Disability and Rehabilitation
ISSN: 0963-8288 (Print) 1464-5165 (Online) Journal homepage: http://www.tandfonline.com/loi/idre20
Correlates of depressive symptoms in individuals attending outpatient stroke clinics Julianne Vermeer, Danielle Rice, Amanda McIntyre, Ricardo Viana, Steven Macaluso & Robert Teasell To cite this article: Julianne Vermeer, Danielle Rice, Amanda McIntyre, Ricardo Viana, Steven Macaluso & Robert Teasell (2017) Correlates of depressive symptoms in individuals attending outpatient stroke clinics, Disability and Rehabilitation, 39:1, 43-49, DOI: 10.3109/09638288.2016.1140837 To link to this article: http://dx.doi.org/10.3109/09638288.2016.1140837
View supplementary material
Published online: 17 Feb 2016.
Submit your article to this journal
Article views: 234
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=idre20 Download by: [Australian Catholic University]
Date: 09 October 2017, At: 08:14
DISABILITY AND REHABILITATION, 2017 VOL. 39, NO. 1, 43–49 http://dx.doi.org/10.3109/09638288.2016.1140837
RESEARCH PAPER
Correlates of depressive symptoms in individuals attending outpatient stroke clinics Julianne Vermeera, Danielle Ricea, Amanda McIntyrea, Ricardo Vianaa,b, Steven Macalusoa,b and Robert Teasella,b,c
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
a Lawson Health Research Institute, Parkwood Institute, London, ON, Canada; bSt. Joseph’s Health Care, Parkwood Institute, London, ON, Canada; cSchulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
ABSTRACT
ARTICLE HISTORY
Background and purpose Depressive symptoms are common post-stroke. We examined stroke deficits and lifestyle factors that are independent predictors for depressive symptomology. Methods A retrospective chart review was performed for patients’ post-stroke who attended outpatient clinics at a hospital in Southwestern Ontario between 1 January 2014 and 30 September 2014. Demographic variables, stroke deficits, secondary stroke risk factors and disability study measures [Patient Health Questionnaire-9 (PHQ-9) and Montreal Cognitive Assessment (MoCA)] were analyzed. Results Of the 221 outpatients who attended the stroke clinics (53% male; mean age ¼ 65.2 ± 14.9 years; mean time post-stroke 14.6 ± 20.1 months), 202 patients were used in the final analysis. About 36% of patients (mean ¼ 5.17 ± 5.96) reported mild to severe depressive symptoms (PHQ-9 5). Cognitive impairment (CI), smoking, pain and therapy enrollment (p50.01) were significantly associated with depressive symptoms. Patients reporting CI were 4 times more likely to score highly on the PHQ-9 than those who did not report CI (OR ¼ 4.72). While controlling for age, MoCA scores negatively related to depressive symptoms with higher PHQ-9 scores associated with lower MoCA scores (r¼ 0.39, p50.005). Conclusions High levels of depressive symptoms are common in the chronic phase post-stroke and were partially related to cognition, pain, therapy enrollment and lifestyle factors.
Received 21 September 2015 Revised 21 December 2015 Accepted 7 January 2016 Published online 10 February 2016 KEYWORDS
Depression; outpatient; rehabilitation; stroke
ä IMPLICATIONS FOR REHABILITATION
Stroke patients who report cognitive deficits, pain, tobacco use or being enrolled in therapy may experience increased depressive symptoms. A holistic perspective of disease and lifestyle factors should be considered while assessing risk of depressive symptoms in stroke patients. Patients at risk for depressive symptoms should be monitored at subsequent outpatient visits.
Introduction Individuals may experience poor health outcomes after a stroke, including motor dysfunction, spasticity, aphasia and mood disorders. Post-stroke depression (PSD) is classified as a ‘‘mood disorder due to a general medical condition’’.[1] Reported prevalence rates of major depression range from 39% to 52% up to 5 year post-stroke. In a recent meta-analysis [2] examining 50 studies published between 1983 and 2011, prevalence rates for depression slightly increased from 28% within 1 month to 31% at 6 months and 33% at 1-year post-stroke. Along with the negative consequences of major depression, including
social isolation, PSD is associated with changes in activities of daily living (ADL) performance.[3] Despite early efforts to reduce depression through depression screening and treatment in the acute phase of rehabilitation, many individuals continue to experience depressive symptoms in the chronic phase of stroke. In the aforementioned meta-analysis,[2] predictors for incidence of PSD were also examined. Overall, predictors for depression included baseline disability,[4,5] cognitive impairment (CI),[4,6] pre-stroke depression,[7] dysphagia,[4] incontinence,[4] and anxiety.[5,8] Interestingly, age and gender did not predict PSD.[2] It is important to
CONTACT Julianne Vermeer [email protected] Lawson Health Research Institute, Parkwood Institute, Aging, Rehabilitation, and Geriatric Care, Rm. B3025, Parkwood Institute, 550 Wellington Road, London, ON N6C 0A7, Canada Supplemental data for this article can be accessed http://dx.doi.org/10.3109/09638288.2016.1140837. ß 2016 Taylor & Francis
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
44
J. VERMEER ET AL.
note that, among 10 studies, only four examined patients who were 41-year post-stroke and the majority of studies examined patients in a hospital setting. Little data exists on the predictors of PSD among stroke survivors in the chronic phase of stroke when patients are not in hospital or attending in-patient rehabilitation programs. After the acute phase of recovery many individuals return home but continue to be followed by a stroke specialist as an outpatient. Given that PSD is still prevalent in the later phases of stroke, it is recommended that individuals are screened, diagnosed and treated for PSD during all phases of recovery.[9] Unfortunately, given the dearth of literature in this area, it is unknown how predictors of PSD compare among varying health settings (e.g. acute care versus outpatient settings). The importance of early recognition and treatment of PSD cannot be understated, as PSD contributes to the development of several adverse outcomes including disability,[10] reduced quality of life,[10,11] and even mortality.[12,13] Developing and adhering to strategies to identify patients at an increased risk for depression has been proposed for managing depression and allowing for improved rehabilitation potential.[14–16] While previous literature has generally focused on stroke deficits as predictors of PSD, considering lifestyle factors that are modifiable by patients is also important when aiming to decrease the risk of PSD. Therefore, it was our objective to perform a retrospective chart review of individuals attending stroke outpatient clinics to examine both stroke deficits and lifestyle factors as predictors for depressive symptomology.
Methods A retrospective chart review was performed using consecutive patients attending three outpatient stroke clinics between 1 January 2014 and 30 September 2014 at Parkwood Institute in Southwestern Ontario, Canada. Ethics approval for this project was obtained by the Office of Research Ethics of Western University, Ontario, Canada.
Inclusion criteria Outpatients included in this study had a confirmed diagnosis of stroke and attended an outpatient appointment at Parkwood Institute during the time of data collection. Further, individuals were included if they had a complete dataset for at least one consultation or follow-up visit. Patients who were aphasic and whose first language was not English were excluded.
Dataset All assessment and appointment-related documentation were originally collected by a physician and Registered Nurse during routine consultation or follow-up appointments held within the outpatient clinic. For patients who attended more than one visit during the specified timeframe, only data from the first appointment was extracted. During each consultation outpatient visit, a Standardized Stroke Form (SSF; Supplementary materials) was completed and a depression score was obtained by verbally administering the Patient Health Questionaire-9 (PHQ-9). During follow-up visits, a twostep administration process was followed for depression screening whereby the Patient Health Questionnaire-2 (PHQ-2) was administered. If patients had one or more depressive symptoms on the PHQ-2 (score 1) then the full PHQ-9 was administered.
Data extraction Medical records were reviewed independently by two research assistants (D.R. and J.V.) trained in procedures related to chart reviews. Variables analyzed were based on significant findings in the stroke rehabilitation literature and information available from the SSF. The following information was extracted from each patient chart: demographic variables (e.g. age, gender, stroke duration and caregiver status), stroke deficits (e.g. CI, pain presence, side of hemiparesis, incontinence, dysphagia and therapy regime), secondary stroke risk factors (e.g. alcohol and nicotine use), disability (e.g. inpatient Functional Independence Measure (FIMÔ admission and gains)) and PHQ-9/PHQ-2 scores. Therapy regime referred to whether a patient was currently enrolled in physical, occupational and/or speech-language therapy as an outpatient. Current stroke deficits and secondary stroke risk factors were self-reported by patients during their clinic visit. Inpatient FIMÔ scores were provided from the National Reporting System (a standardized system used for collecting inpatient rehabilitation facilities in Canada). Available Montreal Cognitive Assessment (MoCA) scores were also extracted in a subset of patients (the MoCA is only administered when deemed necessary by the physician). All self-reported stroke deficits noted as concerns during outpatient visits were checked off on the SSF. These variables were then listed as ‘‘yes’’ or ‘‘no’’ during data extraction and were coded accordingly for statistical analyses. Difficulties in interpreting documentation (e.g. if chart notes were unclear) were addressed by consulting the physician who treated the patient. All data was inputted into a standardized database.
DEPRESSION IN A STROKE OUTPATIENT CLINIC
Study measures
Analysis
Functional independence measure
Data was coded and entered into a Statistical Package for Social Sciences (SPSS; IBM, V22, Chicago, IL) database. Demographic statistics were calculated using frequencies, means and standard deviations. Patients scoring positive for depressive symptoms based on PHQ-9 scores (5–27) were compared to those who did not score in the positive range (0–4). To evaluate associations between stroke patients presenting with depressive symptoms versus those who did not, we used a binary logistic regression. To determine which predictor variables to include within the regression model, we conducted preliminary analyses including independent sample t-tests for continuous variables (i.e. age, time since stroke, FIMÔ admission and gains) and chi-squared test of independence for categorical variables (i.e. gender, enrolled in therapy at time of outpatient appointment, caregiver, CI, pain presence, hemiparesis, incontinence, dysphagia, alcohol and nicotine use). The final logistic regression model included variables proven significant in the preliminary analyses (i.e. independent ttest and chi-square), where presence of depressive symptoms (yes/no) was the dependent variable. Logistic regression model included four predictor variables: nicotine use, pain, CI and therapy enrollment, with presence of depressive symptoms as the dependent variable. In a post hoc test, a partial correlation was conducted while controlling for age on the relationship between MoCA and PHQ-9 scores in order to add objectivity to patients’ self-reported concerns regarding cognition. All analyses were conducted using SPSS and were two tailed. Findings have been presented with odds ratios (OR), 95% confidence interval (C.I.) and p values. Statistical significance was defined as p50.05.
The FIMÔ provides a measure of disability relative to burden of care and is an indicator of independence in ADLs through assessing cognitive and motor functioning.[17] The FIMÔ consists of 18 items scored on a 7-point Likert scale with higher scores indicating greater independence (1 ¼ total assistance to 7 ¼ total independence; total ¼ 126). This measure has been validated within a stroke population with excellent reliability [18] and validity.[19] FIMÔ gains were calculated by subtracting patients’ inpatient FIMÔ admission scores from their inpatient discharge scores.
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
45
Montreal cognitive assessment The MoCA consists of eight subtests and assesses cognitive function in a variety of domains. MoCA scores range from 0 to 30 with a higher score indicating better cognitive performance. In accordance with the original instructions, MoCA scores were adjusted for education level by adding one point to the total score if patients had 12 years of formal education.[20]
Patient health questionnaire (PHQ-9) The PHQ-9 is a set of nine questions that determine depressive symptoms based on patients’ feelings during the 2 weeks previous to the day the test was taken.[21] Patients verbally answer each question on a scale from not at all (score ¼ 0) to nearly every day (score ¼ 3); these answers were recorded by a nurse or physician. The test yields a maximum total of 27, whereby patients are categorized as having minimal (scores ¼ 0–4), mild (scores ¼ 5–9), moderate (scores ¼ 10–14), moderately-severe (scores ¼ 15–19) or severe (scores ¼ 20–27) depressive symptoms. Our study compared patients with minimal depressive symptoms to those scoring in the range of mild to severe depressive symptoms. The PHQ-2 contains the first two questions from the PHQ-9. Patients who scored 0 on the PHQ-2 were coded as not presenting depressive symptoms, while patients with a score 1 were administered the full PHQ-9 and their final score was used in analysis. For the purposes of this study, patient results were dichotomized as showing depressive symptoms or not showing depressive symptoms based on a PHQ-9 score of 5,[21] in order to include patients with mild symptoms whose mood should be monitored at future visits.
Results A total of 221 individuals attended the outpatient clinic between 1 January 2014 and 30 September 2014. A subset of this sample was excluded for not having a depression screen completed (n ¼ 15) or missing predictor variables (n ¼ 4), resulting in a final sample size of 202 (see Figure 1). The majority of patients were male (53%), living at home (90%) and had experienced a left-hemisphere stroke (51%). Prestroke depression was reported by 6% of patients. Patients’ ages ranged from 22 to 98 years (mean ¼ 65.2 ± 14.9) and patients’ were, on an average, 14.6 ± 20.1 months post-stroke (median ¼ 6.6 months). The mean PHQ-9 score was 5.17 ± 5.96 with 73 (36%) patients scoring 5.
46
J. VERMEER ET AL.
Table 1. Preliminary analyses of potential predictor variables for inclusion in regression model. PHQ-955 (n ¼ 129)a
Variables
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
Independent sample t-tests Age 64.98 Time since stroke (days) 450.50 FIM admission 81.83 FIM gains 21.13 Chi-squared test of Independence Variables PHQ-955 (n¼129) Gender (male) Caregiver (yes) Cognitive Impairment (yes) Pain (yes) Hemiparesis (yes) Incontinence (yes) Dysphagia (yes) Alcohol use (yes) Nicotine use (yes) Receiving therapy (yes)
Figure 1. Depression screening patient flow chart 33 mm 38 mm (300 300 DPI).
Preliminary analyses revealed significant differences among patients with depressive symptoms compared to those without depressive symptoms for CI, pain presence, smoking and therapy enrollment based on chisquared tests of independence. None of the independent t-tests (age, days since stroke, FIMÔ admission or gains) or the additional chi-squared tests (gender, caregiver, hemiparesis, incontinence, dysphagia and alcohol use) demonstrated a significant difference between patients presenting with depressive symptoms versus patients who did not (p40.05, see Table 1). Direct logistic regression was performed to assess how stroke deficits and lifestyle factors relate to the likelihood of patients experiencing mild to severe depressive symptoms (5 on the PHQ-9). Prior to conducting the logistic regression, sample size calculations were completed to ensure our sample size was adequate to run the model with the specified independent variables (N ¼ 10 4/0.35 ¼ 114).[22] After confirming the assumption of multicollinearity was not violated, the Hosmer and Lemshow test resulted in a value p40.05, indicating support for the model. Four independent variables (i.e. CI, pain presence, nicotine use and therapy enrollment) were included in the model; which was found to be statistically significant (x2 ¼ 45.23, p50.001). The model explained 20% (Cox and Snell R square) and 28% (Nagelkerke R squared) of the variance in depressive symptoms; further, it correctly classified 73% of cases. Each of the four independent variables made a unique statistically significant contribution to patients’ depressive symptoms (Table 2). The strongest
68 100 30 38 22 18 27 57 11 63
PHQ-9 5 (n ¼ 73)a
t
p
65.25 387.87 78.39 22.98
0.13 0.74 0.87 0.76
0.897 0.460 0.386 0.447
PHQ-9 5 (n¼73) 46 54 39 37 48 7 16 18 18 46
x2
p
2.34 0.03 19.69 9.43 0.75 0.68 0.11 0.09 10.18 6.72
0.083 0.504 0.001* 0.002* 0.241 0.279 0.744 0.769 0.001* 0.007*
PHQ-955, patients with no depressive symptoms; PHQ-9 5, patients with mild to severe depressive symptoms. a Mean is presented for t-tests and number of patients is presented for chisquared tests. *p50.05
predictor for presenting with depressive symptoms was current CI such that outpatients who reported CI as a current deficit were over 4 times more likely to report mild-severe depressive symptoms than those who did not report CI, while controlling for all other factors in the model (OR 4.72, C.I. 95%, 2.38, 9.35). To objectively assess the relationship between CI and depressive symptoms, a post hoc partial correlation was conducted between available patient MoCA scores (n ¼ 55) and PHQ-9 scores while controlling for age. With age controlled, there was a significant negative correlation between patient MoCA and PHQ-9 scores, whereby lower scores in cognition related to higher scores of depressive symptomology (r¼ 0.39, p50.005).
Discussion This study examined a sample of stroke outpatients and identified variables associated with increased symptoms of depression. About 36% of patients demonstrated increased symptoms of depression, consistent with rates of depression reported in stroke rehabilitation literature.[2] Our exploration of how demographic factors, stroke deficits and lifestyle factors contribute to PSD in an outpatient clinic found that significant correlates of depressive symptoms included current CI, pain, therapy enrollment and nicotine use. This model correctly classified 73% of cases with increased depressive symptoms. Self-reported CI was robustly associated with depressive symptoms and this finding was further
DEPRESSION IN A STROKE OUTPATIENT CLINIC
47
Table 2. Logistic regression predicting likelihood of presenting with depressive symptoms (PHQ-9 5) (N ¼ 202)a. 95% C.I. for odds ratio Variable nicotine use Cognitive impairment Pain Receiving therapy
B
SE
Wald
df
p values
Odds ratio
Lower
Upper
1.26 1.60 0.84 0.88
0.49 0.35 0.34 0.35
6.72 19.75 6.05 6.52
1 1 1 1
0.010* 0.001* 0.014* 0.011*
3.53 4.72 2.31 2.42
1.36 2.38 1.19 1.22
9.18 9.35 5.51 4.76
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
CI: confidence interval; Wald: value of Wald statistics; df: degree of freedom. a Number of patients with complete datasets analyzed. *Denotes significance (p50.05).
supported by a significant correlation between MoCA scores and depressive symptomology after adjusting for age. Demographic characteristics such as age and gender had no significant association with depressive symptoms, which is also consistent with stroke literature.[2] Our findings indicate that the presence of depressive symptoms are common among patients with CIs based on subjective and objective measures, a finding which has been previously reported in other stroke samples.[4,23–25] Ayerbe et al. [4] reported that CI was a predictive factor for depression, whereby mood disorder was twice as likely to be present in stroke patients with CIs compared to those without CI. Hommel et al. [26] also reported on the association between depression and CI and identified memory and executive functioning as being particularly involved. In a sample of stroke patients aged 60 and older, Hosking and Marsh [25] found that CI was linked to depression up to 1-year post-stroke. Our findings extend previous research by demonstrating that among patients in the later recovery phases of stroke, CI and depression scores are significantly correlated based on MoCA scores, even while controlling for age. While it is apparent that a correlation between depression and CI exists, it is not clear how the two are linked. Future studies should assess whether CI and awareness of this impairment, leads to the development of depression, or whether CI is the result of the negative symptoms associated with depressed mood. An adequate understanding of the relationship between the two variables is important in providing appropriate management. The comorbid presence of depression and pain has also been well established in the pain literature [27] and in a number of other chronic conditions.[28–30] For example, Appelros [31] reported that among patients with first ever stroke, depression was significantly linked to pain. Similarly, among acute stroke patients, pain has been associated with depression.[32,33] In the general pain population it is well known that worsening pain tends to exacerbate depressive symptoms. Thus, treatment to reduce both issues is typically prioritized by health care providers; often treatment of depression
with pharmacotherapy significantly improves patients’ perception of pain as well.[27] Future studies should examine potential reductions in depressive symptoms through the use of pain management techniques in combination with treatment for depression,[34] within a post-stroke population. Unexpectedly, our study indicated that patients who were currently receiving rehabilitation therapy were more likely to experience depressive symptoms than those who were not. This finding does not necessarily reflect the patients’ level of disability as there was no significant association between FIMÔ scores and depressive symptoms. Hypothetically, this finding could reflect patients’ perception of their disability and functional status since, to be referred for therapy, patients need to express functioning concerns to their physician. Furthermore, mood concerns may affect how patients’ view their progress. Gillan et al. [35] reported individuals with depression attending inpatient rehabilitation participated in therapy for longer periods of time than those without depression. Stroke patients with depression have also been found to participate less during the rehabilitation process, negatively impacting their progress and ultimate outcomes.[36] In a sample of patients with acquired brain injuries, those with high depressive symptoms underestimated their abilities while patients’ with fewer depressive symptoms overestimated their abilities.[37] This perception of progress and impairment may provide an explanation for the relationship between therapy involvement and depressive symptoms among stroke patients in our study. Certainly, more research is needed to assess the factors that mediate and moderate the association between attending therapy and increased depressive symptoms. Finally, nicotine use was a significant predictor of depressive symptoms in our study population, comparative to previous stroke literature.[38] In a recent study involving a sample of patients who had experienced a minor stroke, current smoking was a predictor of late onset PSD.[38] It has been suggested that the relationship between smoking and depression may be cyclical in that depression can lead to smoking while smoking is
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
48
J. VERMEER ET AL.
also a predictor of depression. Smoking was the only modifiable lifestyle factor that was significantly correlated to increased depressive symptoms in this study and is one of the few modifiable variables linked to depressive symptoms in stroke patients. This highlights the importance of health education regarding nicotine use to improve patient well-being in terms of mood and prevention for secondary stroke.[39] Implementing and referring patients to smoking cessation programs may be one strategy to reduce the negative outcomes associated with smoking.
in the chronic phase of stroke, can positively influence the rehabilitative process and decrease symptoms of depression.[41] Nonetheless, mood concerns and associated factors need to be promptly recognized and addressed by a health care professional.
Limitations
Disclosure statement
While the current study extends previous research on correlates of depression in stroke patients attending outpatient rehabilitation, a retrospective research design has inherent limitations. Given that this study included a single site of outpatients, this decreases the generalizability of the findings. Further, patients’ depressive symptoms were based on PHQ-9 scores with mild to severe symptoms being identified rather than a formal diagnosis of depression. Using a cutoff score of 5 to indicate cases of patients with at least mild depressive symptoms may have resulted in a sample of patients eliciting much fewer symptoms of depression than studies using diagnostic criteria to define depression. Nonetheless, our findings based on the PHQ-9 tool are largely consistent with research from studies that applied a diagnostic criteria to define major depression.[38] Due to the subjective nature of the PHQ-9, overlap might exist between symptoms that contribute directly to stroke and common symptoms of depression (e.g. fatigue). It is possible that the PHQ-9 may be insensitive in reflecting these discrepancies among stroke patients, although this should be further explored in the stroke rehabilitation literature.[40] Additionally, patients excluded from PHQ-9 screening, such as those with impairments preventing them from displaying capacity to understand the PHQ-9, may limit the generalizability of our findings.
None declared. We would like to gratefully acknowledge Allergan Inc., who provided an unrestricted educational grant, and the Department of Physical Medicine and Rehabilitation, Schulich School of Medicine and Dentistry, Western University.
Conclusion Our findings suggest that a number of factors that impact depressive symptoms in the acute phase of stroke are also shown to be significant in the latter phases of stroke recovery. While stroke deficits are often considered in isolation from other factors, our study provides a holistic perspective of stroke deficits and lifestyle factors that influence depressive symptoms. Being cognizant of factors significantly associated with PSD can identify high-risk patients. Interventions proven to be effective in improving mood, when implemented
Acknowledgements We would like to thank Angela Woolner RN, BScN CNN(c), a Registered Nurse in the Parkwood Institute Outpatients Department, for her help in implementing the standardized stroke form.
References [1] American Psychiatric Association AP. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington (VA): American Psychiatric Association; 2013. [2] Ayerbe L, Ayis S, Wolfe CD, et al. Natural history, predictors and outcomes of depression after stroke: systematic review and meta-analysis. Br J Psychiatry. 2013;202:14–21. [3] Brown C, Hasson H, Thyselius V, et al. Post-stroke depression and functional independence: a conundrum. Acta Neurol Scand. 2012;126:45–51. [4] Ayerbe L, Ayis S, Rudd AG, et al. Natural history, predictors, and associations of depression 5 years after stroke: the South London Stroke Register. Stroke. 2011;42:1907–1911. [5] Morrison V, Pollard B, Johnston M, et al. Anxiety and depression 3 years following stroke: demographic, clinical, and psychological predictors. J Psychosom Res. 2005;59:209–213. [6] Fatoye FO, Mosaku SK, Komolafe MA, et al. Depressive symptoms and associated factors following cerebrovascular accident among Nigerians. J Ment Health. 2009;18:224–232. [7] Caeiro L, Ferro JM, Santos CO, et al. Depression in acute stroke. J Psychiatry Neurosci. 2006;31:377–383 [8] Sagen U, Finset A, Moum T, et al. Early detection of patients at risk for anxiety, depression and apathy after stroke. Gen Hosp Psychiatry. 2010;32:80–85. [9] Lindsey MPGG, Bayley M, Hill MD, et al. Canadian stroke best practice recommendations overview and methodology. Groups ObotCSBPACaW, editor. Ottawa (ON): Heart and Stroke Foundation, Canada; 2014. [10] Wulsin L, Alwell K, Moomaw CJ, et al. Lifetime depression and post-stroke depressive symptoms as predictors of stroke outcomes at 12 months. Philadelphia (PA): Lippincott Williams & Wilkins; 2008. p. 639–640. [11] Kwok T, Lo RS, Wong E, et al. Quality of life of stroke survivors: a 1-year follow-up study. Arch Phys Med Rehabil. 2006;87:1177–1182.
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
DEPRESSION IN A STROKE OUTPATIENT CLINIC
[12] Morris PL, Robinson RG, Andrzejewski P, et al. Association of depression with 10-year poststroke mortality. Am J Psychiatry. 1993;150:124–129 [13] Morris PL, Robinson RG, Samuels J. Depression, introversion and mortality following stroke. Aust N Z J Psychiatry. 1993;27:443–449. [14] Health NCCfM. The NICE guideline on the management and treatment of depression in adults (updated edition). London, UK: National Institute for Health and Clinical Excellence; 2010. [15] Ramasubbu R, Robinson RG, Flint AJ, et al. Functional impairment associated with acute poststroke depression. J Neuropsychiatry Clin Neurosci. 1998;10:26–33. [16] Salter KL, Foley NC, Zhu L, et al. Prevention of poststroke depression: does prophylactic pharmacotherapy work? J Stroke Cerebrovasc Dis. 2013;22:1243–1251. [17] Keith RA, Granger CV, Hamilton BB, et al. The functional independence measure: a new tool for rehabilitation. Adv Clin Rehabil. 1987;1:6–18. [18] Hobart JC, Lamping DL, Freeman JA, et al. Evidencebased measurement: which disability scale for neurologic rehabilitation? Neurology. 2001;57:639–644. [19] Kwon S, Hartzema AG, Duncan PW, et al. Disability measures in stroke: relationship among the Barthel Index, the Functional Independence Measure, and the Modified Rankin Scale. Stroke. 2004;35:918–923. [20] Nasreddine ZS, Phillips NA, Bedirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53:695–699. [21] Spitzer RL, Kroenke K, Williams JB, Group PHQPCS. Validation and utility of a self-report version of PRIMEMD: the PHQ primary care study. JAMA. 1999;282:1737–1744. [22] Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49:1373–1379. [23] De Ryck A, Fransen E, Brouns R, et al. Poststroke depression and its multifactorial nature: results from a prospective longitudinal study. J Neurol Sci. 2014;347:159–166. [24] Hackett ML, Anderson CS. Predictors of depression after stroke: a systematic review of observational studies. Stroke. 2005;36:2296–2301. [25] Hosking SG, Marsh NV. Predictors of depression at one year post-stroke in older adults. Brain Impairment. 2013;14:381–391. [26] Hommel M, Carey L, Jaillard A. Depression: cognition relations after stroke. Int J Stroke. 2015;10:893–896. [27] Bair MJ, Robinson RL, Katon W, et al. Depression and pain comorbidity: a literature review. Arch Intern Med. 2003;163:2433–2445.
49
[28] Amtmann D, Askew RL, Kim J, et al. Pain affects depression through anxiety, fatigue, and sleep in multiple sclerosis. Rehabil Psychol. 2015;60:81–90 [29] Rogers H, Brotherton H, de Luis A, et al. Depressive symptoms are independently associated with pain perception in Colombians with rheumatoid arthritis. Acta Reumatol Port. 2014;40:40–49. [30] Kwakkenbos L, van Lankveld WG, Vonk MC, et al. Diseaserelated and psychosocial factors associated with depressive symptoms in patients with systemic sclerosis, including fear of progression and appearance selfesteem. J Psychosom Res. 2012;72:199–204. [31] Appelros P. Prevalence and predictors of pain and fatigue after stroke: a population-based study. Int J Rehabil Res. 2006;29:329–333. [32] Lee AC, Tang SW, Yu GK, et al. Incidence and predictors of depression after stroke (DAS). Int J Psychiatry Clin Pract. 2007;11:200–206. [33] Kouwenhoven SE, Gay CL, Bakken LN, et al. Depressive symptoms in acute stroke: a cross-sectional study of their association with sociodemographics and clinical factors. Neuropsychol Rehabil. 2013;23:658–677. [34] Goesling J, Clauw DJ, Hassett AL. Pain and depression: an integrative review of neurobiological and psychological factors. Curr Psychiatry Rep. 2013;15:421. DOI: 10.1007/ s11920-013-0421-0. [35] Gillen R, Tennen H, McKee TE, et al. Depressive symptoms and history of depression predict rehabilitation efficiency in stroke patients. Arch Phys Med Rehabil. 2001;82:1645– 1649. [36] Sinyor D, Amato P, Kaloupek D, et al. Post-stroke depression: relationships to functional impairment, coping strategies, and rehabilitation outcome. Stroke. 1986;17:1102–1107. [37] Smeets SM, Ponds RW, Wolters Grego´rio G, et al. Impaired awareness of deficits in individuals with neuropsychiatric symptoms after acquired brain injury: associations with treatment motivation and depressive symptoms. Neuropsychology. 2014;28:717–725 [38] Shi Y, Xiang Y, Yang Y, et al. and others. Depression after minor stroke: prevalence and predictors. J Psychosom Res. 2015;79:143–147. [39] Bak S, Sindrup SH, Alslev T, et al. Cessation of Smoking After first-ever stroke: a follow-up study. Stroke a followup study. Stroke. 2002;33:2263–2269. [40] de Coster L, Leentjens AF, Lodder J, et al. The sensitivity of somatic symptoms in post-stroke depression: a discriminant analytic approach. Int J Geriatr Psychiatry. 2005;20:358–362. [41] Mehta S, Pereira S, Janzen S, et al. Effectiveness of psychological interventions in chronic stage of stroke: a systematic review. Top Stroke Rehabil. 2012;19:536–544.
ISSN: 0963-8288 (Print) 1464-5165 (Online) Journal homepage: http://www.tandfonline.com/loi/idre20
Correlates of depressive symptoms in individuals attending outpatient stroke clinics Julianne Vermeer, Danielle Rice, Amanda McIntyre, Ricardo Viana, Steven Macaluso & Robert Teasell To cite this article: Julianne Vermeer, Danielle Rice, Amanda McIntyre, Ricardo Viana, Steven Macaluso & Robert Teasell (2017) Correlates of depressive symptoms in individuals attending outpatient stroke clinics, Disability and Rehabilitation, 39:1, 43-49, DOI: 10.3109/09638288.2016.1140837 To link to this article: http://dx.doi.org/10.3109/09638288.2016.1140837
View supplementary material
Published online: 17 Feb 2016.
Submit your article to this journal
Article views: 234
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=idre20 Download by: [Australian Catholic University]
Date: 09 October 2017, At: 08:14
DISABILITY AND REHABILITATION, 2017 VOL. 39, NO. 1, 43–49 http://dx.doi.org/10.3109/09638288.2016.1140837
RESEARCH PAPER
Correlates of depressive symptoms in individuals attending outpatient stroke clinics Julianne Vermeera, Danielle Ricea, Amanda McIntyrea, Ricardo Vianaa,b, Steven Macalusoa,b and Robert Teasella,b,c
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
a Lawson Health Research Institute, Parkwood Institute, London, ON, Canada; bSt. Joseph’s Health Care, Parkwood Institute, London, ON, Canada; cSchulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
ABSTRACT
ARTICLE HISTORY
Background and purpose Depressive symptoms are common post-stroke. We examined stroke deficits and lifestyle factors that are independent predictors for depressive symptomology. Methods A retrospective chart review was performed for patients’ post-stroke who attended outpatient clinics at a hospital in Southwestern Ontario between 1 January 2014 and 30 September 2014. Demographic variables, stroke deficits, secondary stroke risk factors and disability study measures [Patient Health Questionnaire-9 (PHQ-9) and Montreal Cognitive Assessment (MoCA)] were analyzed. Results Of the 221 outpatients who attended the stroke clinics (53% male; mean age ¼ 65.2 ± 14.9 years; mean time post-stroke 14.6 ± 20.1 months), 202 patients were used in the final analysis. About 36% of patients (mean ¼ 5.17 ± 5.96) reported mild to severe depressive symptoms (PHQ-9 5). Cognitive impairment (CI), smoking, pain and therapy enrollment (p50.01) were significantly associated with depressive symptoms. Patients reporting CI were 4 times more likely to score highly on the PHQ-9 than those who did not report CI (OR ¼ 4.72). While controlling for age, MoCA scores negatively related to depressive symptoms with higher PHQ-9 scores associated with lower MoCA scores (r¼ 0.39, p50.005). Conclusions High levels of depressive symptoms are common in the chronic phase post-stroke and were partially related to cognition, pain, therapy enrollment and lifestyle factors.
Received 21 September 2015 Revised 21 December 2015 Accepted 7 January 2016 Published online 10 February 2016 KEYWORDS
Depression; outpatient; rehabilitation; stroke
ä IMPLICATIONS FOR REHABILITATION
Stroke patients who report cognitive deficits, pain, tobacco use or being enrolled in therapy may experience increased depressive symptoms. A holistic perspective of disease and lifestyle factors should be considered while assessing risk of depressive symptoms in stroke patients. Patients at risk for depressive symptoms should be monitored at subsequent outpatient visits.
Introduction Individuals may experience poor health outcomes after a stroke, including motor dysfunction, spasticity, aphasia and mood disorders. Post-stroke depression (PSD) is classified as a ‘‘mood disorder due to a general medical condition’’.[1] Reported prevalence rates of major depression range from 39% to 52% up to 5 year post-stroke. In a recent meta-analysis [2] examining 50 studies published between 1983 and 2011, prevalence rates for depression slightly increased from 28% within 1 month to 31% at 6 months and 33% at 1-year post-stroke. Along with the negative consequences of major depression, including
social isolation, PSD is associated with changes in activities of daily living (ADL) performance.[3] Despite early efforts to reduce depression through depression screening and treatment in the acute phase of rehabilitation, many individuals continue to experience depressive symptoms in the chronic phase of stroke. In the aforementioned meta-analysis,[2] predictors for incidence of PSD were also examined. Overall, predictors for depression included baseline disability,[4,5] cognitive impairment (CI),[4,6] pre-stroke depression,[7] dysphagia,[4] incontinence,[4] and anxiety.[5,8] Interestingly, age and gender did not predict PSD.[2] It is important to
CONTACT Julianne Vermeer [email protected] Lawson Health Research Institute, Parkwood Institute, Aging, Rehabilitation, and Geriatric Care, Rm. B3025, Parkwood Institute, 550 Wellington Road, London, ON N6C 0A7, Canada Supplemental data for this article can be accessed http://dx.doi.org/10.3109/09638288.2016.1140837. ß 2016 Taylor & Francis
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
44
J. VERMEER ET AL.
note that, among 10 studies, only four examined patients who were 41-year post-stroke and the majority of studies examined patients in a hospital setting. Little data exists on the predictors of PSD among stroke survivors in the chronic phase of stroke when patients are not in hospital or attending in-patient rehabilitation programs. After the acute phase of recovery many individuals return home but continue to be followed by a stroke specialist as an outpatient. Given that PSD is still prevalent in the later phases of stroke, it is recommended that individuals are screened, diagnosed and treated for PSD during all phases of recovery.[9] Unfortunately, given the dearth of literature in this area, it is unknown how predictors of PSD compare among varying health settings (e.g. acute care versus outpatient settings). The importance of early recognition and treatment of PSD cannot be understated, as PSD contributes to the development of several adverse outcomes including disability,[10] reduced quality of life,[10,11] and even mortality.[12,13] Developing and adhering to strategies to identify patients at an increased risk for depression has been proposed for managing depression and allowing for improved rehabilitation potential.[14–16] While previous literature has generally focused on stroke deficits as predictors of PSD, considering lifestyle factors that are modifiable by patients is also important when aiming to decrease the risk of PSD. Therefore, it was our objective to perform a retrospective chart review of individuals attending stroke outpatient clinics to examine both stroke deficits and lifestyle factors as predictors for depressive symptomology.
Methods A retrospective chart review was performed using consecutive patients attending three outpatient stroke clinics between 1 January 2014 and 30 September 2014 at Parkwood Institute in Southwestern Ontario, Canada. Ethics approval for this project was obtained by the Office of Research Ethics of Western University, Ontario, Canada.
Inclusion criteria Outpatients included in this study had a confirmed diagnosis of stroke and attended an outpatient appointment at Parkwood Institute during the time of data collection. Further, individuals were included if they had a complete dataset for at least one consultation or follow-up visit. Patients who were aphasic and whose first language was not English were excluded.
Dataset All assessment and appointment-related documentation were originally collected by a physician and Registered Nurse during routine consultation or follow-up appointments held within the outpatient clinic. For patients who attended more than one visit during the specified timeframe, only data from the first appointment was extracted. During each consultation outpatient visit, a Standardized Stroke Form (SSF; Supplementary materials) was completed and a depression score was obtained by verbally administering the Patient Health Questionaire-9 (PHQ-9). During follow-up visits, a twostep administration process was followed for depression screening whereby the Patient Health Questionnaire-2 (PHQ-2) was administered. If patients had one or more depressive symptoms on the PHQ-2 (score 1) then the full PHQ-9 was administered.
Data extraction Medical records were reviewed independently by two research assistants (D.R. and J.V.) trained in procedures related to chart reviews. Variables analyzed were based on significant findings in the stroke rehabilitation literature and information available from the SSF. The following information was extracted from each patient chart: demographic variables (e.g. age, gender, stroke duration and caregiver status), stroke deficits (e.g. CI, pain presence, side of hemiparesis, incontinence, dysphagia and therapy regime), secondary stroke risk factors (e.g. alcohol and nicotine use), disability (e.g. inpatient Functional Independence Measure (FIMÔ admission and gains)) and PHQ-9/PHQ-2 scores. Therapy regime referred to whether a patient was currently enrolled in physical, occupational and/or speech-language therapy as an outpatient. Current stroke deficits and secondary stroke risk factors were self-reported by patients during their clinic visit. Inpatient FIMÔ scores were provided from the National Reporting System (a standardized system used for collecting inpatient rehabilitation facilities in Canada). Available Montreal Cognitive Assessment (MoCA) scores were also extracted in a subset of patients (the MoCA is only administered when deemed necessary by the physician). All self-reported stroke deficits noted as concerns during outpatient visits were checked off on the SSF. These variables were then listed as ‘‘yes’’ or ‘‘no’’ during data extraction and were coded accordingly for statistical analyses. Difficulties in interpreting documentation (e.g. if chart notes were unclear) were addressed by consulting the physician who treated the patient. All data was inputted into a standardized database.
DEPRESSION IN A STROKE OUTPATIENT CLINIC
Study measures
Analysis
Functional independence measure
Data was coded and entered into a Statistical Package for Social Sciences (SPSS; IBM, V22, Chicago, IL) database. Demographic statistics were calculated using frequencies, means and standard deviations. Patients scoring positive for depressive symptoms based on PHQ-9 scores (5–27) were compared to those who did not score in the positive range (0–4). To evaluate associations between stroke patients presenting with depressive symptoms versus those who did not, we used a binary logistic regression. To determine which predictor variables to include within the regression model, we conducted preliminary analyses including independent sample t-tests for continuous variables (i.e. age, time since stroke, FIMÔ admission and gains) and chi-squared test of independence for categorical variables (i.e. gender, enrolled in therapy at time of outpatient appointment, caregiver, CI, pain presence, hemiparesis, incontinence, dysphagia, alcohol and nicotine use). The final logistic regression model included variables proven significant in the preliminary analyses (i.e. independent ttest and chi-square), where presence of depressive symptoms (yes/no) was the dependent variable. Logistic regression model included four predictor variables: nicotine use, pain, CI and therapy enrollment, with presence of depressive symptoms as the dependent variable. In a post hoc test, a partial correlation was conducted while controlling for age on the relationship between MoCA and PHQ-9 scores in order to add objectivity to patients’ self-reported concerns regarding cognition. All analyses were conducted using SPSS and were two tailed. Findings have been presented with odds ratios (OR), 95% confidence interval (C.I.) and p values. Statistical significance was defined as p50.05.
The FIMÔ provides a measure of disability relative to burden of care and is an indicator of independence in ADLs through assessing cognitive and motor functioning.[17] The FIMÔ consists of 18 items scored on a 7-point Likert scale with higher scores indicating greater independence (1 ¼ total assistance to 7 ¼ total independence; total ¼ 126). This measure has been validated within a stroke population with excellent reliability [18] and validity.[19] FIMÔ gains were calculated by subtracting patients’ inpatient FIMÔ admission scores from their inpatient discharge scores.
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
45
Montreal cognitive assessment The MoCA consists of eight subtests and assesses cognitive function in a variety of domains. MoCA scores range from 0 to 30 with a higher score indicating better cognitive performance. In accordance with the original instructions, MoCA scores were adjusted for education level by adding one point to the total score if patients had 12 years of formal education.[20]
Patient health questionnaire (PHQ-9) The PHQ-9 is a set of nine questions that determine depressive symptoms based on patients’ feelings during the 2 weeks previous to the day the test was taken.[21] Patients verbally answer each question on a scale from not at all (score ¼ 0) to nearly every day (score ¼ 3); these answers were recorded by a nurse or physician. The test yields a maximum total of 27, whereby patients are categorized as having minimal (scores ¼ 0–4), mild (scores ¼ 5–9), moderate (scores ¼ 10–14), moderately-severe (scores ¼ 15–19) or severe (scores ¼ 20–27) depressive symptoms. Our study compared patients with minimal depressive symptoms to those scoring in the range of mild to severe depressive symptoms. The PHQ-2 contains the first two questions from the PHQ-9. Patients who scored 0 on the PHQ-2 were coded as not presenting depressive symptoms, while patients with a score 1 were administered the full PHQ-9 and their final score was used in analysis. For the purposes of this study, patient results were dichotomized as showing depressive symptoms or not showing depressive symptoms based on a PHQ-9 score of 5,[21] in order to include patients with mild symptoms whose mood should be monitored at future visits.
Results A total of 221 individuals attended the outpatient clinic between 1 January 2014 and 30 September 2014. A subset of this sample was excluded for not having a depression screen completed (n ¼ 15) or missing predictor variables (n ¼ 4), resulting in a final sample size of 202 (see Figure 1). The majority of patients were male (53%), living at home (90%) and had experienced a left-hemisphere stroke (51%). Prestroke depression was reported by 6% of patients. Patients’ ages ranged from 22 to 98 years (mean ¼ 65.2 ± 14.9) and patients’ were, on an average, 14.6 ± 20.1 months post-stroke (median ¼ 6.6 months). The mean PHQ-9 score was 5.17 ± 5.96 with 73 (36%) patients scoring 5.
46
J. VERMEER ET AL.
Table 1. Preliminary analyses of potential predictor variables for inclusion in regression model. PHQ-955 (n ¼ 129)a
Variables
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
Independent sample t-tests Age 64.98 Time since stroke (days) 450.50 FIM admission 81.83 FIM gains 21.13 Chi-squared test of Independence Variables PHQ-955 (n¼129) Gender (male) Caregiver (yes) Cognitive Impairment (yes) Pain (yes) Hemiparesis (yes) Incontinence (yes) Dysphagia (yes) Alcohol use (yes) Nicotine use (yes) Receiving therapy (yes)
Figure 1. Depression screening patient flow chart 33 mm 38 mm (300 300 DPI).
Preliminary analyses revealed significant differences among patients with depressive symptoms compared to those without depressive symptoms for CI, pain presence, smoking and therapy enrollment based on chisquared tests of independence. None of the independent t-tests (age, days since stroke, FIMÔ admission or gains) or the additional chi-squared tests (gender, caregiver, hemiparesis, incontinence, dysphagia and alcohol use) demonstrated a significant difference between patients presenting with depressive symptoms versus patients who did not (p40.05, see Table 1). Direct logistic regression was performed to assess how stroke deficits and lifestyle factors relate to the likelihood of patients experiencing mild to severe depressive symptoms (5 on the PHQ-9). Prior to conducting the logistic regression, sample size calculations were completed to ensure our sample size was adequate to run the model with the specified independent variables (N ¼ 10 4/0.35 ¼ 114).[22] After confirming the assumption of multicollinearity was not violated, the Hosmer and Lemshow test resulted in a value p40.05, indicating support for the model. Four independent variables (i.e. CI, pain presence, nicotine use and therapy enrollment) were included in the model; which was found to be statistically significant (x2 ¼ 45.23, p50.001). The model explained 20% (Cox and Snell R square) and 28% (Nagelkerke R squared) of the variance in depressive symptoms; further, it correctly classified 73% of cases. Each of the four independent variables made a unique statistically significant contribution to patients’ depressive symptoms (Table 2). The strongest
68 100 30 38 22 18 27 57 11 63
PHQ-9 5 (n ¼ 73)a
t
p
65.25 387.87 78.39 22.98
0.13 0.74 0.87 0.76
0.897 0.460 0.386 0.447
PHQ-9 5 (n¼73) 46 54 39 37 48 7 16 18 18 46
x2
p
2.34 0.03 19.69 9.43 0.75 0.68 0.11 0.09 10.18 6.72
0.083 0.504 0.001* 0.002* 0.241 0.279 0.744 0.769 0.001* 0.007*
PHQ-955, patients with no depressive symptoms; PHQ-9 5, patients with mild to severe depressive symptoms. a Mean is presented for t-tests and number of patients is presented for chisquared tests. *p50.05
predictor for presenting with depressive symptoms was current CI such that outpatients who reported CI as a current deficit were over 4 times more likely to report mild-severe depressive symptoms than those who did not report CI, while controlling for all other factors in the model (OR 4.72, C.I. 95%, 2.38, 9.35). To objectively assess the relationship between CI and depressive symptoms, a post hoc partial correlation was conducted between available patient MoCA scores (n ¼ 55) and PHQ-9 scores while controlling for age. With age controlled, there was a significant negative correlation between patient MoCA and PHQ-9 scores, whereby lower scores in cognition related to higher scores of depressive symptomology (r¼ 0.39, p50.005).
Discussion This study examined a sample of stroke outpatients and identified variables associated with increased symptoms of depression. About 36% of patients demonstrated increased symptoms of depression, consistent with rates of depression reported in stroke rehabilitation literature.[2] Our exploration of how demographic factors, stroke deficits and lifestyle factors contribute to PSD in an outpatient clinic found that significant correlates of depressive symptoms included current CI, pain, therapy enrollment and nicotine use. This model correctly classified 73% of cases with increased depressive symptoms. Self-reported CI was robustly associated with depressive symptoms and this finding was further
DEPRESSION IN A STROKE OUTPATIENT CLINIC
47
Table 2. Logistic regression predicting likelihood of presenting with depressive symptoms (PHQ-9 5) (N ¼ 202)a. 95% C.I. for odds ratio Variable nicotine use Cognitive impairment Pain Receiving therapy
B
SE
Wald
df
p values
Odds ratio
Lower
Upper
1.26 1.60 0.84 0.88
0.49 0.35 0.34 0.35
6.72 19.75 6.05 6.52
1 1 1 1
0.010* 0.001* 0.014* 0.011*
3.53 4.72 2.31 2.42
1.36 2.38 1.19 1.22
9.18 9.35 5.51 4.76
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
CI: confidence interval; Wald: value of Wald statistics; df: degree of freedom. a Number of patients with complete datasets analyzed. *Denotes significance (p50.05).
supported by a significant correlation between MoCA scores and depressive symptomology after adjusting for age. Demographic characteristics such as age and gender had no significant association with depressive symptoms, which is also consistent with stroke literature.[2] Our findings indicate that the presence of depressive symptoms are common among patients with CIs based on subjective and objective measures, a finding which has been previously reported in other stroke samples.[4,23–25] Ayerbe et al. [4] reported that CI was a predictive factor for depression, whereby mood disorder was twice as likely to be present in stroke patients with CIs compared to those without CI. Hommel et al. [26] also reported on the association between depression and CI and identified memory and executive functioning as being particularly involved. In a sample of stroke patients aged 60 and older, Hosking and Marsh [25] found that CI was linked to depression up to 1-year post-stroke. Our findings extend previous research by demonstrating that among patients in the later recovery phases of stroke, CI and depression scores are significantly correlated based on MoCA scores, even while controlling for age. While it is apparent that a correlation between depression and CI exists, it is not clear how the two are linked. Future studies should assess whether CI and awareness of this impairment, leads to the development of depression, or whether CI is the result of the negative symptoms associated with depressed mood. An adequate understanding of the relationship between the two variables is important in providing appropriate management. The comorbid presence of depression and pain has also been well established in the pain literature [27] and in a number of other chronic conditions.[28–30] For example, Appelros [31] reported that among patients with first ever stroke, depression was significantly linked to pain. Similarly, among acute stroke patients, pain has been associated with depression.[32,33] In the general pain population it is well known that worsening pain tends to exacerbate depressive symptoms. Thus, treatment to reduce both issues is typically prioritized by health care providers; often treatment of depression
with pharmacotherapy significantly improves patients’ perception of pain as well.[27] Future studies should examine potential reductions in depressive symptoms through the use of pain management techniques in combination with treatment for depression,[34] within a post-stroke population. Unexpectedly, our study indicated that patients who were currently receiving rehabilitation therapy were more likely to experience depressive symptoms than those who were not. This finding does not necessarily reflect the patients’ level of disability as there was no significant association between FIMÔ scores and depressive symptoms. Hypothetically, this finding could reflect patients’ perception of their disability and functional status since, to be referred for therapy, patients need to express functioning concerns to their physician. Furthermore, mood concerns may affect how patients’ view their progress. Gillan et al. [35] reported individuals with depression attending inpatient rehabilitation participated in therapy for longer periods of time than those without depression. Stroke patients with depression have also been found to participate less during the rehabilitation process, negatively impacting their progress and ultimate outcomes.[36] In a sample of patients with acquired brain injuries, those with high depressive symptoms underestimated their abilities while patients’ with fewer depressive symptoms overestimated their abilities.[37] This perception of progress and impairment may provide an explanation for the relationship between therapy involvement and depressive symptoms among stroke patients in our study. Certainly, more research is needed to assess the factors that mediate and moderate the association between attending therapy and increased depressive symptoms. Finally, nicotine use was a significant predictor of depressive symptoms in our study population, comparative to previous stroke literature.[38] In a recent study involving a sample of patients who had experienced a minor stroke, current smoking was a predictor of late onset PSD.[38] It has been suggested that the relationship between smoking and depression may be cyclical in that depression can lead to smoking while smoking is
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
48
J. VERMEER ET AL.
also a predictor of depression. Smoking was the only modifiable lifestyle factor that was significantly correlated to increased depressive symptoms in this study and is one of the few modifiable variables linked to depressive symptoms in stroke patients. This highlights the importance of health education regarding nicotine use to improve patient well-being in terms of mood and prevention for secondary stroke.[39] Implementing and referring patients to smoking cessation programs may be one strategy to reduce the negative outcomes associated with smoking.
in the chronic phase of stroke, can positively influence the rehabilitative process and decrease symptoms of depression.[41] Nonetheless, mood concerns and associated factors need to be promptly recognized and addressed by a health care professional.
Limitations
Disclosure statement
While the current study extends previous research on correlates of depression in stroke patients attending outpatient rehabilitation, a retrospective research design has inherent limitations. Given that this study included a single site of outpatients, this decreases the generalizability of the findings. Further, patients’ depressive symptoms were based on PHQ-9 scores with mild to severe symptoms being identified rather than a formal diagnosis of depression. Using a cutoff score of 5 to indicate cases of patients with at least mild depressive symptoms may have resulted in a sample of patients eliciting much fewer symptoms of depression than studies using diagnostic criteria to define depression. Nonetheless, our findings based on the PHQ-9 tool are largely consistent with research from studies that applied a diagnostic criteria to define major depression.[38] Due to the subjective nature of the PHQ-9, overlap might exist between symptoms that contribute directly to stroke and common symptoms of depression (e.g. fatigue). It is possible that the PHQ-9 may be insensitive in reflecting these discrepancies among stroke patients, although this should be further explored in the stroke rehabilitation literature.[40] Additionally, patients excluded from PHQ-9 screening, such as those with impairments preventing them from displaying capacity to understand the PHQ-9, may limit the generalizability of our findings.
None declared. We would like to gratefully acknowledge Allergan Inc., who provided an unrestricted educational grant, and the Department of Physical Medicine and Rehabilitation, Schulich School of Medicine and Dentistry, Western University.
Conclusion Our findings suggest that a number of factors that impact depressive symptoms in the acute phase of stroke are also shown to be significant in the latter phases of stroke recovery. While stroke deficits are often considered in isolation from other factors, our study provides a holistic perspective of stroke deficits and lifestyle factors that influence depressive symptoms. Being cognizant of factors significantly associated with PSD can identify high-risk patients. Interventions proven to be effective in improving mood, when implemented
Acknowledgements We would like to thank Angela Woolner RN, BScN CNN(c), a Registered Nurse in the Parkwood Institute Outpatients Department, for her help in implementing the standardized stroke form.
References [1] American Psychiatric Association AP. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington (VA): American Psychiatric Association; 2013. [2] Ayerbe L, Ayis S, Wolfe CD, et al. Natural history, predictors and outcomes of depression after stroke: systematic review and meta-analysis. Br J Psychiatry. 2013;202:14–21. [3] Brown C, Hasson H, Thyselius V, et al. Post-stroke depression and functional independence: a conundrum. Acta Neurol Scand. 2012;126:45–51. [4] Ayerbe L, Ayis S, Rudd AG, et al. Natural history, predictors, and associations of depression 5 years after stroke: the South London Stroke Register. Stroke. 2011;42:1907–1911. [5] Morrison V, Pollard B, Johnston M, et al. Anxiety and depression 3 years following stroke: demographic, clinical, and psychological predictors. J Psychosom Res. 2005;59:209–213. [6] Fatoye FO, Mosaku SK, Komolafe MA, et al. Depressive symptoms and associated factors following cerebrovascular accident among Nigerians. J Ment Health. 2009;18:224–232. [7] Caeiro L, Ferro JM, Santos CO, et al. Depression in acute stroke. J Psychiatry Neurosci. 2006;31:377–383 [8] Sagen U, Finset A, Moum T, et al. Early detection of patients at risk for anxiety, depression and apathy after stroke. Gen Hosp Psychiatry. 2010;32:80–85. [9] Lindsey MPGG, Bayley M, Hill MD, et al. Canadian stroke best practice recommendations overview and methodology. Groups ObotCSBPACaW, editor. Ottawa (ON): Heart and Stroke Foundation, Canada; 2014. [10] Wulsin L, Alwell K, Moomaw CJ, et al. Lifetime depression and post-stroke depressive symptoms as predictors of stroke outcomes at 12 months. Philadelphia (PA): Lippincott Williams & Wilkins; 2008. p. 639–640. [11] Kwok T, Lo RS, Wong E, et al. Quality of life of stroke survivors: a 1-year follow-up study. Arch Phys Med Rehabil. 2006;87:1177–1182.
Downloaded by [Australian Catholic University] at 08:14 09 October 2017
DEPRESSION IN A STROKE OUTPATIENT CLINIC
[12] Morris PL, Robinson RG, Andrzejewski P, et al. Association of depression with 10-year poststroke mortality. Am J Psychiatry. 1993;150:124–129 [13] Morris PL, Robinson RG, Samuels J. Depression, introversion and mortality following stroke. Aust N Z J Psychiatry. 1993;27:443–449. [14] Health NCCfM. The NICE guideline on the management and treatment of depression in adults (updated edition). London, UK: National Institute for Health and Clinical Excellence; 2010. [15] Ramasubbu R, Robinson RG, Flint AJ, et al. Functional impairment associated with acute poststroke depression. J Neuropsychiatry Clin Neurosci. 1998;10:26–33. [16] Salter KL, Foley NC, Zhu L, et al. Prevention of poststroke depression: does prophylactic pharmacotherapy work? J Stroke Cerebrovasc Dis. 2013;22:1243–1251. [17] Keith RA, Granger CV, Hamilton BB, et al. The functional independence measure: a new tool for rehabilitation. Adv Clin Rehabil. 1987;1:6–18. [18] Hobart JC, Lamping DL, Freeman JA, et al. Evidencebased measurement: which disability scale for neurologic rehabilitation? Neurology. 2001;57:639–644. [19] Kwon S, Hartzema AG, Duncan PW, et al. Disability measures in stroke: relationship among the Barthel Index, the Functional Independence Measure, and the Modified Rankin Scale. Stroke. 2004;35:918–923. [20] Nasreddine ZS, Phillips NA, Bedirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53:695–699. [21] Spitzer RL, Kroenke K, Williams JB, Group PHQPCS. Validation and utility of a self-report version of PRIMEMD: the PHQ primary care study. JAMA. 1999;282:1737–1744. [22] Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49:1373–1379. [23] De Ryck A, Fransen E, Brouns R, et al. Poststroke depression and its multifactorial nature: results from a prospective longitudinal study. J Neurol Sci. 2014;347:159–166. [24] Hackett ML, Anderson CS. Predictors of depression after stroke: a systematic review of observational studies. Stroke. 2005;36:2296–2301. [25] Hosking SG, Marsh NV. Predictors of depression at one year post-stroke in older adults. Brain Impairment. 2013;14:381–391. [26] Hommel M, Carey L, Jaillard A. Depression: cognition relations after stroke. Int J Stroke. 2015;10:893–896. [27] Bair MJ, Robinson RL, Katon W, et al. Depression and pain comorbidity: a literature review. Arch Intern Med. 2003;163:2433–2445.
49
[28] Amtmann D, Askew RL, Kim J, et al. Pain affects depression through anxiety, fatigue, and sleep in multiple sclerosis. Rehabil Psychol. 2015;60:81–90 [29] Rogers H, Brotherton H, de Luis A, et al. Depressive symptoms are independently associated with pain perception in Colombians with rheumatoid arthritis. Acta Reumatol Port. 2014;40:40–49. [30] Kwakkenbos L, van Lankveld WG, Vonk MC, et al. Diseaserelated and psychosocial factors associated with depressive symptoms in patients with systemic sclerosis, including fear of progression and appearance selfesteem. J Psychosom Res. 2012;72:199–204. [31] Appelros P. Prevalence and predictors of pain and fatigue after stroke: a population-based study. Int J Rehabil Res. 2006;29:329–333. [32] Lee AC, Tang SW, Yu GK, et al. Incidence and predictors of depression after stroke (DAS). Int J Psychiatry Clin Pract. 2007;11:200–206. [33] Kouwenhoven SE, Gay CL, Bakken LN, et al. Depressive symptoms in acute stroke: a cross-sectional study of their association with sociodemographics and clinical factors. Neuropsychol Rehabil. 2013;23:658–677. [34] Goesling J, Clauw DJ, Hassett AL. Pain and depression: an integrative review of neurobiological and psychological factors. Curr Psychiatry Rep. 2013;15:421. DOI: 10.1007/ s11920-013-0421-0. [35] Gillen R, Tennen H, McKee TE, et al. Depressive symptoms and history of depression predict rehabilitation efficiency in stroke patients. Arch Phys Med Rehabil. 2001;82:1645– 1649. [36] Sinyor D, Amato P, Kaloupek D, et al. Post-stroke depression: relationships to functional impairment, coping strategies, and rehabilitation outcome. Stroke. 1986;17:1102–1107. [37] Smeets SM, Ponds RW, Wolters Grego´rio G, et al. Impaired awareness of deficits in individuals with neuropsychiatric symptoms after acquired brain injury: associations with treatment motivation and depressive symptoms. Neuropsychology. 2014;28:717–725 [38] Shi Y, Xiang Y, Yang Y, et al. and others. Depression after minor stroke: prevalence and predictors. J Psychosom Res. 2015;79:143–147. [39] Bak S, Sindrup SH, Alslev T, et al. Cessation of Smoking After first-ever stroke: a follow-up study. Stroke a followup study. Stroke. 2002;33:2263–2269. [40] de Coster L, Leentjens AF, Lodder J, et al. The sensitivity of somatic symptoms in post-stroke depression: a discriminant analytic approach. Int J Geriatr Psychiatry. 2005;20:358–362. [41] Mehta S, Pereira S, Janzen S, et al. Effectiveness of psychological interventions in chronic stage of stroke: a systematic review. Top Stroke Rehabil. 2012;19:536–544.
