Pharmacological Manipulation of Peripheral Vascular Resistance in Single Ventricle Patients (Stages I, II, and III of Palliation)
Bibliographic record
Abstract
Pharmacological manipulation of afterload is often used in the management of single ventricle patients, both in the acute post-operative setting and more chronically. After the first stage of palliation the pulmonary and systemic circulations are in parallel and afterload reduction is often used to increase total cardiac output and systemic oxygen delivery. The effectiveness of this approach is likely to be dependent on the intrinsic contractile state of the myocardium as well as the post-operative vascular tone. A variety of clinical studies and theoretical models support this approach. The use of afterload reduction in this context must be balanced with the need to maintain a critical systemic blood pressure for organ perfusion and to promote pulmonary blood flow. After the second and third stages of palliation the use of acute afterload reduction is less complex and primarily directed at promoting cardiac output when it is low and/or controlling high blood pressure. Second stage palliation is particularly unique in that the cerebral and pulmonary circulations are in series and respond differently to many manipulations designed to control vascular resistance. The incidence of long-term circulatory failure in single ventricle patients has led to frequent use of afterload reducing agents in this population but data to suggest that this improves overall outcomes is lacking. Newer studies suggest there may be a role for drugs that reduce pulmonary vascular resistance. This chapter will discuss the principles of manipulation of systemic vascular resistance, or afterload, following each of the three stages of single ventricle reconstruction. This article addresses the seventh of eight topics comprising the special issue entitled "Pharmacologic strategies with afterload reduction in low cardiac output syndrome after pediatric cardiac surgery".
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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 | 0.000 |
| 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) | 0.003 | 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".