The relationship between hematological parameters and bronchopulmonary dysplasia in premature infants

Jiang, Junsheng; Zhou, Qian; Wu, Jianhua; Mao, Yueyan

doi:10.21203/rs.3.rs-2517316/v1

Cited by 2 publications

(2 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous research has identi ed SIRI as a potential biomarker for predicting BPD [34] . PMI re ects the body's in ammatory and immune statuses [33] , consistent with Sati research [35] .…”

Section: Discussionsupporting

confidence: 84%

Construction and Application of Early Stratification Dynamic Prediction Model for Bronchopulmonary Dysplasia in Extremely Premature / Very Low Birth Weight Infants

An,

Yang,

Zhang

et al. 2024

Preprint

View full text Add to dashboard Cite

Objective To investigate the independent risk factors for Bronchopulmonary Dysplasia (BPD) at different time points within the first week in extremely premature/very low birth weight infants and to construct an early stratification dynamic prediction model for BPD through machine learning, aiming to achieve dynamic prediction of BPD for the early identification of high-risk groups and preemptive prevention. Methods A retrospective collection of clinical data was conducted on premature infants admitted to the Neonatology Department of the First Affiliated Hospital of Xinjiang Medical University from January 2017 to December 2022, with gestational age (GA) < 32 weeks or birth weight (BW) < 1500g. Eligible subjects were randomly divided into training and validation sets in a 7:3 ratio for model building and internal validation. Prospective clinical data from preterm infants admitted to six neonatal rescue centers in various districts of Xinjiang from January to October 2023 were independently collected to validate the practical application value of each model. Clinical parameters were collected, and study participants were divided into three groups: no BPD, mild BPD, and moderate to severe BPD (msBPD). Machine learning predictive models for BPD stratification employing logistic regression (LR), random forest (RF), XGBoost (XGB), and gradient boosting decision tree (GBDT) were constructed for postnatal days 1, 3, and 7. Comprehensive evaluation was performed to select the optimal model at each time point and proceed to external validation. Results The study retrospectively gathered data from 554 preterm infants (286 no BPD, 212 mild, and 56 msBPD cases). Prospectively, 387 preterm infants (208 no BPD, 138 mild, and 41 msBPD cases). On ordinal logistic regression, GA, BW, prenatal steroids, interruption of umbilical blood flow, severe preeclampsia, FIO2, CRP, RBC, systemic inflammatory response index (SIRI), prognostic nutritional index, platelet mass index, alveolar-arterial oxygen difference, and oxygenation index were independent risk factors for BPD severity at different times after birth. After comprehensive evaluation, the LR and XGB models were identified as better BPD stratification prediction models for postnatal days 1, 3, and 7 (AUC = 0.810,0.837 and 0.813 respectively). Conclusion Early stratification dynamic prediction machine learning models for BPD have been constructed for postnatal days 1, 3, and 7 in extremely premature/very low birth weight infants. These may serve as effective tools for the screening of high-risk BPD populations.

show abstract

“…Previous research has identi ed SIRI as a potential biomarker for predicting BPD [34] . PMI re ects the body's in ammatory and immune statuses [33] , consistent with Sati research [35] .…”

Section: Discussionsupporting

confidence: 84%

Construction and Application of Early Stratification Dynamic Prediction Model for Bronchopulmonary Dysplasia in Extremely Premature / Very Low Birth Weight Infants

An,

Yang,

Zhang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Previous research indicated that Many biomarkers, such as CRP, and PCT, could be used in the auxiliary diagnosis of sepsis, but their serum levels may be affected by many other stimulations other than infection. [22][23][24] therefore, compared with HDL and LDL, their predictive abilities appeared low. That's consistent with our research.…”

Section: Discussionmentioning

confidence: 95%

The potential role of serum lipoprotein in children with sepsis

Wu,

Su,

Jiang

et al. 2023

Medicine

Self Cite

View full text Add to dashboard Cite

To determine whether serum lipoprotein is correlated with sepsis on the day of admission and help with early warning, identification, and intervention for sepsis. This retrospective study involved all children admitted to our pediatric intensive care unit from January 2021 to June 2023. Clinical data of involved patients were collected via inquiring databases of our hospital. The Pediatric Risk of Mortality and Pediatric Index of Mortality II scores were calculated, multivariate analysis was conducted to evaluate the independence of the association between serum lipoprotein and the risk of sepsis on the day of admission. This study involved 88 children (48 with sepsis, 40 non-sepsis). The sepsis group had a lower level of high-density lipoprotein (HDL), total cholesterol, and low-density lipoprotein (LDL). The CRP, white blood cell, and procalcitonin (PCT) were considerably higher than the non-sepsis group. After adjusting for covariates, logistic regression analysis suggested that the CRP, PCT, HDL, Pediatric Risk of Mortality score, Pediatric Index of Mortality II score and LDL were independent risk factors for sepsis. Moreover, the AUC of CRP, PCT, HDL, and LDL were 0.58, 0.76, 0.82, and 0.86, respectively. Our results may indicate that serum lipoprotein is correlated with sepsis on the day of admission and may help with early warning, identification, and intervention for sepsis.

show abstract

The relationship between hematological parameters and bronchopulmonary dysplasia in premature infants

Cited by 2 publications

References 21 publications

Construction and Application of Early Stratification Dynamic Prediction Model for Bronchopulmonary Dysplasia in Extremely Premature / Very Low Birth Weight Infants

Construction and Application of Early Stratification Dynamic Prediction Model for Bronchopulmonary Dysplasia in Extremely Premature / Very Low Birth Weight Infants

The potential role of serum lipoprotein in children with sepsis

Contact Info

Product

Resources

About