Bronchopulmonary dysplasia predicted at birth by artificial intelligence

Abstract

Aim: To develop a fast bedside test for prediction and early targeted intervention of bronchopulmonary dysplasia (BPD) to improve the outcome.

Methods: In a multicentre study of preterm infants with gestational age 24-31 weeks, clinical data present at birth were combined with spectral data of gastric aspirate samples taken at birth and analysed using artificial intelligence. The study was designed to develop an algorithm to predict development of BPD. The BPD definition used was the consensus definition of the US National Institutes of Health: Requirement of supplemental oxygen for at least 28 days with subsequent assessment at 36 weeks postmenstrual age.

Results: Twenty-six (43%) of the 61 included infants developed BPD. Spectral data analysis of the gastric aspirates identified the most important wave numbers for classification and surfactant treatment, and birth weight and gestational age were the most important predictive clinical data. By combining these data, the resulting algorithm for early diagnosis of BPD had a sensitivity of 88% and a specificity of 91%.

Conclusion: A point-of-care test to predict subsequent development of BPD at birth has been developed using a new software algorithm allowing early targeted intervention of BPD which could improve the outcome.

Keywords: bronchopulmonary dysplasia; chorioamnionitis; respiratory distress syndrome; spectroscopy; surfactant.

Figure 1

Flow chart of inclusion and number of infants with and without BPD. Three infants without BPD died before day 21 and were excluded. BPD indicates bronchopulmonary dysplasia. NEC indicates necrotizing enterocolitis.

Figure 2

Fourier transform infrared spectrum of gastric aspirate from an infant born in week 31. The fingerprint region is the most informative region in the spectrum for analysis of biological material. Each peak denotes a composition of chemical bonds. The spectrum can be further differentiated to obtain underlying signals. To diagnose bronchopulmonary dysplasia, calculations as described in the manuscript are needed. The infant is not included in the actual study. Dipalmitoyl‐phosphatidylcholine the most surface‐active part of surfactant is expressed in the high peak at 1740 cm⁻¹ together with other phospholipids. Therefore, the infant may have mature lungs.

Figure 3

Predictions of bronchopulmonary dysplasia (BPD) and no BPD were considered accurate in samples where repeated cross‐validation outcomes exceeded 50%. Cross‐validation is a method to evaluate how accurately the predictive model will perform in practice. (A) It can be seen that the spectral data predicted the outcome accurately in 42 (69%) of the 61 infants. (B) The combined spectral and clinical data, surfactant treatment, birth weight and gestational age, predicted the outcome accurately in 52 (85%) cases. Infant no 1, 11, 40 and 42 could only be predicted accurately by spectroscopy (A).