Electroencephalography Versus Psychometric Tests in Diagnosis of Minimal Hepatic Encephalopathy
Bibliographic record
Abstract
Background: Minimal hepatic encephalopathy (MHE) in patients with liver cirrhosis is defined by the presence of otherwise unexplained cognitive abnormalities, only detectable on psychometric or neurophysiological testing, in the absence of overt hepatic encephalopathy (OHE). The objectives were to study the incidence of MHE in patients with liver cirrhosis, and to compare the sensitivity of the electroencephalography (EEG) versus psychometric hepatic encephalopathy score (PHES) in its diagnosis. Methods: This study was conducted on 50 patients with liver cirrhosis. All patients underwent complete medical and neurological examination, laboratory investigations, abdominal ultrasound, EEG, and PHES involving star construction test, the number connection tests, block design test, the digit symbol test, the line drawing test and the circle dotting test. Results: The neuropsychiatric symptoms (but not sufficient to diagnose OHE) were present in 40% of our patients. The psychometric test results were positive in 80% of them. EEG records showed that 64.7% of the patients had no slow waves, 23.5% showed theta waves, 9.8% showed delta waves, while no patients showed triphasic waves. There was a significant correlation between slow waves in EEG and inattention, amnesia and disturbed thinking (P < 0.05). Also, it was present between psychometric test results and inattention, amnesia, and sleep disturbances (P < 0.05). There was a very significant correlation between psychometric test and Child score (P < 0.05), while it was not present between Child score and slow waves in EEG records (P > 0.05). Conclusion: The PHES and EEG are important in diagnosis of MHE in patients with liver cirrhosis, but PHES appears to be more sensitive than EEG. J Neurol Res. 2016;6(4):65-71 doi: http://dx.doi.org/10.14740/jnr391w
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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".