Quality of life after stroke: a longitudinal analysis of a cluster randomized trial

Orman, Zhomart; Thrift, Amanda G; Olaiya, Muideen T.; Ung, David; Cadilhac, Dominique A.; Phan, Thanh G.; Nelson, Mark; Srikanth, Velandai; Vuong, Jason; Bladin, Christopher; Gerraty, Richard; Fitzgerald, Sharyn M.; Frayne, Judith; Kim, Joosup

doi:10.1007/s11136-021-03066-y

Cited by 10 publications

(11 citation statements)

References 47 publications

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“…When mHealth was used as the intervention, a reduction in both depression and anxiety was reported [ 26 , 27 , 29 , 30 , 32 , 33 , 35 , 36 , 38 , 39 , 41 , 43 , 45 - 50 , 53 , 55 , 56 ]. The same can be said for telemedicine [ 25 , 28 , 31 , 40 , 44 , 51 , 52 ], and mostly for telephone intervention [ 34 , 37 , 42 , 54 ]. Only 1 of each telephone [ 34 ] intervention and telemonitoring [ 57 ] intervention had no effect on depression or anxiety.…”

Section: Resultsmentioning

confidence: 97%

“…A total of 11 themes and 2 individual observations were identified by the reviewers for a total of 48 occurrences in the literature, whereas 11 themes and 7 observations were noted for a total of 95 observations. In the 33 studies analyzed, 26 (79%) showed an improvement in symptoms of depression [ 25 , 26 , 28 - 33 , 35 - 37 , 40 - 44 , 46 - 52 , 54 - 56 ], while 19 (58%) showed an improvement in anxiety [ 26 - 33 , 36 , 38 - 40 , 44 - 46 , 53 - 56 ]. Only 11/33 (33%) reported that at least one symptom was not statistically significant when compared with results from the control group, but the improvement was still noted [ 25 - 28 , 30 , 36 , 40 , 41 , 44 , 51 , 55 ].…”

Section: Resultsmentioning

confidence: 99%

“…Only 11/33 (33%) reported that at least one symptom was not statistically significant when compared with results from the control group, but the improvement was still noted [ 25 - 28 , 30 , 36 , 40 , 41 , 44 , 51 , 55 ]. As many as 7/33 (21%) showed an increase in quality of life [ 36 , 41 , 44 , 49 , 54 , 56 , 57 ], and 5 (15%) showed an increase in mental well-being, cognitive flexibility, or confidence [ 45 - 47 , 49 , 57 ]. A total of 4 themes emerged that each appeared 4/33 times (12%): decreased distress (body image or COVID-19 distress) [ 30 , 36 , 43 , 53 ], increased sleep (less sleep disturbance or sleep-related impairment) [ 26 , 45 , 47 , 50 ], increased self-efficacy [ 41 , 42 , 44 , 57 ], and the intervention had no effect on depression [ 27 , 34 , 39 , 57 ].…”

Section: Resultsmentioning

confidence: 99%

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Leveraging Mobile Health to Manage Mental Health/Behavioral Health Disorders: Systematic Literature Review

Kruse¹,

Betancourt²,

Gonzales³

et al. 2022

JMIR Ment Health

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Background Mental health is a complex condition, highly related to emotion. The COVID-19 pandemic caused a significant spike in depression (from isolation) and anxiety (event related). Mobile Health (mHealth) and telemedicine offer solutions to augment patient care, provide education, improve symptoms of depression, and assuage fears and anxiety. Objective This review aims to assess the effectiveness of mHealth to provide mental health care by analyzing articles published in the last year in peer-reviewed, academic journals using strong methodology (randomized controlled trial). Methods We queried 4 databases (PubMed, CINAHL [Cumulative Index to Nursing and Allied Health Literature], Web of Science, and ScienceDirect) using a standard Boolean search string. We conducted this systematic literature review in accordance with the Kruse protocol and reported it in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 checklist (n=33). Results A total of 4 interventions (mostly mHealth) from 14 countries identified improvements in primary outcomes of depression and anxiety as well as in several secondary outcomes, namely, quality of life, mental well-being, cognitive flexibility, distress, sleep, self-efficacy, anger, decision conflict, decision regret, digestive disturbance, pain, and medication adherence. Conclusions mHealth interventions can provide education, treatment augmentation, and serve as the primary modality in mental health care. The mHealth modality should be carefully considered when evaluating modes of care. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42022343489; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=343489

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Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Leveraging Mobile Health to Manage Mental Health/Behavioral Health Disorders: Systematic Literature Review

Kruse¹,

Betancourt²,

Gonzales³

et al. 2022

JMIR Ment Health

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“…The methodology, primary outcome, and secondary analyses of this trial have been published 6,[15][16][17] . There were 35 covariates (features) available for analyses including demographic, social, anxiety, depression and education status (9 variables), dietary and alcohol intake (8 variables), stroke risk factors (9 variables), blood and urine electrolytes (8 variables) and FRS.…”

Section: Datamentioning

confidence: 99%

Framingham risk score prediction at 12 months in the STANDFIRM randomised control trial

Phan,

Srikanth,

Cadilhac

et al. 2023

Preprint

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BackgroundThe Shared Team Approach between Nurses and Doctors For Improved Risk factor Management (STANDFIRM, ACTRN12608000166370) trial was designed to test the effectiveness of chronic disease care management for modifying the Framingham risk score (FRS) among patients with stroke or transient ischemic attack. The primary outcome of change in FRS between baseline and 12 months was not met. We aimed to determine characteristics of participants at baseline that predict reduction in FRS at 12 months and whether future FRS is predetermined at the time of randomizationMethodData included 35 variables encompassing demographics, risk factors, psychological, social and education status, and laboratory tests. Five supervised machine learning (ML) methods were used: random forest (RF), extreme gradient boosting (XGBoost), support vector regression (SVR), multilayer perceptron artificial neural network (MLP) and K-nearest neighbor (KNN). We split data for training (80%, n=406) and testing (20%, n=102).ResultsTraining and test data were evenly matched for age, sex, baseline and 12-month FRS. Following tuning of the five ML methods, the optimal model for predicting FRS at 12 months was SVR (R2=0.763, root mean squared error or RMSE=8.52). The five most important variables for SVR were: baseline FRS, age, male sex, sodium/potassium excretion and proteinuria. All ML methods were poor at determining change in FRS at 12 months (R2<0.161).ConclusionOur findings suggest that change in FRS as an endpoint in trials may have limited value as it is largely determined at baseline. In this cohort, Support Vector Regression was the optimal method to predict future but not change in FRS.

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“…Stroke is a leading cause of disability and health burden worldwide [1]. Poststroke rehabilitation and quality of life are often hindered by the presence of depressive symptoms [2,3], so that the effective management and prevention of depression has become an integral part of strategies designed to improve the clinical outcomes of stroke survivors. Antidepressants have been used to prevent and treat clinically significant symptoms of depression after a stroke, and more recently to promote neuro-regeneration and stroke recovery.…”

Section: Introductionmentioning

confidence: 99%

Stroke, depression, and self-harm in later life

Almeida

2023

Current Opinion in Psychiatry

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Purpose of the review To examine recently published results of randomized placebo-controlled trials investigating the clinical effects of selective serotonin reuptake inhibitors on the prevalence of clinically significant symptoms of depression and suicidal ideation after an acute stroke. Recent findings The prevalence of poststroke depression varies markedly according to the approach used to define depression, with recently published data suggesting that about one in every three stroke survivors will experience clinically significant symptoms of depression over a period of 12 months. The proportion of stroke survivors with clinically significant symptoms of depression decreases progressively with time, but in 30% of them symptoms persist or recur over 12 months. Routine daily treatment with 20 mg of fluoxetine for 6 months does not affect the prevalence of depression in this population, nor is it effective at treating or preventing poststroke depressive symptoms. Treatment discontinuation, gastrointestinal adverse effects, seizures and bone fractures are more frequent among stroke survivors treated with antidepressants than placebo. Moreover, current data show that thoughts about death or suicide are more frequent among adults who had a stroke than the general population, although recurring suicidal thoughts are uncommon. Routine daily treatment with 20 mg of fluoxetine for 6 months does not change the proportion of people who disclose suicidal thoughts over a period of 12 months after an acute stroke. Summary Current evidence raises concerns about the efficacy and safety of antidepressants for the management and prevention of poststroke clinically significant symptoms of depression. It is unclear if these findings can be generalized to people with severe strokes or to stroke survivors with moderate to severe major depressive episodes.

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Quality of life after stroke: a longitudinal analysis of a cluster randomized trial

Cited by 10 publications

References 47 publications

Leveraging Mobile Health to Manage Mental Health/Behavioral Health Disorders: Systematic Literature Review

Leveraging Mobile Health to Manage Mental Health/Behavioral Health Disorders: Systematic Literature Review

Framingham risk score prediction at 12 months in the STANDFIRM randomised control trial

Stroke, depression, and self-harm in later life

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