Longitudinal Effects of Left Ventricular Assist Device Implantation on Global and Domain-Specific Cognitive Function
Bibliographic record
Abstract
BACKGROUND: Left ventricular assist devices (LVADs) are a common treatment of advanced heart failure, but cognitive dysfunction, which is common in heart failure, could limit the ability to perform postimplantation LVAD care. Implantation of an LVAD has been associated with improved cerebral perfusion and may improve cognitive function post implantation. OBJECTIVE: The aim of this study was to quantify longitudinal change in cognitive function after LVAD implantation. METHODS: A secondary analysis of data on 101 adults was completed to evaluate cognitive function before implantation and again at 1, 3, and 6 months post implantation of an LVAD. Latent growth curve modeling was conducted to characterize change over time. Serial versions of the Montreal Cognitive Assessment were used to measure overall (total) cognitive function and function in 6 cognitive domains. RESULT: There was moderate, nonlinear improvement from preimplantation to 6 months post implantation in Montreal Cognitive Assessment total score (Hedges' g = 0.50) and in short-term memory (Hedges' g = 0.64). There also were small, nonlinear improvements in visuospatial ability, executive function, and attention from preimplantation to 6 months post implantation (Hedges' g = 0.20-0.28). The greatest improvements were observed in the first 3 months after implantation and were followed by smaller, sustained improvements or no additional significant change. CONCLUSIONS: Implantation of an LVAD is associated with significant, nonlinear improvement in short-term memory and global cognitive function, with the most significant improvements occurring in the first 3 months after implantation. Clinicians should anticipate improvements in cognitive function after LVAD implantation and modify postimplantation education to maximize effectiveness of LVAD self-care.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".