Variation in use of intensive care for adults with diabetic ketoacidosis*
Bibliographic record
Abstract
OBJECTIVE: Intensive care unit beds are limited, yet few guidelines exist for triage of patients to the intensive care unit, especially patients at low risk for mortality. The frequency with which low-risk patients are admitted to intensive care units in different hospitals is unknown. Our objective was to assess variation in the use of intensive care for patients with diabetic ketoacidosis, a common condition with a low risk of mortality. DESIGN: Observational study using the New York State In-patient Database (2005-2007). SETTING: One hundred fifty-nine New York State acute care hospitals. PATIENTS: Fifteen thousand nine hundred ninety-four adult (≥ 18) hospital admissions with a primary diagnosis of diabetic ketoacidosis (International Classification of Diseases, Ninth Revision, Clinical Modification 250.1x). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We calculated reliability- and risk-adjusted intensive care unit utilization, hospital length of stay, and mortality. We identified hospital-level factors associated with increased likelihood of intensive care unit admission after controlling patient characteristics using multilevel, mixed-effects logistic regression analyses; we assessed the amount of residual variation in intensive care unit utilization using the intraclass correlation coefficient. Use of intensive care for diabetic ketoacidosis patients varied widely across hospitals (adjusted range: 2.1% to 87.7%), but was not associated with hospital length of stay or mortality. After multilevel adjustment, hospitals with a high volume of diabetic ketoacidosis admissions admitted diabetic ketoacidosis patients to the intensive care unit less often (odds ratio 0.40, p = .002, highest quintile compared to lowest), whereas hospitals with higher rates of intensive care unit utilization for all nondiabetic ketoacidosis in-patients admitted diabetic ketoacidosis patients to the intensive care unit more frequently (odds ratio 1.31, p = .001, for each additional 10% increase). In the multilevel model, more than half (58%) of the variation in the intensive care unit admission practice attributable to hospitals remained unexplained. CONCLUSIONS: We observed variations across hospitals in the use of intensive care for diabetic ketoacidosis patients that was not associated with differences in-hospital length of stay or mortality. Institutional practice patterns appear to impact admission decisions and represent a potential target for reduction of resource utilization in higher use institutions.
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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 | 0.001 | 0.006 |
| 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 | 0.000 |
| 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".