P066: Comfort of emergency medicine physicians in implementing early goal directed therapy for sepsis
Bibliographic record
Abstract
Introduction: The recently published ProMISe, ARISE and ProCESS trials demonstrated that protocol-based resuscitation (EGDT) of ER patients in whom septic shock was diagnosed did not improve outcome when compared to usual care. The objective of this project was to survey McMaster emergency physicians in areas including sepsis definition, clinical recognition in adults, self-rated skills assessment, attitudes towards skills augmentation and compare results to the cohort surveyed 11 years ago, close to the introduction of EGDT. Methods: Full time faculty at McMaster’s Department of Emergency Medicine and ER residents were surveyed anonymously using an electronic survey. The questions covered demographics and training data, identification of septic patients, sepsis intervention and attitudes towards skills augmentation. Results: A total of 18 physicians responded to the electronic survey to date. All respondents were able to correctly input definitions for SIRS, sepsis, severe sepsis and septic shock. The majority of respondents felt the best strategy to identify potentially septic adults involved monitoring abnormal vital signs (67%) with some stating serum lactate assessment (33%). Of the 11 possible interventions options provided to care for septic patients, respondents appeared more comfortable with placement of lines, giving vasopressors and appropriate use of fluids for resuscitation. This was compared to more specialized interventions like initiating IV steroids in vasopressor dependant shock despite adequate fluid loading. 22% of respondents believed that patients without respiratory compromise with clinically severe sepsis should be intubated which was found to be 48% in the previous cohort surveyed 11 years ago. 78% believed patients in septic shock without respiratory comprise should be intubated, reassuringly similar to the previous survey result of 87%. Conclusion: Emergency physicians at our Canadian institution are comfortable with the skill set required to care for patients with sepsis. Respondents surveyed to date were all comfortable with important resuscitative measures including accurate identification, placement of lines and appropriate fluid administration and were receptive to additional training. Our study emphasizes that our physicians have the skill set to identify and provide care for sepsis using their clinical judgment in cases that may not require protocolized 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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".