Sonographic Findings of Left Ventricular Dysfunction to Predict Shock Type in Undifferentiated Hypotensive Patients: An Analysis From the Sonography in Hypotension and Cardiac Arrest in the Emergency Department (SHoC-ED) Study
Bibliographic record
Abstract
Introduction Patients that present to the emergency department (ED) with undifferentiated hypotension have a high mortality rate. Hypotension can be divided into four categories: obstructive, hypovolemic, distributive, and cardiogenic. While it is possible to have overlapping or concomitant shock states, being able to differentiate between cardiogenic shock and the other categories is important as it entails a different treatment regime and extra cautions. In this secondary analysis, we investigate if using focused cardiac ultrasonography (FOCUS) to determine left ventricular dysfunction (LVD) can serve as a reliable test for cardiogenic shock. Methods We prospectively collected FOCUS findings performed in 135 ED patients with undifferentiated hypotension as part of an international study. Patients with clearly identified etiologies for hypotension were excluded, along with other specific presumptive diagnoses. LVD was defined as the identification of a generally hypodynamic left ventricle in the setting of shock. FOCUS findings were collected using a standardized protocol and data collection form. All scans were performed by emergency physicians trained in ultrasound. Final shock type was defined as cardiogenic or noncardiogenic by independent specialist blinded chart review. Results In our findings, 135 patients had complete records for assessment of left ventricular function and additional follow-up data and so were included in this secondary analysis. The median age was 56 years and 53% of patients were male. Disease prevalence for cardiogenic shock was 12% and the mortality rate was 24%. The presence of LVD on FOCUS had a sensitivity of 62.50% (95% confidence interval 35.43% to 84.80%), specificity of 94.12% (88.26% to 97.60%), positive likelihood ratio (LR) 10.62 (4.71 to 23.95), negative LR 0.40 (0.21 to 0.75) and accuracy of 90.37% (84.10% to 94.77%) for detecting cardiogenic shock. Conclusion Detecting left ventricular dysfunction on FOCUS may be useful in the early identification of cardiogenic shock in otherwise undifferentiated hypotensive adult patients in the emergency department.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".