Bibliographic record
Abstract
Introduction Delirium is a common and frequently distressing neuropsychiatric complication in cancer patients. It has been defined as a transient global disorder of cognition and attention. These features are highlighted in the Diagnostic and Statistical Manual of Mental Disorders (4th edition; DSM–IV) core diagnostic criteria for delirium (Table 48.1), which also includes perceptual disturbance, acuity of onset (hours to days), fluctuation in clinical features, and the presence of an underlying cause, such as a general medical condition, substance induced, multiple etiologies, or unknown etiology. Delirium is associated with increased morbidity and mortality, prolonged hospital stay, and especially in the elderly, an increased requirement for institutional care. Epidemiological aspects Delirium occurrence rates in the range of 8–88% have been reported in hospitalized cancer patients. This wide range likely represents differences in diagnostic criteria, and populations selected on the basis of admission to different settings (for example, early versus advanced disease) or referral to different consult services such as psychiatry or neurology. Prospective studies have reported delirium in 40% of advanced cancer patients on hospital admission and in almost 90% of these patients in the last hours or days prior to death. Despite its remarkable frequency as a terminal event, delirium reversal has been reported in approximately 50% of episodes. Clinical features Delirium is a syndrome with protean manifestations. Perceptual disturbance, one of the potential core criteria, includes misperceptions, illusions, and hallucinations. Hallucinations are most commonly visual but tactile and auditory types can also occur.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.026 |
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".