RETRACTED: Comparative analysis of pressure ulcer development in stroke patients within and outside healthcare facilities: A systematic review and meta‐analysis
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
The risk of pressure ulcers in stroke patients is a significant concern, impacting their recovery and quality of life. This systematic review and meta-analysis investigate the prevalence and risk factors of pressure ulcers in stroke patients, comparing those in healthcare facilities with those in home-based or non-clinical environments. The study aims to elucidate how different care settings affect the development of pressure ulcers, serving as a crucial indicator of patient care quality and management across diverse healthcare contexts. Following PRISMA guidelines, a comprehensive search was conducted across PubMed, Embase, Web of Science and the Cochrane Library. Inclusion criteria encompassed studies on stroke patients in various settings, reporting on the incidence or prevalence of pressure ulcers. Exclusion criteria included non-stroke patients, non-original research and studies with incomplete data. The Newcastle-Ottawa scale was used for quality assessment, and statistical analyses involved both fixed-effect and random-effects models, depending on the heterogeneity observed. A total of 1542 articles were initially identified, with 11 studies meeting the inclusion criteria. The studies exhibited significant heterogeneity, necessitating the use of a random-effects model. The pooled prevalence of pressure injuries was 9.53% in patients without family medical services and 2.64% in patients with medical services. Sensitivity analysis confirmed the stability of these results, and no significant publication bias was detected through funnel plot analysis and Egger's linear regression test. The meta-analysis underscores the heightened risk of pressure injuries in stroke patients, especially post-discharge. It calls for concerted efforts among healthcare providers, policymakers and caregivers to implement targeted strategies tailored to the specific needs of different care environments. Future research should focus on developing and evaluating interventions to effectively integrate into routine care and reduce the incidence of pressure injuries in stroke patients.
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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 | 0.029 | 0.095 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".