Influence of socioeconomic status on functional outcomes after stroke: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Despite advances in stroke treatment and rehabilitation, socioeconomic factors have an important impact on recovery from stroke. This review aimed to quantify the impact of socioeconomic status (SES) on functional outcomes from stroke and identify the SES indicators that exhibit the highest magnitude of association. Methods We performed a systematic literature search across Medline and Embase databases up to May 2022, for studies fulfilling the following criteria: observational studies with ≥100, patients aged ≥18 years with stroke diagnosis based on clinical examination or in combination with neuroimaging, reported data on the association between SES and functional outcome, assessed functional outcomes with the modified Rankin Scale (mRS) or Barthel index tools, provided estimates of association (odds ratios [OR] or equivalent), and published in English. Risk of bias was assessed using the modified Newcastle Ottawa Scale. Findings We identified 7,698 potentially eligible records through the search after removing duplicates. Of these, 19 studies (157,715 patients, 47.7% women) met our selection criteria and were included in the meta-analyses. Ten studies (53%) were assessed as low risk of bias. Measures of SES reported were education (11 studies), income (8), occupation (4), health insurance status (3), and neighbourhood socioeconomic deprivation (3). Random-effect meta-analyses revealed low SES was significantly associated with poor functional outcomes: incomplete education or below high school level versus high school attainment and above (OR [95% CI]: 1.66 [1.40, 1.95]), lowest income versus highest income (1.36 [1.02, 1.83], a manual job/unemployed versus a non-manual job/employed (1.62 [1.29, 2.02]), and living in the most disadvantaged socioeconomic neighbourhood versus the least disadvantaged (1.55 [1.25, 1.92]). Low health insurance status was also associated with an increased risk of poor functional outcomes (1.32 [0.95, 1.84]), although not statistically significant. Conclusions Socioeconomic disadvantage remains a risk factor for poor functional outcomes after an acute stroke. Further research is needed to better understand causal mechanisms and disparities. Funding This study is supported by an NHMRC Investigator grant (APP1195237).
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".