Background: To construct a nomogram for predicting necrotizing enterocolitis (NEC) in preterm infants.
Methods: A total of 4,724 preterm infants who were admitted into 8 hospitals between April 2019 and September 2020 were initially enrolled this retrospective multicenter cohort study. Finally, 1,092 eligible cases were divided into training set and test set based on a 7:3 ratio. A univariate logistic regression analysis was performed to compare the variables between the two groups. Stepwise backward regression, LASSO regression, and Boruta feature selection were utilized in the multivariate analysis to identify independent risk factors. Then a nomogram model was constructed based on the identified risk factors.
Results: Risk factors for NEC included gestational diabetes mellitus, gestational age, small for gestational age, patent ductus arteriosus, septicemia, red blood cell transfusion, intravenous immunoglobulin, severe feeding intolerance, and absence of breastfeeding. The nomogram model developed based on these factors showed well discriminative ability. Calibration and decision curve analysis curves confirmed the good consistency and clinical utility of the model.
Conclusions: We developed a nomogram model with strong discriminative ability, consistency, and clinical utility for predicting NEC. This model could be valuable for the early prediction of preterm infants at risk of developing NEC.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.dld.2024.08.038 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Survival and immune microenvironment prediction of glioma based on MRI imaging genomics method: a retrospective observational study.
Neurosurg Rev
January 2025
Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
Glioma is characterized by high heterogeneity and poor prognosis. Attempts have been made to understand its diversity in both genetic expressions and radiomic characteristics, while few integrated the two omics in predicting survival of glioma. This study was intended to investigate the connection between glioma imaging and genome, and examine its predictive value in glioma mortality risk and tumor immune microenvironment (TIME).
View Article and Find Full Text PDFNomogram model based on serum chitotriosidase activity to predict coronary artery aneurysm in Kawasaki disease.
Coron Artery Dis
January 2025
Department of Pediatrics, Pidu Maternal and Child Care Hospital.
Objective: Kawasaki disease (KD) is a common children's disease with unknown etiology, which easily involves coronary artery and causes serious cardiovascular sequelae. The purpose was to investigate the relationship between chitotriosidase activity and coronary artery aneurysm (CAA) and develop and validate a nomogram to predict CAA in KD patients.
Methods: A total of 338 KD patients were included in this study.
Identification and validation of the diagnostic biomarker MFAP5 for CAVD with type 2 diabetes by bioinformatics analysis.
Front Immunol
January 2025
Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Introduction: Calcific aortic valve disease (CAVD) is increasingly prevalent among the aging population, and there is a notable lack of drug therapies. Consequently, identifying novel drug targets will be of utmost importance. Given that type 2 diabetes is an important risk factor for CAVD, we identified key genes associated with diabetes - related CAVD via various bioinformatics methods, which provide further potential molecular targets for CAVD with diabetes.
View Article and Find Full Text PDFMachine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response.
Front Immunol
January 2025
Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Introduction: Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is often associated with unfavorable prognosis. Due to its unique anatomical position and the absence of effective early inspection methods, surgical intervention alone is frequently inadequate for achieving complete remission. Therefore, the identification of reliable biomarker is crucial to enhance the accuracy of screening and treatment strategies for HNSCC.
View Article and Find Full Text PDFA Novel Differentiation Nomogram Model for Brucellar Spondylitis and Tuberculous Spondylitis.
Infect Drug Resist
December 2024
Department of Spine Surgery, The First People's Hospital of Kashi Prefecture, Kashi, Xinjiang, 844000, People's Republic of China.
Background: Tuberculous spondylitis (TS) and brucellar spondylitis (BS) exhibit certain similarities in clinical presentation and imaging characteristics, making differential diagnosis challenging. Developing a reliable differential diagnosis model can assist clinicians in distinguishing between these two conditions at an early stage, allowing for targeted prevention and treatment strategies.
Methods: Patients diagnosed with TS and BS were retrospectively collected and randomized into training and validation cohorts (ratio 7:3).
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!