Diabetic status and the relation of the three domains of glycemic control tomortality in critically ill patients: an international multicenter cohort study
Bibliographic record
Abstract
INTRODUCTION: Hyperglycemia, hypoglycemia, and increased glycemic variability have each been independently associated with increased risk of mortality in critically ill patients. The role of diabetic status on modulating the relation of these three domains of glycemic control with mortality remains uncertain. The purpose of this investigation was to determine how diabetic status affects the relation of hyperglycemia, hypoglycemia, and increased glycemic variability with the risk of mortality in critically ill patients. METHODS: This is a retrospective analysis of prospectively collected data involving 44,964 patients admitted to 23 intensive care units (ICUs) from nine countries, between February 2001 and May 2012. We analyzed mean blood glucose concentration (BG), coefficient of variation (CV), and minimal BG and created multivariable models to analyze their independent association with mortality. Patients were stratified according to the diagnosis of diabetes. RESULTS: Among patients without diabetes, mean BG bands between 80 and 140 mg/dl were independently associated with decreased risk of mortality, and mean BG bands>or=140 mg/dl, with increased risk of mortality. Among patients with diabetes, mean BG from 80 to 110 mg/dl was associated with increased risk of mortality and mean BG from 110 to 180 mg/dl with decreased risk of mortality. An effect of center was noted on the relation between mean BG and mortality. Hypoglycemia, defined as minimum BG<70 mg/dl, was independently associated with increased risk of mortality among patients with and without diabetes and increased glycemic variability, defined as CV>or=20%, was independently associated with increased risk of mortality only among patients without diabetes. Derangements of more than one domain of glycemic control had a cumulative association with mortality, especially for patients without diabetes. CONCLUSIONS: Although hyperglycemia, hypoglycemia, and increased glycemic variability is each independently associated with mortality in critically ill patients, diabetic status modulates these relations in clinically important ways. Our findings suggest that patients with diabetes may benefit from higher glucose target ranges than will those without diabetes. Additionally, hypoglycemia is independently associated with increased risk of mortality regardless of the patient's diabetic status, and increased glycemic variability is independently associated with increased risk of mortality among patients without diabetes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".