Mechanisms underlying neurocognitive dysfunction following critical illness: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Cognitive impairment is a significant healthcare problem globally and its prevalence is projected to affect over 150 million people worldwide. Survivors of critical illness are impacted frequently by long-term neurocognitive dysfunction regardless of presenting illness, but the mechanisms are poorly understood. The goal of this review was to synthesise the existing evidence regarding potential mechanisms underlying neurocognitive dysfunction following critical illness in order to guide potential avenues for future research. METHODS: We performed a systematic search of the literature for studies published between 1 January 1974 and 15 July 2023. We included publications involving adult patients with critical illness due to any aetiology that assessed for cognitive impairment following recovery from illness, and explored or investigated potential underlying causative mechanisms. The quality and risk of bias of the individual studies was assessed using the Newcastle-Ottawa scale. RESULTS: Of the 7658 reviewed references, 37 studies comprising 4344 patients were selected for inclusion. Most studies were single centre with sample sizes of < 100 patients. The proportion of patients with long-term cognitive impairment ranged from 13% to 100%. A wide variety of theoretical mechanisms were explored, with biomarkers and neuroimaging utilised most frequently. Many studies reported associations between investigated mechanisms and reduced cognition; several of these mechanisms have been implicated in other forms of long-term neurodegenerative conditions. Increased levels of inflammatory cytokines during acute illness and white matter hyperintensities on neuroimaging following recovery were the associations reported most commonly. DISCUSSION: The underlying pathophysiology of neurocognitive decline after critical illness is not yet understood fully. The mechanisms implicated in other neurodegenerative conditions suggest that this may represent an accelerated version of the same processes. Large scale studies are required to further elucidate the cause of this significant problem for survivors of critical illness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".