Clinically Evident Cardiopulmonary Congestion Does Not Significantly Impact the Prognosis of Patients With Septic Acute Kidney Injury
Bibliographic record
Abstract
Background: Acute kidney injury (AKI) is a common issue among in-hospital patients, with high mortality rates. Sepsis is a primary cause of AKI, particularly in the intensive care unit. Patients with septic AKI often experience cardiovascular congestion, leading to the formal classification of cardiorenal syndrome type 5. The study aimed to evaluate the prognosis of septic AKI patients with and without clinical evidence of cardiovascular congestion. Methods: This was a retrospective observational study. AKI patients were identified using the in-hospital AKI alert system. Sepsis was diagnosed based on laboratory, clinical, and hemodynamic characteristics, with additional consideration of the quickSOFA score. Cardiovascular congestion was diagnosed by assessing clinical (edema), radiographic (pulmonary congestion), echocardiographic (e.g., wall motion abnormalities), and laboratory variables (e.g., N-terminal pro-B-type natriuretic peptide). Endpoints included in-hospital survival, the need for kidney replacement therapy (KRT), and recovery of kidney function (ROKF). Results: In total, 102 patients were included, and cardiopulmonary congestion was diagnosed in 78.4%. Individuals with congestion did not differ from patients without congestion in any of the pre-defined endpoints. Conclusions: . Rather, especially in the case of sepsis, clinically apparent positive fluid balance does not seem to be a disadvantage in terms of survival, KRT, and ROKF.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".