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Bacterial Gastroenteritis01:18

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Bacterial gastroenteritis, characterized by diarrhea, abdominal cramps, and vomiting, is often caused by ingestion of contaminated food or water and is frequently associated with pathogenic Escherichia coli strains. These microbes exploit two principal mechanisms to inflict disease.Shiga toxin–producing E. coli, also referred to as STEC—notably O157:H7—release Shiga toxins that target ribosomes, blocking protein synthesis. The B subunit of the toxin binds the host glycolipid receptor...

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A Novel Human Epithelial Enteroid Model of Necrotizing Enterocolitis
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Rapidly progressive necrotizing enterocolitis: Risk factors and a predictive model.

Jicheng Li1,2, Jingjing Zhou1,2, Jingwen Weng1,2

  • 1Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, 100045, China.

Pediatric Research
|August 15, 2024
PubMed
Summary

A new predictive model identifies infants at high risk for rapidly progressive necrotizing enterocolitis (RP-NEC), a severe condition with high mortality. This model aids in early detection and intervention for neonatal care.

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Area of Science:

  • Neonatal Medicine
  • Pediatric Surgery
  • Critical Care

Background:

  • Rapidly progressive necrotizing enterocolitis (RP-NEC) is a severe subtype of necrotizing enterocolitis (NEC) with a high mortality rate.
  • Limited research exists on predicting RP-NEC, highlighting the need for early identification strategies.

Purpose of the Study:

  • To establish a predictive model for identifying infants with RP-NEC.
  • To investigate risk factors associated with surgical intervention or death within 48 hours of NEC onset.

Main Methods:

  • Retrospective single-center cohort study of newborn infants with NEC (Bell's stage ≥ IIB) from 2016-2023.
  • Defined RP-NEC as the need for surgical intervention and/or death within 48 hours of NEC onset.
  • Identified independent risk factors using statistical analysis.

Main Results:

  • 82 out of 334 infants (24.6%) were diagnosed with RP-NEC.
  • Independent risk factors for RP-NEC included low plasma sodium, elevated C-reactive protein, low platelet count, low lymphocyte count, acidosis (pH <7.2), and ascites.
  • The predictive model demonstrated high accuracy with an AUC of 0.983.

Conclusions:

  • A predictive model incorporating six key factors (plasma sodium, CRP, platelets, lymphocytes, blood gas pH, ascites) is highly effective for identifying RP-NEC.
  • This model shows excellent calibration and is a promising tool for early detection and management of RP-NEC.