Bibliographic record
Abstract
Vasopressin is a stress hormone. However, vasopressin levels are inappropriately low in septic shock. Vasopressin stimulates AVPR1a, AVPR1b, AVPR2 and purinergic receptors. Vasopressin increases blood pressure by occupying AVPR1a receptors on vascular smooth muscle. An increase in ventricular afterload due to vasopressor administration limits ventricular systolic ejection, an effect that becomes increasingly important as systolic contractility is decreased. Stimulation of AVPR1a receptors may also decrease edemagenesis. Stimulation of AVPR1b by vasopressin releases ACTH and cortisol. AVPR2 stimulation increases retention of water by increasing cyclic AMP. Yet, vasopressin infusion may increase urine output, creatinine clearance and improve renal function in septic shock. Vasopressin has many effects on immune function such as altering cytokines, neuroimmunity, prostaglandins, humoral immunity and immune cells. For example, vasopressin decreases sepsis-induced pulmonary inflammation, could have renal anti-inflammatory effects and may decrease prostaglandin levels in a dose-dependent manner. Vasopressin may also modulate responses to stress by expression and release from immune cells. Interestingly, there are vasopressin receptors on immune cells. Many small clinical studies of vasopressin infusion in septic shock have shown that vasopressin infusion increases blood pressure, decreases requirements for norepinephrine and improves renal function. However, vasopressin could decrease coronary, cerebral and mesenteric perfusion. A multicenter trial of vasopressin versus norepinephrine in septic shock found no overall difference in mortality. Vasopressin may decrease mortality in patients with less severe septic shock. Vasopressin plus corticosteroid treatment may decrease mortality compared to corticosteroids plus norepinephrine. Potential mechanisms are that vasopressin plus corticosteroids beneficially alter immunity in septic shock.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".