Julia M Pantalone1, Silvia Liu2, Oluwabunmi O Olaloye3,4, Erica C Prochaska3,5, Toby Yanowitz3, Melissa M Riley3,6, Justin R Buland3,6, Beverly S Brozanski3,6, Misty Good3,6, Liza Konnikova1,3,4,7,8. 1. University of Pittsburgh School of Medicine, Pittsburgh, PA, United States. 2. Department of Pathology, University of Pittsburgh, Pittsburgh, PA, United States. 3. Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, United States. 4. Department of Pediatrics, Yale School of Medicine, New Haven, CT, United States. 5. Division of Infectious Diseases, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United States. 6. Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States. 7. Department of Immunology, University of Pittsburgh, Pittsburgh, PA, United States. 8. Department of Developmental Biology, University of Pittsburgh, Pittsburgh, PA, United States.
Abstract
Objective: Necrotizing enterocolitis (NEC) is characterized by peripheral cell abnormalities, yet few studies have analyzed the complete blood count (CBC) specifically by gestational age (GA). Our objective was to describe GA-specific immune abnormalities in NEC through a comprehensive analysis of the CBC differential. Methods: Using a cohort of 246 infants (177 cases, 69 controls) admitted to neonatal intensive care units at a single institution, we retrospectively analyzed CBCs around illness onset in NEC cases compared with controls. Cases included surgical NEC (S-NEC, 34.5%) and medical NEC (M-NEC, 65.5%). Infants were divided into those born at GA <33 and ≥33 weeks. Differences in CBC values were described as absolute and percent changes at NEC onset from baseline and at antibiotic completion after NEC. We used machine learning algorithms based on the CBC at NEC to generate predictive models for diagnosis. Results: At NEC onset, there was an acute drop in monocytes and lymphocytes along with a rise in bands in S-NEC infants born <33 weeks compared with M-NEC. In comparison, both M-NEC and S-NEC ≥33 weeks had a percent drop in neutrophils at diagnosis compared with controls. At antibiotic completion, monocytes in S-NEC <33 weeks significantly rose compared with M-NEC, yet for S-NEC ≥33 weeks, bands significantly dropped compared with M-NEC. Predictive modeling was able to accurately predict S-NEC from M-NEC and controls. Conclusion: There are discrete leukocyte patterns in NEC based on GA. The CBC at diagnosis may be useful in identifying patients who will require surgery.
Objective: Necrotizing enterocolitis (NEC) is characterized by peripheral cell abnormalities, yet few studies have analyzed the complete blood count (CBC) specifically by gestational age (GA). Our objective was to describe GA-specific immune abnormalities in NEC through a comprehensive analysis of the CBC differential. Methods: Using a cohort of 246 infants (177 cases, 69 controls) admitted to neonatal intensive care units at a single institution, we retrospectively analyzed CBCs around illness onset in NEC cases compared with controls. Cases included surgical NEC (S-NEC, 34.5%) and medical NEC (M-NEC, 65.5%). Infants were divided into those born at GA <33 and ≥33 weeks. Differences in CBC values were described as absolute and percent changes at NEC onset from baseline and at antibiotic completion after NEC. We used machine learning algorithms based on the CBC at NEC to generate predictive models for diagnosis. Results: At NEC onset, there was an acute drop in monocytes and lymphocytes along with a rise in bands in S-NEC infants born <33 weeks compared with M-NEC. In comparison, both M-NEC and S-NEC ≥33 weeks had a percent drop in neutrophils at diagnosis compared with controls. At antibiotic completion, monocytes in S-NEC <33 weeks significantly rose compared with M-NEC, yet for S-NEC ≥33 weeks, bands significantly dropped compared with M-NEC. Predictive modeling was able to accurately predict S-NEC from M-NEC and controls. Conclusion: There are discrete leukocyte patterns in NEC based on GA. The CBC at diagnosis may be useful in identifying patients who will require surgery.
Authors: O Troyanskaya; M Cantor; G Sherlock; P Brown; T Hastie; R Tibshirani; D Botstein; R B Altman Journal: Bioinformatics Date: 2001-06 Impact factor: 6.937
Authors: D K Lambert; R D Christensen; V L Baer; E Henry; P V Gordon; G E Besner; J Wilkes; S E Wiedmeier; E Gerday Journal: J Perinatol Date: 2011-05-12 Impact factor: 2.521