Monitoramento de pacientes neurocirúrgicos no pós‐operatório – utilidade dos escores de avaliação neurológica e do índice bispectral
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: We examined the additive effect of the Ramsay scale, Canadian Neurological Scale (CNS), Nursing Delirium Screening Scale (Nu-DESC), and Bispectral Index (BIS) to see whether along with the assessment of pupils and Glasgow Coma Scale (GCS) it improved early detection of postoperative neurological complications. METHODS: We designed a prospective observational study of two elective neurosurgery groups of patients: craniotomies (CG) and non-craniotomies (NCG). We analyze the concordance and the odds ratio (OR) of altered neurological scales and BIS in the Post-Anesthesia Care Unit (PACU) for postoperative neurological complications. We compared the isolated assessment of pupils and GCS (pupils-GCS) with all the neurologic assessment scales and BIS (scales-BIS). RESULTS: In the CG (n=70), 16 patients (22.9%) had neurological complications in PACU. The scales-BIS registered more alterations than the pupils-GCS (31.4% vs. 20%; p<0.001), were more sensitive (94% vs. 50%) and allowed a more precise estimate for neurological complications in PACU (p=0.002; OR=7.15, 95% CI=2.1-24.7 vs. p=0.002; OR=9.5, 95% CI=2.3-39.4). In the NCG (n=46), there were no neurological complications in PACU. The scales-BIS showed alterations in 18 cases (39.1%) versus 1 (2.2%) with the pupils-GCS (p<0.001). Altered CNS on PACU admission increased the risk of neurological complications in the ward (p=0.048; OR=7.28, 95% CI=1.021-52.006). CONCLUSIONS: Applied together, the assessment of pupils, GCS, Ramsay scale, CNS, Nu-DESC and BIS improved early detection of postoperative neurological complications in PACU after elective craniotomies.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".