Monotherapy Versus Combination Therapy in Agitation Management in the Intensive Care Unit: A Narrative Review
Bibliographic record
Abstract
Agitation, defined as excessive restlessness or psychomotor activity leading to potential harm or disruption, is a common and challenging complication in the intensive care unit (ICU), often associated with delirium, withdrawal syndromes, or environmental stressors. Monotherapy refers to the use of a single pharmacologic agent (commonly benzodiazepines or antipsychotics), whereas combination therapy involves the concurrent use of both classes. Agitation contributes to adverse outcomes, including prolonged mechanical ventilation, unintentional removal of intravenous lines, feeding tubes, or endotracheal tubes. This can increase morbidity in rare cases, such as patients with difficult airways who can self-extubate, which may increase mortality. This narrative review evaluates evidence from 2000 to 2025, comparing monotherapy and combination therapy in ICU agitation. Although benzodiazepines remain essential for alcohol or sedative withdrawal, their broader use is associated with higher delirium incidence and longer ICU stay. Antipsychotics are widely used but have not consistently demonstrated improvement in delirium outcomes in randomized trials. Combination therapy may provide rapid behavioral control in refractory or mixed etiology agitation, but it appears to increase the risk of oversedation, hypotension, and prolonged mechanical ventilation. Current critical care guidelines, including the 2018 Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption (PADIS) recommendations, do not recommend routine combination therapy; instead, they emphasize individualized patient selection, structured sedation protocols, and cautious titration. Clinical decision-making should balance immediate control of agitation with long-term neurologic and functional outcomes.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".