Response to first dose of inhaled albuterol in mechanically ventilated preterm infants

The impact of intermittent hypoxemia on type 1 retinopathy of prematurity in preterm infants

BACKGROUND

Intermittent hypoxemia (IH) may influence retinopathy of prematurity (ROP) development in preterm infants, however, previous studies had mixed results. This study tests the hypothesis that increased IH is associated with Type 1 ROP; a stage beyond which treatment is indicated.

METHODS

IH was quantified by continuously monitoring oxygen saturation (SpO2) using high-resolution pulse oximeters during the first 10 weeks of life. Statistical analyses assessed the relationship and predictive ability of weekly and cumulative IH for Type 1 ROP development.

RESULTS

Most analyses showed no association between IH and Type 1 ROP adjusting for gestational age (GA) and birth weight (BW). However, cumulative IH of longer duration during weeks 5-10, 6-10, and 7-10 were significantly associated with Type 1 ROP adjusting for GA and BW, e.g., the adjusted odds ratio of Type 1 ROP was 2.01 (p = 0.03) for every 3.8 seconds increase in IH duration from week 6-10. IH did not provide statistically significant added predictive ability above GA and BW.

CONCLUSIONS

For most analyses there was no significant association between IH and Type 1 ROP adjusting for GA and BW. However, infants with longer IH duration during the second month of life had higher risk for Type 1 ROP.

IMPACT

The relationship and predictive ability of intermittent hypoxemia (IH) on retinopathy of prematurity (ROP) is controversial. This study shows no significant association between IH events and Type 1 ROP after adjusting for gestational age (GA) and birth weight (BW), except for cumulative IH of longer duration in the second month of life. In this cohort, IH does not provide a statistically significant improvement in ROP prediction over GA and BW. This study is the first to assess the cumulative impact of IH measures on Type 1 ROP. Interventions for reducing IH duration during critical postnatal periods may improve ROP outcomes.

Predicting Extubation Readiness in Preterm Infants Utilizing Machine Learning: A Diagnostic Utility Study

OBJECTIVE

The objective of this study was to predict extubation readiness in preterm infants using machine learning analysis of bedside pulse oximeter and ventilator data.

STUDY DESIGN

This is an observational study with prospective recordings of oxygen saturation (SpO2) and ventilator data from infants <30 weeks of gestation age. Research pulse oximeters collected SpO2 (1 Hz sampling rate) to quantify intermittent hypoxemia (IH). Continuous ventilator metrics were collected (4-5-minute sampling) from bedside ventilators. Data modeling was completed using unbiased machine learning algorithms. Three model sets were created using the following data source combinations: (1) IH and ventilator (IH + SIMV), (2) IH, and (3) ventilator (SIMV). Infants were also analyzed separated by postnatal age (infants <2 or ≥2 weeks of age). Models were compared by area under the receiver operating characteristic curve (AUC).

RESULTS

A total of 110 extubation events from 110 preterm infants were analyzed. Infants had a median gestation age and birth weight of 26 weeks and 825 g, respectively. Of the 3 models presented, the IH + SIMV model achieved the highest AUC of 0.77 for all infants. Separating infants by postnatal age increased accuracy further achieving AUC of 0.94 for <2 weeks of age group and AUC of 0.83 for ≥2 weeks group.

CONCLUSIONS

Machine learning analysis has the potential to enhance prediction accuracy of extubation readiness in preterm infants while utilizing readily available data streams from bedside pulse oximeters and ventilators.

Aerosol delivery in models of pediatric high flow nasal oxygen and mechanical ventilation

BACKGROUND

Aerosol drug delivery during high flow nasal oxygen (HFNO) and invasive mechanical ventilation (IMV) are key respiratory care strategies available for the treatment of pediatric patients. We aimed to quantify the impact of different HFNO and IMV set-ups on tracheal drug delivery via a vibrating mesh nebuliser (VMN).

METHODS

Percent tracheal dose via VMN was quantified during HFNO therapy and IMV in a benchtop model of a 9-month-old infant. Under HFNO, 3 cannula sizes were used at 3 flow rate settings with the VMN placed at the dry side of the humidifier. Under IMV, tracheal dose when VMN was placed at the dry side of the humidifier, 15 cm from the wye and between the wye and endotracheal tube (ETT) was assessed. Salbutamol at 2.5 mg/2.5 ml (1 mg/ml) was used for each test (N = 5). The impact of VMN refill on circuit pressure under HFNO and IMV was also assessed.

RESULTS

Tracheal dose was highest during HFNO with the largest cannula size (OPT318) set to the lowest flow rate setting of 2 L/min (liter per minute) (5.80 ± 0.17%). Increasing flow rate reduced tracheal drug delivery for all cannulas. For IMV, VMN on the dry side of the humidifier and between the wye and ETT gave optimal drug delivery (4.49 ± 0.14% vs. 4.43 ± 0.26% respectively). VMN refill did not impact circuit pressure for either HFNO therapy or IMV.

CONCLUSIONS

Gas flow rate and cannula size during HFNO and VMN position during IMV has a significant effect on tracheal drug delivery in a pediatric setting.