Early blood glucose control and mortality in critically ill patients in Australia*
Bibliographic record
Abstract
OBJECTIVE: To measure temporal trends in blood glucose (BG) control and describe their association with hospital mortality in a cohort of critically ill patients from Australia. DESIGN: Interrogation of prospectively collected data from the Australia New Zealand Intensive Care Society Adult Patient Database. SETTING: Twenty-four intensive care units (ICU) across Australia. PATIENTS AND PARTICIPANTS: A cohort of 66,184 adult ICU admissions for >or=24 hours from January 1, 2000, to December 31, 2005. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Highest and lowest BG values within 24 hours of ICU admission, standard demographic, clinical, and physiologic data, and hospital mortality. Medical, mechanically ventilated surgical, cardiac surgical, and septic subgroups were evaluated. Average BG was evaluated as a continuous variable and by quartiles (low [<5.6 mmol/L], near normal [5.6-8.69 mmol/L], high [8.69-11.79 mmol/L], and highest [>11.79 mmol/L]). There were 132,368 BG values, with a mean (95% confidence intervals) value 8.69 mmol/L (8.66-8.73). There was no trend in BG for the entire cohort (p = 0.66) over the study period; yet, BG increased after 2002 (0.17 mmol/L, p < 0.0001). The mechanically ventilated surgical and cardiac surgical subgroups had decreasing trends in BG (p < 0.001), whereas the septic subgroup had an increasing BG trend (p < 0.001). BG in the low, high, and highest quartiles, compared with the near-normal quartile, were consistently associated with higher hospital mortality in crude (odds ratio 1.31, 1.58, and 2.00) and multivariable analysis (odds ratio 1.29, 1.07, and 1.10), respectively. This association was similarly shown for the mechanically ventilated surgical and cardiac surgical subgroups. CONCLUSIONS: In a large cohort of ICU patients from Australia, there was no significant change in early glycemic control from 2000 to 2005. There were differences in selected subgroups. Average BG decreased in surgical subgroups, whereas it increased in septic patients. Both high and early low BG values were independently associated with hospital mortality.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".