50% and 84%) (31,32,33). Our findings should be interpreted carefully because the assessment of adherence with a patient self-report approach may cause bias. Especially in face-to-face interviews, patients may omit to provide some information and therefore adherence may be overestimated. This explanation suggested by Rossi et al. (2018) (29) would partially explain the discrepancy between the (inadequate) knowledge and (high) adherence in our sample, and also the inconsistency between our adherence rates and our national adherence rates. On the other hand, prior stroke, as a dramatic life event, may in itself be an adherence-enhancing factor, as previously suggested by Polymeris et al. (2016) (32). This may explain the lower adherence rates in observational studies in mixed populations as compared with our study, which included only patients with stroke. Another issue that should be considered in adherence studies on patients with stroke is family involvement (34). Family involvement in medication management should be investigated, especially in collectivist cultures such as in Turkey.

Drug adherence was better in patients who were younger and literate and married (due to caregiver support) and was not affected by their sex (7,11,31). The findings of earlier studies were similar to our study with regard to age, educational status, and marital status, whereas male sex was related to poor drug adherence (7,27). No effect of sex on drug adherence observed in this study was believed to be due to the female patients having a lower educational status than the male patients. In contrast to the current time, in the studied generation, the educational status varied between the two sexes, and this was reflected in our sample.

In terms of disease-related factors that may impact adherence, an increased number of risk factors was observed to be associated with drug adherence. As known, the presence of concomitant diseases in elderly patients causing polypharmacy reduces drug adherence (35,36,37). In our study, hospitalization within the previous year was also found to be associated with poor drug adherence. Another factor that may impact adherence is the duration of drug use. In our study, the duration of warfarin use was correlated with drug adherence negatively. Long-term warfarin has a risk of hemorrhage and also requires lifestyle modifications such as regular INR monitoring, considering drug-food or drug-drug interactions, and coping with the fear of experiencing adverse effects; therefore, it may complicate drug adherence (7,11,35). The adherence scores of patients who attended regular INR monitoring were better than those who did not. Another important subject in patients under warfarin treatment is carrying a note (such as identity card/document or wristband) showing the use of the drug and also documenting the use of their medications. However, in our sample, these habits were not found to be associated with drug adherence (38). Drug adherence was poorer in patients receiving their drugs with the help of other people (family members) compared with self-users. There is a knowledge gap in the stroke literature about factors that influence adherence in survivors of stroke with severe disability and the role of their caregivers in patients' adherence (34,38). Moreover, other variables such as patients' characteristics (age, education, drug knowledge score, anxiety and depression, MMSE, mRS, and Barthel) and caregiver characteristics and continuity of the same caregiver may impact adherence. Another factor that was found to be associated with adherence was experiencing adverse effects. This factor was also found to be a predictor of adherence. Causing fear and frustration, experiencing adverse effects may result in non-adherence (34).

In our study, univariate analysis showed significant correlations between drug adherence and functional state (Barthel, mRS, MMSE) and HADS (anxiety and depression). Furthermore, depression was determined to be an independent predictor of drug adherence in the regression analysis. Disability has been reported as one of the factors that impairs drug adherence because disabled patients would be dependent on other people for drug use, thus drug adherence was reported to be poor (28,39,40). In our study, significant correlations were obtained between the functional state (measured using the Barthel and mRS scales) and drug adherence, and better adherence scores were obtained in self-drug users, and these findings support this suggestion. One of the factors that may affect drug adherence is mental state. Impaired cognition was reported as a predictor of non-adherence (7). Cognitively impaired patients cannot easily afford the high degree of adherence that anticoagulants require. Our study also confirmed the findings of earlier studies conducted on different patient groups, which revealed a relation between depression and anxiety and poor adherence (41,42). When the relationship between drug adherence and knowledge regarding the drug was investigated, moderate positive correlations were determined between these variables. The regression analysis revealed that knowledge on the drug was an independent predictor of adherence. This finding was similar to those obtained in other studies (28,33,43,44). A positive correlation was determined between adherence and the quality of life in our study. This may have resulted from the fact that patients with a better quality of life may have adjusted to the stroke better and therefore they may be ready to adhere to the drug treatment (45).

Oral anticoagulants are widely used in patients with stroke for secondary prevention. Healthcare professionals should be aware of patients who have risk factors for non-adherence. Prevention of non-adherence can contribute to improved patient outcomes in stroke. This research has made a contribution to the knowledge base of risk factors for non-adherence in patients with stroke.

Study Limitations

There are some limitations of this study. These include the small sample size, lack of follow-up, lack of evaluation at to whether the INR level was within the therapeutic range, and lack of evaluation of adherence using more objective methods (e.g. pill counting). Future studies are recommended to address these limitations.


In conclusion, although the majority of our sample reported adherence it was observed that more than 40% the patients had poor knowledge regarding the drug. Drug adherence was determined to be related to some sociodemographic and clinical factors and functional state. Experiencing adverse effects, knowledge about the drug, and depression were determined to be predictors of adherence. Also, adherence was found to have a relationship with quality of life. Therefore, in order to improve drug adherence, patients should be assessed for depression and given training regarding drug use, especially on what to do if an adverse event occurs.


Ethics Committee Approval: Ethical approval was obtained from the Ethics Board of the Istanbul Training and Research Hospital (25.11.2016/892).

Informed Consent: Written informed consent was obtained from the participants.

Peer-review: Externally and internally peer-reviewed.

Authorship Contributions

Concept: Z.T., Design: Z.T., Data Collection or Processing: C.P.D., R.R.C., Analysis or Interpretation: Z.T., C.P.D., Literature Search: Z.T., C.P.D., R.R.C., Writing: Z.T., C.P.D., R.R.C., H.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study received no financial support.


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[iD] Zeliha Tulek (1), [iD] Cansu Polat Dunya (1), [iD] Refika Reva Ciftcioglu (2), [iD] Himmet Dereci (3)

(1) Istanbul University Cerrahpasa Florence Nightingale Faculty of Nursing, Istanbul, Turkey

(2) Istanbul Training and Research Hospital, Clinic of Cardiology, Istanbul, Turkey

(3) Istanbul Training and Research Hospital, Clinic of Neurology, Istanbul, Turkey

Address for Correspondence/Yazsima Adresi: Zeliha Tulek, Istanbul University Cerrahpasa Florence Nightingale Faculty of Nursing, Istanbul, Turkey

Phone: +90 532 776 29 93 E-mail: ORCID:

Received/Gelifl Tarihi: 02.01.2019 Accepted/Kabul Tarihi: 18.03.2019

This study was presented in 22nd European Stroke Conference as a poster presentation and funded by the Research Fund of Istanbul University (UDP-32468).

Table 1. Sociodemographic and disease characteristics of the patients

Characteristics                                  n                %

Male                                             54               54.5
Female                                           45               45.5
Illiterate                                       47               47.5
Literate                                         52               52.5
Employed                                         10               10.1
Housewife                                        34               34.3
Retired                                          55               55.6
Marital status
Single/divorced/widow                            41               41.4
Married                                          58               58.6
Age (Mean [+ or -] SD, range)                    68.6[+ or -]8.9  46-93
Time since diagnosis (years) (Mean [+ or -] SD,   5.9[+ or -]3.4  1-14
Duration of anticoagulant use (years)             4.2[+ or -]3.3  0.5-13
(Mean [+ or -] SD, range)

SD: Standard deviation

Table 2. Drug use characteristics of the patients

Characteristics                            n   %

Taking medications without assistance      62  62.6
Regular INR and PT monitoring              72  72.7
Experiencing drug-related adverse effects  33  33.3
Getting knowledge on the use of the        96  97.0
Documenting drug use                       54  54.5
Carrying identity card about drug use      34  34.3

INR: International normalized ratio, PT: Prothrombin time

Table 3. Mean scores of the scales

Characteristics                   Mean [+ or -] SD  Range

HADS: Anxiety                      8.5[+ or -]4.5   0-17
HADS: Depression                   9[+ or -]4.3     0-20
MMSE                              25.3[+ or -]4.4   16-32
Modified rankin scale              1.8[+ or -]1.4   0-5
Barthel                           82.6[+ or -]16.3  45-100
EQ-5DVA S                         59.3[+ or -]23.9  5-100
MedTake: Total                    78.5[+ or -]17.2  35-100
MedTake: Dose                     22.4[+ or -]3.3   10-25
MedTake: Indications              20.0[+ or -]4.8   10-25
MedTake: Regimen                  19.7[+ or -]4.8   5-25
MedTake: Coingestion              16.4[+ or -]8.0   0-25
Poor knowledge according to the   n=42              42.4%
MedTake (n, %)
Adherence: Score                   3.3[+ or -]11    0-4
Moderate or low adherence (n, %)  n=20              20.2%
High adherence (n, %)             n=79              79.8%

EQ-[5D.sub.VAS] : EUROQoL five dimensions questionaire, HADS: Hospital
anxiety and depression scale, MMSE: Mini mental state examination, SD:
Standard deviation

Table 4. Drug adherence according to the sociodemographic,
disease-related, and drug use-related characteristics of the patients

Sociodemographics                 Mean [+ or -] SD  Median     p

Age (rho, p)                                        rho=-0.39  <0.001
Male                              3.25[+ or -]1.16       4.0    0.617
Female                            3.36[+ or -]1.12       4.0
Educational status
Illiterate                        3.00[+ or -]1.26       4.0    0.007
Literate                          3.57[+ or -]0.95       4.0
Marital status
Single/divorced/widow             3.02[+ or -]1.32       4.0    0.053
Married                           3.50[+ or -]0.95       4.0
Disease-related characteristics
Affected hemisphere
Right                             3.36[+ or -]1.15       4.0    0.214
Left                              3.17[+ or -]1.13       4.0
Hospitalization within last
Present                           2.45[+ or -]1.56       3.0    0.001
Absent                            3.55[+ or -]0.85       4.0
Number of risk factors                              rho=-0.33   0.001
(rho, p)
Drug use-related characteristics
Duration of anticoagulant                           rho=-0.52  <0.001
use (rho, p)
Taking medication w/o
Yes                               3.50[+ or -]1.05       4.0    0.005
No                                2.97[+ or -]1.21       3.0
Regular INR and PT
Yes                               3.41[+ or -]1.13       4.0    0.034
No                                3.00[+ or -]1.13       3.0
Drug-related adverse effect
Experienced                       2.93[+ or -]1.32       4.0    0.018
Not-experienced                   3.49[+ or -]1.00       4.0
Documenting drug use
Yes                               3.29[+ or -]1.15       4.0    0.936
No                                3.31[+ or -]1.13       4.0
Carrying ID card about drug
Yes                               3.38[+ or -]1.25       4.0    0.262
No                                3.26[+ or -]1.08       4.0

Mann-Whitney U test was used to compare groups. Spearman was used for
correlation analysis.
INR: International normalized ratio, PT: Prothrombin time, SD: Standard

Table 5. Correlations between drug adherence and the MedTake, HADS,
MMSE, Barthel, Rankin, and EQ-5D

Scales                rho    p

MedTake: Dose          0.28  0.004
MedTake: Indications   0.48  0.001
MedTake: Regimen       0.57  0.001
MedTake: Coingestion   0.50  0.001
MedTake: Total         0.56  0.001
HADS-anxiety          -0.45  0.001
HADS-depression       -0.42  0.001
MMSE                   0.50  0.001
Barthel index          0.52  0.001
Rankin                -0.46  0.001
EQ-[5D.sub.VAS]        0.45  0.001

Spearman correlation analysis was used.
EQ-[5D.sub.VAS] : EUROQoL five dimensions questionnaire, HADS: Hospital
anxiety and depression scale, MMSE: Mini mental state examination

Table 6. Stepwise regression analysis in order to determine predictors
of adherence

Variables        Beta    SE     Wald    p      OR     95% CI
Adverse effects                                       Lower  Upper

                 -1.540  0.671   5.276  0.022  0.214  0.058  0.798
HADS-Depression   0.075  0.023  10.690  0.001  1.078  1.031  1.128
                 -0.229  0.103   4.947  0.026  0.795  0.650  0.973
Constant         -1.065  2.013   0.280  0.597  0.345

CI: Confidence interval, OR: Odds ratio, SE: Standard error, HADS:
Hospital anxiety and depression scale
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Title Annotation:Original Article / Ozgun Arastirma
Author:Tulek, Zeliha; Dunya, Cansu Polat; Ciftcioglu, Refika Reva; Dereci, Himmet
Publication:Turkish Journal of Neurology
Date:Sep 1, 2019
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