Bibliographic record
Abstract
BACKGROUND: Postintubation hypotension (PIH) is an adverse event associated with poor outcomes in emergency department endotracheal intubations. Study objective was to determine the incidence of PIH and its impact on outcomes following tracheal intubation in a general anesthesia population. METHODS: Structured chart audit of adult patients intubated for a vascular surgery procedure at a tertiary care center over a 3-year period. Outcomes included in-hospital mortality, extended intensive care unit length of stay (ICU LOS), and requirement for postoperative (postop) hemodialysis or mechanical ventilation. RESULTS: Incidence of PIH was 60% (837 of 1395). Patients who developed PIH had increased mortality (8.8% PIH vs 5.2% no-PIH; P = .014), extended ICU LOS (7.9% PIH vs 2.0% no-PIH; P < .001), and postop mechanical ventilation requirement (20.7% PIH vs 3.8% no-PIH; P < .001). When controlling for confounding factors, PIH was associated with extended ICU LOS (odds ratio [OR] 2.55, 95% confidence interval [CI] 1.01-6.62, P = .049), postop ventilation (OR 2.43, 95% CI 1.27-4.74, P = .008), and a composite end point (OR 1.72, 95% CI 1.02-2.92, P = .043). CONCLUSIONS: Development of PIH occurs in 60% of patients undergoing intubation for vascular surgery and was associated with adverse outcomes including extended ICU LOS and postop ventilation requirement.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".