Cigarette Smoking as a Risk Factor for Delirium in Hospitalized and Intensive Care Unit Patients. A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Active smokers are prevalent in hospitalized and critically ill patients. Cigarette smoking and nicotine withdrawal may increase delirium in these populations. This systematic review aims to determine whether active cigarette smoking increases the risk for delirium in hospitalized and intensive care unit (ICU) patients. METHODS: A systematic search of English-, Spanish-, and French-language articles published from 1966 to April 2013 was performed. Studies were included if they measured cigarette smoking as a risk factor and delirium as an outcome in adult hospitalized or ICU patients. Methodologic quality of studies was assessed using both the validated Newcastle Ottawa Scale and an additional evidence-based quality rating scale. RESULTS: A total of 14 cohort studies of surgical and ICU populations were included in the review. No studies in non-ICU inpatients were identified. The incidence of delirium ranged from 9 to 52%, and the prevalence of active smokers ranged from 9 to 44%. The quality of assessment for active smoking varied widely. None of the studies used biochemical measures to determine cigarette smoke exposure. Of the six studies restricting the smoking group to active smokers only, active smoking was independently associated with delirium in one study, trended toward an association in one study, and showed a dose response in one study. Quantitative summary measures were not calculated due to study heterogeneity and missing data. CONCLUSIONS: There is currently insufficient evidence to determine if cigarette smoking is a risk factor for delirium. Future studies should consider using biochemical measures of cigarette smoke exposure to objectively quantify smoking behavior.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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 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".