A Multi-Center Evaluation of Early Acute Kidney Injury in Critically Ill Trauma Patients
Why this work is in the frame
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Bibliographic record
Abstract
RATIONALE: Few studies have evaluated the epidemiology of acute kidney injury (AKI) in trauma. OBJECTIVE: To evaluate the incidence, risk factors, and outcomes associated with early AKI (evident within 24 hours of admission) in critically ill trauma patients. METHODS: A retrospective interrogation of prospectively collected data from the Australian New Zealand Intensive Care Society Adult Patient Database. A total of 9,449 trauma patients were admitted for >or=24 hours to 57 intensive care units across Australia from January 1(st), 2000, to December 31(st), 2005. MAIN FINDINGS: The crude incidence of AKI was 18.1% (n = 1,711). Older age, female sex (OR 1.60, 95% CI, 1.43-1.78, p < 0.0001), and the presence of co-morbid illness (OR 2.70, 95% CI 2.3-3.2, p < 0.0001) were associated with higher odds of AKI. Those with trauma not associated with brain injury (OR 2.40, 95% CI, 2.1-2.7, p < 0.0001) and a higher illness severity (OR 1.12, 95% CI, 1.11-1.12, p < 0.001) also had higher likelihood of AKI. Overall, AKI was associated with a higher crude mortality (16.7% vs. 7.8%, OR 2.36, 95% CI, 2.0-2.7, p < 0.001). Each RIFLE category of AKI was independently associated with hospital mortality in multi-variable analysis (risk: OR 1.69; injury OR 1.88; failure 2.29). CONCLUSIONS: Trauma admissions to ICU are frequently complicated by early AKI. Those at high risk for AKI appear to be older, female, with co-morbid illnesses, and present with greater illness severity. Early AKI in trauma is also independently associated with higher mortality. These data indicate a higher burden of AKI than previously described.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it