Incidence and outcomes of acute kidney injury stratified by cardiogenic shock severity
Bibliographic record
Abstract
BACKGROUND: Acute kidney injury (AKI) is common among patients with cardiogenic shock (CS) and it is independently associated with mortality. We sought to assess the prevalence, severity, and prognosis of AKI as a function of cardiogenic shock severity in unselected Cardiac Intensive Care Unit (CICU) patients. METHODS: We retrospectively reviewed admissions to the Mayo Clinic between 2007 to 2015 and stratified patients by the AKI stage (based on modified Kidney Disease: Improving Global Outcomes criteria) and Society for cardiovascular angiography and interventions (SCAI) shock stage. The association with in-hospital mortality was analyzed using multivariable logistic regression. RESULTS: We included 9,311 unique patients with a mean age of 67 years and 37% females. SCAI shock stages A, B, C, D, and E were present in 47%, 30%, 15%, 7%, and 1% of patients. The incidence of AKI of any severity was 39% in the CICU and 51% during the hospitalization. Hospital mortality occurred in 8% of all patients, and the risk increased as a function of the rising AKI and SCAI shock stage. Worsening AKI stage was associated with increased adjusted hospital mortality (adjusted OR per AKI stage 1.22, 95% CI 1.10-1.36, p < .001). Higher AKI stages were associated with increased adjusted hospital mortality in SCAI stage A/B (p < .001), but not in SCAI stage C, D, or E (all p > .05). CONCLUSIONS: Higher AKI stages were independently associated with mortality in CICU patients after accounting for shock severity and may add incremental prognostic utility in patients with lower SCAI stages.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".