Journal of Psychosomatic Research 173 (2023) 111466
Contents lists available at ScienceDirect
Journal of Psychosomatic Research
journal homepage: www.elsevier.com/locate/jpsychores
Trajectories of post-stroke quality of life and long-term prognosis: Results
from an eleven-year prospective study
Meijing Hu, Baiyang Zhang, Yidie Lin, Minghan Xu, Cairong Zhu *
Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People's Republic of
China
A R T I C L E I N F O
A B S T R A C T
Keywords:
Stroke
Quality of life
Prognosis
Trajectory
Purpose: The relationship between quality of life (QoL) and long-term prognosis in stroke patients is still unclear.
We explored physical and mental QoL trajectories during the first six months after stroke and determined the
associations between trajectories and long-term prognosis in patients with first-ever ischemic stroke.
Methods: Included were 733 participants from a prospective study. QoL was assessed with the 12-item Short Form
Survey (SF-12) at baseline, 3 and 6 months. Patients' prognoses (stroke recurrence and death) were identified
from 2010 to 2021. The latent class growth model (LCGM) was used to identify distinct trajectories of physical
and mental QoL measured over the first 6 months. We employed the Cox model or Fine-Gray model for prognoses
to examine the associations between QoL trajectories and prognosis.
Results: Five trajectories of physical QoL and five trajectories of mental QoL were identified. For physical QoL of
the Poor-Improved, and Moderate-Impaired trajectory versus Moderate-Improved trajectory, the hazard ratio
(HR) for death was 2.39 (1.14 to 5.02), and 2.03(0.93 to 4.44); the HR for recurrence was 1.56 (0.83 to 2.94) and
2.33 (1.28 to 4.24). For mental QoL of the Moderate-Impaired trajectory versus the Moderate-Improved tra­
jectory, the HR for death was 2.48 (1.21 to 5.07). The results were robust in the sensitivity analysis.
Conclusion: QoL during the first six months after ischemic stroke can be categorized into distinct groups. Change
in QoL was associated with long-term survival. Secondary prevention of recurrent strokes might rely more on
improving patients' physical QoL.
1. Introduction
Stroke is a leading cause of death and disability worldwide [1,2].
Poor quality of life (QoL) was reported in stroke survivors due to chal­
lenges like loss of economic sources, disability, and mental difficulties
such as depressive symptoms [3]. Compromised QoL in stroke survivors
is one of the causes that stroke is regarded as an essential public health
problem [4,5]. The support of health personnel and family members can
help stroke survivors improve their QoL, including physical, mental, and
social aspects [6]. Assessing the QoL for patients in the hospital and
survivors living at home might be necessary, which helps healthcare
providers ensure that survivors receive adequate community support
and medical services to improve their health.
In the early stage of stroke, QoL is an appropriate prognostic risk
determination tool for planning post-stroke therapy strategies. A short
follow-up study proposed that the poor QoL of patients three months
after stroke was related to the low 1-year survival rate [7]. The corre­
lation between QoL and survival after stroke was limited because pa­
tients' QoL was investigated at a certain time, resulting in the loss of data
information. There has been a growing body of studies evaluating the
average change of QoL among individuals with first-ever stroke but
reaching inconsistent conclusions. Some studies investigated QoL with a
follow-up period of up to 6 months post-stroke and found an improve­
ment in QoL [8–10]. Another study reported different results; substan­
tial gains in QoL during inpatient stroke rehabilitation were followed by
declines six months after discharge [11]. A possible explanation of this
disparity is the presence of heterogeneity in longitudinal change pat­
terns of post-stroke QoL, and the averaged data masked subgroup in­
formation on QoL changes over time in prior studies. As far as we know,
some scholars found QoL of stroke patients in the Netherlands [12] and
Italy [13] has changed and can be divided into different trajectories. The
QoL of stroke patients in different socioeconomic environments have
* Corresponding author at: Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan
University, NO.16 Renmin South Road, Chengdu, Sichuan 610041, People's Republic of China.
E-mail address: cairong.zhu@hotmail.com (C. Zhu).
https://doi.org/10.1016/j.jpsychores.2023.111466
Received 25 November 2022; Received in revised form 14 August 2023; Accepted 15 August 2023
Available online 18 August 2023
0022-3999/© 2023 Elsevier Inc. All rights reserved.
M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
different heterogeneous trajectories, but the trajectory pattern of stroke
patients in upper-middle-income countries is still unclear. Besides, with
the progress of stroke treatment and management, more stroke patients
can survive the disease, and the importance of knowledge of the longterm prognosis of health also increases [14]. The evidence on the cor­
relation between QoL and the long-term prognosis of patients with firstepisode stroke is still insufficient.
In this context, we hypothesized that QoL trajectory patterns exist in
Chinese stroke patients and that these patterns have prognostic signifi­
cance for the risk of subsequent events. Our study objectives were to (1)
establish a plausible QoL trajectory pattern within the first six months of
stroke patients and (2) elucidate the association of QoL trajectories with
subsequent clinical events, including all-cause death and recurrent
stroke, until the end of follow-up.
and stroke characteristics (TOAST (Trial of Org 10,172 in Acute Stroke
Treatment), mRS score > 1 at arrival, side of brain damage). Marital
status was divided into two groups, married (in marriage, separated)
and single (divorced, widowed, or never married). The classification of
smoking or drinking status was based on the question, “Were you a
regular smoker/drinker before the stroke?”. Physical activity was clas­
sified according to “Did you participate in physical activity at least once
a week for one year before the stroke?”. Following the TOAST criteria,
all patients with ischemic stroke were further classified into different
stroke subtypes: large-artery atherosclerosis (LAA), cardio-embolism
(CE), small-artery occlusion (SAO), other determined etiology (SOE),
and undetermined etiology. In the study, the proportion of strokes due to
other identified or unidentified causes (i.e., interlayer or other causes)
was deficient (only 4 individuals), similar to the previous study [24].
Only three categories of TOAST (LAA, SAO and CE) were included in our
study. Side of brain damage includes LHD (left hemisphere damage),
RHD (right hemisphere damage), BHD (bilateral hemisphere damage),
and Other (side of brain damage is uncertain).
2. Materials and methods
2.1. Participants and procedures
Patients diagnosed with first-ever ischemia stroke in the Department
of Neurology of West China Hospital of Sichuan University from January
2010 to December 2019 were recruited and followed up to September
2021. Patients were diagnosed according to WHO criteria in combina­
tion with a CT scan and/or MRI [15]. Iatrogenic stroke, such as carotid
endarterectomy, cardiac surgery, or angioplasty, and patients with se­
vere cognitive impairment or in critical were excluded.
One thousand one hundred twenty-seven stroke patients were
included in the participating centers during the study period. For
analytical purposes, 394 respondents were excluded for the following
reasons: (1) Repeated or invalid enrollment (n = 14), (2) Non-first-ever
ischemic stroke (n = 90), (3) TOAST is classified as an interlayer or other
reasons (n = 4), (4) Missing values for relevant covariates (n = 59), (5)
No follow-up at 3 and 6 months (n = 186), and (6) Recurrence or death
in the first 6 months (n = 41). The remaining 733 patients for whom the
baseline data sets were complete and at least one reassessment of QoL
were conducted were included in the final analyses.
2.3. Survey method
Trained graduate students in epidemiology and health statistics are
employed as staff for baseline collection and telephone follow-up. The
survey included demographic characteristics, health-related behaviors,
vascular risk factors, and stroke characteristics. At least four people will
visit the ward weekly for a baseline survey. The investigator will explain
the study's purpose and significance and introduce the questionnaire's
contents to the patients and their families. After questionnaire collection
is completed, the survey team will exchange questionnaires for review. If
there are incomplete or unclear questionnaires, they should return to the
ward immediately to complete the questionnaires. Patients were fol­
lowed up by phone every three months. The score of the SF-12 (Chinese
version of the 12-item short-form survey; version 2) and the self-report
prognosis (ischemia stroke recurrence and death events) were collected.
The survey team exchanged questionnaires for review, and if incomplete
or unclear questionnaires were found, the patient or family should be
contacted again, and the questionnaires continued to be completed.
Double data entry and validation were done using EpiData software.
2.2. Measures
2.2.1. QoL
The 12-item Short Form Survey (SF-12) has good reliability and
validity [16], which is reliable and sensitive for the Chinese population
[17,18], and has been widely used to assess the quality of life of stroke
patients [19,20]. The 12-item Short Form Survey performs similarly to
the MOS 36-item Short Form Survey (SF-36) [21–23]. It is built with
questions extracted from the eight dimensions of SF-36, but the
completion time is effectively shortened. The SF-12 includes 12 items
about health status and eight health dimensions: Physical function (PF);
Role-Physical (RP); Bodily Pain (BP); General Health (GH); Vitality (VT);
Social Functioning (SF); Role-Emotional (RE) and Mental Health (MH).
According to the American scoring method, two summary scores can be
calculated, physical component score (PCS) and mental component
score (MCS). Scores above or below 50 are above or below the general
population's mean.
2.4. Statistical analysis
Continuous variables were represented as Mean ± SD and Median
(quartiles), and categorical variables were represented as percentages.
We adopted a group-based trajectory modeling approach through the
TRAJ procedure in SAS software, version 9.4 (SAS Institute, Inc), to
identify trajectories of PCS and MCS during the first 6 months after
stroke. This special form of finite mixture modeling fixes the slope and
the intercept to equality across individuals within a trajectory. This
approach permits all available data to be included in the estimated
model, assuming the data were missing randomly. The longitudinal QoL
data were fitted by a maximum likelihood method as a mixture of
multiple latent trajectories in a censored normal model with a poly­
nomial function of time [25].
We evaluated each trajectory's growth factor (intercept, linear, or
quadratic) to obtain the optimal polynomial function forms describing
the dynamic QoL change. The best-fitting model is selected by
comparing the Bayesian information criterion (BIC) and the Akaike in­
formation criterion (AIC). The model with a lower BIC value and AIC
value fits better. In addition, the proportion of each trajectory member
needs to be considered to ensure the rationality of the analysis. Each
trajectory should hold an approximate trajectory membership proba­
bility of at least 3 % [26,27]. Average posterior probabilities (APP) of
trajectory membership >0.70 are taken to indicate that the modeled
trajectories are individuals with similar patterns of change and
discriminate between individuals with distinct patterns of change.
Once the distinct trajectories of physical QoL and mental QoL were
2.2.2. Outcome events
Outcome events were all-cause death and recurrent stroke. If the
patient relapse repeatedly, the survival time of the recurrent is based on
the first recurrence time. Outcome events were collected through
structured telephone interviews by trained investigators.
2.2.3. Covariates
Covariates included demographic characteristics (age, sex, marital
status, education level, annual household income), health-related be­
haviors (smoking status, drinking status, physical activity), vascular risk
factors (BMI, hypertension, diabetes, hyperlipidemia, heart disease),
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M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
determined, the Kruskal-Wallis and Chi-square tests were conducted to
explore the difference in individual characteristics between distinct
trajectories. Cox multivariate model was used to examine the association
between QoL trajectories and all-cause mortality. The Fine-Gray model
examined the association between trajectories and stroke recurrence,
which was applied to correct the possible bias caused by competing risks
of death on stroke recurrence [28]. Models included physical trajec­
tories, mental trajectories, and the covariates mentioned above. We
started with the unadjusted models and continued to the multivariable
models by gradually adding covariates.
Sensitivity analyses were performed to test the robustness of the
results. We reconstructed trajectory models by including individuals
with all three visits of QoL measures at baseline, 3, and 6 months and
duplicated the Cox multivariate model and Fine-Gray model analyses.
Data analyses were performed using software programs SAS 9.4 (SAS
Institute, Inc), and statistical significance was set at P < 0.05 (2-tailed)
throughout.
Table 1
Baseline Characteristics and Outcomes of Included Subjects (N = 733).
Categories
Variables
Demographics
Age (years)
Mean ± SD
Median(Q1,Q3)
3. Results
3.1. Participants' characteristics
Health-related
behaviors
A total of 733 patients with ischemic stroke met the pre-defined
eligibility criteria (Fig. S1). The all-cause mortality and stroke recur­
rence rates during follow-up were 139(19%) and 155(21.2%). The me­
dian follow-up time was 57 months, and the maximum follow-up time
was up 138 months. The average age was 61.25 ± 12.99 years, of which
61.7% were men. Table 1 describes the baseline characteristics and
outcomes of included subjects.
Vascular risk factors
3.2. Trajectories of QoL
The specified models considered equally spaced time points. The
results of the fit indices for the models with 1–6 physical trajectories are
given in Table 2. The 5-trajectory model (1 intercept and 4 quadratic)
(Table S1) with physical QoL is the most superior according to BIC, AIC,
and average posterior probability: The Persistently Poor trajectory
(14.9%) represents those with consistently low scores; the PoorImproved trajectory (20.5%) refers to those whose scores were similar
to the Persistently Poor trajectory at initial presentation but steadily
increased; the Poor-Acutely Improved trajectory (28.7%) indicates those
who initially performance with similar score levels to the Persistently
Poor trajectory but with a sharp increase; the Moderate-Impaired tra­
jectory (13.2%) indicates those who scored the same as the ModerateImproved trajectory at initial presentation but declined; and the
Moderate-Improved trajectory (22.8%) indicated those who scored
slightly below 50 at initial presentation but had a sustained increase to
above 50 (Fig. 1 and Supplementary Table S2).
The results of the fit indices for the models with 1–6 mental QoL
trajectories are given in Table 3. The 5-trajectory model (1 intercept and
4 quadratic) (Table S3) with mental QoL is superior: The Poor-Improved
trajectory (9.5%) refers to those who scored low at the initial presen­
tation but steadily increased to near 50; the Moderate-Impaired trajec­
tory (5.2%) indicates those who scored slightly below 50 at first
presentation but consistently declined; the Moderate-Improved trajec­
tory (33.4%) indicated those who scored slightly below 50 at initial
presentation but had a sustained increase to above 50; the GoodImpaired trajectory (23.9%) indicates those who had scores levels
similar to the Persistently Good trajectory at initial presentation but
declined; and the Persistently Good trajectory (28.0%) those whose
scores had remained stable at about 58 (Fig. 2 and Supplementary
Table S4).
Stroke characteristics
Stroke outcomes
Sex, n (%)
Male
Female
Marital status, n (%)
Married
Single
Educational level, n (%)
≤6 years
7–9 years
10–12 years
≥12 years
Annual household income, n
(%)
≤￥20,000
￥20,001≥￥50,000
Smoking status, n (%)
No
Yes
Drinking status, n (%)
No
Yes
Physical activity, n (%)
No
Yes
BMI (kg/m2)
Mean ± SD
Median(Q1,Q3)
Hypertension, n (%)
No
Yes
Diabetes, n (%)
No
Yes
Hyperlipidemia, n (%)
No
Yes
Heart disease, n (%)
No
Yes
TOAST, n (%)
LAA
SAO
CE
mRS score > 1 at arrival, n (%)
No
Yes
Side of brain damage, n (%)
LHD
RHD
BHD
Other
Recurrent, n (%)
No
Yes
Mortality, n (%)
No
Yes
Values
61.25 ± 12.99
62.00(53.00,
71.00)
452(61.7)
281(38.3)
641(87.4)
92(12.6)
262(35.7)
216(29.5)
134(18.3)
121(16.5)
219(29.9)
300(40.9)
214(29.2)
417(56.9)
316(43.1)
445(60.7)
288(39.3)
392(53.5)
341(46.5)
23.9 ± 4.2
23.7(21.3, 26)
278(37.9)
455(62.1)
518(70.7)
215(29.3)
500(68.2)
233(31.8)
571(77.9)
162(22.1)
388(52.9)
243(33.2)
102(13.9)
169(23.1)
564(76.9)
244(33.3)
233(31.8)
106(14.5)
150(20.5)
578(78.9)
155(21.2)
594(81.0)
139(19.0)
SD: standard deviation; Q1: first quartile; Q3: third quartile; BMI: body mass
index; TOAST: trial of org 10,172 in acute stroke treatment; LAA: large-artery
atherosclerosis; SAO: small-artery occlusion; CE: cardio-embolism; mRS: modi­
fied rankin score; LHD: left hemisphere damage; RHD: right hemisphere dam­
age; BHD: bilateral hemisphere damage; Other: side of brain damage is
uncertain.
in each trajectory group for physical and mental QoL. The physical
Moderate-Improved group was relatively younger (median, 59 years)
with a high proportion of SAO (37.1%), and the group had the lowest
proportion of mRS score > 1 at arrival (34.7%). The mental Persistently-
3.3. Trajectory sub-population characteristics
Table 4 and Table 5 display the baseline characteristics of individuals
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M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
Persistently Poor trajectory, HR: 2.19 (95% CI:1.10,4.34) p = 0.02; in
the Moderate-Impaired trajectory of physical QoL, HR: 2.33 (95% CI:
1.28,4.24) p = 0.01. The increased risk of recurrence in the PoorImproved trajectory and the Poor-Acutely Improved trajectory of
physical QoL was not observed, HR: 1.56 (95% CI: 0.83,2.94) p = 0.17
and 1.35 ((95% CI: 0.75,2.44) p = 0.32. None of the mental trajectories
showed an association with recurrence.
Table 2
Fit statistics for trajectories of physical QoL.
Number of
classes
BIC
AIC
Class proportion
APP
1
2
3
− 8125.92
− 7870.73
− 7808.33
− 8116.73
− 7854.64
− 7785.35
100%
33.8%, 66.2%
29.1%, 37.5%,33.4%
4
− 7774.16
− 7739.69
5
¡7732.00
¡7690.62
13.8%, 31.0%, 24.6%,
30.7%
14.9%, 13.2%,
20.5%, 28.7%, 22.8%
6
− 7739.03
− 7695.35
1
0.91, 0.94
0.89, 0.81,
0.85
0.88, 0.81,
0.81, 0.87
0.89, 0.77,
0.80, 0.82,
0.88
0.89, 0.76,
0.80, 0.84,
0.88
14.9%, 13.6%, 20.3%,
30.8%, 20.3%, 0.0%
3.5. Sensitivity analyses
The shape of each trajectory and the proportion of the sample
included varied slightly due to changes in sample size (n = 666) (Sup­
plementary Fig. S2, Fig. S3), the point estimates of QoL are shown in
Table S5 and Table S6. Trends in quality-of-life changes in each trajec­
tory and the association of each trajectory with prognosis remained
consistent with the primary analysis (Supplementary Table S7).
BIC: Bayesian information criteria; AIC: Akaike's information criterion; APP:
average posterior probability.
4. Discussion
Good age group was similar to others (median, 62 years). This group had
the highest proportion of SAO (45.4%), and the group had the relatively
lower proportion of mRS score > 1 at arrival (67.8%).
Our study suggests distinct trajectories for both physical and mental
QoL in stroke patients during the first six months. We identified five
physical trajectories: Persistently Poor, Poor-Improved, Poor-Acutely
3.4. Trajectories of QoL after stroke and long-term prognosis
Table 3
Fit statistics for trajectories of mental QoL.
Patients' physical QoL trajectories and mental QoL trajectories
showed different associations with all-cause mortality risk (Table 6).
Compared to the Moderate-Improved trajectory of physical QoL, the risk
of death was increased in the Persistently Poor trajectory, HR: 2.78 (95%
CI: 1.25,6.19) p = 0.01; in the Poor-Improved trajectory of physical QoL,
HR: 2.39 (95% CI: 1.14,5.02) p = 0.02. The increased risk of death in the
Poor-Acutely Improved trajectory of physical QoL was not observed, HR:
1.53 (95% CI: 0.74,3.19) p = 0.25. Increased risk of death was not
observed in the Moderate-Impaired trajectory of physical QoL after
adjustment for recurrence, HR: 2.03 (95% CI: 0.93,4.44) p = 0.08. The
risk of death was significantly increased in the Moderate-Impaired tra­
jectory of mental QoL, HR: 2.48 (95% CI: 1.21,5.07) p = 0.01. An
increased risk of death in the other mental trajectories was not observed.
Patients' physical QoL trajectories showed different associations with
stroke recurrence (Table 6). Compared to the Moderate-Improved tra­
jectory of physical QoL, the risk of recurrence was increased in the
Number of
classes
BIC
AIC
Class proportion
APP
1
2
3
− 7848.85
− 7753.21
− 7706.53
− 7841.95
− 7734.82
− 7681.24
4
− 7691.21
− 7659.03
5
¡7665.47
¡7624.10
100%
14.7%, 85.3%
12.4%, 13.9%,
73.7%
4.2%, 15.8%,
18.1%, 61.8%
5.2%, 9.5%, 23.9%,
33.4%, 28.0%
6
− 7664.09
− 7620.41
1
0.84, 0.95
0.86, 0.78,
0.90
0.79, 0.75,
0.79, 0.87
0.90, 0.77,
0.78, 0.73,
0.78
0.78, 0.98,
0.82, 0.70,
0.69, 0.79
7.0%, 1.0%, 9.3%,
18.6%, 30.4%,
33.8%
BIC: Bayesian information criteria; AIC: Akaike's information criterion; APP:
average posterior probability.
Fig. 1. Trajectory grouping of physical QoL during the first 6 months for 733 participants. QoL means quality of life.
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M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
Fig. 2. Trajectory grouping of mental QoL during the first 6 months for 733 participants. QoL means quality of life.
physical health.
Change in QoL was associated with long-term survival. Failure of the
physical QoL score to return to 50 may be associated with an increased
risk of all-cause death in patients with first-ever stroke - but only one of 2
trajectory patterns was associated with an increased risk of death. The
Poor-Improved trajectory failed to return to the general population level
at six months. The risk of all-cause death was increased compared with
the Moderate-Improved trajectory. In previous studies on the long-term
outcome of stroke, stroke patients with physical difficulties such as poor
physical function [37] or physical pain [38]have a higher risk of death.
On the other hand, patients with Moderate-Impaired trajectory have not
poor basic physical QoL, and the risk of all-cause mortality did not in­
crease (Table 6 and Supplementary Table S7). In a study focusing on the
long-term outcome after stroke, the 7-year mortality rate of patients who
were judged to be moderately disabled at three months did not increase
compared with patients without disabilities [39]. It may be related to
the fact that the neurological impairments scores of the two groups of
patients at baseline were not poor, which is consistent with our result.
The decrease in mental score to a low level is related to the increased risk
of all-cause death in stroke patients. The score of the Moderate-Impaired
trajectory was moderate at baseline and decreased to about 30 at six
months. The risk of all-cause death increased compared with the
Moderate-Improved trajectory. Past studies have shown that patients
with impaired mental health, such as depression, insufficient energy,
and other mental health diagnoses after stroke, have a higher mortality
rate [40,41]. Patients with impaired mental health are difficult to get out
of the attack of illness, which is bad for the long-term prognosis of
patients.
The prevention of recurrent strokes might rely more on improving
patients' physical QoL. Compared with the Moderate-Improved trajec­
tory, the physical Moderate-Impaired trajectory has an increased risk of
recurrence, but the mental Moderate-Impaired trajectory did not show
an increased risk of recurrence. We did not observe that the risk of
recurrence of any mental trajectory was higher than that of the control
trajectory. Previous studies have reported that the prevalence of poststroke anxiety is 25%, and the association between 3-month anxiety
and stroke recurrence was not significant during the 10-year follow-up
period [42]. Some studies with limited time data (<2 years) have
linked post-stroke depression (PSD) with recurrence rates [43,44], but
results are not entirely consistent in longer-term and larger sample-size
Improved, Moderate-Impaired, and Moderate-Improved. Trajectories
identified for mental QoL were: Poor-Improved, Moderate-Impaired,
Moderate-Improved, Good-Impaired, and Persistently Good. Short-term
improvement in QoL can translate into substantial benefits for the longterm survival of patients. Interventions focused on stroke survivors with
impaired physical QoL may reduce poststroke recurrence.
The evolution of the health status of stroke patients is often un­
known, especially in the first six months after stroke. The study showed
that patients' QoL changed in the first six months after stroke and was
more stable after three months. It was aligned with the recovery time
frame of physical functions and activities after stroke. Most functional
recovery occurs in the first six months after stroke, and the recovery
reaches the plateau stage three to six months after stroke [29]. Mental
adaptation was in accord with the time frame of healing of physical
functions. The tremendous benefits of recovery after injury occur within
a limited time window, which can be supported by animal research
evidence. An ischemic injury will trigger a series of genetic, molecular,
cellular, and electrophysiological events that promote nerve recovery
[30,31]. The QoL monitoring conducted by health care providers for
patients in the first six months after stroke can obtain sufficient health
information to help hospitalized or discharged patients. Still, these data
have not been routinely collected [32].
Resilience is common; treatment is still needed, especially the re­
covery of physical health. It can be found by observing the trajectory of
physical and mental trajectories that many patients showed a positive
promotion and finally maintained a high level. Bonanno et al. proposed
that most people can deal with trauma well [33], which was consistent
with our results; trajectories were mainly characterized by recovery and
resilience [33]. We also observed low and descent QoL trajectories,
which made up about 30% of our total patients, which was in keeping
with Mierlo at el (30–37%) [12]. There is no decline in stroke patients
from Italy, because they focus on survivors with low to moderate dis­
abilities [13]. The mental QoL of stroke patients seems to recover well.
Scores of mental QoL (MCS) after stroke are comparable to that in the
general population (50 is the score for the general population), whereas
scores of physical QoL (PCS) are worse at the six months (the plateau
stage), which is consistent with the results of previous studies focusing
on QoL for a longer time [34–36]. In order to achieve a substantial
improvement in quality of life, patients still need continuous efforts and
appropriate treatment, with a particular focus on the recovery of
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M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
Table 4
Patients' characteristics by trajectories of physical QoL (N = 733).
Characteristic
Age (years)
Mean ± SD
Median(Q1,Q3)
Sex, n (%)
Male
Female
Marital status, n (%)
Married
Unmarried
Educational level, n (%)
≤6 years
7–9 years
10–12 years
≥12 years
Annual household income,
n (%)
≤￥20,000
￥20,001≥￥50,000
Smoking status, n (%)
No
Yes
Drinking status, n (%)
No
Yes
Physical activity, n (%)
No
Yes
BMI (kg/m2)
Mean ± SD
Median(Q1,Q3)
Hypertension, n (%)
No
Yes
Diabetes, n (%)
No
Yes
Hyperlipidemia, n (%)
No
Yes
Heart disease, n (%)
No
Yes
TOAST, n (%)
LAA
SAO
CE
mRS score > 1 at arrival, n
(%)
No
Yes
Side of brain damage, n (%)
LHD
RHD
BHD
Other
Recurrent, n (%)
No
Yes
Mortality, n (%)
No
Yes
Trajectories of physical QoL
Persistently Poor(n =
109)
Poor-Improved(n =
150)
Poor-Acutely Improved (n
= 210)
Moderate-Impaired(n
= 97)
Moderate-Improved (n
= 167)
65.67 ± 12.78
65.00(56.00,77.00)
62.50 ± 11.51
63.00(56.00,69.00)
60.17 ± 13.31
61.50(50.00,71.00)
61.88 ± 13.10
63.00(54.00,72.00)
58.25 ± 13.10
59.00(49.00,68.00)
45(41.3)
64(58.7)
93(62.0)
57(38.0)
143(68.1)
67(31.9)
62(63.9)
35(36.1)
109(65.3)
58(34.7)
84(77.1)
25(22.9)
134(89.3)
16(10.7)
182(86.7)
28(13.3)
87(89.7)
10(10.3)
154(92.2)
13(7.8)
52(47.7)
26(23.9)
18(16.5)
13(11.9)
59(39.3)
45(30.0)
27(18.0)
19(12.7)
75(35.7)
63(30.0)
39(18.6)
33(15.7)
30(30.9)
37(38.1)
17(17.5)
13(13.4)
46(27.5)
45(26.9)
33(19.8)
43(25.7)
38(34.9)
38(34.9)
33(30.3)
49(32.7)
72(48.0)
29(19.3)
55(26.2)
86(41.0)
69(32.9)
38(39.2)
37(38.1)
22(22.7)
39(23.4)
67(40.1)
61(36.5)
80(73.4)
29(26.6)
84(56.0)
66(44.0)
106(50.5)
104(49.5)
51(52.6)
46(47.4)
96(57.5)
71(42.5)
79(72.5)
30(27.5)
91(60.7)
59(39.3)
117(55.7)
93(44.3)
64(66.0)
33(34.0)
94(56.3)
73(43.7)
53(48.6)
56(51.4)
89(59.3)
61(40.7)
113(53.8)
97(46.2)
49(50.5)
48(49.5)
88(52.7)
79(47.3)
23.6 ± 4.1
23.4(20.8,26)
23.7 ± 4
23.9(21.2,25.5)
24.2 ± 5.1
23.6(21.3,26)
23.7 ± 3.9
23.3(21.1,25.6)
24.1 ± 3.5
23.9(21.8,26.3)
37(33.9)
72(66.1)
65(43.3)
85(56.7)
67(31.9)
143(68.1)
39(40.2)
58(59.8)
70(41.9)
97(58.1)
73(67.0)
36(33.0)
106(70.7)
44(29.3)
151(71.9)
59(28.1)
70(72.2)
27(27.8)
118(70.7)
49(29.3)
80(73.4)
29(26.6)
108(72)
42(28.0)
142(67.6)
68(32.4)
62(63.9)
35(36.1)
108(64.7)
59(35.3)
76(69.7)
33(30.3)
112(74.7)
38(25.3)
166(79.0)
44(21.0)
81(83.5)
16(16.5)
136(81.4)
31(18.6)
66(60.6)
26(23.9)
17(15.6)
85(56.7)
37(24.7)
28(18.7)
103(49.0)
84(40.0)
23(11.0)
47(48.5)
34(35.1)
16(16.5)
87(52.1)
62(37.1)
18(10.8)
P
value*
<0.001
<0.001
0.004
0.01
0.01
0.003
0.03
0.48
0.64
0.13
0.91
0.38
0.08
0.02
<0.001
3(2.8)
106(97.2)
5(3.3)
145(96.7)
25(11.9)
185(88.1)
27(27.8)
70(72.2)
109(65.3)
58(34.7)
31(28.4)
41(37.6)
13(11.9)
24(22.0)
45(30)
47(31.3)
21(14.0)
37(24.7)
67(31.9)
65(31.0)
32(15.2)
46(21.9)
39(40.2)
30(30.9)
15(15.5)
13(13.4)
62(37.1)
50(29.9)
25(15.0)
30(18.0)
80(73.4)
29(26.6)
116(77.3)
34(22.7)
168(80.0)
42(20.0)
68(70.1)
29(29.9)
146(87.4)
21(12.6)
76(69.7)
33(30.3)
109(72.7)
41(27.3)
179(85.2)
31(14.8)
76(78.4)
21(21.6)
154(92.2)
13(7.8)
0.60
0.01
<0.001
SD: standard deviation; Q1: first quartile; Q3: third quartile; QoL: quality of life; BMI: body mass index; TOAST: trial of org 10,172 in acute stroke treatment; LAA:
large-artery atherosclerosis; SAO: small-artery occlusion; CE: cardio-embolism; mRS: modified rankin score; LHD: left hemisphere damage; RHD: right hemisphere
damage; BHD: bilateral hemisphere damage; Other: side of brain damage is uncertain.
*
Chi-square tests for categorical variables and Kruskal-Wallis tests for continuous variables.
studies [45,46]. Depression (HR: 1.68 (1.07 to 2.63)) was reported to be
associated with stroke recurrence in a 12-year follow-up study, but no
variables representing physical health (the degree of disability, self-care
ability, etc) were included in the multivariate model [45]. In another
study, the Barthel index, which determine the basic activities of daily
living ability of stroke patients, was included in the adjusted model, and
no association was found between patients with depression at three
months (HR: 0.98 (0.60 to 1.62)) and the risk of recurrence 5 years later,
6
M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
Table 5
Patients' characteristics by trajectories of mental QoL (N = 733).
Characteristic
Age (years)
Mean ± SD
Median(Q1,Q3)
Sex, n (%)
Male
Female
Marital status, n (%)
Married
Unmarried
Educational level, n (%)
≤6 years
7–9 years
10–12 years
≥12 years
Annual household income, n
(%)
≤￥20,000
￥20,001≥￥50,000
Smoking status, n (%)
No
Yes
Drinking status, n (%)
No
Yes
Physical activity, n (%)
No
Yes
BMI (kg/m2)
Mean ± SD
Median(Q1,Q3)
Hypertension, n (%)
No
Yes
Diabetes, n (%)
No
Yes
Hyperlipidemia, n (%)
No
Yes
Heart disease, n (%)
No
Yes
TOAST, n (%)
LAA
SAO
CE
mRS score > 1 at arrival, n
(%)
No
Yes
Side of brain damage, n (%)
LHD
RHD
BHD
Other
Recurrent, n (%)
No
Yes
Mortality, n (%)
No
Yes
Trajectory of mental QoL
Poor-Improved (n =
70)
Moderate-Impaired (n
= 38)
Moderate-Improved (n =
245)
Good-Impaired (n =
175)
Persistently Good(n =
205)
60.14 ± 13.78
61.00(52.00,68.00)
65.37 ± 13.79
66.50(56.00,79.00)
60.54 ± 12.58
61.00(50.00,70.00)
62.26 ± 12.21
63.00(55.00,72.00)
60.85 ± 13.61
62.00(53.00,71.00)
38(54.3)
32(45.7)
24(63.2)
14(36.8)
157(64.1)
88(35.9)
101(57.7)
74(42.3)
132(64.4)
73(35.6)
59(84.3)
11(15.7)
32(84.2)
6(15.8)
215(87.8)
30(12.2)
150(85.7)
25(14.3)
185(90.2)
20(9.8)
31(44.3)
22(31.4)
10(14.3)
7(10.0)
9(23.7)
12(31.6)
10(26.3)
7(18.4)
79(32.2)
82(33.5)
51(20.8)
33(13.5)
69(39.4)
49(28.0)
31(17.7)
26(14.9)
74(36.1)
51(24.9)
32(15.6)
48(23.4)
19(27.1)
26(37.1)
25(35.7)
11(28.9)
14(36.8)
13(34.2)
65(26.5)
118(48.2)
62(25.3)
61(34.9)
61(34.9)
53(30.3)
63(30.7)
81(39.5)
61(29.8)
37(52.9)
33(47.1)
20(52.6)
18(47.4)
141(57.6)
104(42.4)
102(58.3)
73(41.7)
117(57.1)
88(42.9)
44(62.9)
26(37.1)
23(60.5)
15(39.5)
152(62.0)
93(38.0)
114(65.1)
61(34.9)
112(54.6)
93(45.4)
37(52.9)
33(47.1)
23(60.5)
15(39.5)
133(54.3)
112(45.7)
92(52.6)
83(47.4)
107(52.2)
98(47.8)
23.2 ± 4.1
22.9(20.5,25)
25.1 ± 5.4
24.5(21.3,27.4)
24.0 ± 4.4
23.7(21.1,26.1)
23.8 ± 4
23.5(21.3,25.7)
24.0 ± 3.9
23.9(21.9,26)
31(44.3)
39(55.7)
13(34.2)
25(65.8)
90(36.7)
155(63.3)
57(32.6)
118(67.4)
87(42.4)
118(57.6)
49(70.0)
21(30.0)
28(73.7)
10(26.3)
167(68.2)
78(31.8)
117(66.9)
58(33.1)
157(76.6)
48(23.4)
47(67.1)
23(32.9)
25(65.8)
13(34.2)
170(69.4)
75(30.6)
123(70.3)
52(29.7)
135(65.9)
70(34.1)
54(77.1)
16(22.9)
24(63.2)
14(36.8)
184(75.1)
61(24.9)
144(82.3)
31(17.7)
165(80.5)
40(19.5)
47(67.1)
11(15.7)
12(17.1)
21(55.3)
8(21.1)
9(23.7)
124(50.6)
76(31.0)
45(18.4)
103(58.9)
55(31.4)
17(9.7)
93(45.4)
93(45.4)
19(9.3)
12(17.1)
58(82.9)
6(15.8)
32(84.2)
52(21.2)
193(78.8)
33(18.9)
142(81.1)
66(32.2)
139(67.8)
27(38.6)
20(28.6)
17(24.3)
6(8.6)
15(39.5)
13(34.2)
8(21.1)
2(5.3)
88(35.9)
66(26.9)
34(13.9)
57(23.3)
55(31.4)
58(33.1)
24(13.7)
38(21.7)
59(28.8)
76(37.1)
23(11.2)
47(22.9)
58(82.9)
12(17.1)
32(84.2)
6(15.8)
186(75.9)
59(24.1)
138(78.9)
37(21.1)
164(80.0)
41(20.0)
57(81.4)
13(18.6)
23(60.5)
15(39.5)
205(83.7)
40(16.3)
143(81.7)
32(18.3)
166(81.0)
39(19.0)
P
value*
0.16
0.40
0.56
0.06
0.23
0.92
0.29
0.91
0.26
0.24
0.23
0.88
0.07
<0.001
0.01
0.01
0.60
0.02
SD: standard deviation; Q1: first quartile; Q3: third quartile; QoL: quality of life; BMI: body mass index; TOAST: trial of org 10,172 in acute stroke treatment; LAA:
large-artery atherosclerosis; SAO: small-artery occlusion; CE: cardio-embolism; mRS: modified rankin score; LHD: left hemisphere damage; RHD: right hemisphere
damage; BHD: bilateral hemisphere damage; Other: side of brain damage is uncertain.
*
Chi-square tests for categorical variables and Kruskal-Wallis tests for continuous variables.
which was consistent with the results of this study [46]. Mental health
may not be an independent risk factor for the recurrence of stroke pa­
tients. The omission of physical variables in the multivariable model
overestimates the correlation between mental state and recurrence of
stroke patients and requires the attention of researchers.
To our knowledge, this is the first study to identify trajectories of
physical and mental QoL in the first six months after stroke and to
determine the associations between distinct trajectories of QoL and long7
M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
Table 6
The associations between trajectory groups of QoL and prognosis after stroke.
Mortality, HR (95%CI)
Trajectories of
physical QoL
Persistently Poor
Poor-Improved
Poor-Acutely
Improved
ModerateImpaired
ModerateImproved
Trajectories of
mental QoL
Poor-Improved
ModerateImpaired
ModerateImproved
Good-Impaired
Persistently Good
Recurrent, HR (95%CI)
Model 1
Model 2
Model 3
Model 4
Model 5
Model 1
Model 2
Model 3
Model 4
4.26
(2.17,8.35)
3.46
(1.85,6.49)
1.91
(0.996,3.66)
2.71
(1.34,5.48)
3.24
(1.59,6.57)
2.86
(1.50,5.45)
1.74
(0.91,3.36)
2.38
(1.15,4.92)
3.15
(1.55,6.37)
2.85
(1.49,5.46)
1.73
(0.90,3.35)
2.45
(1.18,5.11)
2.87
(1.29,6.34)
2.40
(1.15,5.01)
1.52
(0.74,3.15)
2.24
(1.04,4.84)
2.78
(1.25,6.19)
2.39
(1.14,5.02)
1.53
(0.74,3.19)
2.03
(0.93,4.44)
2.40
(1.34,4.30)
1.62
(0.93,2.85)
1.43
(0.85,2.43)
2.50
(1.43,4.39)
2.19
(1.17,4.08)
1.50
(0.84,2.66)
1.43
(0.83,2.46)
2.30
(1.28,4.13)
2.20
(1.18,4.11)
1.50
(0.84,2.68)
1.39
(0.81,2.39)
2.27
(1.26,4.1)
2.19
(1.10,4.34)
1.56
(0.83,2.94)
1.35
(0.75,2.44)
2.33
(1.28,4.24)
Referent
Referent
Referent
Referent
Referent
Referent
Referent
Referent
Referent
1.31
(0.69,2.48)
2.76
(1.47,5.19)
1.37
(0.71,2.64)
2.14
(1.09,4.22)
1.38
(0.71,2.69)
2.37
(1.18,4.78)
1.12
(0.56,2.24)
2.28
(1.12,4.66)
1.19
(0.60,2.39)
2.48
(1.21,5.07)
0.65
(0.35,1.2)
0.50
(0.22,1.18)
0.69
(0.37,1.30)
0.54
(0.24,1.26)
0.70
(0.37,1.31)
0.54
(0.24,1.25)
0.79
(0.42,1.46)
0.63
(0.27,1.45)
Referent
Referent
Referent
Referent
Referent
Referent
Referent
Referent
Referent
1.06
(0.66,1.71)
1.03
(0.66,1.62)
1.02
(0.63,1.66)
1.09
(0.68,1.73)
1.11
(0.68,1.82)
1.15
(0.72,1.83)
1.1
(0.67,1.80)
1.18
(0.73,1.90)
1.15
(0.70,1.88)
1.23
(0.76,2.00)
0.77
(0.51,1.15)
0.71
(0.48,1.07)
0.74
(0.49,1.13)
0.69
(0.45,1.06)
0.72
(0.47,1.10)
0.71
(0.46,1.10)
0.72
(0.47,1.09)
0.70
(0.44,1.09)
Model 1 is unadjusted.
Model 2 is adjusted for age, sex, marital status, education level, annual household income, smoking status, drinking status, physical activity.
Model 3 is plus adjusted for BMI, hypertension, diabetes, hyperlipidemia, heart disease.
Model 4 is plus adjusted for TOAST, mRS score > 1 at arrival, side of brain damage.
Model 5 is plus adjusted for recurrent.
QoL: quality of life; HR: hazard ratio; CI: confidence interval.
term prognosis in Chinese patients with first-ever ischemic stroke.
Stroke survivors face multiple obstacles after a stroke, may lack physical
activity, and be accompanied by mental trauma. Therefore, it is neces­
sary to cooperate with the medical team and home care to provide early
mobilization and continuous mental care for stroke survivors to prevent
the deterioration of the condition and obtain an excellent long-term
prognosis. This study had several limitations. First, data were
collected from a single center in China, limiting the findings' general­
izability to other countries. However, this is one of the few prospective
studies focusing on stroke patients with a large sample size, effective
information, and long-term follow-up. Furthermore, we controlled for
all observed influences as much as possible, but some important factors
still affect patients' QoL, such as pre-stroke depression. Finally, some
covariates rely entirely on self-reported data, and family members
answering questions that some patients could not do may lead to in­
formation bias. Even with these biases, this study is enough to make us
realize that the QoL has not been fully utilized. More research is needed
to explore the value of this indicator in influencing clinical decisionmaking and policy-making for stroke patients.
Contributors
MH, BZ, CZ designed the study. YL, MH, MX and BZ collected part of
the data. MH and BZ conducted the analysis. All authors critically
revised the manuscript for important intellectual content critically.
Funding
This research was supported by grants from National Natural Science
Foundation of China (grant no. 30600511, no. 81673273, and no.
82173618, http://www.nsfc.gov.cn/). The funders had no role in study
design, data collection and analysis, decision to publish, or preparation
of the manuscript. The funding agreement ensured the authors' inde­
pendence in designing the study.
Ethics approval
The study protocol was approved by the Ethics Committee of the
West China Hospital, Sichuan University, Chengdu, China (ethical
approval number, “2009 year 50”).
5. Conclusion
Patient consent
The present study identified five distinct trajectories of physical and
mental QoL. Most people can deal with trauma well and show physical
and mental health recovery. Interventions that promote physical health
and avoid deterioration of mental health during the first six months
positively impact long-term survival. Secondary prevention of recurrent
strokes relies more on improving patients' physical QoL. The routine
data collection of QoL can enable medical care providers to understand
the changes in the health status of survivors and provide needed medical
services promptly, such as prompt return to the hospital immediately,
adjusting the medication plan, and others. It has reference significance
for cost-benefit research of stroke treatment, health care planning pol­
icies, and research.
All patients had signed informed consent before the baseline survey.
We confirmed that all methods were performed in accordance with
relevant guidelines and regulations.
Provenance and peer review
Not commissioned; externally peer reviewed.
Declaration of Competing Interest
The authors have no competing interests to report.
8
M. Hu et al.
Journal of Psychosomatic Research 173 (2023) 111466
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We thank all patients, and healthcare professionals involved.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.jpsychores.2023.111466.
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