Prognostication of Electrocardiographic Changes With Status Epilepticus in African American Population
Bibliographic record
Abstract
Background: Status epilepticus (SE) is a medical emergency and requires rapid diagnosis and treatment to reduce morbidity and mortality. The general approach to management and treatment of SE is largely unexplored and it remains unclear if other factors besides age and etiology represent independent outcome predictors for SE. There have been previous studies that document changing electrocardiogram (ECG) tracing through SE and following the termination of SE, indicating a dynamic, pathological response of the myocardium to this neurological process. Here we examine the ECG changes in African American patients during and after SE and consider the prognostic indication of ECG readings. Methods: The study was conducted on 113 African American patients older than 15 years who experienced SE following new onset or pre-existing epilepsy. Data were compiled through a retrospective analysis of the type of ECG changes with comparison of ECGs taken within 6 hours and after 24 hours in patients with SE. Results: ECG changes were documented in 81% of patients with SE in the first 6 hours. Of the eight patients who died, seven had persistent ECG abnormalities. Looking at our group of patients with new onset epilepsy, 25% returned to baseline function post SE, 46% were left with some disability and 19% resulted in death. This can be compared to patients who had a history of seizures in which 90% returned to baseline, 6% were left with a disability and 3% resulted in death. Conclusions: The high mortality rate associated with SE patients having ECG abnormalities indicates that close observation of cardiac function is essential in managing SE. Knowing that persistent ECG changes following SE are predictive of increased morbidity and mortality gives us the information we need to begin to change the way we manage and monitor SE patients. Cardiac monitoring using ECGs is a cost effective and non-invasive method to allow for early detection of potentially life threatening cardiovascular abnormalities in patients during and after SE. J Neurol Res. 2014;4(2-3):63-71 doi: http://dx.doi.org/10.14740/jnr271w
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".