Neurological Determination of Death Following Infratentorial Stroke: A Population-Based Cohort Study
Bibliographic record
Abstract
ABSTRACT: Background: There is international variability in whether neurological determination of death (NDD) is conceptually defined based on permanent loss of brainstem function or “whole brain death.” Canadian guidelines are not definitive. Patients with infratentorial stroke may meet clinical criteria for NDD despite persistent cerebral blood flow (CBF) and relative absence of supratentorial injury. Methods: We performed a multicenter cohort study involving patients that died from ischemic or hemorrhagic stroke in Alberta intensive care units from 2013 to 2019, focusing on those with infratentorial involvement. Medical records were reviewed to determine the incidence and proportion of patients that met clinical criteria for NDD; whether ancillary testing was performed; and if so, whether this demonstrated the absence of CBF. Results: There were 95 (27%) deaths from infratentorial and 263 (73%) from supratentorial stroke. Sixteen patients (17%) with infratentorial stroke had neurological examination consistent with NDD (0.55 cases per million per year). Among patients that underwent confirmatory evaluation for NDD with an apnea test, ancillary test (radionuclide scan), or both, ancillary testing was more common with infratentorial compared with supratentorial stroke (10/12 (85%) vs. 25/47 (53%), p = 0.04). Persistent CBF was detected in 6/10 (60%) patients with infratentorial compared with 0/25 with supratentorial stroke (p = 0.0001). Conclusions: Infratentorial stroke leading to clinical criteria for NDD occurs with an annual incidence of about 0.55 per million. There is variability in clinicians’ use of ancillary testing. Persistent CBF was detected in more than half of patients that underwent radionuclide scans. Canadian consensus is needed to guide clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".