Literature DB >> 23457330

Poststroke fatigue and depression are related to mortality in young adults: a cohort study.

Halvor Naess1, Harald Nyland.   

Abstract

OBJECTIVES: To investigate the relationship between poststroke fatigue and depression and subsequent mortality in young ischaemic stroke patients in a population-based study.
DESIGN: A prospective cohort study.
SETTING: All surviving young ischaemic stroke patients living in Hordaland County. PARTICIPANTS: Young ischaemic stroke patients aged 15-50 years at the time of the stroke were invited to a follow-up on an average 6 years after the index stroke. Psychosocial factors and risk factors were registered. Fatigue was self-assessed by the Fatigue Severity Scale (FSS). Depression was measured by Montgomery-Åsberg Depression Rating Scale (MADRS). INTERVENTION: No intervention was performed. PRIMARY AND SECONDARY OUTCOME MEASURE: Mortality on follow-up.
RESULTS: In total, 190 patients were included. The mean age on follow-up was 48 years and subsequent follow-up period was 12 years. Cox regression analysis showed that mortality was associated with FSS score (p=0.005) after adjusting for age (p=0.06) and sex (p=0.19). Cox regression analysis showed that mortality was associated with MADRS score (p=0.006) after adjusting for age (p=0.10) and sex (p=0.11).
CONCLUSIONS: Both fatigue and depression are associated with long-term mortality in young adults with ischaemic stroke. Depression may be linked to higher mortality because of psychosocial factors and unhealthy lifestyles whereas the link between fatigue and mortality is broader including connection to diabetes mellitus, myocardial infarction and psychosocial factors.

Entities:  

Year:  2013        PMID: 23457330      PMCID: PMC3612756          DOI: 10.1136/bmjopen-2012-002404

Source DB:  PubMed          Journal:  BMJ Open        ISSN: 2044-6055            Impact factor:   2.692


We hypothesised that fatigue and depression are associated with increased mortality in young adults with ischaemic stroke irrespective of stroke severity. On Cox regression analyses both fatigue and depression are associated with long-term mortality in young adults with ischaemic stroke after adjusting for age, sex and stroke severity. Depression may be linked to higher mortality because of psychosocial factors and unhealthy lifestyles whereas the link between fatigue and mortality is broader including a connection to diabetes mellitus, myocardial infarction and psychosocial factors. Strengths include population-based approach and long follow-up period. Limitations include retrospective case finding and no data on cause of death. Outcome after ischaemic stroke is better among young adults than older patients. However, several studies have reported high long-term mortality in young adults with ischaemic stroke as compared to matched controls.1 Factors such as hypertension, alcoholism, coronary heart disease, severe stroke and age have been linked to mortality in young adults with ischaemic stroke.1–3 The study of stroke among young people is important for several reasons. The aetiology of stroke is much more diverse and risk factors for stroke differ between young and old patients and may indicate separate approaches as to treatment. Stroke in young adults provides an opportunity to study stroke in general because of less comorbidity than in old patients. Fatigue has been recognised as a disabling symptom in non-depressed stroke patients.4 Young stroke patients need information on prognosis, including factors related to fatigue or depression, to make informed choices about vocation and employment. Among old stroke patients it has been shown that both fatigue5 and depression6 are associated with mortality. However, little is known about the effect of fatigue or depression on survival in young adults with ischaemic stroke. We present data on the effect of fatigue and depression measured on an average 6 years after the index stroke and subsequent mortality. We hypothesised that fatigue and depression are associated with increased mortality in young adults with ischaemic stroke irrespective of stroke severity.

Method

All patients 15–49 years old with first-ever cerebral infarction from 1988 to 1997 living in Hordaland County were included in a database. An upper limit of 49 years was chosen because these patients have low comorbidity compared with that among older patients and because they still have many years left in the work force. Cerebral infarction was defined in accordance with the Baltimore-Washington Cooperative Young Stroke Study Criteria comprising neurological deficits lasting more than 24 h because of ischaemic lesions or transient ischaemic attacks where CT or MRI showed infarctions related to the clinical findings.7 We excluded patients with cerebral infarction associated with other intracranial diseases such as subarachnoidal haemorrhage, sinus venous thrombosis or severe head trauma. Case-finding was performed retrospectively as described previously.8 Surviving patients were invited to a follow-up investigation in person in our out-clinic department on an average 6 years after the index stroke. On follow-up, data on employment, level of education and marital status were obtained by the authors. Risk factors including alcoholism, smoking, diabetes mellitus and myocardial infarction were registered. Stroke severity was determined by the modified Rankin Scale (mRS), Barthel Index (BI) and Scandinavian Stroke Scale (SSS) on follow-up. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Fatigue was measured by the Fatigue Severity Scale (FSS).9 10 FSS is a nine-item questionnaire that assesses the effect of fatigue on daily living. Each item is a statement on fatigue that the subject rates from 1, ‘completely disagree’ to 7, ‘completely agree’. Examples of the items in the questionnaire are: ‘Fatigue is among my three most disabling symptoms’, ‘Exercise brings on my fatigue’ and ‘I am easily fatigued’. The average score of the nine items represents the FSS score (the minimum score being 1 and maximum 7). Fatigue was defined as FSS score ≥5.11 Depressive symptoms were quantified using Montgomery-Åsberg Depression Rating Scale (MADRS) at the follow-up.12 Poststroke depression (PSD) was defined as MADRS score ≥7.13 14 Subsequent survival state was registered by examining the official population registry by 1 August 2011. The study was approved by the local Ethics committee.

Statistics

Fisher's exact test (categorical variables), Student t test (continuous variables) and pair-wise correlation test were used as appropriate. Cox regression analyses were used for disclosing variable associated with mortality. Kaplan-Meier survival curves grouped by dichotomised FSS (FSS<5 vs ≥5) and MADRS scores (MADRS<7 vs MADRS≥7) were obtained. All tests were two sided. Level of significance was set at p<0.05. STATA V.11.0 was used for analyses.

Results

A total of 232 patients had first-ever ischaemic stroke. At the time of invitation 209 patients were alive and the present study includes 190 patients: 81 (43%) female patients and 109 (57%) male patients. The mean age on follow-up was 48 years. During a subsequent mean follow-up time of 12.4 years 32 (16.8%) patients had died. (The mean total follow-up time since the index stroke was 18 years.) Univariate analyses showed that mortality was associated with factors such as being unmarried, unemployed, alcoholism, diabetes mellitus, myocardical infarction, age, mRS, SSS, BI, MMSE, FSS and MADRS scores (table 1).
Table 1

Characteristics of young ischaemic stroke patients according to survival or death

Dead, n (%)Alive, n (%)p Value
Total32 (17)158 (83)
Male patients22 (20)87 (80)0.17
Female patients10 (12)71 (88)
Unmarried13 (27)36 (73)0.05
Higher education8 (14)48 (86)0.67
Unemployed22 (29)53 (71)<0.001
Alcoholism6 (55)5 (45)0.004
Smoking17 (22)60 (78)0.12
Diabetes mellitus7 (35)13 (65)0.05
Myocardial infarction10 (53)9 (47)<0.001

Mean (SD)Mean (SD)

Age on follow-up51.2 (6.6)47.2 (8.3)0.01
mRS score1.7 (1.1)1.3 (1.0)0.03
SSS score54 (8.4)56 (4.5)0.08
BI96 (13)99 (5)0.04
FSS score4.9 (1.6)4.0 (1.6)0.003
MADRS score7.8 (7.3)4.3 (5.9)0.004
MMSE26.8 (3.6)28.2 (2.1)0.003

BI, Barthel Index; FSS, Fatigue Severity Scale; MMSE, Mini-Mental State Examination; mRS, modified Rankin Scale; MADRS, Montgomery-Åsberg Depression Rating Scale; SSS, Scandinavian Stroke Scale.

Characteristics of young ischaemic stroke patients according to survival or death BI, Barthel Index; FSS, Fatigue Severity Scale; MMSE, Mini-Mental State Examination; mRS, modified Rankin Scale; MADRS, Montgomery-Åsberg Depression Rating Scale; SSS, Scandinavian Stroke Scale. Cox regression analysis showed that mortality was associated with FSS (HR=1.4, CI 1.1 to 1.7, p=0.005) after adjusting for age (p=0.06) and sex (p=0.19). Including BI, mRS or SSS separately did not change these findings. Figure 1 shows Kaplan-Meier survival curves dichotomised for FSS<5 and ≥5.
Figure 1

Kaplan-Meier survival curves dichotomised for FSS<5 and FSS≥5. FSS, Fatigue Severity Scale.

Kaplan-Meier survival curves dichotomised for FSS<5 and FSS≥5. FSS, Fatigue Severity Scale. Cox regression analysis showed that mortality was associated with the MADRS score (HR=1.06, CI 1.02 to 1.11, p=0.006) after adjusting for age (p=0.10) and sex (p=0.11). Including BI, mRS or SSS separately did not change these findings. Figure 2 shows Kaplan-Meier survival curves dichotomised for MADRS<7 and ≥7.
Figure 2

Kaplan-Meier survival curves dictotomised for MADRS<7 & MADRS≥7. MADRS, Montgomery-Åsberg Depression Rating Scale.

Kaplan-Meier survival curves dictotomised for MADRS<7 & MADRS≥7. MADRS, Montgomery-Åsberg Depression Rating Scale. Stepwise Cox regression analyses based on all variables in table 1 showed mortality to be associated with alcoholism (HR=5.3, p=0.001), myocardial infarction (HR=3.0, p= 0.011) and unemployment (HR=2.9, p=0.013) after adjusting for age (p=0.29) and sex (p=0.28). Stepwise Cox regression analyses based on all variables in table 1 excluding alcoholics showed mortality to be associated with diabetes mellitus (HR=3.1, p=0.023), myocardial infarction (HR=4.1, p=0.001) and MADRS score (HR=1.08, p=0.002) after adjusting for age (p=0.32) and sex (p=0.36) (see table 2).
Table 2

Cox regression survival analysis among non-alcoholic young adults with ischaemic stroke

HRCIp Value
Age1.040.97 to 1.10.32
Sex1.50.6 to 3.40.36
Diabetes mellitus3.11.2 to 8.30.023
Myocardial infarction4.11.8 to 9.40.001
MADRS score1.081.03 to 1.130.002

MADRS, Montgomery-Åsberg Depression Rating Scale.

Cox regression survival analysis among non-alcoholic young adults with ischaemic stroke MADRS, Montgomery-Åsberg Depression Rating Scale. Tables 3 and 4 show correlation analyses between MADRS and FSS scores and relevant factors. MADRS was correlated with smoking, alcoholism, being unmarried, unemployment and stroke severity (all p<0.05). FSS was correlated with diabetes mellitus, myocardial infarction, alcoholism, unemployment, depression and stroke severity (all p<0.05). Correlation was the highest between MADRS scores and FSS scores (r=0.60, p<0.001). There was moderately high correlation between FSS scores and unemployment (r=0.31, p<0.001).
Table 3

Montgomery-Åsberg Depression Rating Scale (MADRS) and correlation analyses in young ischaemic stroke patients[colcnt=3]

Correlationp Value
Age0.050.49
Female patients0.070.31
Diabetes mellitus0.080.27
Myocardial infarction0.010.90
Smoking0.150.04
Alcoholism−0.170.02
Married−0.200.007
Employed−0.31<0.001
Higher education−0.120.11
FSS score0.60<0.001
mRS score0.140.05
MMSE−0.080.25

FSS, Fatigue Severity Scale; MMSE, Mini-Mental State Examination; mRS, modified Rankin Scale; MADRS, Montgomery-Åsberg Depression Rating Scale.

Table 4

Fatigue severity scale score and correlation analyses in young ischaemic stroke patients

Correlationp Value
Age0.050.47
Female patients0.060.41
Diabetes mellitus0.130.007
Myocardial infarction0.160.002
Smoking0.070.36
Alcoholism−0.150.003
Married0.130.08
Employed−0.230.002
Higher education−0.110.13
MADRS0.60<0.001
mRS score0.240.001
MMSE−0.080.25

MMSE, Mini-Mental State Examination; mRS, modified Rankin Scale; MADRS, Montgomery-Åsberg Depression Rating Scale.

Montgomery-Åsberg Depression Rating Scale (MADRS) and correlation analyses in young ischaemic stroke patients[colcnt=3] FSS, Fatigue Severity Scale; MMSE, Mini-Mental State Examination; mRS, modified Rankin Scale; MADRS, Montgomery-Åsberg Depression Rating Scale. Fatigue severity scale score and correlation analyses in young ischaemic stroke patients MMSE, Mini-Mental State Examination; mRS, modified Rankin Scale; MADRS, Montgomery-Åsberg Depression Rating Scale.

Discussion

The main findings in the present study were that both fatigue and depression were associated with subsequent long-term mortality irrespective of stroke severity. Consistent with these findings other studies have disclosed that fatigue is associated with mortality in older stroke patients.15 16 Likewise others have reported depression to be associated with mortality in older stroke patients.6 17–19 It is unlikely that fatigue causes death. It is more probable that fatigue is linked to other factors that directly cause death. Consistent with this, fatigue disappeared in the stepwise Cox regression analyses including all variables associated with death on univariate analyses. We found a strong correlation between fatigue and depression. Weaker correlations were found between fatigue and mRS, unemployment, alcoholism, diabetes mellitus and myocardial infarction. Studies including older stroke patients reported poststroke fatigue to be associated with diabetes mellitus and myocardial infarction.15 20 Both diabetes mellitus and myocardial infarction are diseases associated with mortality in young adults with ischaemic stroke.1 It seems likely that the link between fatigue and diseases such as diabetes mellitus and myocardial infarction partially explains the association between fatigue and mortality in young ischaemic stroke patients. This probably also pertains to the link between fatigue and alcoholism. As with fatigue, we found that depression was weakly linked to other factors including unemployment, being unmarried, alcoholism and mRS. However, unlike fatigue, depression was not associated with diabetes mellitus and myocardial infarction. Consistent with our findings another study including older stroke patients disclosed depression on follow-up, which was found to be associated with being unmarried but not with diabetes mellitus and myocardial infarction, whereas there was a correlation between fatigue and myocardial infarction and a trend towards correlation between fatigue and diabetes mellitus.6 15 It is possible that there is a more direct link between depression and mortality than between fatigue and mortality. Possible mechanisms include suicide, alcoholism and less focus on healthy lifestyle. The weak correlation between smoking and depression among our patients hints at the unhealthy lifestyle among depressed patients. On univariate analyses, we found that depression was mostly linked to psychosocial factors whereas fatigue was linked to a wider set of factors including both psychosocial factors and specific diseases such as diabetes mellitus and myocardial infarction. Similar findings have been disclosed among older stroke patients.6 15 This shows that there is a multifactorial basis for poststroke fatigue. Careful investigations are needed to determine the cause of fatigue and target treatment both to improve general health and survival. Depression seems mostly confined to psychosocial factors. Alcoholic abuse should be considered as an unhealthy lifestyle which may need particular attention in depressed patients with ischaemic stroke. We found age to be associated with increased mortality on univariate analysis, but this association disappeared on Cox regression analyses. Others have found increasing age to be associated with higher mortality among young ischaemic stroke patients.2 3 The strengths of this study are the population-based approach and the long-term follow-up period. A weakness is that patient finding was performed retrospectively which may have affected both case finding and case ascertainment. Another weakness is that we have no data on the cause of death or the use of antidepressive medication. Risk factor profile and stroke treatment have changed since 1988–1997, and this should be taken into account while interpreting the results. In conclusion, both fatigue and depression are associated with long-term mortality in young adults with ischaemic stroke. Depression may be linked to higher mortality because of psychosocial factors and unhealthy lifestyles whereas the link between fatigue and mortality is broader including connection to diabetes mellitus, myocardial infarction and psychosocial factors.
  20 in total

1.  Depressive symptoms and increased risk of stroke mortality over a 29-year period.

Authors:  S A Everson; R E Roberts; D E Goldberg; G A Kaplan
Journal:  Arch Intern Med       Date:  1998-05-25

2.  Does the Modified Fatigue Impact Scale offer a more comprehensive assessment of fatigue in MS?

Authors:  N Téllez; J Río; M Tintoré; C Nos; I Galán; X Montalban
Journal:  Mult Scler       Date:  2005-04       Impact factor: 6.312

3.  Depression predicts unfavourable functional outcome and higher mortality in stroke patients: the Bergen Stroke Study.

Authors:  H Naess; L Lunde; J Brogger; U Waje-Andreassen
Journal:  Acta Neurol Scand Suppl       Date:  2010

Review 4.  Fatigue after stroke: a major but neglected issue.

Authors:  F Staub; J Bogousslavsky
Journal:  Cerebrovasc Dis       Date:  2001-08       Impact factor: 2.762

5.  The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus.

Authors:  L B Krupp; N G LaRocca; J Muir-Nash; A D Steinberg
Journal:  Arch Neurol       Date:  1989-10

6.  The Sunnybrook Stroke Study: a prospective study of depressive symptoms and functional outcome.

Authors:  N Herrmann; S E Black; J Lawrence; C Szekely; J P Szalai
Journal:  Stroke       Date:  1998-03       Impact factor: 7.914

7.  Association of depression with 10-year poststroke mortality.

Authors:  P L Morris; R G Robinson; P Andrzejewski; J Samuels; T R Price
Journal:  Am J Psychiatry       Date:  1993-01       Impact factor: 18.112

8.  Interrater reliability of an etiologic classification of ischemic stroke.

Authors:  C J Johnson; S J Kittner; R J McCarter; M A Sloan; B J Stern; D Buchholz; T R Price
Journal:  Stroke       Date:  1995-01       Impact factor: 7.914

9.  Psychiatric aspects of diabetes mellitus.

Authors:  D H Surridge; D L Erdahl; J S Lawson; M W Donald; T N Monga; C E Bird; F J Letemendia
Journal:  Br J Psychiatry       Date:  1984-09       Impact factor: 9.319

10.  Incidence and short-term outcome of cerebral infarction in young adults in western Norway.

Authors:  H Naess; H I Nyland; L Thomassen; J Aarseth; G Nyland; K-M Myhr
Journal:  Stroke       Date:  2002-08       Impact factor: 7.914

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  19 in total

1.  Post-stroke fatigue as an indicator of underlying bioenergetics alterations.

Authors:  N Jennifer Klinedinst; Rosemary Schuh; Steven J Kittner; William T Regenold; Glenn Kehs; Christine Hoch; Alisha Hackney; Gary Fiskum
Journal:  J Bioenerg Biomembr       Date:  2019-01-07       Impact factor: 2.945

2.  Stroke in young adults: Five new things.

Authors:  Nirav Bhatt; Amer M Malik; Seemant Chaturvedi
Journal:  Neurol Clin Pract       Date:  2018-12

3.  Analysis of young ischemic stroke patients in northeast China.

Authors:  Jiao-Jiao Ge; Ying-Qi Xing; Hong-Xiu Chen; Li-Juan Wang; Li Cui
Journal:  Ann Transl Med       Date:  2020-01

Review 4.  Atrial Fibrillation in the Young: A Neurologist's Nightmare.

Authors:  Nikhil Aggarwal; Subothini Selvendran; Claire E Raphael; Vassilios Vassiliou
Journal:  Neurol Res Int       Date:  2015-04-02

5.  Prevalence of fatigue in patients 3 months after stroke and association with early motor activity: a prospective study comparing stroke patients with a matched general population cohort.

Authors:  Thorlene Egerton; Anne Hokstad; Torunn Askim; Julie Bernhardt; Bent Indredavik
Journal:  BMC Neurol       Date:  2015-10-06       Impact factor: 2.474

Review 6.  Factors Associated with Poststroke Fatigue: A Systematic Review.

Authors:  Amélie Ponchel; Stéphanie Bombois; Régis Bordet; Hilde Hénon
Journal:  Stroke Res Treat       Date:  2015-05-25

7.  Influence of Medication on Fatigue Six Months after Stroke.

Authors:  Amélie Ponchel; Julien Labreuche; Stéphanie Bombois; Christine Delmaire; Régis Bordet; Hilde Hénon
Journal:  Stroke Res Treat       Date:  2016-06-19

8.  Poststroke Fatigue Is Related to Motor and Cognitive Performance: A Secondary Analysis.

Authors:  Hui-Ting Goh; Jill C Stewart
Journal:  J Neurol Phys Ther       Date:  2019-10       Impact factor: 3.649

9.  Cardiorespiratory responses to exercise related to post-stroke fatigue severity.

Authors:  Kazuaki Oyake; Yasuto Baba; Yuki Suda; Jun Murayama; Ayumi Mochida; Yuki Ito; Honoka Abe; Kunitsugu Kondo; Yohei Otaka; Kimito Momose
Journal:  Sci Rep       Date:  2021-06-17       Impact factor: 4.379

10.  Self-Reported Fatigue and Associated Factors Six Years after Stroke.

Authors:  Marie Elf; Gunilla Eriksson; Sverker Johansson; Lena von Koch; Charlotte Ytterberg
Journal:  PLoS One       Date:  2016-08-30       Impact factor: 3.240

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