The Clinical Epidemiology and 30-Day Outcomes of Emergency Department Patients With Acute Kidney Injury
Bibliographic record
Abstract
BACKGROUND: Acute kidney injury (AKI) is associated with increased mortality and dialysis in hospitalized patients but has been little explored in the emergency department (ED) setting. OBJECTIVE: The objective of this study was to describe the risk factors, prevalence, management, and outcomes in the ED population, and to identify the proportion of AKI patients who were discharged home with no renal-specific follow-up. DESIGN: This is a retrospective cohort study using administrative and laboratory databases. SETTING: Two urban EDs in Vancouver, British Columbia, Canada. PATIENTS: We included all unique ED patients over a 1-week period. METHODS: All patients had their described demographics, comorbidities, medications, laboratory values, and ED treatments collected. AKI was defined pragmatically, based upon accepted guidelines. The cohort was then probabilistically linked to the provincial renal database to ascertain renal replacement (transplant or dialysis) and the provincial vital statistics database to obtain mortality. The primary outcome was the prevalence of AKI; secondary outcomes included (1) the proportion of AKI patients who were discharged home with no renal-specific follow-up and (2) the combined 30-day rate of death or renal replacement among AKI patients. RESULTS: There were 1651 ED unique patients, and 840 had at least one serum creatinine (SCr) obtained. Overall, 90 patients had AKI (10.7% of ED patients with at least one SCr, 95% confidence interval [CI], 8.7%-13.1%; 5.5% of all ED patients, 95% CI, 4.4%-6.7%) with a median age of 74 and 70% male. Of the 31 (34.4%) AKI patients discharged home, 4 (12.9%) had renal-specific follow-up arranged in the ED. Among the 90 AKI patients, 11 died and none required renal replacement at 30 days, for a combined outcome of 12.2% (95% CI, 6.5%-21.2%). LIMITATIONS: Sample sizes may be small. Nearly half of ED patients did not obtain an SCr. Many patients did not have sequential SCr testing, and a modified definition of AKI was used.
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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 | 0.002 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".