Potential pharmacological confounders in the setting of death determined by neurologic criteria: a narrative review
Bibliographic record
Abstract
Guidelines for the determination of death by neurologic criteria (DNC) require an absence of confounding factors if clinical examination alone is to be used. Drugs that depress the central nervous system suppress neurologic responses and spontaneous breathing and must be excluded or reversed prior to proceeding. If these confounding factors cannot be eliminated, ancillary testing is required. These drugs may be present after being administered as part of the treatment of critically ill patients. While measurement of serum drug concentrations can help guide the timing of assessments for DNC, they are not always available or feasible. In this article, we review sedative and opioid drugs that may confound DNC, along with pharmacokinetic factors that govern the duration of drug action. Pharmacokinetic parameters including a context-sensitive half-life of sedatives and opioids are highly variable in critically ill patients because of the multitude of clinical variables and conditions that can affect drug distribution and clearance. Patient-, disease-, and treatment-related factors that influence the distribution and clearance of these drugs are discussed including end organ function, age, obesity, hyperdynamic states, augmented renal clearance, fluid balance, hypothermia, and the role of prolonged drug infusions in critically ill patients. In these contexts, it is often difficult to predict how long after drug discontinuation the confounding effects will take to dissipate. We propose a conservative framework for evaluating when or if DNC can be determined by clinical criteria alone. When pharmacologic confounders cannot be reversed, or doing so is not feasible, ancillary testing to confirm the absence of brain blood flow should be obtained.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".