Demonstrating Feasibility of Point of Care Ultrasound (POCUS)-Guided Inpatient Transthoracic Echo Triage Decision Pathway
Bibliographic record
Abstract
Background: Prolonged inpatient length of stay (LOS) is associated with worse clinical outcomes and increased healthcare costs. Transthoracic echocardiography (TTE) is commonly utilized in cardiac evaluation of hospital inpatients but is associated with prolonged LOS and may not always be necessary. Point of care ultrasound (POCUS) may help reduce the need for inpatient TTEs. Objective: We aimed to demonstrate the feasibility of a POCUS-guided TTE triage protocol and estimate its impact on inpatient TTE utilization. Methods: From September to December 2023, inpatient clinicians and participating patients at a large academic institution were surveyed about their perspectives and experiences with POCUS. Cardiac POCUS exams were performed and interpreted for pre-specified clinical indications by POCUS-trained hospitalists, then reviewed independently by at least two board-certified cardiologists. Interpretations were compared using pairwise agreement analysis (kappa (κ) statistic). Finally, hospitalists and cardiologists independently offered their TTE triage recommendation, categorized as either inpatient, outpatient, or cancellation. Triage agreement between the two groups was reported as a percentage of overall cases. Results: Clinicians and patients were receptive to integrating POCUS exams into clinical care. Ninety POCUS exams were completed during the intervention period, on average 22 hours before TTE. Hospitalist and cardiologist agreement was moderate to very good (0.57-0.99) for specific cardiac findings. The hospitalist and at least one cardiologist agreed that 59 (66%) of 90 exams performed within the triage pathway could result in deferral or cancellation of inpatient TTE. Conclusions: A POCUS-guided TTE triage protocol can reduce low-value inpatient TTE use, potentially expediting necessary TTEs and reducing TTE backlog.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".