Cardiorenal Syndrome: Role of Arginine Vasopressin and Vaptans in Heart Failure
Bibliographic record
Abstract
Heart and kidney failure continued to be of increasing prevalence in today's society, and their comorbidity has synergistic effect on the morbidity and mortality of patients. Cardiorenal syndrome (CRS) is a complex disease with multifactorial pathophysiology. Better understanding of this pathophysiological network is crucial for the successful intervention to prevent advancement of the disease process. One of the major factors in this process is neurohormonal activation, predominantly involving renin-angiotensin-aldosterone system (RAAS) and arginine vasopressin (AVP). Heart failure causes reduced cardiac output/cardiac index (CO/CI) and fall in renal perfusion pressures resulting in activation of baroreceptors and RAAS, respectively. Activated baroreceptors and RAAS stimulate the release of AVP (non-osmotic pathway), which acts on V 2 receptors located in the renal collecting ducts, causing fluid retention and deterioration of heart failure. Effective blockade of AVP action on V 2 receptors has emerged as a potential treatment option in volume overload conditions especially in the setting of hyponatremia. Vasopressin receptor antagonists (VRAs), such as vaptans, are potent aquaretics causing electrolyte-free water diuresis without significant electrolyte abnormalities. Vaptans are useful in hypervolemic hyponatremic conditions like heart failure and liver cirrhosis, and euvolemic hyponatremic conditions like syndrome of inappropriate anti-diuretic hormone secretion. Tolvaptan and conivaptan are pharmaceutical agents that are available for the treatment of these conditions. Cardiol Res. 2017;8(3):87-95 doi: https://doi.org/10.14740/cr553w
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".