Impaired subcortical and cortical sensory evoked potential pathways in septic patients*
Bibliographic record
Abstract
OBJECTIVE: Sensory evoked potential (SEP) peak latencies were recorded in order to evaluate the incidence and severity of septic encephalopathy, testing the hypothesis that the occurrence of septic encephalopathy is more frequent than generally assumed. DESIGN: Prospective cohort study. SETTING: Medical intensive care unit of a university hospital. PATIENTS: Sixty-eight critically ill patients were studied within 48 hrs after the development of severe sepsis (n = 41) or septic shock (n = 27). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Septic encephalopathy was defined as prolongation of SEP peak latencies beyond the upper limit of the reference range of subcortical (N13-N20 interpeak latency) and cortical SEP pathways (N20-N70 interpeak latency), as well as asymmetry of peak latencies marked by the presence of subclinical cerebral focal signs. Subcortical SEP pathways were impaired in 34% and cortical SEP pathways in 84% of all patients. The prolongation of the cortical SEP pathway correlated with the Acute Physiology and Chronic Health Evaluation III score (r = 0.23; p <.0001). SEP peak latencies did not differ in patients with severe sepsis compared with those with septic shock. Subclinical cerebral focal signs were present in 24% of the subcortical SEP pathways and in 6% of the cortical SEP pathways. CONCLUSIONS: Septic encephalopathy occurs more frequently than generally assumed, and its severity is associated with the severity of illness. The impairment of subcortical and cortical SEP pathways was not different between patients with severe sepsis and those with septic shock.
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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 | 0.001 |
| 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".