Anesthesia and Perioperative Care of the High-Risk Patient
Bibliographic record
Abstract
The fully updated third edition of this popular handbook provides a concise summary of perioperative management of high-risk surgical patients. Written by an international group of senior clinicians, chapters retain the practical nature of previous editions, with concise text in a bulleted format offering rapid access to key facts and advice. Several new chapters cover topics including: anesthetic mortality; cardiopulmonary exercise testing; perioperative optimization; obstructive sleep apnea and obesity hypoventilation syndrome; smoking, alcohol and recreational drug abuse; intraoperative ventilatory management; the role of simulation in managing the high-risk patient; anesthesia, surgery and palliative care; anesthesia and cancer surgery; neurotrauma and other high-risk neuro cases; anesthesia for end-stage renal and liver disease; and transplant patients. Essential reading for trainee anesthesiologists managing seriously ill patients during surgery or studying for postgraduate examinations, this is also a valuable refresher for anesthesiologists and intensivists looking for an update on the latest evidence-based care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.030 |
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".