The Frequency of POCUS in the Treatment of Sepsis in the Emergency Department: A Retrospective Cohort Study
Bibliographic record
Abstract
Background: Point of care ultrasound (POCUS) is ubiquitous in the modern emergency department (ED). POCUS can be helpful in the management of patients with sepsis in many ways including determining the cause of sepsis, assessing fluid status, guiding resuscitation, and performing procedures. However, the frequency and manner in which POCUS is incorporated into the care of septic patients in community emergency medicine remains unclear. Objective: To evaluate POCUS frequency and exam types used in the care of patients with sepsis in two community EDs in Southern California. Methods: We performed a retrospective analysis of 5,264 ED visits with a diagnosis of sepsis at two community emergency departments between January 2014 and December 2018. Patients 18 years or older who were diagnosed with sepsis and had either lactate ≥ 4 mmol, a documented mean arterial pressure (MAP) < 65 mmHg, or a systolic blood pressure (SBP) < 90 mmHg were included. Charts were reviewed to determine if POCUS was used during the ED evaluation. Primary outcomes were frequency of POCUS use in the cohort, change in POCUS use over the study period, and the types of exams performed. Results: POCUS was used in 21% of encounters meeting inclusion criteria and was positively correlated with ED arrival year (OR = 1.09; CI 1.04, 1.15; p=0.001). The most common POCUS exam was ultrasound-guided central line placement, with the next most common exams being cardiac, followed by inferior vena cava (IVC). Only the frequency of cardiac, IVC, lung and Focused Assessment with Sonography in Trauma (FAST) exams were found to increase significantly over the study period. Conclusions: Total POCUS use increased significantly in this cohort of septic patients over the study period due to more cardiac, IVC, lung and FAST exams being performed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".