Cardiorenal Syndrome Type 3: Pathophysiologic and Epidemiologic Considerations
Bibliographic record
Abstract
Cardiorenal syndrome (CRS) type 3 is a subclassification of the CRS whereby an episode of acute kidney injury (AKI) precipitates and contributes to the development of acute cardiac injury. There is limited understanding of the pathophysiologic mechanisms of how AKI contributes to acute cardiac injury and/or dysfunction. An episode of AKI may have effects that depend on the severity and duration of AKI and that both directly and indirectly predispose to an acute cardiac event. Moreover, baseline susceptibility will modify the subsequent risk for cardiac events associated with AKI. Experimental data suggest cardiac injury may be directly induced by inflammatory mediators, oxidative stress, apoptosis and activation of neuroendocrine systems early after AKI. Likewise, AKI may be associated with physiologic derangements (i.e. volume overload; metabolic acidosis, retention of uremic toxins, hyperkalemia; hypocalcemia), alterations to coronary vasoreactivity, and ventricular remodeling and fibrosis that indirectly exert negative effects on cardiac function. AKI may also adversely impact cardiac function by contributing to alternations in drug pharmacokinetics and pharmacodynamics. Additional experimental and translational investigations coupled with epidemiologic surveys are needed to better explore that pathophysiologic mechanisms underpinning acute cardiac events associated with AKI and their impact on outcomes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".