Arterial Pressure Monitoring in Pediatric Patients Undergoing Cardiac Surgery: An Observational Study Comparing Invasive and Non-invasive Measurements

A cluster-randomized trial of water, sanitation, handwashing and nutritional interventions on stress and epigenetic programming

A regulated stress response is essential for healthy child growth and development trajectories. We conducted a cluster-randomized trial in rural Bangladesh (funded by the Bill & Melinda Gates Foundation, ClinicalTrials.gov NCT01590095) to assess the effects of an integrated nutritional, water, sanitation, and handwashing intervention on child health. We previously reported on the primary outcomes of the trial, linear growth and caregiver-reported diarrhea. Here, we assessed additional prespecified outcomes: physiological stress response, oxidative stress, and DNA methylation (N = 759, ages 1-2 years). Eight neighboring pregnant women were grouped into a study cluster. Eight geographically adjacent clusters were block-randomized into the control or the combined nutrition, water, sanitation, and handwashing (N + WSH) intervention group (receiving nutritional counseling and lipid-based nutrient supplements, chlorinated drinking water, upgraded sanitation, and handwashing with soap). Participants and data collectors were not masked, but analyses were masked. There were 358 children (68 clusters) in the control group and 401 children (63 clusters) in the intervention group. We measured four F2-isoprostanes isomers (iPF(2α)-III; 2,3-dinor-iPF(2α)-III; iPF(2α)-VI; 8,12-iso-iPF(2α)-VI), salivary alpha-amylase and cortisol, and methylation of the glucocorticoid receptor (NR3C1) exon 1F promoter including the NGFI-A binding site. Compared with control, the N + WSH group had lower concentrations of F2-isoprostanes isomers (differences ranging from -0.16 to -0.19 log ng/mg of creatinine, P < 0.01), elevated post-stressor cortisol (0.24 log µg/dl; P < 0.01), higher cortisol residualized gain scores (0.06 µg/dl; P = 0.023), and decreased methylation of the NGFI-A binding site (-0.04; P = 0.037). The N + WSH intervention enhanced adaptive responses of the physiological stress system in early childhood.

Predicting acute kidney injury with an artificial intelligence-driven model in a pediatric cardiac intensive care unit

BACKGROUND

Acute kidney injury (AKI) is among the most common complications following cardiac surgery in adult and pediatric patients, significantly affecting morbidity and mortality. Artificial Intelligence (AI) with Machine Learning (ML) can be used to predict outcomes. AKI diagnosis anticipation may be an ideal target of these methods. The scope of the study is building a Machine Learning (ML) train model with Random Forest (RF) algorithm, based on electronic health record (EHR) data, able to forecast AKI continuously after 48 h in post-cardiac surgery children, and to test its performance. Four hundred nineteen consecutive patients out of 1115 hospital admissions were enrolled in a single-center retrospective study. Patients were younger than 18 years and admitted from August 2018 to February 2020 in a pediatric cardiac intensive care unit (PCICU) undergoing cardiac surgery, invasive procedure (hemodynamic studies), and medical conditions with complete EHR records and discharged after 48 h or more.

RESULTS

Thirty-six variables were selected to build the algorithm according to commonly described cardiac surgery-associated AKI clinical predictors. We evaluated different models for different outcomes: binary AKI (no AKI vs. AKI), severe AKI (no-mild vs severe AKI), and multiclass classification (maximum AKI and the most frequent level of AKI, mode AKI). The algorithm performance was assessed with the area under the curve receiver operating characteristics (AUC ROC) for binary classification, with accuracy and K for multiclass classification. AUC ROC for binary AKI was 0.93 (95% CI 0.92-0.94), and for severe AKI was 0.99 (95% CI 0.98-1). Mode AKI accuracy was 0.95, and K was 0.80 (95% CI 0.94-0.96); maximum AKI accuracy was 0.92, and K was 0.71 (95% CI 0.91-0.93). The importance matrix plot demonstrated creatinine, basal creatinine, platelets count, adrenaline support, and lactate dehydrogenase for binary AKI with the addition of cardiopulmonary bypass duration for severe AKI as the most relevant variables of the model.

CONCLUSIONS

We validated a ML model to detect AKI occurring after 48 h in a retrospective observational study that could help clinicians in individuating patients at risk of AKI, in which a preventive strategy can be determinant to improve the occurrence of renal dysfunction.

Near-infrared spectroscopy monitoring of neonatal cerebrovascular reactivity: where are we now?

Cerebrovascular reactivity defines the ability of the cerebral vasculature to regulate its resistance in response to both local and systemic factors to ensure an adequate cerebral blood flow to meet the metabolic demands of the brain. The increasing adoption of near-infrared spectroscopy (NIRS) for non-invasive monitoring of cerebral oxygenation and perfusion allowed investigation of the mechanisms underlying cerebrovascular reactivity in the neonatal population, confirming important associations with pathological conditions including the development of brain injury and adverse neurodevelopmental outcomes. However, the current literature on neonatal cerebrovascular reactivity is mainly still based on small, observational studies and is characterised by methodological heterogeneity; this has hindered the routine application of NIRS-based monitoring of cerebrovascular reactivity to identify infants most at risk of brain injury. This review aims (1) to provide an updated review on neonatal cerebrovascular reactivity, assessed using NIRS; (2) to identify critical points that need to be addressed with targeted research; and (3) to propose feasibility trials in order to fill the current knowledge gaps and to possibly develop a preventive or curative approach for preterm brain injury. IMPACT: NIRS monitoring has been largely applied in neonatal research to assess cerebrovascular reactivity in response to blood pressure, PaCO₂ and other biochemical or metabolic factors, providing novel insights into the pathophysiological mechanisms underlying cerebral blood flow regulation. Despite these insights, the current literature shows important pitfalls that would benefit to be addressed in a series of targeted trials, proposed in the present review, in order to translate the assessment of cerebrovascular reactivity into routine monitoring in neonatal clinical practice.

Comparison of invasive blood pressure monitoring versus normal non-invasive blood pressure monitoring in ST-elevation myocardial infarction patients with percutaneous coronary intervention

BACKGROUND

Hypotension post percutaneous coronary intervention (PCI) causes stent thrombosis and reduced coronary perfusion, which aggravate myocardial ischemia and lead to patient death. Therefore, the accuracy and timeliness of blood pressure monitoring (BPM) are crucial for the nursing of patients post PCI. However, it is still controversial whether invasive blood pressure monitoring (IBPM) or non-invasive blood pressure monitoring (NIBPM) should be used for patients post PCI, and the magnitude of their assistance for patients' recovery remains unclear.

METHODS

A randomized controlled trial was performed in this study. 126 ST-segment elevation myocardial infarction (STEMI) patients post PCI were recruited and randomly divided into two groups (NIBPM group n = 63; IBPM group n = 63).

RESULTS

Clinical characteristics and physiological outcomes of participants received different BPM methods were collected and analyzed to compare the effects of these two methods on the nursing of PCI patients. Compared to NIBPM group, IBPM assisted to shorten the time of myocardial ischemia, promote coronary reperfusion, reduce the occurrence of cardiovascular disease and other complications, and ultimately reduce the mortality of patients post PCI.

CONCLUSION

The application of IBPM contributed to reduce the occurrence of complications, shorten the time of vascular reperfusion, and guide treatment of clinicians in time.

Cardiac Output Measurement With Echocardiography and Pressure Recording Analytical Method in Pediatric Patients Admitted to the Cardiac Intensive Care Unit: A Retrospective Assessment of Bias Between the Two Methods

OBJECTIVES

This study aimed to compare, in a cohort of critically ill children with biventricular anatomy and no cardiovascular shunt, cardiac output (CO) and cardiac index (CI) assessed by echocardiography and a continuous pulse-contour method, MostCare^UP, to measure the differences between these techniques (biasCO and biasCI), and their association with clinical variables.

DESIGN

Retrospective study.

SETTING

Tertiary pediatric cardiac intensive care unit.

PARTICIPANTS

Children admitted to the pediatric cardiac intensive care unit who underwent echocardiography with CO measurement.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Thirty-five patients were included. BiasCO was -0.02 (0.26) L/min (percentage error 36%). BiasCI was 0.07 (0.34) L/min/m² (percentage error 18%). Biases and percentage errors were higher in 24 nonsupervised echocardiographies. A negative biasCO (overestimation by MostCare^UP) was associated with post-surgical status (v cardiomyopathy), higher systolic arterial pressure, and spontaneous breathing (v intubation). When only absolute values were considered, biasCO_NONEG correlated with age, weight, arterial pressure, and heart rate, whereas biasCI_NONEG was associated with a femoral arterial cannula, no use of inotropes, and the absence of mechanical ventilation. After adjustment, biasCO_NONEG remained independently associated with patients' body weight(p = 0.0001). BiasCI_NONEG showed a nonlinear relationship with weight below 20 kg and above 40 kg.

CONCLUSIONS

Children with extreme low or high weights, those who are extubated, and those with a femoral cannula carry the highest bias. When younger patients are considered, CI should be evaluated instead of CO, because biases are better highlighted by indexing data on body surface area. In children, both echocardiography and MostCare^UP may be responsible of inaccurate CO/CI assessment.