Mechanical ventilation strategies alter cardiovascular biomarkers in an infant rat model.
Philipp BaumannSusanne WiegertFrancesco GrecoSven WellmannPietro L'AbateVincenzo CannizzaroPublished in: Physiological reports (2019)
Mechanical ventilation (MV) is routinely used in pediatric general anesthesia and critical care, but may adversely affect the cardiocirculatory system. Biomarkers are increasingly measured to assess cardiovascular status and improve clinical treatment decision-making. As the impact of mechanical ventilation strategies on cardiovascular biomarkers in ventilated infants is largely unknown, we conducted this retrospective study in a healthy in vivo infant rat ventilation model using 14-days old Wistar rats. We hypothesized that 2 h of mechanical ventilation with high and low positive end-expiratory pressure (PEEP), hyperoxemia, hypoxemia, hypercapnia, and hypocapnia would significantly impact B-type natriuretic peptide (BNP), vascular endothelial growth factor (VEGF), and endothelin-1 (ET-1). We found BNP to be driven by both high (9 cmH2 O) and low (1 cmH2 O) PEEP compared to ventilated control animals (P < 0.05). VEGF concentrations were associated with high PEEP, hyperoxemia, hypoxemia, and hypocapnia (P < 0.05), whereas ET-1 levels were changed only in response to hypoxemia (P < 0.05). In conclusion, the mode of mechanical ventilation alters plasma biomarker concentrations. Moreover, BNP and VEGF might serve as surrogate parameters for ventilation induced cardiovascular compromise and lung tissue damage. Furthermore, our data support the hypothesis, that sudden onset of hyperoxemia may trigger a quick VEGF release as a possible cellular survival reflex.
Keyphrases
- mechanical ventilation
- vascular endothelial growth factor
- acute respiratory distress syndrome
- intensive care unit
- respiratory failure
- endothelial cells
- extracorporeal membrane oxygenation
- high glucose
- decision making
- oxidative stress
- machine learning
- electronic health record
- drug induced
- artificial intelligence
- data analysis