Prevalence of depression and anxiety symptoms after stroke in young adults: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Young adults with stroke have distinct professional and social roles making them vulnerable to symptoms of post-stroke depression (PSD) and post-stroke anxiety (PSA). Prior reviews have examined the prevalence of anxiety and depression in stroke populations. However, there are a lack of studies that have focused on these conditions in young adults. OBJECTIVE: We performed a systematic review and meta-analysis of observational studies that reported on symptoms of PSD, PSA and comorbid PSD/PSA in young adults aged 18 to 55 years of age. METHODS: MEDLINE, EMBASE, SCOPUS and PsycINFO were searched for studies reporting the prevalence of symptoms of PSD and/or PSA in young adults with stroke from inception until June 23, 2023. We included studies that evaluated depression and/or anxiety symptoms with screening tools or interviews following ischemic or hemorrhagic stroke. Validated methods were employed to evaluate risk of bias. RESULTS: 4748 patients from twenty eligible studies were included. Among them, 2420 were also evaluated for symptoms of PSA while 847 participants were evaluated for both PSD and PSA symptoms. Sixteen studies were included in the random effects meta-analysis for PSD symptoms, with a pooled prevalence of 31 % (95 % CI 24-38 %). Pooled PSA symptom prevalence was 39 % (95 % CI 30-48 %) and comorbid PSD with PSA symptom prevalence was 25 % (95 % CI 12-39 %). Varying definitions of 'young adult', combinations of stroke subtypes, and methods to assess PSD and PSA contributed to high heterogeneity amongst studies. CONCLUSIONS: We identified high heterogeneity in studies investigating the prevalence of symptoms of PSD and PSA in young adults, emphasizing the importance of standardized approaches in future research to gain insight into the outcomes and prognosis of PSD and PSA symptoms following stroke in young adults. Larger longitudinal epidemiological studies as well as studies on tailored interventions are required to address the mental health needs of this important population. FUNDING: None.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.029 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".