Early screening for post-stroke depression, and the effect on functional outcomes, quality of life and mortality: a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Post-stroke depression (PSD) is a severe complication of cerebrovascular stroke affecting about one-third of stroke survivors. Moreover, PSD is associated with functional recovery and quality of life (QOL) in stroke survivors. Screening for PSD is recommended. There are, however, differences in the literature on the impact of early screening on functional outcomes. In this systematic review, we synthesise the currently available literature regarding the associations between timing and setting of PSD screening and mortality, QOL and functional outcomes in stroke survivors. METHODS AND ANALYSIS: We will systematically search electronic databases including PubMed, Embase, APA PsycINFO, Web of Science, Scopus and CINAHL from inception to August 2021. Four reviewers will screen the title and abstract and full-text level records identified in the search in a blinded fashion to determine the study eligibility. Any selection disagreements between the reviewers will be resolved by the study investigator. Data extraction of eligible studies will be conducted by two reviewers using a predefined template. We will complete the quality assessment of included articles independently by two reviewers using the Newcastle Ottawa Scale. Eventual discrepancies will be resolved by the principal investigator. ETHICS AND DISSEMINATION: Due to the nature of the study design, ethical approval is not required. The systematic review and meta-analysis findings will be published and disseminated in a peer-reviewed journal. Our results will also be disseminated through posters and presentations at appropriate scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42021235993.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.098 | 0.125 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.054 | 0.008 |
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".