Electrocardiographic manifestations of patients with cardiogenic shock due to acute pulmonary embolism
Bibliographic record
Abstract
Background: Cardiogenic shock (CS) is associated with poorer pulmonary embolism (PE) prognosis and increased total mortality. ECG plays an important role in the differential diagnosis and helps with the decision making process in the emergency. The aim of the study was to compare ECG parameters in patients with PE presenting with or without CS. Methods: We analyzed ECG and clinical data from 470 patients (pts) with acute PE, mean age 65.9 years ± 15.2 old, female 274 pts. Patients were divide into 2 groups: with CS (n=98 pts) or without CS (n=372 pts). Chi square and T student were used to compare dichotomic and continuous variables. A p value =/- than 0.05 was considered significant. Results: ECG parameters of both groups can be seen in the table. A new ECG index called STE-aVR (ST-segment elevation in lead aVR) was observed in 96 (20.8%) pts. There were 50 (10.6%) cardiac deaths; 35/98 (35.7%) in the CS (+) group, and 15 (4%) deaths in the CS (–) group. Use of fibrynolytic therapy in 50 (10.6%) of the cases. Results: See Table 1. Table 1 RBBB, right bundle branch block; STD, ST-segment depression; STE, ST-segment elevation. Conclusion: In patients with PE and CS; ECG changes including S1Q3T3 sign, qR sign in lead V1, RBBB, STD in lateral leads, and STE in leads III, aVR and V1 are significantly more frequent than in patients without CS.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".