100 Prevalence of Cognitive Impairment in Vascular Surgery Patients: Preliminary Results of A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Introduction Single-centre studies have shown a high prevalence of undiagnosed cognitive impairment in patients undergoing vascular surgery. The aim of this meta-analysis was to estimate the pooled prevalence of cognitive impairment in vascular surgery patients. Methods A systematic review and meta-analysis was performed of studies reporting cognitive impairment in vascular surgery patients (PROSPERO registration: CRD42019134684). Databases searched included: Medline, Embase, Emcare, CINAHL, PsychINFO and Scopus. Studies were excluded if they: did not use a validated cognitive assessment tool, included patients with asymptomatic or sub-threshold (for treatment) disease, or excluded patients with cognitive impairment. Quality of included studies was assessed using Newcastle-Ottawa scores (NOS), risk of bias was assessed using the ROBINS-E tool, and quality of evidence assessed using GRADE criteria. A pooled estimate of prevalence was calculated using the inverse-variance method separately for carotid artery disease (CAD), lower extremity arterial disease (LEAD), and studies including patients with multiple vascular surgery presentations. Data were pooled using random effects models and estimated prevalence presented with 95% confidence intervals (95%CI). Subgroup analyses were performed by cognitive assessment tool used. Authors of 24 studies meeting inclusion criteria that did not report numbers of cognitively impaired patients were contacted to enable inclusion: responses are awaited. Results After de-duplication of search results, 7,169 records were screened and 11 studies (911 patients) included in the meta-analysis. Nine studies were deemed high quality (NOS ≥7) however 8 studies had a serious risk of bias. Only one study explicitly stated provision for recruiting patients without capacity. Six different tools were used to assess cognitive function (MoCA, MMSE, ACE-R, HDS-R, Mini-Cog and a global cognitive score). Two studies found an association of cognitive impairment with post-op delirium whilst one did not, and a further study showed an association with increased length of stay. Pooled estimate of prevalence of cognitive impairment in CAD patients was 38% (95%CI 17%, 62%; 7 studies), and in “vascular surgery patients” was 61% (95%CI 47%, 74%, 3 studies). Only one study reported prevalence of cognitive impairment in LEAD patients alone of 19% (95%CI 14%, 24%). Quality of evidence was moderate to very low. Conclusions Cognitive impairment is highly prevalent in vascular surgery patients highlighting the need for close collaboration between vascular surgeons and geriatricians.
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 | 0.029 | 0.061 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.047 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".