Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Postnatal Risk Factors

The Bronchopulmonary Dysplasia score: A predictive model for bronchopulmonary dysplasia or death in high-risk preterm infants

AIM

Progressive respiratory deterioration in infants at high risk of bronchopulmonary dysplasia (BPD) is associated with patent ductus arteriosus (PDA) exposure. This study aimed to design an early predictive model for BPD or death in preterm infants using early echocardiographic markers and clinical data.

METHODS

Infants born with gestational age (GA) ≤ 29 weeks and/or birth weight (BW) < 1500 g at Cork University Maternity Hospital, Ireland were retrospectively evaluated. Those with echocardiography performed between 36 h and 7 days of life were eligible for inclusion. Exclusion criteria were pulmonary hypertension and major congenital anomalies. The primary outcome was a composite of BPD and death before discharge.

RESULTS

The study included 99 infants. A predictive model for the primary outcome was developed, which included three variables (BW, Respiratory Severity Score and flow pattern across the PDA), and yielding an area under the curve of 0.98 (95% CI 0.96-1.00, p < 0.001). Higher scores were predictive of the primary outcome. A cut-off of -1.0 had positive and negative predictive values of 89% and 98%, and sensitivity and specificity of 98% and 88%, respectively.

CONCLUSION

Our prediction model is an accessible bedside tool that predicts BPD or death in premature infants.

Prevalence, Severity Patterns and Risk Factors of Bronchopulmonary Dysplasia in Preterm Infants Younger than 32 Weeks of Gestation in a Tertiary Centre in Oman

Objectives

This study aimed to determine the rate and severity patterns of bronchopulmonary dysplasia (BPD) and identify antenatal and postnatal factors associated with BPD in preterm infants <32 weeks of gestational age (GA).

Methods

This retrospective observational study included preterm neonates <32 weeks of gestation admitted into the neonatal intensive care unit between January 2010 and December 2017 at Sultan Qaboos University Hospital, Muscat, Oman. A data set of antenatal and perinatal factors were collected. BPD was defined as the need for oxygen and/or respiratory support at 36 weeks post-menstrual age (PMA). Infants with and without BPD were compared in their antenatal and perinatal factors.

Results

A total of 589 preterm infants <32 weeks were admitted. Among them, 505 (85.7%) survived to 36 weeks' PMA and 90 (17.8%) had BPD. The combined BPD and mortality rate was 28.4%. Grades 1, 2 and 3 BPD constituted 77.8%, 7.8% and 14.4%, respectively. BPD was associated with lower GA, lower birth weight, need for intubation at resuscitation, lower Apgar scores, longer duration of ventilation, surfactant therapy and higher rates of neonatal morbidities. On binary logistic regression analysis, predictors of BPD were longer duration of ventilation, intraventricular haemorrhage (IVH) and necrotising enterocolitis (NEC).

Conclusion

In an Omani centre, 17.8% of preterm infants (<32 weeks GA) developed BPD. Various perinatal and neonatal factors were associated with BPD. However, longer duration of ventilation, IVH grades 1 and 2 and NEC stages II and III were significant predictors. Future multicentre research is necessary to provide the overall prevalence of BPD in Oman to help optimise the resources for BPD prevention and management in preterm infants.

Plasma KL-6 as a Potential Biomarker for Bronchopulmonary Dysplasia in Preterm Infants

Background

KL-6 is a biomarker of interstitial lung injury and increases during repair.

Aim

Our aim was to determine the predictive value of plasma KL-6 for the development of bronchopulmonary dysplasia (BPD) in preterm infants.

Methods

Ninety-five extremely preterm infants (EPIs), born at <28 gestational age (GA), were divided into two main BPD groups as follows: the moderate/severe and the no/mild group. KL-6 was analyzed on days 7 and 14. Binary logistic regression analyses and ROC curve analyses were performed.

Results

Infants <26 + 0 weeks' GA have higher mean KL-6 than infants >25 + 6 weeks' GA on 7 and 14 days (335 vs. 286 U/ml and 378 vs. 260 U/ml; p = 0.005 and 0.018, respectively). In the binary regression model at KL-6 day 7, three of the prognostic factors remained significant-mechanical ventilation OR: 10.38 (95% CI: 3.57-30.14), PDA OR: 6.39 (95% CI: 0.87-46.74), and KL-6 OR: 4.98 (95% CI: 1.54-16.08). The AUC was 0.86 with a sensitivity and specificity of 79% at a cutoff value ≥0.34. In the binary regression model at KL-6 day 14, six of the prognostic factors were significant-PDA OR: 23.34 (95% CI: 2.14-254.24), KL-6 OR: 13.59 (95% CI: 3.19-57.96), GA OR: 4.58 (95% CI: 1.16-18.06), mechanical ventilation OR: 4.45 (95% CI: 1.23-16.16), antenatal steroids OR: 0.19 (95% CI: 0.04-0.95), and gender (female OR: 0.30 (95% CI 0.08-1.12)). The AUC was 0.91, and the sensitivity and accuracy for a cutoff ≥0.37 were 89% and 85%, respectively.

Conclusion

KL-6 could be a useful screening biomarker for early detection of infants at increased risk for developing BPD.

The value of hematocrit for predicting bronchopulmonary dysplasia in very low birth weight preterm infants

To determine hematocrit (HCT) and to identify independent risk factors for predicting bronchopulmonary dysplasia (BPD) in preterm infants with very low birth weight (VLBW) infants. This retrospective study included 296 premature infants with VLBW in the neonatal intensive care unit of the First Affiliated Hospital of the University of Science and Technology of China between January 2015 and December 2019. Maternal pregnant information and clinical information as well as hematological parameters of preterm babies were collected and compared. Then the maximum area under the curve of receiver operating characteristic curve was developed to estimate the predictive indicator in the blood. Finally, differential variables together with the predictive index were screened for multiple logistic regression analysis to determine independent prognostic factors for BPD. Infants were divided into a BPD group (134 cases) and a non-BPD group (162 cases). The area under the curve of HCT at postnatal 1 week was 0.737 with the sensitivity of 52.30 % and the specificity of 86.00%. Birth weight (BW) <1.12 kg, gestational age <28.4 weeks, newborn respiratory distress syndrome, mechanical ventilation ≥ 7 days, ventilation associated pneumonia, patent arterial duct, PaO2/FiO2 <300 mm Hg and HCT <0.455 at postnatal 1 week were risk factors for BPD of VLBW infants. HCT levels below 0.455 at 1 week after birth serve as a valuable indicator for the potential development of BPD.

A nomogram for predicting the risk of Bronchopulmonary dysplasia in premature infants

Background

Bronchopulmonary dysplasia (BPD) is a prevalent and critical complication among premature infants, with potentially long-lasting adverse effetcs. The present study aimed to establish a nomogram model to predict the risk of BPD in premature infants born at <32 weeks gestational age.

Methods

A retrospective single-center study was conducted on premature infants admitted to the neonatal intensive care unit (NICU) of the Children's Hospital of Nanjing Medical University from January 2018 to December 2020. Data were collected from clinical medical records, including the perinatal data and the critical information after birth. Clinical parameters and features were analyzed using univariate and multivariate logistic regression. A nomogram based on clinical data was established and validated using bootstrapping samples. The specificity and sensitivity of the nomogram were estimated using the receiver operating characteristic (ROC) based area under the curve (AUC).

Results

A total of 542 premature babies were included, and 152 infants (28.04%) were diagnosed with BPD. Birth weight, cesarean delivery, invasive/non-invasive ventilation at day 7 and 14 were identified as significant factors (p < 0.05) using univariate and the multivariate logistic regression analysis, and were entered into a nomogram. The calibration curve for BPD probability demonstrated a favorable concurrence between actual probability and predicted ability of the BPD nomogram. The nomogram showed potential differentiation, with an AUC of 0.925, 89.90% sensitivity, 76.71% specificity, and 86.35% accuracy.

Conclusion

The nomogram developed in this study provides a straightforward tool to predict the probability of BPD and assist clinicians in optimizing treatment regimens for premature infants born at <32 weeks gestational age. This study highlights the importance of identifying and monitoring significant clinical factors associated with BPD in premature infants to improve clinical outcomes.

Two-stage learning-based prediction of bronchopulmonary dysplasia in very low birth weight infants: a nationwide cohort study

Introduction

The aim of this study is to develop an enhanced machine learning-based prediction models for bronchopulmonary dysplasia (BPD) and its severity through a two-stage approach integrated with the duration of respiratory support (RSd) using prenatal and early postnatal variables from a nationwide very low birth weight (VLBW) infant cohort.

Methods

We included 16,384 VLBW infants admitted to the neonatal intensive care unit (NICU) of the Korean Neonatal Network (KNN), a nationwide VLBW infant registry (2013-2020). Overall, 45 prenatal and early perinatal clinical variables were selected. A multilayer perceptron (MLP)-based network analysis, which was recently introduced to predict diseases in preterm infants, was used for modeling and a stepwise approach. Additionally, we applied a complementary MLP network and established new BPD prediction models (PMbpd). The performances of the models were compared using the area under the receiver operating characteristic curve (AUROC) values. The Shapley method was used to determine the contribution of each variable.

Results

We included 11,177 VLBW infants (3,724 without BPD (BPD 0), 3,383 with mild BPD (BPD 1), 1,375 with moderate BPD (BPD 2), and 2,695 with severe BPD (BPD 3) cases). Compared to conventional machine learning (ML) models, our PMbpd and two-stage PMbpd with RSd (TS-PMbpd) model outperformed both binary (0 vs. 1,2,3; 0,1 vs. 2,3; 0,1,2 vs. 3) and each severity (0 vs. 1 vs. 2 vs. 3) prediction (AUROC = 0.895 and 0.897, 0.824 and 0.825, 0.828 and 0.823, 0.783, and 0.786, respectively). GA, birth weight, and patent ductus arteriosus (PDA) treatment were significant variables for the occurrence of BPD. Birth weight, low blood pressure, and intraventricular hemorrhage were significant for BPD ≥2, birth weight, low blood pressure, and PDA ligation for BPD ≥3. GA, birth weight, and pulmonary hypertension were the principal variables that predicted BPD severity in VLBW infants.

Conclusions

We developed a new two-stage ML model reflecting crucial BPD indicators (RSd) and found significant clinical variables for the early prediction of BPD and its severity with high predictive accuracy. Our model can be used as an adjunctive predictive model in the practical NICU field.

Risk factors and machine learning prediction models for bronchopulmonary dysplasia severity in the Chinese population

BACKGROUND

Bronchopulmonary dysplasia (BPD) is a common chronic lung disease in extremely preterm neonates. The outcome and clinical burden vary dramatically according to severity. Although some prediction tools for BPD exist, they seldom pay attention to disease severity and are based on populations in developed countries. This study aimed to develop machine learning prediction models for BPD severity based on selected clinical factors in a Chinese population.

METHODS

In this retrospective, single-center study, we included patients with a gestational age < 32 weeks who were diagnosed with BPD in our neonatal intensive care unit from 2016 to 2020. We collected their clinical information during the maternal, birth and early postnatal periods. Risk factors were selected through univariable and ordinal logistic regression analyses. Prediction models based on logistic regression (LR), gradient boosting decision tree, XGBoost (XGB) and random forest (RF) models were implemented and assessed by the area under the receiver operating characteristic curve (AUC).

RESULTS

We ultimately included 471 patients (279 mild, 147 moderate, and 45 severe cases). On ordinal logistic regression, gestational diabetes mellitus, initial fraction of inspiration O2 value, invasive ventilation, acidosis, hypochloremia, C-reactive protein level, patent ductus arteriosus and Gram-negative respiratory culture were independent risk factors for BPD severity. All the XGB, LR and RF models (AUC = 0.85, 0.86 and 0.84, respectively) all had good performance.

CONCLUSIONS

We found risk factors for BPD severity in our population and developed machine learning models based on them. The models have good performance and can be used to aid in predicting BPD severity in the Chinese population.

Development and Validation of a Risk Scoring Tool for Bronchopulmonary Dysplasia in Preterm Infants Based on a Systematic Review and Meta-Analysis

Background: Bronchopulmonary dysplasia (BPD) is the most common serious pulmonary morbidity in preterm infants with high disability and mortality rates. Early identification and treatment of BPD is critical. Objective: This study aimed to develop and validate a risk scoring tool for early identification of preterm infants that are at high-risk for developing BPD. Methods: The derivation cohort was derived from a systematic review and meta-analysis of risk factors for BPD. The statistically significant risk factors with their corresponding odds ratios were utilized to construct a logistic regression risk prediction model. By scoring the weights of each risk factor, a risk scoring tool was established and the risk stratification was divided. External verification was carried out by a validation cohort from China. Results: Approximately 83,034 preterm infants with gestational age < 32 weeks and/or birth weight < 1500 g were screened in this meta-analysis, and the cumulative incidence of BPD was about 30.37%. The nine predictors of this model were Chorioamnionitis, Gestational age, Birth weight, Sex, Small for gestational age, 5 min Apgar score, Delivery room intubation, and Surfactant and Respiratory distress syndrome. Based on the weight of each risk factor, we translated it into a simple clinical scoring tool with a total score ranging from 0 to 64. External validation showed that the tool had good discrimination, the area under the curve was 0.907, and that the Hosmer-Lemeshow test showed a good fit (p = 0.3572). In addition, the results of the calibration curve and decision curve analysis suggested that the tool showed significant conformity and net benefit. When the optimal cut-off value was 25.5, the sensitivity and specificity were 0.897 and 0.873, respectively. The resulting risk scoring tool classified the population of preterm infants into low-risk, low-intermediate, high-intermediate, and high-risk groups. This BPD risk scoring tool is suitable for preterm infants with gestational age < 32 weeks and/or birth weight < 1500 g. Conclusions: An effective risk prediction scoring tool based on a systematic review and meta-analysis was developed and validated. This simple tool may play an important role in establishing a screening strategy for BPD in preterm infants and potentially guide early intervention.

Predictors of Bronchopulmonary Dysplasia in Infants With Birth Weight Less Than 1500 g

Bronchopulmonary dysplasia (BPD) is a complication of preterm and low birth weight infants. The incidence of BPD has not decreased over the past 20 years. Complications of BPD include rehospitalization, chronic lung disease, cardiovascular disease, and impaired growth and development which will affect the patient's quality of life. There are unfortunately limited data available regarding BPD in Indonesia. This study is expected to be a reference in taking preventive measures to reduce mortality and morbidity in preterm and low birth infants. This study aims to determine predictors of BPD in infants with birth weight less than 1500 g. We conducted a retrospective cohort study that included 116 infants with birth weight <1500 g. Twenty-two (19%) infants had BPD with the highest proportion (63.6%) in the 28 to 31 weeks of gestational age. Multivariate analysis showed mechanical ventilation in more than first 2 days of life (P = .008; HR = 7.7), hematocrit <39% (P = .001; HR = 12), and hemodynamically significant patent ductus arteriosus (hsPDA; P = .041; HR = 3.5) were significant predictors of BPD in infants with birth weight <1500 g.

The Role of the Interleukin-1 Family in Complications of Prematurity

Preterm birth is a major contributor to neonatal morbidity and mortality. Complications of prematurity such as bronchopulmonary dysplasia (BPD, affecting the lung), pulmonary hypertension associated with BPD (BPD-PH, heart), white matter injury (WMI, brain), retinopathy of prematurity (ROP, eyes), necrotizing enterocolitis (NEC, gut) and sepsis are among the major causes of long-term morbidity in infants born prematurely. Though the origins are multifactorial, inflammation and in particular the imbalance of pro- and anti-inflammatory mediators is now recognized as a key driver of the pathophysiology underlying these illnesses. Here, we review the involvement of the interleukin (IL)-1 family in perinatal inflammation and its clinical implications, with a focus on the potential of these cytokines as therapeutic targets for the development of safe and effective treatments for early life inflammatory diseases.

Extracellular Vesicle-microRNAs as Diagnostic Biomarkers in Preterm Neonates

Neonates born prematurely (<37 weeks of gestation) are at a significantly increased risk of developing inflammatory conditions associated with high mortality rates, including necrotizing enterocolitis, bronchopulmonary dysplasia, and hypoxic-ischemic brain damage. Recently, research has focused on characterizing the content of extracellular vesicles (EVs), particularly microRNAs (miRNAs), for diagnostic use. Here, we describe the most recent work on EVs-miRNAs biomarkers discovery for conditions that commonly affect premature neonates.

Lung ultrasound in premature infants as an early predictor of bronchopulmonary dysplasia

PURPOSE

Lung ultrasound (LUS) is a widely used technique in neonates to diagnose a lot of acute diseases. However, its role in the diagnosis of chronic lung conditions is still to be evaluated. We aimed to describe the changes in ultrasound images as well as the appearance of lung consolidations (LC) in very low birth weight (VLBW) infants with and without bronchopulmonary dysplasia (BPD).

METHODS

For a period of 2 years we prospectively examined 124 VLBW infants, divided into two main groups: below 28 gestational weeks with two subgroups-BPD (moderate and severe) and non-BPD, and 28-32 gestational weeks with two subgroups-BPD (moderate and severe) and non-BPD group. We performed weekly LUS until 36 weeks' postmenstrual age (PMA). On the seventh postnatal day, we calculated the LUS score as a semiquantitative score that represents the aeration (0-3) in three different areas (upper anterior, lower anterior, lateral) of each lung.

RESULTS

We performed around 750 LUS exams. The BPD groups had LUS scores above 8 on the seventh day, p < 0.001. The number of LC was higher in the BPD groups 14 (3-45) than in the mild or non-BPD groups 2.5 (0-6), p < 0.001, and the difference was significant for the period between 1 week and 1 month after birth, p = 0.001. In the BPD group <28 weeks' PMA, LC appeared equally in the anterior, lateral, and posterior fields, while in the BPD group 28-32 weeks' PMA, LC are more typical for the anterior-lateral fields.

CONCLUSION

Serial LUS exams and identification of LC could be early predictors of moderate and severe forms of BPD. LUS score >8 on the seventh postnatal day is an early predictor of severe BPD. LC in more lung fields are typical for the severe forms of the disease.

Landscape analysis for a neonatal disease progression model of bronchopulmonary dysplasia: Leveraging clinical trial experience and real-world data

The 21^st Century Cures Act requires FDA to expand its use of real-world evidence (RWE) to support approval of previously approved drugs for new disease indications and post-marketing study requirements. To address this need in neonates, the FDA and the Critical Path Institute (C-Path) established the International Neonatal Consortium (INC) to advance regulatory science and expedite neonatal drug development. FDA recently provided funding for INC to generate RWE to support regulatory decision making in neonatal drug development. One study is focused on developing a validated definition of bronchopulmonary dysplasia (BPD) in neonates. BPD is difficult to diagnose with diverse disease trajectories and few viable treatment options. Despite intense research efforts, limited understanding of the underlying disease pathobiology and disease projection continues in the context of a computable phenotype. It will be important to determine if: 1) a large, multisource aggregation of real-world data (RWD) will allow identification of validated risk factors and surrogate endpoints for BPD, and 2) the inclusion of these simulations will identify risk factors and surrogate endpoints for studies to prevent or treat BPD and its related long-term complications. The overall goal is to develop qualified, fit-for-purpose disease progression models which facilitate credible trial simulations while quantitatively capturing mechanistic relationships relevant for disease progression and the development of future treatments. The extent to which neonatal RWD can inform these models is unknown and its appropriateness cannot be guaranteed. A component of this approach is the critical evaluation of the various RWD sources for context-of use (COU)-driven models. The present manuscript defines a landscape of the data including targeted literature searches and solicitation of neonatal RWD sources from international stakeholders; analysis plans to develop a family of models of BPD in neonates, leveraging previous clinical trial experience and real-world patient data is also described.

Progressive Metabolic Abnormalities Associated with the Development of Neonatal Bronchopulmonary Dysplasia

Objective: To assess the longitudinal metabolic patterns during the evolution of bronchopulmonary dysplasia (BPD) development. Methods: A case-control dataset of preterm infants (<32-week gestation) was obtained from a multicenter database, including 355 BPD cases and 395 controls. A total of 72 amino acid (AA) and acylcarnitine (AC) variables, along with infants’ calorie intake and growth outcomes, were measured on day of life 1, 7, 28, and 42. Logistic regression, clustering methods, and random forest statistical modeling were utilized to identify metabolic variables significantly associated with BPD development and to investigate their longitudinal patterns that are associated with BPD development. Results: A panel of 27 metabolic variables were observed to be longitudinally associated with BPD development. The involved metabolites increased from 1 predominant different AC by day 7 to 19 associated AA and AC compounds by day 28 and 16 metabolic features by day 42. Citrulline, alanine, glutamate, tyrosine, propionylcarnitine, free carnitine, acetylcarnitine, hydroxybutyrylcarnitine, and most median-chain ACs (C5:C10) were the most associated metabolites down-regulated in BPD babies over the early days of life, whereas phenylalanine, methionine, and hydroxypalmitoylcarnitine were observed to be up-regulated in BPD babies. Most calorie intake and growth outcomes revealed similar longitudinal patterns between BPD cases and controls over the first 6 weeks of life, after gestational adjustment. When combining with birth weight, the derived metabolic-based discriminative model observed some differences between those with and without BPD development, with c-statistics of 0.869 and 0.841 at day 7 and 28 of life on the test data. Conclusions: The metabolic panel we describe identified some metabolic differences in the blood associated with BPD pathogenesis. Further work is needed to determine whether these compounds could facilitate the monitoring and/or investigation of early-life metabolic status in the lung and other tissues for the prevention and management of BPD.

Corticosteroid response predicts bronchopulmonary dysplasia status at 36 weeks in preterm infants treated with dexamethasone: A pilot study

IMPORTANCE

A major barrier to therapeutic development in neonates is a lack of standardized drug response measures that can be used as clinical trial endpoints. The ability to quantify treatment response in a way that aligns with relevant downstream outcomes may be useful as a surrogate marker for new therapies, such as those for bronchopulmonary dysplasia (BPD).

OBJECTIVE

To construct a measure of clinical response to dexamethasone that was well aligned with the incidence of severe BPD or death at 36 weeks' postmenstrual age.

DESIGN

Retrospective cohort study.

SETTING

Level IV Neonatal Intensive Care Unit.

PARTICIPANTS

Infants treated with dexamethasone for developing BPD between 2010 and 2020.

MAIN OUTCOME(S) AND MEASURE(S)

Two models were built based on demographics, changes in ventilatory support, and partial pressure of carbon dioxide (pCO₂ ) after dexamethasone administration. An ordinal logistic regression and regularized binary logistic model for the composite outcome were used to associate response level to BPD outcomes defined by both the 2017 BPD Collaborative and 2018 Neonatal Research Network definitions.

RESULTS

Ninety-five infants were treated with dexamethasone before 36 weeks. Compared to the baseline support and demographic data at the time of treatment, changes in ventilatory support improved ordinal model sensitivity and specificity. For the binary classification, BPD incidence was well aligned with risk levels, increasing from 16% to 59%.

CONCLUSIONS AND RELEVANCE

Incorporation of response variables as measured by changes in ventilatory parameters and pCO₂ following dexamethasone administration were associated with downstream outcomes. Incorporating drug response phenotype into a BPD model may enable more rapid development of future therapeutics.

Enteral Feeding/Total Fluid Intake Ratio Is Associated With Risk of Bronchopulmonary Dysplasia in Extremely Preterm Infants

Background

Nutrition is an essential factor in preventing and managing bronchopulmonary dysplasia (BPD), a multifactorial chronic respiratory disease in premature infants. This study examined the association between nutritional intakes during the first 2 weeks of life and BPD in extremely preterm infants.

Methods

A retrospective single-center cohort study was performed in infants born <28 weeks' gestational age or with a birth weight <1,000 g. Intake of energy and ratio of enteral feeding/ total fluid intake during the first 2 weeks of life and association with outcome of BPD were examined.

Results

134 infants were included in our study, and 43 infants (32.1%) developed BPD. During the first 2 weeks of life, the average of total caloric intake and the ratio of enteral feeding/ total fluid intake were significantly lower in the BPD group (total caloric intake:91.90 vs. 95.72 kcal/kg/d, p < 0.05, ratio of enteral feeding/total fluid intake: 0.14 vs. 0.18, p < 0.05), while the average of total fluid intake, caloric and protein intake from parenteral nutrition did not differ between the groups. The ratio of enteral feeding/ total fluid intake during the second week were significantly lower in the BPD group (0.21 vs. 0.28, p < 0.05), while this ratio during the first week did not differ between the groups. An increase of 10% in the ratio of enteral feeding/ total fluid intake during the second week of life significantly reduced the risk of BPD (OR 0.444, 95% CI: 0.270-0.731).

Conclusions

A higher ratio of enteral feeding/ total fluid intake was associated with a lower risk for BPD. Early and rapidly progressive enteral nutrition should be encouraged in extremely preterm infants in the absence of feeding intolerance.

Predictive values of clinical data,molecular biomarkers, and echocardiographic measurements in preterm infants with bronchopulmonary dysplasia

Objective

We aimed to use molecular biomarkers and clinical data and echocardiograms that were collected during admission to predict bronchopulmonary dysplasia (BPD) in preterm infants with gestational age ≤32 weeks.

Methods

Eighty-two patients (40 with BPD, BPD group and 42 healthy as controls, non-BPD group) admitted to the Department of Neonatology of the Children's Hospital of Soochow University between October 1, 2018, and February 29, 2020, were enrolled in this study at the tertiary hospital. Basic clinical data on the perinatal period, echocardiographic measurements, and molecular biomarkers (N-terminal-pro-B-brain natriuretic peptide, NT-proBNP) were collected. We used multiple logistic regression analysis to establish an early predictive model for detecting BPD development in preterm infants of gestational age ≤32 weeks. We also used a receiver operating characteristic curve to assess the sensitivity and specificity of the model.

Results

No significant differences were found between the BPD and non-BPD groups in terms of sex, birth weight, gestational age, incidence of asphyxia, maternal age, gravidity, parity, mode of delivery, premature rupture of membranes >18 h, use of prenatal hormones, placental abruption, gestational diabetes mellitus, amniotic fluid contamination, prenatal infections, and maternal diseases. The use of caffeine, albumin, gamma globulin; ventilation; days of FiO₂ ≥ 40%; oxygen inhalation time; red blood cell suspension infusion volume (ml/kg); and proportion of infants who received total enteral nutrition (120 kcal/kg.d) ≥24 d after birth were higher in the BPD group than in the non-BPD group. The levels of hemoglobin, hematocrit, and albumin in the BPD group were significantly lower than those in the non-BPD group. The total calorie intake was significantly lower in the BPD group on the 3rd, 7th, and 14th day after birth than in the non-BPD group (P < 0.05). The incidence rates of patent ductus arteriosus (PDA), pulmonary hypertension, and tricuspid regurgitation were significantly higher in the BPD group than in the non-BPD group (P < 0.05). The serum level of NT-proBNP 24 h after birth was significantly higher in the BPD group than in the non-BPD group (P < 0.05). Serum NT-proBNP levels were significantly higher in infants with severe BPD than in those with mild or moderate BPD (P < 0.05).

Conclusion

As there were various risk factors for BPD, a combining clinical data, molecular biomarkers, and echocardiogram measurements can be valuable in predicting the BPD. The tricuspid regurgitation flow rate (m/s), NT-proBNP (pg/ml), ventilator-associated pneumonia, days of FiO₂ ≥ 40% (d), red blood cell suspension infusion volume (ml/kg), and proportion of infants who received total enteral nutrition (120 kcal/kg.d) ≥24 d after birth were the most practical factors considered for designing an appropriate model for predicting the risk of BPD.

The value of plasma insulin-like growth factor 1 and interleukin-18 in the diagnosis of bronchopulmonary dysplasia in premature infants

OBJECTIVE

To explore the diagnostic value of IGF-1 and IL-18 in premature infants with BPD.

METHODS

Through a prospective observational study, the serum samples of infants in the BPD group and the non-BPD group were collected at different targeted time points, and the serum IGF-1 and IL-18 concentrations were dynamically monitored by ELISA. The Student t-test and one-way analysis of variance were adopted to analyze data, and the receiver operating characteristic (ROC) curve was used to test the diagnostic value.

RESULT

A total of 90 VLBW premature infants admitted to NICU between January 2020 and 2021 were finally included. Compared with the non-BPD group, infants diagnosed with BPD had a significantly lower serum concentration of IGF-1 (P < 0.05) but a higher level of IL-18 (P < 0.05) on days 1, 7, 14, and 28 after birth. With the ROC curve analysis, the serum concentration IGF-1 on day 14 and IL-18 on day 28 reported high sensitivity and specificity to predict the risk of BPD (IGF-1: sensitivity: 89.29%, specificity: 77.78%, AUC: 0.8710; IL-18: sensitivity: 53.57%, specificity: 83.33%, AUC: 0.7887). And more substantial predictive power was found in combined analysis of IGF-1 and serum IL-18 on day 14: the sensitivity was 91.07% and the specificity was 83.33%, with the AUC of 0.9142.

CONCLUSION

IGF-1 and IL-18 might be closely involved in the occurrence and development of BPD. The serum concentration of IGF-1 combined with IL-18 could be potentially sensitive markers for the early diagnosis and severity of BPD.

Construction of early risk prediction models for bronchopulmonary dysplasia in preterm infants

OBJECTIVES

To construct risk prediction models for bronchopulmonary dysplasia (BPD) in preterm infants on postnatal days 3, 7, and 14.

METHODS

A retrospective analysis was performed on the medical data of 414 preterm infants, with a gestational age of <32 weeks and a birth weight (BW) of <1 500 g, who were admitted to the neonatal intensive care unit from July 2019 to April 2021. According to the diagnostic criteria for BPD revised in 2018, they were divided into a BPD group with 98 infants and a non-BPD group with 316 infants. The two groups were compared in terms of general status, laboratory examination results, treatment, and complications. The logistic regression model was used to identify the variables associated with BPD. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of models.

RESULTS

The logistic regression analysis showed that BW, asphyxia, grade III-IV respiratory distress syndrome (RDS), acute chorioamnionitis, interstitial pneumonia, fraction of inspired oxygen (FiO2), and respiratory support mode were the main risk factors for BPD (P<0.05). The prediction models on postnatal days 7 and 14 were established as logit (P7) =-2.049-0.004×BW (g) +0.686×asphyxia (no=0, yes=1) +1.842×grade III-IV RDS (no=0, yes=1) +0.906×acute chorioamnionitis (no=0, yes=1) +0.506×interstitial pneumonia (no=0, yes=1) +0.116×FiO2 (%) +0.816×respiratory support mode (no=0, nasal tube=1, nasal continuous positive airway pressure=2, conventional mechanical ventilation=3, high-frequency mechanical ventilation=4) and logit (P14) =-1.200-0.004×BW (g) +0.723×asphyxia+2.081×grade III-IV RDS+0.799×acute chorioamnionitis+0.601×interstitial pneumonia+0.074×FiO2 (%) +0.800×respiratory support mode, with an area under the ROC curve (AUC) of 0.876 and 0.880, respectively, which was significantly larger than the AUC of the prediction model on postnatal day 3 (P<0.05).

CONCLUSIONS

BW, asphyxia, grade III-IV RDS, acute chorioamnionitis, interstitial pneumonia, FiO2, and respiratory support mode are the main risk factors for BPD and can be used to construct risk prediction models. The prediction models on postnatal days 7 and 14 can effectively predict BPD.

Does Chrysin prevent severe lung damage in Hyperoxia-Induced lung injury Model?

BACKGROUND

Oxidative stress and inflammation play a critical role in the etiopathogenesis of bronchopulmonary dysplasia (BPD). The aim of this study was to evaluate the preventive effect of Chrysin (CH), an antioxidant, antiinflammatory, antiapoptotic and antifibrotic drug, on hyperoxia-induced lung injury in a neonatal rat model.

METHODS

Forty infant rats were divided into four groups labeled the Control, CH, BPD, and BPD + CH. The control and CH groups were kept in a normal room environment, while the BPD and BPD + CH groups were kept in a hyperoxic (90-95%) environment. At the end of the study, lung tissue was evaluated with respect to apoptosis, histopathological damage and alveolar macrophage score as well as oxidant capacity, antioxidant capacity, and inflammation.

RESULTS

Compared to the BPD + CH and control groups, the lung tissues of the BPD group displayed substantially higher levels of MDA, TOS, TNF-α, and IL-1β (p < 0.05). While the BPD + CH group showed similar levels of TNF-α and IL-1β as the control group, MDA and TOS levels were higher than the control group, and significantly lower than the BPD group (p < 0.05). The BPD group exhibited considerably lower levels of TAS, SOD, GSH, and GSH-Px in comparison to the control group (p < 0.05). The BPD and BPD + CH groups exhibited higher mean scores of histopathological damage and alveolar macrophage when compared to the control and CH groups (p ≤ 0.0001). Both scores were found to be lower in the BPD + CH group in comparison to the BPD group (p ≤ 0.0001). The BPD + CH group demonstrated a significantly lower average of TUNEL and caspase-3 positive cells than the BPD group.

CONCLUSION

We found that prophylaxis with CH results in lower histopathological damage score and reduces apoptotic cell count, inflammation and oxidative stress while increasing anti-oxidant capacity.

Hyperoxia-activated circulating extracellular vesicles induce lung and brain injury in neonatal rats

Hyperoxia-induced lung injury plays a key role in the development of bronchopulmonary dysplasia (BPD), characterized by inflammatory injury and impaired lung development in preterm infants. Although BPD is a predictor of poor neurodevelopmental outcomes, currently it is uncertain how lung injury contributes to brain injury in preterm infants. Extracellular vesicles (EVs) are a heterogeneous group of cell-derived membranous structures that regulate intercellular and inter-organ communications. Gasdermin D (GSDMD) has emerged as a key executor of inflammasome-mediated cell death and inflammation. In this study, we utilized a neonatal rat model of BPD to assess if hyperoxia stimulates lung release of circulating EVs and if these EVs induce lung and brain injury. We found that hyperoxia-exposed rats had elevated numbers of plasma-derived EVs compared to rats maintained in room air. These EVs also had increased cargos of surfactant protein C, a marker of type II alveolar epithelial cells (AEC), and the active (p30) form of GSDMD. When these EVs were adoptively transferred into normal newborn rats via intravenous injection, they were taken up both by lung and brain tissues. Moreover, EVs from hyperoxic animals induced not only the pathological hallmarks of BPD, but also brain inflammatory injury in recipient rats, as well as inducing cell death in cultured pulmonary vascular endothelial cells and neural stem cells (NSC). Similarly, hyperoxia-exposed cultured AEC-like cells released EVs that also contained increased GSDMD-p30 and these EVs induced pyroptotic cell death in NSC. Overall, these data indicate that hyperoxia-activated circulating EVs mediate a lung to brain crosstalk resulting in brain injury and suggest a mechanism that links lung injury and neurodevelopmental impairment in BPD infants.

[Association of early nutrition deficiency with the risk of bronchopulmonary dysplasia: a Meta analysis]

OBJECTIVE

To systematically evaluate the association of early nutrition intake with the risk of bronchopulmonary dysplasia (BPD).

METHODS

PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data, and Weipu Periodical Database were searched for the observational studies on the association between early nutrition intake and BPD. RevMan 5.3 software was used to perform a Meta analysis of eligible studies.

RESULTS

Eight observational studies were included, with 548 infants with BPD and 522 infants without BPD. The Meta analysis showed that the BPD group had a significantly lower caloric intake than the non-BPD group within the first week after birth and in the first 2 weeks after birth (P < 0.05). The BPD group had a significantly lower enteral nutrition intake than the non-BPD group (WMD=-18.27, 95%CI:-29.70 to -6.84, P < 0.05), as well as a significantly lower intake of carbohydrate, fat, and protein (P < 0.05). The BPD group had a significantly longer duration of parenteral nutrition than the non-BPD group (WMD=14.26, 95%CI:13.26-15.25, P < 0.05).

CONCLUSIONS

Early nutrition deficiency may be associated with the development of BPD, and more attention should be paid to enteral feeding of infants at a high risk of BPD to achieve total enteral feeding as soon as possible.

Evidence for the Management of Bronchopulmonary Dysplasia in Very Preterm Infants

BACKGROUND

Very preterm birth often results in the development of bronchopulmonary dysplasia (BPD) with an inverse correlation of gestational age and birthweight. This very preterm population is especially exposed to interventions, which affect the development of BPD.

OBJECTIVE

The goal of our review is to summarize the evidence on these daily procedures and provide evidence-based recommendations for the management of BPD.

METHODS

We conducted a systematic literature research using MEDLINE/PubMed on antenatal corticosteroids, surfactant-replacement therapy, caffeine, ventilation strategies, postnatal corticosteroids, inhaled nitric oxide, inhaled bronchodilators, macrolides, patent ductus arteriosus, fluid management, vitamin A, treatment of pulmonary hypertension and stem cell therapy.

RESULTS

Evidence provided by meta-analyses, systematic reviews, randomized controlled trials (RCTs) and large observational studies are summarized as a narrative review.

DISCUSSION

There is strong evidence for the use of antenatal corticosteroids, surfactant-replacement therapy, especially in combination with noninvasive ventilation strategies, caffeine and lung-protective ventilation strategies. A more differentiated approach has to be applied to corticosteroid treatment, the management of patent ductus arteriosus (PDA), fluid-intake and vitamin A supplementation, as well as the treatment of BPD-associated pulmonary hypertension. There is no evidence for the routine use of inhaled bronchodilators and prophylactic inhaled nitric oxide. Stem cell therapy is promising, but should be used in RCTs only.

Development and Validation of a Nomogram for Predicting Bronchopulmonary Dysplasia in Very-Low-Birth-Weight Infants

Background: Bronchopulmonary dysplasia is a common pulmonary disease in newborns and is one of the main causes of death. The aim of this study was to build a new simple-to-use nomogram to screen high-risk populations. Methods: In this single-center retrospective study performed from January 2017 to December 2020, we reviewed data on very-low-birth-weight infants whose gestational ages were below 32 weeks. LASSO regression was used to select variables for the risk model. Then, we used multivariable logistic regression to build the prediction model incorporating these selected features. Discrimination was assessed by the C-index, and and calibration of the model was assessed by and calibration curve and the Hosmer-Lemeshow test. Results: The LASSO regression identified gestational age, duration of ventilation and serum NT-proBNP in the 1st week as significant predictors of BPD. The nomogram-illustrated model showed good discrimination and calibration. The C-index was 0.853 (95% CI: 0.851-0.854) in the training set and 0.855 (95% CI: 0.77-0.94) in the validation set. The calibration curve and Hosmer-Lemeshow test results showed good calibration between the predictions of the nomogram and the actual observations. Conclusion: We demonstrated a simple-to-use nomogram for predicting BPD in the early stage. It may help clinicians recognize high-risk populations.

Risk Identification of Bronchopulmonary Dysplasia in Premature Infants Based on Machine Learning

Bronchopulmonary dysplasia (BPD) is one of the most common complications in premature infants. This disease is caused by long-time use of supplemental oxygen, which seriously affects the lung function of the child and imposes a heavy burden on the family and society. This research aims to adopt the method of ensemble learning in machine learning, combining the Boruta algorithm and the random forest algorithm to determine the predictors of premature infants with BPD and establish a predictive model to help clinicians to conduct an optimal treatment plan. Data were collected from clinical records of 996 premature infants treated in the neonatology department of Liuzhou Maternal and Child Health Hospital in Western China. In this study, premature infants with congenital anomaly, premature infants who died, and premature infants with incomplete data before the diagnosis of BPD were excluded from the data set. After exclusion, we included 648 premature infants in the study. The Boruta algorithm and 10-fold cross-validation were used for feature selection in this study. Six variables were finally selected from the 26 variables, and the random forest model was established. The area under the curve (AUC) of the model was as high as 0.929 with excellent predictive performance. The use of machine learning methods can help clinicians predict the disease so as to formulate the best treatment plan.