Anesthesiologist to Patient Communication
Bibliographic record
Abstract
Importance: Many patients are admitted to the intensive care unit following surgery, and some of them will experience incomplete recovery. For patients in this situation, preoperative discussions regarding patient values and preferences may direct care decisions. Existing literature shows that it is uncommon for surgeons to have these conversations preoperatively; it is unclear whether anesthesia professionals engage with patients on this topic prior to surgery. Objective: To review the literature on communication between patients and anesthesia professionals, with a focus on discussions related to postoperative critical care. Evidence Review: MEDLINE and Web of Science were searched using specific search criteria from January 1980 to April 2020. Studies describing encounters between patients and anesthesia professionals were selected, and data regarding study objectives, study design, methodology, measures, outcomes, patient characteristics, and clinical setting were extracted and collated. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed. Findings: A total of 12 studies including 1284 individual patient encounters were eligible for inclusion in the review. These studies demonstrated that communication between patients and anesthesia professionals related to postoperative care is rare: only 2 studies reported communication regarding adverse postoperative events, and this communication behavior was reported in only 46 of 1284 consultations (3.6%) across all studies. Additional findings were that communication during these encounters is dominated by anesthetic planning and perioperative logistics, with variable discussion of perioperative risks vs benefits and infrequent elicitation of patient values and preferences. Some data suggest that patients wish to be involved in perioperative decision-making but are often limited by an incomplete understanding of risks and benefits. Conclusions and Relevance: This systematic review found that communication in anesthesia is dominated by anesthetic planning and discussion of preoperative logistics, whereas postoperative critical care is rarely discussed. Most patients who are admitted to an intensive care unit after a major operation will not have had a discussion regarding goals of care specific to protracted recovery or prolonged intensive care with their anesthesiologist.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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; both teacher heads agree on what is shown here.
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".