Electrocardiographic and Echocardiographic Changes in Subarachnoid Hemorrhage and Their Final Impact on Early Outcome: A Prospective Study Before and After the Treatment
Bibliographic record
Abstract
Background: We aimed to prospectively investigate the changes in the electrocardiography (ECG) and the echocardiography of the patients with subarachnoid hemorrhage (SAH) before and after treatment, and to evaluate the overall role of the findings on early patients’ outcome. Methods: All consecutive patients with SAH were evaluated with on-admission ECG and echocardiography. For those with an abnormal result, a second evaluation was performed after the therapeutic interventions. All of the participants were followed until discharged or possibly expired in the hospital. Proper statistical methods were used to compare the changes between the two groups of the patients: the “expired” group, and the “discharged” group. Results: Of the total of 60 subjects, 25 (41.6%) and three (5%) had an abnormal ECG and echocardiography that were dropped to four (6.7%) and one (1.7%) after treatment, respectively. The most frequent ECG finding was T-wave inversion. Six subjects (10%) were expired in the hospital. Abnormal primary ECG was found in five out of the six dead subjects (83.3%) and 20 out of the 54 discharged ones (37%) (P = 0.029). None of the three patients with abnormal primary echocardiograms were expired during the hospitalization. Conclusion: Most SAH-induced changes in the ECG and the echocardiography are transient and reversible. Abnormal ECG is a good predictor of inpatient mortality, but abnormal echocardiography is not. J Neurol Res. 2015;5(1-2):181-185 doi: http://dx.doi.org/10.14740/jnr317w
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".