Use of a Cardiopulmonary Resuscitation Video to Assist Intensive Care Unit Resident Physicians during Code Status Discussions
Bibliographic record
Abstract
Background: Code status discussions (CSDs) in the intensive care unit (ICU) are frequently conducted by resident physicians. Cardiopulmonary resuscitation (CPR) videos when used to aid ICU patients and families in code status decision making have been shown to have a positive impact. The purpose of this study is to evaluate the impact of a CPR video, when made available to supplement trainee-patient CSDs, on ICU residents' comfort level when conducting these discussions. Objectives: To assess whether a CPR video as an intervention tool would increase residents' comfort level when conducting CSDs. Methods: This is a pre- and postintervention pilot study. A presurvey querying details about trainees' comfort level when conducting CSDs was administered to the residents at the beginning of the ICU rotation, and a CPR video was availed to them to supplement their trainee-patient CSDs. A postsurvey was administered to trainees at the end of their ICU rotation to evaluate and analyze the impact of the CPR video on residents' comfort level when conducting trainee-patient CSDs. Results: A total of 118 trainees rotated through the ICU with 43 (36%) answering the presurvey and 28 (24%) answering the postsurvey. Twenty-two (51%) presurvey respondents felt extremely comfortable and 18 (42%) felt somewhat comfortable conducting CSDs. Thirteen (46%) postsurvey respondents felt extremely comfortable and 12 (43%) felt somewhat comfortable conducting CSDs. Most postsurvey respondents (79%) almost never used the video and (67%) neither agree nor disagree that the video was useful. Conclusion: In our small cohort, CPR video when made available to supplement trainee-patient CSDs did not impact resident physicians' comfort level when conducting these discussions. The residents' low level of engagement with this video, among other factors, could explain our results.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".