Comparison of the Acute Physiology and Chronic Health Evaluation Score (APACHE) II with GCS in Predicting Hospital Mortality of Neurosurgical Intensive Care Unit Patients
Bibliographic record
Abstract
BACKGROUND: The Glasgow Coma Scale (GCS) is popular, simple, and reliable, and provides information about the level of consciousness in trauma patients. However, a systemic evaluation scale specially in patients with multiple trauma is so important. The revised Acute Physiology and Chronic Health Evaluation system type 2 (APACHE II) is a physiologically based system including physiological variables. This study compares the efficacy of the predicting power for mortality and functional outcome of GCS and APACHEII in patients with multiple trauma in intensive care unit. METHODS: This study included the patients with head injury associated with systemic trauma admitted in the ICU of Shahid Rajaee Hospital in 2007 and 2008. Sensitivity, specificity and correct prediction of outcome by GCS and APACHE II were assessed and compared. RESULTS: This study included 93 patients (79 males, 14 females; mean age 60.5; range 14 to 87 years) with head injury associated with systemic trauma in 2007 and 2008. Mortality increased in the elderly group. The mean survival score using APACHE II was 36.5 and death score was 67.4 . These values using GCS were 10.3 and 6.8, respectively. CONCLUSION: For the assessment of mortality, the GCS score still provides simple, less-time consuming and effective information concerning head injury patients, especially in emergencies; however, for the prediction of mortality in patients with multiple trauma. APACHE II is superior to GCS since it includes the main physiologic parameters of patients.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".