Respiratory Drive in Critically Ill Patients. Pathophysiology and Clinical Implications
Bibliographic record
Abstract
Respiratory drive, the intensity of the respiratory center's output, determines the effort exerted in each breath. The increasing awareness of the adverse effects of both strong and weak respiratory efforts during mechanical ventilation on patient outcome brings attention to the respiratory drive of the critically ill patient. Critical illness can affect patients' respiratory drive through multiple pathways, mainly operating through three feedback systems: cortical, metabolic, and chemical. The chemical feedback system, defined as the response of the respiratory center's output to changes in arterial blood gases and pH, is one of the most important determinants of respiratory drive. The purpose of this state-of-the-art review is to describe the determinants of respiratory drive in critically ill patients, review the tools available to assess respiratory drive at the bedside, and discuss the implications of altered respiratory drive during mechanical ventilation. An analysis that relates arterial carbon dioxide levels with brain's response to this stimulus will be presented, contrasting the brain's responses to the patient's ability to generate effective alveolar ventilation, both during unassisted breathing and with different modes of ventilatory assist. This analysis may facilitate comprehension of the pathophysiology of respiratory drive in critically ill patients. As we aim to avoid both over- and under-assistance with mechanical ventilation, considering the patients' respiratory drive at the bedside may improve clinical assessment and management of the patient and the ventilator.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".