Enhanced predictive accuracy of mortality in VLBW infants with late-onset sepsis through a time-specific nomogram

This dynamic, time-specific nomogram demonstrates high predictive accuracy and clinical utility for mortality in VLBW infants with LOS. The impact of maternal COVID-19 infection on neonatal outcomes offers a novel perspective for future research in sepsis prognostication.

Authors

Institutions

Publication Details

Journal
Frontiers in Public Health
Published
2025-04-02
DOI
https://doi.org/10.3389/fpubh.2025.1548695
Primary Topic
Neonatal and Maternal Infections
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhanced predictive accuracy of mortality in VLBW infants with late-onset sepsis through a time-specific nomogram

Lun Yu, Yanhong Li, Zuming Yang
Frontiers in Public Health
Neonatal and Maternal Infections
article

Enhanced predictive accuracy of mortality in VLBW infants with late-onset sepsis through a time-specific nomogram

Lun Yu, Yanhong Li, Zuming Yang
article en

Abstract

This dynamic, time-specific nomogram demonstrates high predictive accuracy and clinical utility for mortality in VLBW infants with LOS. The impact of maternal COVID-19 infection on neonatal outcomes offers a novel perspective for future research in sepsis prognostication.

Frontiers in Public HealthVol. 13
Soochow University (CN), Suzhou Municipal Hospital (CN)
Openalex Percentile: Top 91%
Neonatal and Maternal Infections
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.