Targeted RNA sequencing identified gene expression profiles linked to severe necrosis and mortality in preterm infants with surgical necrotizing enterocolitis

Targeted RNA sequencing identified gene expression profiles linked to severe necrosis and mortality in preterm infants with surgical necrotizing enterocolitis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Targeted RNA sequencing identified gene expression profiles linked to severe necrosis and mortality in preterm infants with surgical necrotizing enterocolitis Parvesh Mohan Garg, David Sawaya, Robin Riddick, Seth Lirette, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7244063/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: We aim to determine the gene expression changes that occur in surgical NEC infants with and without moderate to severe necrosis and survivors and non-survivors. Methods: Targeted RNA sequencing was performed on RNA isolated from formalin-fixed, paraffin-embedded (FFPE) intestinal tissue samples (N=36) .DeSeq2 was used to analyze differential expressions between infants with mild to moderate and severe necrosis and with respect to survival status. Results: Thirty-five genes were differentially expressed (FDR- adjusted p < 0.05) between mild-medium necrosis and severe necrosis. Genes involved in altered host defense, natural killer (NK) cell signaling and development, and apoptosis were overexpressed in severe necrosis ( IGJ , GZMA , TNFSF10 , KLRB1 , and CD160 ). Expression of leukocytes antigens ( ITGAM , ITGAX ) and cytokine and chemokine receptors (such as IL1A , IL1B , CCL2 , CCL3 ) were increased in patients with mild necrosis. Six genes were significantly differentially expressed (FDR- adjusted p < 0.05) between survivors and the non-survivors. Genes related to chemokines attracting neutrophils ( CXCL1 , GBP , PTGS2 , CXCL11 , CXCL9 , and CXCL10) were upregulated in non-survivors. Conclusion: Severe necrosis and non-survival of NEC infants were associated with differential genes expression related to host defense, NK cell signaling and development, and apoptosis. Understanding these pathways can guide the development of prognostic and treatment pathways. Epigenetics & Genomics Preterm Infants NEC Necrosis Mortality Gene Expression RNA sequencing Neonate Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Impact The gene expression profiles in surgical necrotizing enterocolitis (NEC) were found to differ depending on necrosis severity and survival outcome. Significant differences in gene expression levels helped to identify molecular pathways that may be regulated and involved in disease progression. The differentially expressed genes and molecular pathways are potential therapeutic targets for NEC, an incompletely understood and life-threatening disease. Introduction Necrotizing enterocolitis (NEC) is a devastating acute gastrointestinal illness of the neonatal period, affecting about 5-10% of premature infants with birth weights of ≤1500 grams 1,2 . Despite major advances in neonatal intensive care and reductions in all-cause mortality among premature infants, NEC continues to be associated with mortality rates of 25-40% 3-8 . Histopathologically, NEC lesions are marked by coagulative necrosis, inflammation, bacterial overgrowth, and reparative tissue changes 9-16 . A recent study correlated outcomes in NEC with the depth of bacterial invasion and the severity of inflammation in the resected bowel. In addition, the presence of NEC lesions in the resection margins, presumably indicating incomplete removal of necrotic bowel, was also associated with mortality 17 . There is also evidence that including genetic information may be helpful in predicting the disease outcomes in NEC. Twin studies suggest that genetic factors may account for up to 50% of the risk of NEC 18 . Certain single nucleotide polymorphisms SNPs, such as those in carbamyl phosphate synthetase ( T1405N ) 19 , IL12 (p40 promoter CTCTAA/GC) 20 , VEGF (C-2578A) 21 , and NFKB1 (g.-24519delATTG), 22 have been found to be associated with NEC, but genome-wide association studies for NEC are very few 23 . The challenge for neonatologists is to detect early clinical manifestations of NEC. One strategy would be to identify specific markers that could be used as early diagnostic tools to identify preterm infants most at risk of developing NEC or in the event of a diagnostic dilemma of suspected disease. As a step in this direction, we aimed to determine the immune gene expression changes associated with different severities of necrosis, in preterm infants with surgical necrotizing enterocolitis. Additionally, we aimed to determine the differential immune gene expression that occur in survivors and non-survivors in preterm infants with surgical NEC. Methods This study was conducted at the University of Mississippi Medical Center (UMMC), under the oversight of the Institutional Review Board (protocol 2017-0127). The neonatal intensive care unit at UMMC is a regional referral center for infants with surgical NEC. We reviewed the medical and pathology records to identify patients with advanced NEC 24 who underwent an exploratory laparotomy and surgical resection of the bowel during 15 years (January 2000 to December 2015). The patients with spontaneous intestinal perforation were excluded. Demographic characteristics, including birth weight, gestational age, gender, race, mode of delivery, and out born status were retrieved from the patients’ medical records. Maternal data, including pregnancy-induced hypertension, chorioamnionitis, and antenatal steroid use was recorded. Infant characteristics, including mode of delivery, small for gestational age status, Apgar score at 5 minutes, age of NEC onset, mode of clinical presentation (bloody stools, abdominal distension, feeding intolerance), persistent patency of the ductus arteriosus (PDA), use of non-steroidal agents for medical treatment of PDA, assisted ventilation, blood culture-positive sepsis, and duration of antibiotics were recorded. The region of the affected bowel and length of bowel resected was also noted. We also collected data on the length of hospital stay and mortality. The length of hospital stay was defined as the total length of stay from the day of admission until discharge. Mortality was defined as death due to NEC or NEC-associated sepsis. The length of stay was defined as the total length of stay from the day of admission until discharge. To assess postoperative morbidity, we recorded the duration of postoperative ileus, days of parenteral nutrition days, development of short bowel syndrome (SGS), and time to achieve full feeds. Short bowel syndrome was defined as infants who were still requiring TPN more than 90 days following the NEC surgery. Days of parenteral nutrition were defined as the interval between postoperative day 0 until full enteral feedings were achieved (defined as 120 ml/kg/day). Surgical morbidity was classified as surgical site infections (including dehiscence and abscesses), strictures, fistulas, adhesions, and perforations. Histopathological Evaluation: Specimens of surgically resected bowel tissue from the patients with NEC were identified in pathology archives. Hematoxylin and eosin-stained resected bowel tissue sections were recorded for the area of necrosis on the slide (percent), scored as 0, 1 (0-25%), 2 (26-50%), 3 (51-75%), and 4 (76-100%); maximum depth of necrosis, scored as 0, 1 (mucosa), 2 (submucosa), 3 ( muscularis propria ), and 4 (transmural); severity of inflammation, scored as 0 (no inflammatory cells), 1 [up to 50 inflammatory cells/high power field (hpf)], 2 (51-200 inflammatory cells/hpf, 3 (>201 cells/hpf); depth of inflammatory infiltrates, scored as 0, 1 (mucosa), 2 (submucosa), 3 (muscularis propria), and 4 (transmural) 17 . RNA Sequencing Methods: RNA was isolated from 10um section of NEC formalin-fixed, paraffin-embedded (FFPE) human intestine specimens (N=36) obtained following laparotomy Targeted RNA sequencing using the AmpliSeq Illumina Immune Response Panel was utilized for targeted quantitative expression of genes linked to immune system interactions which included 400 genes. Raw reads were de-multiplexed and aligned to human reference genome assembly (hg19) using RNA Amplicon Application (along with custom panel manifest) available on Illumina BaseSpace Computing Platform (DRAGEN APP; http://basespace.illumina.com/). Aligned reads for each gene were normalized for sequencing depth and RNA composition using DESeq2’s median of ratios method and used for downstream differential expression analysis in survivors and the non -survivors while accounting for other covariates such as necrosis. Statistical Analysis: Descriptive statistics were computed; categorical data was summarized as frequencies (absolute and relative) and any simple bivariate comparisons were performed using Fisher’s exact tests or chi square tests. Continuous data were presented as either means with standard deviations, when underlying distributions would be roughly symmetric, or medians with first and third quartiles when skew was noted. Differences in the continuous data were tested using a student’s t -test or if symmetry was in question, a Mann-Whitney U test. A p-value of less than 0.05 was considered significant. Results Clinical data of the 36 infants included in the study are summarized in Table 1. The cohort had mean birth weight of 1005 gm (SD 555 gm) and the mean gestational age of 27.2 weeks (SD3.0). 23 infants were males, and 13 infants were female in the study cohort. In the study 21 infants (21/36, 58.3%) had mild to moderate necrosis and 15 infants (15/36,41.6%) had severe necrosis (score 3-4). Out of 36 infants with surgical NEC, 11 infants (11/36, 30.5%) had died, and 25 infants (25/36, 69.4%) had survived and were included in the analysis. The data are summarized in Table 1. Gene Expression in infants with mild-moderate necrosis and severe necrosis: RNA-Seq analysis and identification of differentially expressed genes (DEGs): Differential expression analysis was used to investigate the association with stage of necrosis and gene expression in preterm infants with NEC. The analysis showed 35 genes were differentially expressed (p < 0.05) between mild-medium necrosis (score 0-2) and severe necrosis (score of 3-4). A majority of the amplicons included in the panel were detected. Genes related to altered host defense, natural killer cell signaling and development, apoptosis etc. were overexpressed in severe necrosis ( IGJ , GZMA , TNFSF10 , KLRB1 , CD160 ). Expression of leukocyte antigens ( ITGAM , ITGAX ) and cytokines and chemokines receptors ( IL1A , IL1B , CCL2 , CCL3 ) were upregulated in patients with mild to moderate necrosis. The data are summarized in figure 1-3. Gene expression in survivor and non-survivor: RNA-Seq analysis and identification of DEGs: Differential expression analysis showed six genes being significantly differentially expressed (FDR adjusted p < 0.05) between survivors and the non-survivors. Genes related to chemokines attracting neutrophils ( CXCL1 ), GBP1 (Guanylate binding protein -1, role in cell-autonomous immunity) and PTGS2 ( prostaglandin-endoperoxide synthase 2 gene, encodes for the cyclooxygenase-2 ( COX2 ) enzyme, needed for prostanoid biosynthesis involved in inflammation and mitogenesis), CXCL11 ( cellular response to lipopolysaccharide; chemokine-mediated signaling pathway; and neutrophil chemotaxis), CXCL9 (Leukocyte chemotaxis, recruitment and differentiation), and CXCL10 (recruits immune cells like macrophages, DCs, NK cells, and Th1 cells to sites of inflammation) were all increased in non-survivors. When tested and accounted for the severity of necrosis contributing to the outcome, 26 genes were differentially expressed between survivors and non-survivors. Genes involved in epithelial cell structure, altered host defense and immune cell signaling and development ( IGJ , GZMA , KLRB1 , KRT5 and CD160 ), were all downregulated in patients with severe necrosis, suggesting a suppressed immune response compared to those with less severe necrosis. On the other hand, expressions of leukocyte antigens ( ITGAM and ITGAX ) and cytokines and chemokines receptors ( IL1B , CCL2 , CCL3 , and CCL4 ) were upregulated in patients with mild to moderate necrosis. The data are summarized in figure 4-7. Discussion Our study investigated the gene expression underlying the severe necrosis and death in preterm infants with surgical NEC, by utilizing mRNA sequencing from formalin-fixed paraffin-embedded intestinal tissue samples. Our results showed that severe necrosis (based on intestinal pathology) in NEC infants was associated with increased expression of genes related to host defense, natural killer cell signaling and development, and apoptosis. Our data also shows that survivors in surgical NEC patients showed distinct immune gene expression profiles, with non-survivors exhibiting increased inflammation and chemotactic signaling. Survivors had increased gene expression of leukocyte antigens and cytokine receptors, indicating a more active immune response relative to non-survivors. The degree of necrosis was associated with additional genes, emphasizing its role in immune regulation differences. Tremblay et al 25 analyzed RNA expression in ileal samples from preterm infants with NEC and compared them to samples from infants with other diseases. They found that NEC intestines showed over-representation of pathways related to innate immunity, such as altered T and B cell signaling, granulocyte adhesion and diapedesis, B cell development, and pattern recognition receptor roles. ToppCluster analysis further revealed that NEC was marked by increased lymphocyte and leukocyte migration, chemotaxis, and adhesion, while functions related to lipid metabolism were down-regulated, defining a distinct biological signature for NEC 25 . We also identified genes related to altered host defense, natural killer cell signaling and development, and apoptosis as being overexpressed in surgical NEC infants with severe necrosis, relative to the others. Tremblay et al 25 reported the up-regulation of CXCL10 , TLR4 , TLR10 , DEFA5 , REG3A , LCN2 and TFF3 and down-regulation of HBA2 and HBG2 expression in NEC. They also reported a high degree of similarity between NEC and Crohn's disease gene expression 25 . Similarly, in our cohort, CXCL11 (cellular response to lipopolysaccharide; chemokine-mediated signaling pathway; and neutrophil chemotaxis), CXCL9 (leukocyte chemotaxis, recruitment and differentiation), and CXCL10 (recruit’s immune cells like macrophages, DCs, NK cells, and Th1 cells to sites of inflammation) were all increased in non-survivors. A recent study by Xie et al. analyzed RNA-Seq data from intestinal tissues of 12 preterm infants with NEC, NEC self-control, and normal controls, detecting 34,712 genes and identifying 7,463 differentially expressed genes (DEGs). Gene Ontology analysis showed these DEGs were mainly involved in chemokine receptor binding, transporter activity, and growth factor binding, while KEGG analysis indicated significant enrichment in toll-like receptor signaling, Th17 cell differentiation, and cytokine–cytokine receptor interaction pathways. Immune infiltration profiles differed notably among the three tissue groups 26 . A recent study analyzed 129 formula-fed preterm piglets diagnosed with necrotizing enterocolitis (NEC) at necropsy on day 5, comparing subgroups of NEC ( n = 20) and control piglets ( n = 19) via whole-blood transcriptome analysis 27 . Lesions were scored on a 1–6 scale, with scores ≥3 indicating NEC. Severe cases (scores 5–6) showed transmural necrosis or pneumatosis intestinalis 27 . 344 differentially expressed genes (DEGs) were identified between NEC and control groups, highlighting systemic immune responses and inflammation. Validation confirmed AOAH, ARG2, FKBP5, PAK2, and STAT3 as genes significantly altered in severe NEC cases, detectable in both whole blood and dried blood spots (DBS) 27 . In summary, blood gene expression changes occurred before severe clinical manifestations, suggesting potential for early NEC detection. DBS sampling emerged as a feasible method for small-volume blood collection in infants, enabling practical biomarker screening 27 . The strength of our study is that we have provided a unique perspective, as we compared gene expression in preterm infants with surgical NEC with varying degrees of disease severity, whereas other studies have compared NEC patients to healthy controls. Some limitations of our study are that our samples were collected from a single center, our sample size was small, and we did not include lack of healthy controls. In addition, FFPE samples typically have poorer quality RNA, which may have biased our results towards more stable transcripts. Finally, due to the design of the study we are unable to demonstrate a cause-and-effect relationship, so it is unclear if the expression differences observed between groups are due to the primary phenotype or a systemic effect due to the disease process. Conclusion In conclusion, this study has led to the identification of several DEGs in intestinal samples of premature infants affected with NEC that could be of clinical interest as potential biomarkers for the prediction of the disease and its diagnosis. Survivors and non-survivors with surgical NEC show distinct immune gene expression profiles, with non-survivors exhibiting increased inflammation and chemotactic signaling. Survivors have upregulation of leukocyte antigens and cytokine receptors, indicating a more active immune response. Degree of necrosis impacts additional genes, emphasizing its role in immune regulation differences. Targeting excessive inflammation and understanding these pathogenic pathways may improve outcomes. Declarations author confirmed that they would like this processed and posted as a preprint. Okay to proceed. Data User Agreement: All data generated and analyzed during this study are included in this article and its supplementary information files. Author Contribution: PMG, and AM designed the study; PMG,DS, RR,AM,PG, NV, NH,TH, SL,WBH analyzed the data and wrote the manuscript. All the authors contributed and approved the manuscript. Funding: Parvesh Garg is partially supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number U54GM115428. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The work performed through the UMMC Molecular and Genomics Facility is supported, in part, by funds from the NIGMS, including the Molecular Center of Health and Disease-COBRE (P20GM144041), Mississippi INBRE (P20GM103476) and Obesity, Cardiorenal and Metabolic Diseases- COBRE (P30GM149404) and Mississippi Center of Perinatal Research (1P20GM121334). Acknowledgment : We are grateful to Dr. Micheal Garrett and Lavanya Challagundla from the UMMC Molecular and Genomics department for supporting the NEC genomics study. We are also grateful to the Mississippi Center for Clinical and Translational Research for supporting NEC research. Conflicts of interest: None Declared Consent: Patient consent was not required as per IRB. References Neu, J. & Walker, W.A. Necrotizing enterocolitis. N. Engl. J. Med. 364 , 255-264 (2011). Sankaran, K. , et al. Variations in incidence of necrotizing enterocolitis in Canadian neonatal intensive care units. J Pediatr Gastroenterol Nutr 39 , 366-372 (2004). Sjoberg Bexelius, T. , et al. Intestinal failure after necrotising enterocolitis: incidence and risk factors in a Swedish population-based longitudinal study. BMJ paediatrics open 2 , e000316 (2018). Allin, B.S.R., Long, A.M., Gupta, A., Lakhoo, K. & Knight, M. One-year outcomes following surgery for necrotising enterocolitis: a UK-wide cohort study. Archives of disease in childhood. Fetal and neonatal edition 103 , F461-f466 (2018). Knell, J., Han, S.M., Jaksic, T. & Modi, B.P. Current Status of Necrotizing Enterocolitis. Curr Probl Surg 56 , 11-38 (2019). Stoll, B.J. , et al. Trends in Care Practices, Morbidity, and Mortality of Extremely Preterm Neonates, 1993-2012. Jama 314 , 1039-1051 (2015). Nair, R., Kahlenberg, C.A., Patel, R.M., Knesek, M. & Terry, M.A. All-Arthroscopic Suprapectoral Biceps Tenodesis. Arthrosc Tech 4 , e855-861 (2015). Santulli, T.V. , et al. Acute necrotizing enterocolitis in infancy: a review of 64 cases. Pediatrics 55 , 376-387 (1975). Tanner, S.M. , et al. Pathogenesis of necrotizing enterocolitis: modeling the innate immune response. Am J Pathol 185 , 4-16 (2015). Terrin, G., Scipione, A. & De Curtis, M. Update in pathogenesis and prospective in treatment of necrotizing enterocolitis. Biomed Res Int 2014 , 543765 (2014). Nowicki, P.T. & Nankervis, C.A. The role of the circulation in the pathogenesis of necrotizing enterocolitis. Clin. Perinatol. 21 , 219-234 (1994). Leaphart, C.L. , et al. A Critical Role for TLR4 in the Pathogenesis of Necrotizing Enterocolitis by Modulating Intestinal Injury and Repair. J. Immunol. 179 , 4808-4820 (2007). McElroy, S.J., Underwood, M.A. & Sherman, M.P. Paneth cells and necrotizing enterocolitis: a novel hypothesis for disease pathogenesis. Neonatology 103 , 10-20 (2013). Hackam, D.J., Afrazi, A., Good, M. & Sodhi, C.P. Innate immune signaling in the pathogenesis of necrotizing enterocolitis. Clin Dev Immunol 2013 , 475415 (2013). Ballance, W.A., Dahms, B.B., Shenker, N. & Kliegman, R.M. Pathology of neonatal necrotizing enterocolitis: a ten-year experience. J. Pediatr. 117 , S6-13 (1990). Chen, Y. , et al. The role of ischemia in necrotizing enterocolitis. J Pediatr Surg 51 , 1255-1261 (2016). Remon, J.I. , et al. Depth of bacterial invasion in resected intestinal tissue predicts mortality in surgical necrotizing enterocolitis. J Perinatol 35 , 755-762 (2015). Bhandari, V. , et al. Familial and genetic susceptibility to major neonatal morbidities in preterm twins. Pediatrics 117 , 1901-1906 (2006). Moonen, R.M. , et al. Carbamoyl phosphate synthetase polymorphisms as a risk factor for necrotizing enterocolitis. Pediatr Res 62 , 188-190 (2007). Bokodi, G., Derzbach, L., Banyasz, I., Tulassay, T. & Vasarhelyi, B. Association of interferon gamma T+874A and interleukin 12 p40 promoter CTCTAA/GC polymorphism with the need for respiratory support and perinatal complications in low birthweight neonates. Archives of disease in childhood. Fetal and neonatal edition 92 , F25-29 (2007). Banyasz, I. , et al. Genetic polymorphisms for vascular endothelial growth factor in perinatal complications. European cytokine network 17 , 266-270 (2006). Sampath, V. , et al. The NFKB1 (g.-24519delATTG) variant is associated with necrotizing enterocolitis (NEC) in premature infants. J Surg Res 169 , e51-57 (2011). Jilling, T. , et al. Surgical necrotizing enterocolitis in extremely premature neonates is associated with genetic variations in an intergenic region of chromosome 8. Pediatr Res 83 , 943-953 (2018). Walsh, M.C. & Kliegman, R.M. Necrotizing enterocolitis: treatment based on staging criteria. Pediatr. Clin. North Am. 33 , 179-201 (1986). Tremblay, É. , et al. Gene expression profiling in necrotizing enterocolitis reveals pathways common to those reported in Crohn's disease. BMC Med Genomics 9 , 6 (2016). Xie, Z., Kang, Q., Shi, Y., Du, J. & Jiang, H. A transcriptomic landscape analysis of human necrotizing enterocolitis: Important roles of immune infiltration. Pediatric Discovery 1 , e1 (2023). Pan, X. , et al. Blood transcriptomic markers of necrotizing enterocolitis in preterm pigs. Pediatr Res 91 , 1113-1120 (2022). Tables Table 1 : Clinical information of surgical NEC preterm infants with and without severe necrosis and in relation to survivors and mortality Total n=36 Death n=11 Discharge n=25 p Necrosis 0-2 n=21 Necrosis 3-4 n=15 p Appropriate Gestational Age, n (%) 36 8 (72.7%) 10 (40%) 0.07 11 (52.4%) 7 (46.7%) 0.5 Gestational Age (weeks, mean (SD)) 36 27.2 (2.98) 27.3 (3.07) 0.92 26.4 (3.11) 28.5 (2.47) 0.043 Gender, n (%) 36 0.63 9 (42.9%) 4 (26.7%) 0.26 Male 7 (63.6%) 16 (64%) 12 (57.1%) 11 (73.3%) Female 4 (36.4%) 9 (36%) 9 (42.9%) 4 (26.7%) Ethnicity, n (%) 36 0.37 Caucasian 5 (23.8%) 5 (33.3%) African American 14 (66.7%) 9 (60.0%) Hispanic 0 (0.0%) 1 (6.7%) Other 2 (9.5%) 0 (0.0%) Mode of Delivery, n (%) 36 0.25 0.52 C-section 9 (81.8%) 16 (64%) 15 (71.4%) 10 (66.7%) Vaginal 2 (18.2%) 9 (36%) 6 (28.6%) 5 (33.3%) Birth Weight (g, mean (SD)) 36 1005.2 (655.05) 1006.3 (520.63) 0.99 900.8 (570.82) 1153.3 (515.60) 0.18 Outborn, n (%) 36 5 (45.5%) 16 (64.0%) 0.25 12 (57.1%) 9 (60.0%) 0.57 Length of Stay (days, mean (SD)) 36 93.0 (94.24) 146.0 (60.87) 0.022 145.9 (60.86) 123.9 (96.27) 0.41 Time to surgery from NEC onset, (hrs, mean (SD)) 355.7 (401.45) 88.6 (99.33) 0.017 Clinical Presentation of NEC, n (%) 36 0.1 0.08 Abdominal Distention 8 (72.7%) 24 (96%) 20 (95.2%) 12 (80.0%) Bloody Stools 2 (18.2%) 1 (4.0%) 0 (0.0%) 3 (20.0%) Feeding Intolerance 1 (9.1%) 0 (0.0%) 1 (4.8%) 0 (0.0%) Portal Venous Gas, n (%) 36 0 (0.0%) 2 (8.0%) 0.48 2 (9.5%) 0 (0.0%) 0.33 Pneumatosis, n (%) 36 7 (63.6%) 8 (32.0%) 0.08 6 (28.6%) 9 (60.0%) 0.06 Pneumoperitoneum, n (%) 36 4 (36.4%) 14 (56.0%) 0.24 10 (47.6%) 8 (53.3%) 0.5 Length and Region of Bowel Resected (cm, mean (SD)) 36 22.7 (12.51) 27.6 (22.21) 0.5 18.5 (14.30) 36.8 (21.66) 0.004 Region of Bowel Resected, n (%) 36 0.26 Small Bowel 7 (63.6%) 20 (80.0%) Large Bowel 1 (9.1%) 0 (0.0%) Both 3 (27.3%) 5 (20.0%) Time to reach full feeds (mean (SD)) 25 67.0 (55.15) 81.5 (46.85) 0.68 83.6 (43.86) 74.4 (52.89) 0.65 Central line (days, mean (SD)) 75.5 (45.94) 50.6 (36.83) 0.12 TPN (days, mean (SD)) 110.7 (53.57) 78.7 (61.06) 0.11 Pregnancy Induced Hypertention, n (%) 36 4 (36.4%) 6 (24.0%) 0.35 6 (28.6%) 4 (26.7%) 0.6 Chronic Hypertension, n (%) 30 4 (50.0%) 3 (13.6%) 0.06 3 (15.8%) 4 (36.4%) 0.2 Chorioamnionitis, n (%) 36 11 (100%) 25 (100%) 0 (0.0%) 0 (0.0%) Cholestasis, n (%) 30 12 (70.6%) 7 (53.8%) 0.29 Antenatal Steroids, n (%) 36 8 (72.7%) 18 (78.3%) 0.52 Patent Ductus Arteriosus, n (%) 36 7 (63.6%) 13 (52%) 0.39 13 (61.9%) 7 (46.7%) 0.29 24 hour Ionotropic support, n (%) 36 9 (81.8%) 16 (64.0%) 0.25 14 (66.7%) 11 (73.3%) 0.48 Platelets after NEC (mean (SD)) 35 100 (52.67) 152.4 (91.75) 0.09 Positive Blood Culture Sepsis, n (%) 36 4 (36.4%) 9 (36%) 0.63 9 (42.9%) 4 (26.7%) 0.26 Indomethacin Use, n (%) 36 1 (9.1%) 3 (12.0%) 0.64 Surgical Complication, n (%) 36 7 (63.6%) 10 (40%) 0.17 11 (52.4%) 6 (40.0%) 0.35 Single Complication, n (%) 36 3 (27.3%) 6 (24.0%) 0.57 6 (28.6%) 3 (20.0%) 0.43 More than 1 Complication, n (%) 36 2 (18.2%) 4 (16.0%) 0.61 4 (19.0%) 2 (13.3%) 0.51 White Matter Injury, n (%) 23 1 (33.3%) 9 (45.0%) 0.6 6 (42.9%) 4 (44.4%) 0.64 Inflammation, n (%) 36 0.81 0.2 0% 0 (0.0%) 3 (12.0%) 0 (0.0%) 3 (20.0%) 25% 2 (18.2%) 5 (20.0%) 5 (23.8%) 2 (13.3%) 25-50% 6 (54.5%) 12 (48.0%) 12 (57.1%) 6 (40.0%) 50-75% 2 (18.2%) 3 (12.0%) 3 (14.3%) 2 (13.3%) >75% 1 (9.1%) 2 (8.0%) 1 (4.8%) 2 (13.3%) Hemorrhage, n (%) 36 0.89 0.35 0% 0 (0.0%) 2 (8.0%) 0 (0.0%) 2 (13.3%) 25% 1 (9.1%) 3 (12.0%) 3 (14.3%) 1 (6.7%) 25-50% 5 (45.5%) 9 (36.0%) 7 (33.3%) 7 (46.7%) 50-75% 3 (27.3%) 6 (24.0%) 6 (28.6%) 3 (20.0%) >75% 2 (18.2%) 5 (20.0%) 5 (23.8%) 2 (13.3%) Heal, n (%) 36 6 (54.5%) 11 (44.0%) 0.41 11 (52.4%) 6 (40.0%) 0.35 Penrose Drain, n (%) 35 4 (40.0%) 9 (36.0%) 0.56 10 (50.0%) 3 (20.0%) 0.07 CRP on day of NEC (mean (SD)) 29 8.3 (10.87) 7.8 (10.19) 0.92 6.1 (5.64) 10.2 (13.88) 0.3 CRP 24 hrs after NEC (mean (SD)) 25 15.1 (12.95) 12.3 (14.57) 0.68 7.6 (6.78) 19.8 (17.83) 0.027 Disposition, n (%) 36 0.25 Death (due to NEC) 5 (23.8%) 6 (40.0%) Discharged 16 (76.2%) 9 (60.0%) Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7244063","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492657793,"identity":"201d25b5-48e0-40f0-abdf-53f611cb85da","order_by":0,"name":"Parvesh Mohan Garg","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYHADHsbHYJqZuYFoLczGDAwGQC2MxGthkwZrYSCgRd797OPXBTX3Evv5zx6rLqj4E83fDtTyo2IbTi2GZ9LNrGccK06cOSMv7faMMwa5Mw4zNjD2nLmNW0tDGpsxD1uCscENHrPbvG0GuQ1ALcyMbXi09D8DavmXYGx//oxZMUjLfEJa5CXSmB/ztiXIGTDkmDGDtGwgpMVA4hkb88y+BDmJGznG0jxnjHM3ArUcxOcX+f405s8F3xJ4+PvPGH7mqZDLnXf+8MEHPyrw2HKAARQdaOAATvUgWxoYmD/jUzAKRsEoGAWjgAEADwlUVQM4J1UAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-5949-7304","institution":"Department of Pediatrics/Neonatology, Wake Forest University School of Medicine, Winston Salem, North Carolina","correspondingAuthor":true,"prefix":"","firstName":"Parvesh","middleName":"Mohan","lastName":"Garg","suffix":""},{"id":492657795,"identity":"537a3a07-343d-44d0-a48b-2979affd3b87","order_by":1,"name":"David Sawaya","email":"","orcid":"","institution":"Department of Pediatric Surgery, University of Mississippi Medical Center, Jackson, Mississippi","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Sawaya","suffix":""},{"id":492658661,"identity":"01dcf038-2647-49d7-b4ea-281abec7ce39","order_by":2,"name":"Robin Riddick","email":"","orcid":"","institution":"Department of Pediatrics, University of Mississippi Medical Center, Jackson, Mississippi","correspondingAuthor":false,"prefix":"","firstName":"Robin","middleName":"","lastName":"Riddick","suffix":""},{"id":492667377,"identity":"caa55a83-2cfc-40c0-8018-d64f2cbbcf03","order_by":3,"name":"Seth Lirette","email":"","orcid":"","institution":"Department of Biostatistics, University of Mississippi Medical Center, Jackson, Mississippi","correspondingAuthor":false,"prefix":"","firstName":"Seth","middleName":"","lastName":"Lirette","suffix":""},{"id":492667378,"identity":"3d978262-009f-4aa5-aef9-557b4fe617e1","order_by":4,"name":"Nicole Hall","email":"","orcid":"","institution":"Department of Biochemistry, Wake Forest University School of Medicine, Winston Salem, North Carolina","correspondingAuthor":false,"prefix":"","firstName":"Nicole","middleName":"","lastName":"Hall","suffix":""},{"id":492667379,"identity":"40032e88-a3f8-4563-b499-f81fcc718966","order_by":5,"name":"Neha Varshney","email":"","orcid":"","institution":"Department of Pathology, University of Mississippi Medical Center, Jackson, Mississippi","correspondingAuthor":false,"prefix":"","firstName":"Neha","middleName":"","lastName":"Varshney","suffix":""},{"id":492667380,"identity":"8e493561-535e-402a-9632-5ca727295461","order_by":6,"name":"Timothy D. Howard","email":"","orcid":"","institution":"Department of Biochemistry, Wake Forest University School of Medicine, Winston Salem, North Carolina","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"D.","lastName":"Howard","suffix":""},{"id":492667848,"identity":"255ef3a5-623f-4ec6-8cc7-08a8d3c7f6c5","order_by":7,"name":"William B Hillegass","email":"","orcid":"","institution":"Department of Biostatistics, University of Mississippi Medical Center, Jackson, Mississippi","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"B","lastName":"Hillegass","suffix":""},{"id":492668643,"identity":"bcdcb376-2c51-4afb-a7cc-7ab576c284a0","order_by":8,"name":"Akhil Maheshwari","email":"","orcid":"","institution":"Neonatology, Boston Children’s Physicians Group at New York Medical College and Maria Ferrari Children’s Hospital, Westchester, NY","correspondingAuthor":false,"prefix":"","firstName":"Akhil","middleName":"","lastName":"Maheshwari","suffix":""},{"id":492673498,"identity":"3969c28b-2705-4ab8-83ca-fec37af1624a","order_by":9,"name":"Padma Garg","email":"","orcid":"","institution":"Department of Pediatrics, University of Mississippi Medical Center, Jackson, Mississippi","correspondingAuthor":false,"prefix":"","firstName":"Padma","middleName":"","lastName":"Garg","suffix":""}],"badges":[],"createdAt":"2025-07-29 13:57:43","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7244063/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7244063/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88004407,"identity":"d66e9417-b6ce-4b4c-b4ed-04695bcf6a68","added_by":"auto","created_at":"2025-07-31 10:36:35","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30897,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrincipal component analysis. \u003c/strong\u003ePCA analysis showing gene expression variability in PC1 and PC2 with low necrosis (orange) and high necrosis (blue) infants.\u003c/p\u003e","description":"","filename":"Figure1PCnecrosis.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/88626d6a1921961e9b7cfd5b.jpg"},{"id":88004411,"identity":"63553628-5b85-4039-bbcf-ab7a07e5dd2d","added_by":"auto","created_at":"2025-07-31 10:36:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":40388,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolcano plot analysis for necrosis DEGs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eX\u003c/em\u003e axis represents the log2 transformed difference fold value, and the \u003cem\u003eY\u003c/em\u003e axis represents the −log10 transformed significance value.\u003c/p\u003e","description":"","filename":"figure2volcanoplotnecrosis.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/b92da5f3cff24fed9c5381c2.jpg"},{"id":88004412,"identity":"9f5a608c-edaa-4425-961b-921291f106ba","added_by":"auto","created_at":"2025-07-31 10:36:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":299245,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeat Map of necrosis DEGs. \u003c/strong\u003eRows represent the differential gene expression of the listed gene, and columns represent the individual patients. Necrosis levels are indicated by blue (low) or red (high) colors.\u003c/p\u003e","description":"","filename":"figure3necrosisRNA.png","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/d2170fb73ffc9bdf4054d24b.png"},{"id":88005559,"identity":"358b8dfa-0e5f-45f1-9c81-f6725ffe3cc6","added_by":"auto","created_at":"2025-07-31 10:44:35","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":30267,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrincipal component analysis: \u003c/strong\u003ePCA analysis shows gene expression variability in PC1 and PC2 with respect to survival status.\u003c/p\u003e","description":"","filename":"figure4PCdeath.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/98ac8e30c84088d52218fe71.jpg"},{"id":88004408,"identity":"d31f419a-1ffd-4f37-b40b-ed461d268b33","added_by":"auto","created_at":"2025-07-31 10:36:35","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":34802,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVolcano plot analysis with respect to survival and non- survival status DEGs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eX\u003c/em\u003e axis represents the log2 transformed difference fold value, and the \u003cem\u003eY\u003c/em\u003e axis represents the −log10 transformed significance value.\u003c/p\u003e","description":"","filename":"figure5volcanoplotDeathcases.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/99566bee196549159eebb66d.jpg"},{"id":88004415,"identity":"f61676d8-5b79-41ec-aeb5-dda60ce951aa","added_by":"auto","created_at":"2025-07-31 10:36:35","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":130097,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeat Map of DEGs in relation to survival status. \u003c/strong\u003eRows represent the differential gene expression of the listed gene, and columns represent the individual patients.\u003c/p\u003e","description":"","filename":"FIGURE6deathsurvivour.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/33ec0ae5108374aa83e34089.jpg"},{"id":88004418,"identity":"c4ddbc83-68e9-4091-9463-b86f9e66144c","added_by":"auto","created_at":"2025-07-31 10:36:35","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":163798,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeat Map of DEGs in relation to necrosis and survival status. \u003c/strong\u003eRows represent the differential gene expression of the listed gene, and columns represent the individual patients.\u003c/p\u003e","description":"","filename":"figure7a.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/25357b277b2c32dcdb7510cd.jpg"},{"id":88006539,"identity":"22045496-110a-4ea7-be58-1fb68fa269fe","added_by":"auto","created_at":"2025-07-31 11:00:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2482109,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7244063/v1/e4fefa9a-4601-4387-927b-f0ff57998c17.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTargeted RNA sequencing identified gene expression profiles linked to severe necrosis and mortality in preterm infants with surgical necrotizing enterocolitis\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"Impact","content":"\u003col\u003e\n \u003cli\u003eThe gene expression profiles in surgical necrotizing enterocolitis (NEC) were found to differ depending on necrosis severity and survival outcome.\u003c/li\u003e\n \u003cli\u003eSignificant differences in gene expression levels helped to identify molecular pathways that may be regulated and involved in disease progression.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe differentially expressed genes and molecular pathways are potential therapeutic targets for NEC, an incompletely understood and life-threatening disease.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Introduction","content":"\u003cp\u003eNecrotizing enterocolitis (NEC) is a devastating acute gastrointestinal illness of the neonatal period, affecting about 5-10% of premature infants with birth weights of \u0026le;1500 grams \u003csup\u003e1,2\u003c/sup\u003e. Despite major advances in neonatal intensive care and reductions in all-cause mortality among premature infants, NEC continues to be associated with mortality rates of 25-40% \u003csup\u003e3-8\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHistopathologically, NEC lesions are marked by coagulative necrosis, inflammation, bacterial overgrowth, and reparative tissue changes \u003csup\u003e9-16\u003c/sup\u003e. A recent study correlated outcomes in NEC with the depth of bacterial invasion and the severity of inflammation in the resected bowel. In addition, the presence of NEC lesions in the resection margins, presumably indicating incomplete removal of necrotic bowel, was also associated with mortality \u003csup\u003e17\u003c/sup\u003e. There is also evidence that including genetic information may be helpful in predicting the disease outcomes in NEC. Twin studies suggest that genetic factors may account for up to 50% of the risk of NEC\u003csup\u003e18\u003c/sup\u003e. Certain single nucleotide polymorphisms SNPs, such as those in carbamyl phosphate synthetase (\u003cem\u003eT1405N\u003c/em\u003e)\u003csup\u003e19\u003c/sup\u003e, \u003cem\u003eIL12\u003c/em\u003e (p40 promoter CTCTAA/GC)\u003csup\u003e20\u003c/sup\u003e, \u003cem\u003eVEGF\u003c/em\u003e (C-2578A)\u003csup\u003e21\u003c/sup\u003e, and \u003cem\u003eNFKB1\u003c/em\u003e(g.-24519delATTG),\u003csup\u003e22\u003c/sup\u003e have been found to be associated with NEC,\u0026nbsp;but genome-wide association studies for NEC are very few\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe challenge for neonatologists is to detect early clinical manifestations of NEC. One strategy would be to identify specific markers that could be used as early diagnostic tools to identify preterm infants most at risk of developing NEC or in the event of a diagnostic dilemma of suspected disease. As a step in this direction, we aimed to determine the immune gene expression changes associated with different severities of necrosis, in preterm infants with surgical necrotizing enterocolitis. Additionally, we aimed to determine the differential immune gene expression that occur in survivors and non-survivors in preterm infants with surgical NEC.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study was conducted at the University of Mississippi Medical Center (UMMC), under the oversight of the Institutional Review Board (protocol 2017-0127). The neonatal intensive care unit at UMMC is a regional referral center for infants with surgical NEC. We reviewed the medical and pathology records to identify patients with advanced NEC \u003csup\u003e24\u003c/sup\u003e who underwent an exploratory laparotomy and surgical resection of the bowel during 15 years (January 2000 to December 2015). The patients with spontaneous intestinal perforation were excluded.\u003c/p\u003e\n\u003cp\u003eDemographic characteristics, including birth weight, gestational age, gender, race, mode of delivery, and out born status were retrieved from the patients\u0026rsquo; medical records. Maternal data, including pregnancy-induced hypertension, chorioamnionitis, and antenatal steroid use was recorded. Infant characteristics, including mode of delivery, small for gestational age status, Apgar score at 5 minutes, age of NEC onset, mode of clinical presentation (bloody stools, abdominal distension, feeding intolerance), persistent patency of the \u003cem\u003eductus arteriosus\u0026nbsp;\u003c/em\u003e(PDA), use of non-steroidal agents for medical treatment of PDA, assisted ventilation, blood culture-positive sepsis, and duration of antibiotics were recorded. The region of the affected bowel and length of bowel resected was also noted. We also collected data on the length of hospital stay and mortality. The length of hospital stay was defined as the total length of stay from the day of admission until discharge. Mortality was defined as death due to NEC or NEC-associated sepsis. The length of stay was defined as the total length of stay from the day of admission until discharge. To assess postoperative morbidity, we recorded the duration of postoperative ileus, days of parenteral nutrition days, development of short bowel syndrome (SGS), and time to achieve full feeds. Short bowel syndrome was defined as infants who were still requiring TPN more than 90 days following the NEC surgery. Days of parenteral nutrition were defined as the interval between postoperative day 0 until full enteral feedings were achieved (defined as 120 ml/kg/day). Surgical morbidity was classified as surgical site infections (including dehiscence and abscesses), strictures, fistulas, adhesions, and perforations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistopathological Evaluation:\u0026nbsp;\u003c/strong\u003eSpecimens of surgically resected bowel tissue from the patients with NEC were identified in pathology archives. Hematoxylin and eosin-stained resected bowel tissue sections were recorded for the \u0026nbsp;area of necrosis on the slide (percent), scored as 0, 1 (0-25%), 2 (26-50%), 3 (51-75%), and 4 (76-100%); maximum depth of necrosis, scored as 0, 1 (mucosa), 2 (submucosa), 3 (\u003cem\u003emuscularis propria\u003c/em\u003e), and 4 (transmural); severity of inflammation, scored as 0 (no inflammatory cells), 1 [up to 50 inflammatory cells/high power field (hpf)], 2 (51-200 inflammatory cells/hpf, 3 (\u0026gt;201 cells/hpf); depth of inflammatory infiltrates, scored as 0, 1 (mucosa), 2 (submucosa), 3 (muscularis propria), and 4 (transmural)\u003csup\u003e17\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA Sequencing\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA was isolated from 10um section of NEC formalin-fixed, paraffin-embedded (FFPE) human intestine specimens (N=36) obtained following laparotomy Targeted RNA sequencing using the AmpliSeq Illumina Immune Response Panel was utilized for targeted quantitative expression of genes linked to immune system interactions which included 400 genes. Raw reads were de-multiplexed and aligned to human reference genome assembly (hg19) using RNA Amplicon Application (along with custom panel manifest) available on Illumina BaseSpace Computing Platform (DRAGEN APP; http://basespace.illumina.com/). Aligned reads for each gene were normalized for sequencing depth and RNA composition using DESeq2\u0026rsquo;s median of ratios method and used for downstream differential expression analysis in survivors and the non -survivors while accounting for other covariates such as necrosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis:\u0026nbsp;\u003c/strong\u003eDescriptive statistics were computed; categorical data was summarized as frequencies (absolute and relative) and any simple bivariate comparisons were performed using Fisher\u0026rsquo;s exact tests or chi square tests. Continuous data were presented as either means with standard deviations, when underlying distributions would be roughly symmetric, or medians with first and third quartiles when skew was noted. Differences in the continuous data were tested using a student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test or if symmetry was in question, a Mann-Whitney \u003cem\u003eU\u003c/em\u003e test. A p-value of less than 0.05 was considered significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eClinical data of the 36 infants included in the study are summarized in Table 1. The cohort had mean birth weight of 1005 gm (SD 555 gm) and the mean gestational age of 27.2 weeks (SD3.0). 23 infants were males, and 13 infants were female in the study cohort. In the study 21 infants (21/36, 58.3%) had mild to moderate necrosis and 15 infants (15/36,41.6%) had severe necrosis (score 3-4). Out of 36 infants with surgical NEC, 11 infants (11/36, 30.5%) had died, and 25 infants (25/36, 69.4%) had survived and were included in the analysis. \u003cstrong\u003eThe data are summarized in Table 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene Expression in infants with mild-moderate necrosis and severe necrosis:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA-Seq analysis and identification of differentially expressed genes (DEGs):\u0026nbsp;\u003c/strong\u003eDifferential expression analysis was used to investigate the association with stage of necrosis and gene expression in preterm infants with NEC. The analysis showed 35 genes were differentially expressed (p \u0026lt; 0.05)\u0026nbsp;between mild-medium necrosis (score 0-2) and severe necrosis (score of 3-4). A majority of the amplicons included in the panel were detected. Genes related\u0026nbsp;to altered host defense, natural killer cell signaling and development, apoptosis etc. were overexpressed in severe necrosis (\u003cem\u003eIGJ\u003c/em\u003e, \u003cem\u003eGZMA\u003c/em\u003e, \u003cem\u003eTNFSF10\u003c/em\u003e, \u003cem\u003eKLRB1\u003c/em\u003e, \u003cem\u003eCD160\u003c/em\u003e). Expression of leukocyte antigens (\u003cem\u003eITGAM\u003c/em\u003e, \u003cem\u003eITGAX\u003c/em\u003e) and cytokines and chemokines receptors ( \u003cem\u003eIL1A\u003c/em\u003e, \u003cem\u003eIL1B\u003c/em\u003e, \u003cem\u003eCCL2\u003c/em\u003e, \u003cem\u003eCCL3\u003c/em\u003e) were upregulated in patients with mild to moderate necrosis. \u003cstrong\u003eThe data are summarized in figure 1-3.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene expression in survivor and non-survivor:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA-Seq analysis and identification of DEGs:\u0026nbsp;\u003c/strong\u003eDifferential expression analysis showed six genes being significantly differentially expressed (FDR adjusted\u0026nbsp;p \u0026lt; 0.05) between survivors and the non-survivors. Genes related to chemokines attracting neutrophils (\u003cem\u003eCXCL1\u003c/em\u003e), \u003cem\u003eGBP1\u0026nbsp;\u003c/em\u003e(Guanylate binding protein -1, role in cell-autonomous immunity) and \u003cem\u003ePTGS2\u003c/em\u003e ( prostaglandin-endoperoxide synthase 2 gene, encodes for the cyclooxygenase-2 (\u003cem\u003eCOX2\u003c/em\u003e) enzyme, needed for prostanoid biosynthesis involved in inflammation and mitogenesis), \u003cem\u003eCXCL11\u0026nbsp;\u003c/em\u003e( cellular response to lipopolysaccharide; chemokine-mediated signaling pathway; and neutrophil chemotaxis), \u003cem\u003eCXCL9\u003c/em\u003e (Leukocyte chemotaxis, recruitment and differentiation), and \u003cem\u003eCXCL10\u003c/em\u003e (recruits immune cells like macrophages, DCs, NK cells, and Th1 cells to sites of inflammation) were all increased in \u0026nbsp;non-survivors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen tested and accounted for the severity of necrosis contributing to the outcome, 26 genes were differentially expressed between survivors and non-survivors. Genes involved in epithelial cell structure, altered host defense and immune cell signaling and development (\u003cem\u003eIGJ\u003c/em\u003e, \u003cem\u003eGZMA\u003c/em\u003e, \u003cem\u003eKLRB1\u003c/em\u003e, \u003cem\u003eKRT5\u003c/em\u003e and \u003cem\u003eCD160\u003c/em\u003e), were all downregulated in patients with severe necrosis, suggesting a suppressed immune response compared to those with less severe necrosis. On the other hand, expressions of leukocyte antigens (\u003cem\u003eITGAM\u003c/em\u003e and \u003cem\u003eITGAX\u003c/em\u003e) and cytokines and chemokines receptors (\u003cem\u003eIL1B\u003c/em\u003e, \u003cem\u003eCCL2\u003c/em\u003e, \u003cem\u003eCCL3\u003c/em\u003e, and \u003cem\u003eCCL4\u003c/em\u003e) were upregulated in patients with mild to moderate necrosis. \u003cstrong\u003eThe data are summarized in figure 4-7.\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study investigated the gene expression underlying the severe necrosis and death in preterm infants with surgical NEC, by utilizing mRNA sequencing from formalin-fixed paraffin-embedded intestinal tissue samples. Our results showed that severe necrosis (based on intestinal pathology) in NEC infants was associated with increased expression of genes related to host defense, natural killer cell signaling and development, and apoptosis. Our data also shows that survivors in\u0026nbsp;surgical NEC patients showed distinct immune gene expression profiles, with non-survivors exhibiting increased inflammation and chemotactic signaling. Survivors had increased gene expression of leukocyte antigens and cytokine receptors, indicating a more active immune response relative to non-survivors. \u0026nbsp;The degree of necrosis was associated with additional genes, emphasizing its role in immune regulation differences.\u003c/p\u003e\n\u003cp\u003eTremblay et al \u003csup\u003e25\u003c/sup\u003eanalyzed RNA expression in ileal samples from preterm infants with NEC and compared them to samples from infants with other diseases. They found that NEC intestines showed over-representation of pathways related to innate immunity, such as altered T and B cell signaling, granulocyte adhesion and diapedesis, B cell development, and pattern recognition receptor roles. ToppCluster analysis further revealed that NEC was marked by increased lymphocyte and leukocyte migration, chemotaxis, and adhesion, while functions related to lipid metabolism were down-regulated, defining a distinct biological signature for NEC \u003csup\u003e25\u003c/sup\u003e. We also identified genes related to altered host defense, natural killer cell signaling and development, and apoptosis as being overexpressed in surgical NEC infants with severe necrosis, relative to the others.\u003c/p\u003e\n\u003cp\u003eTremblay et al\u003csup\u003e25\u003c/sup\u003e\u0026nbsp; \u0026nbsp;reported the up-regulation of \u003cem\u003eCXCL10\u003c/em\u003e, \u003cem\u003eTLR4\u003c/em\u003e, \u003cem\u003eTLR10\u003c/em\u003e, \u003cem\u003eDEFA5\u003c/em\u003e, \u003cem\u003eREG3A\u003c/em\u003e, \u003cem\u003eLCN2\u003c/em\u003e and \u003cem\u003eTFF3\u003c/em\u003e and down-regulation of \u003cem\u003eHBA2\u003c/em\u003e and \u003cem\u003eHBG2\u003c/em\u003e expression in NEC. They also reported a high degree of similarity between NEC and Crohn\u0026apos;s disease gene expression\u003csup\u003e25\u003c/sup\u003e. Similarly, in our cohort, \u003cem\u003eCXCL11\u003c/em\u003e (cellular response to lipopolysaccharide; chemokine-mediated signaling pathway; and neutrophil chemotaxis), \u003cem\u003eCXCL9\u003c/em\u003e (leukocyte chemotaxis, recruitment and differentiation), and \u003cem\u003eCXCL10\u003c/em\u003e (recruit\u0026rsquo;s immune cells like macrophages, DCs, NK cells, and Th1 cells to sites of inflammation) were all increased in non-survivors.\u003c/p\u003e\n\u003cp\u003eA recent study by Xie et al. analyzed RNA-Seq data from intestinal tissues of 12 preterm infants with NEC, NEC self-control, and normal controls, detecting 34,712 genes and identifying 7,463 differentially expressed genes (DEGs). Gene Ontology analysis showed these DEGs were mainly involved in chemokine receptor binding, transporter activity, and growth factor binding, while KEGG analysis indicated significant enrichment in toll-like receptor signaling, Th17 cell differentiation, and cytokine\u0026ndash;cytokine receptor interaction pathways. Immune infiltration profiles differed notably among the three tissue groups\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA recent study analyzed 129 formula-fed preterm piglets diagnosed with necrotizing enterocolitis (NEC) at necropsy on day 5, comparing subgroups of NEC (\u003cem\u003en\u003c/em\u003e = 20) and control piglets (\u003cem\u003en\u003c/em\u003e = 19) via whole-blood transcriptome analysis\u003csup\u003e27\u003c/sup\u003e. Lesions were scored on a 1\u0026ndash;6 scale, with scores \u0026ge;3 indicating NEC. Severe cases (scores 5\u0026ndash;6) showed transmural necrosis or pneumatosis intestinalis \u0026nbsp;\u003csup\u003e27\u003c/sup\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e344 differentially expressed genes (DEGs) were identified between NEC and control groups, highlighting systemic immune responses and inflammation. Validation confirmed AOAH, ARG2, FKBP5, PAK2, and STAT3 as genes significantly altered in severe NEC cases, detectable in both whole blood and dried blood spots (DBS) \u003csup\u003e27\u003c/sup\u003e.\u0026nbsp;In summary, blood gene expression changes occurred before severe clinical manifestations, suggesting potential for early NEC detection. DBS sampling emerged as a feasible method for small-volume blood collection in infants, enabling practical biomarker screening\u0026nbsp;\u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe strength of our study is that we have provided a unique perspective, as we compared gene expression in preterm infants with surgical NEC with varying degrees of disease severity, whereas other studies have compared NEC patients to healthy controls. Some limitations of our study are that our samples were collected from a single center, our sample size was small, and we did not include lack of healthy controls. In addition, FFPE samples typically have poorer quality RNA, which may have biased our results towards more stable transcripts. Finally, due to the design of the study we are unable to demonstrate a cause-and-effect relationship, so it is unclear if the expression differences observed between groups are due to the primary phenotype or a systemic effect due to the disease process.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study has led to the identification of several DEGs in intestinal samples of premature infants affected with NEC that could be of clinical interest as potential biomarkers for the prediction of the disease and its diagnosis.\u003c/p\u003e\n\u003cp\u003eSurvivors and non-survivors with surgical NEC show distinct immune gene expression profiles, with non-survivors exhibiting increased inflammation and chemotactic signaling. Survivors have upregulation of leukocyte antigens and cytokine receptors, indicating a more active immune response. Degree of necrosis impacts additional genes, emphasizing its role in immune regulation differences. Targeting excessive inflammation and understanding these pathogenic pathways may improve outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cspan\u003eauthor confirmed that they would like this processed and posted as a preprint. Okay to proceed.\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData User Agreement:\u0026nbsp;\u003c/strong\u003eAll data generated and analyzed during this study are included in this article and its supplementary information files.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePMG, and AM \u0026nbsp; designed the study; PMG,DS, RR,AM,PG, NV, NH,TH, SL,WBH analyzed the data and wrote the manuscript. All the authors contributed and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding:\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eParvesh Garg is partially supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number U54GM115428. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.\u003c/p\u003e\n\u003cp\u003eThe work performed through the UMMC Molecular and Genomics Facility is supported, in part, by funds from the NIGMS, including the Molecular Center of Health and Disease-COBRE (P20GM144041), Mississippi INBRE (P20GM103476) and Obesity, Cardiorenal and Metabolic Diseases- COBRE (P30GM149404) and Mississippi Center of Perinatal Research (1P20GM121334).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgment\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/em\u003eWe are grateful to Dr. Micheal Garrett and Lavanya Challagundla from the UMMC Molecular and Genomics department for supporting the NEC genomics study. We are also grateful to the Mississippi Center for Clinical and Translational Research for supporting NEC research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflicts of interest:\u003c/em\u003e\u003c/strong\u003e None Declared\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent:\u003c/strong\u003e Patient consent was not required as per IRB.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNeu, J. \u0026amp; Walker, W.A. Necrotizing enterocolitis. \u003cem\u003eN. Engl. J. Med.\u003c/em\u003e \u003cstrong\u003e364\u003c/strong\u003e, 255-264 (2011).\u003c/li\u003e\n\u003cli\u003eSankaran, K.\u003cem\u003e, et al.\u003c/em\u003e Variations in incidence of necrotizing enterocolitis in Canadian neonatal intensive care units. \u003cem\u003eJ Pediatr Gastroenterol Nutr\u003c/em\u003e \u003cstrong\u003e39\u003c/strong\u003e, 366-372 (2004).\u003c/li\u003e\n\u003cli\u003eSjoberg Bexelius, T.\u003cem\u003e, et al.\u003c/em\u003e Intestinal failure after necrotising enterocolitis: incidence and risk factors in a Swedish population-based longitudinal study. \u003cem\u003eBMJ paediatrics open\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, e000316 (2018).\u003c/li\u003e\n\u003cli\u003eAllin, B.S.R., Long, A.M., Gupta, A., Lakhoo, K. \u0026amp; Knight, M. One-year outcomes following surgery for necrotising enterocolitis: a UK-wide cohort study. \u003cem\u003eArchives of disease in childhood. Fetal and neonatal edition\u003c/em\u003e \u003cstrong\u003e103\u003c/strong\u003e, F461-f466 (2018).\u003c/li\u003e\n\u003cli\u003eKnell, J., Han, S.M., Jaksic, T. \u0026amp; Modi, B.P. Current Status of Necrotizing Enterocolitis. \u003cem\u003eCurr Probl Surg\u003c/em\u003e \u003cstrong\u003e56\u003c/strong\u003e, 11-38 (2019).\u003c/li\u003e\n\u003cli\u003eStoll, B.J.\u003cem\u003e, et al.\u003c/em\u003e Trends in Care Practices, Morbidity, and Mortality of Extremely Preterm Neonates, 1993-2012. \u003cem\u003eJama\u003c/em\u003e \u003cstrong\u003e314\u003c/strong\u003e, 1039-1051 (2015).\u003c/li\u003e\n\u003cli\u003eNair, R., Kahlenberg, C.A., Patel, R.M., Knesek, M. \u0026amp; Terry, M.A. All-Arthroscopic Suprapectoral Biceps Tenodesis. \u003cem\u003eArthrosc Tech\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, e855-861 (2015).\u003c/li\u003e\n\u003cli\u003eSantulli, T.V.\u003cem\u003e, et al.\u003c/em\u003e Acute necrotizing enterocolitis in infancy: a review of 64 cases. \u003cem\u003ePediatrics\u003c/em\u003e \u003cstrong\u003e55\u003c/strong\u003e, 376-387 (1975).\u003c/li\u003e\n\u003cli\u003eTanner, S.M.\u003cem\u003e, et al.\u003c/em\u003e Pathogenesis of necrotizing enterocolitis: modeling the innate immune response. \u003cem\u003eAm J Pathol\u003c/em\u003e \u003cstrong\u003e185\u003c/strong\u003e, 4-16 (2015).\u003c/li\u003e\n\u003cli\u003eTerrin, G., Scipione, A. \u0026amp; De Curtis, M. Update in pathogenesis and prospective in treatment of necrotizing enterocolitis. \u003cem\u003eBiomed Res Int\u003c/em\u003e \u003cstrong\u003e2014\u003c/strong\u003e, 543765 (2014).\u003c/li\u003e\n\u003cli\u003eNowicki, P.T. \u0026amp; Nankervis, C.A. The role of the circulation in the pathogenesis of necrotizing enterocolitis. \u003cem\u003eClin. Perinatol.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 219-234 (1994).\u003c/li\u003e\n\u003cli\u003eLeaphart, C.L.\u003cem\u003e, et al.\u003c/em\u003e A Critical Role for TLR4 in the Pathogenesis of Necrotizing Enterocolitis by Modulating Intestinal Injury and Repair. \u003cem\u003eJ. Immunol.\u003c/em\u003e \u003cstrong\u003e179\u003c/strong\u003e, 4808-4820 (2007).\u003c/li\u003e\n\u003cli\u003eMcElroy, S.J., Underwood, M.A. \u0026amp; Sherman, M.P. Paneth cells and necrotizing enterocolitis: a novel hypothesis for disease pathogenesis. \u003cem\u003eNeonatology\u003c/em\u003e \u003cstrong\u003e103\u003c/strong\u003e, 10-20 (2013).\u003c/li\u003e\n\u003cli\u003eHackam, D.J., Afrazi, A., Good, M. \u0026amp; Sodhi, C.P. Innate immune signaling in the pathogenesis of necrotizing enterocolitis. \u003cem\u003eClin Dev Immunol\u003c/em\u003e \u003cstrong\u003e2013\u003c/strong\u003e, 475415 (2013).\u003c/li\u003e\n\u003cli\u003eBallance, W.A., Dahms, B.B., Shenker, N. \u0026amp; Kliegman, R.M. Pathology of neonatal necrotizing enterocolitis: a ten-year experience. \u003cem\u003eJ. Pediatr.\u003c/em\u003e \u003cstrong\u003e117\u003c/strong\u003e, S6-13 (1990).\u003c/li\u003e\n\u003cli\u003eChen, Y.\u003cem\u003e, et al.\u003c/em\u003e The role of ischemia in necrotizing enterocolitis. \u003cem\u003eJ Pediatr Surg\u003c/em\u003e \u003cstrong\u003e51\u003c/strong\u003e, 1255-1261 (2016).\u003c/li\u003e\n\u003cli\u003eRemon, J.I.\u003cem\u003e, et al.\u003c/em\u003e Depth of bacterial invasion in resected intestinal tissue predicts mortality in surgical necrotizing enterocolitis. \u003cem\u003eJ Perinatol\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 755-762 (2015).\u003c/li\u003e\n\u003cli\u003eBhandari, V.\u003cem\u003e, et al.\u003c/em\u003e Familial and genetic susceptibility to major neonatal morbidities in preterm twins. \u003cem\u003ePediatrics\u003c/em\u003e \u003cstrong\u003e117\u003c/strong\u003e, 1901-1906 (2006).\u003c/li\u003e\n\u003cli\u003eMoonen, R.M.\u003cem\u003e, et al.\u003c/em\u003e Carbamoyl phosphate synthetase polymorphisms as a risk factor for necrotizing enterocolitis. \u003cem\u003ePediatr Res\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 188-190 (2007).\u003c/li\u003e\n\u003cli\u003eBokodi, G., Derzbach, L., Banyasz, I., Tulassay, T. \u0026amp; Vasarhelyi, B. Association of interferon gamma T+874A and interleukin 12 p40 promoter CTCTAA/GC polymorphism with the need for respiratory support and perinatal complications in low birthweight neonates. \u003cem\u003eArchives of disease in childhood. Fetal and neonatal edition\u003c/em\u003e \u003cstrong\u003e92\u003c/strong\u003e, F25-29 (2007).\u003c/li\u003e\n\u003cli\u003eBanyasz, I.\u003cem\u003e, et al.\u003c/em\u003e Genetic polymorphisms for vascular endothelial growth factor in perinatal complications. \u003cem\u003eEuropean cytokine network\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 266-270 (2006).\u003c/li\u003e\n\u003cli\u003eSampath, V.\u003cem\u003e, et al.\u003c/em\u003e The NFKB1 (g.-24519delATTG) variant is associated with necrotizing enterocolitis (NEC) in premature infants. \u003cem\u003eJ Surg Res\u003c/em\u003e \u003cstrong\u003e169\u003c/strong\u003e, e51-57 (2011).\u003c/li\u003e\n\u003cli\u003eJilling, T.\u003cem\u003e, et al.\u003c/em\u003e Surgical necrotizing enterocolitis in extremely premature neonates is associated with genetic variations in an intergenic region of chromosome 8. \u003cem\u003ePediatr Res\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, 943-953 (2018).\u003c/li\u003e\n\u003cli\u003eWalsh, M.C. \u0026amp; Kliegman, R.M. Necrotizing enterocolitis: treatment based on staging criteria. \u003cem\u003ePediatr. Clin. North Am.\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 179-201 (1986).\u003c/li\u003e\n\u003cli\u003eTremblay, \u0026Eacute;.\u003cem\u003e, et al.\u003c/em\u003e Gene expression profiling in necrotizing enterocolitis reveals pathways common to those reported in Crohn\u0026apos;s disease. \u003cem\u003eBMC Med Genomics\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 6 (2016).\u003c/li\u003e\n\u003cli\u003eXie, Z., Kang, Q., Shi, Y., Du, J. \u0026amp; Jiang, H. A transcriptomic landscape analysis of human necrotizing enterocolitis: Important roles of immune infiltration. \u003cem\u003ePediatric Discovery\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, e1 (2023).\u003c/li\u003e\n\u003cli\u003ePan, X.\u003cem\u003e, et al.\u003c/em\u003e Blood transcriptomic markers of necrotizing enterocolitis in preterm pigs. \u003cem\u003ePediatr Res\u003c/em\u003e \u003cstrong\u003e91\u003c/strong\u003e, 1113-1120 (2022).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"122%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1 : Clinical information of surgical NEC preterm infants with and without severe necrosis and in relation to survivors and mortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal n=36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath n=11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDischarge n=25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNecrosis 0-2 n=21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNecrosis 3-4 n=15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAppropriate Gestational Age, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e8 (72.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e10 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e11 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e7 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestational Age (weeks, mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e27.2 (2.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e27.3 (3.07)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e26.4 (3.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e28.5 (2.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e7 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e16 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e11 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e9 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCaucasian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfrican American\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e14 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHispanic\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode of Delivery, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC-section\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e9 (81.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e16 (64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e15 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e10 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaginal\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e9 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth Weight (g, mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1005.2 (655.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1006.3 (520.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e900.8 (570.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1153.3 (515.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutborn, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e5 (45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e16 (64.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of Stay (days, mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e93.0 (94.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e146.0 (60.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e145.9 (60.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e123.9 (96.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime to surgery from NEC onset, (hrs, mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e355.7 (401.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e88.6 (99.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Presentation of NEC, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAbdominal Distention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e8 (72.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e24 (96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e20 (95.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBloody Stools\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeeding Intolerance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePortal Venous Gas, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e2 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumatosis, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e7 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e8 (32.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumoperitoneum, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e14 (56.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e10 (47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e8 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength and Region of Bowel Resected (cm, mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e22.7 (12.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e27.6 (22.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e18.5 (14.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e36.8 (21.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion of Bowel Resected, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmall Bowel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e7 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e20 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLarge Bowel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBoth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e3 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e5 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime to reach full feeds (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e67.0 (55.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e81.5 (46.85)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e83.6 (43.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e74.4 (52.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCentral line (days, mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e75.5 (45.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e50.6 (36.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPN (days, mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e110.7 (53.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e78.7 (61.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePregnancy Induced Hypertention, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e6 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic Hypertension, n (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e4 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e3 (13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChorioamnionitis, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e11 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e25 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCholestasis, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (70.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e7 (53.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntenatal Steroids, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e8 (72.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e18 (78.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatent Ductus Arteriosus, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e7 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e13 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e13 (61.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e7 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24 hour Ionotropic support, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e9 (81.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e16 (64.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e14 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e11 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlatelets after NEC (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e100 (52.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e152.4 (91.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive Blood Culture Sepsis, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e9 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndomethacin Use, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e3 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgical Complication, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e7 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e10 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e11 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSingle Complication, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e3 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e6 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMore than 1 Complication, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e4 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (19.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhite Matter Injury, n (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e9 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInflammation, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e3 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e5 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-50%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e6 (54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e12 (48.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e12 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e50-75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e3 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e2 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemorrhage, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e2 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e3 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-50%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e5 (45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e9 (36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e7 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e7 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e50-75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e3 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e6 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;75%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e2 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e5 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeal, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e6 (54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e11 (44.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e11 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePenrose Drain, n (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e4 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e9 (36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e10 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP on day of NEC (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e8.3 (10.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e7.8 (10.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6.1 (5.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e10.2 (13.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP 24 hrs after NEC (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e15.1 (12.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e12.3 (14.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e7.6 (6.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e19.8 (17.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisposition, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeath (due to NEC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e5 (23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDischarged\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e16 (76.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e9 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"a1a89234-0e58-4045-9068-5a5436053973","identifier":"10.13039/100000057","name":"National Institute of General Medical Sciences","awardNumber":"U54GM115428","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Mississippi Medical Center","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Preterm Infants, NEC, Necrosis, Mortality, Gene Expression, RNA sequencing, Neonate","lastPublishedDoi":"10.21203/rs.3.rs-7244063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7244063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e We aim to determine the gene expression changes that occur in surgical NEC infants with and without moderate to severe necrosis and survivors and non-survivors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eTargeted RNA sequencing was performed on RNA isolated from formalin-fixed, paraffin-embedded (FFPE) intestinal tissue samples (N=36) .DeSeq2 was used to analyze differential expressions between infants with mild to moderate and severe necrosis and with respect to survival status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThirty-five genes were differentially expressed (FDR- adjusted p \u0026lt; 0.05) between mild-medium necrosis and severe necrosis. Genes involved in altered host defense, natural killer (NK) cell signaling and development, and apoptosis were overexpressed in severe necrosis (\u003cem\u003eIGJ\u003c/em\u003e, \u003cem\u003eGZMA\u003c/em\u003e, \u003cem\u003eTNFSF10\u003c/em\u003e, \u003cem\u003eKLRB1\u003c/em\u003e, and \u003cem\u003eCD160\u003c/em\u003e). Expression of leukocytes antigens (\u003cem\u003eITGAM\u003c/em\u003e, \u003cem\u003eITGAX\u003c/em\u003e) and cytokine and chemokine receptors (such as \u003cem\u003eIL1A\u003c/em\u003e, \u003cem\u003eIL1B\u003c/em\u003e, \u003cem\u003eCCL2\u003c/em\u003e, \u003cem\u003eCCL3\u003c/em\u003e) were increased in patients with mild necrosis. Six genes were significantly differentially expressed (FDR- adjusted p \u0026lt; 0.05) between survivors and the non-survivors. Genes related to chemokines attracting neutrophils (\u003cem\u003eCXCL1\u003c/em\u003e, \u003cem\u003eGBP\u003c/em\u003e,\u003cem\u003ePTGS2\u003c/em\u003e,\u003cem\u003eCXCL11\u003c/em\u003e,\u003cem\u003eCXCL9\u003c/em\u003e, and \u003cem\u003eCXCL10)\u003c/em\u003e were upregulated in non-survivors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eSevere necrosis and non-survival of NEC infants were associated with differential genes expression related to host defense, NK cell signaling and development, and apoptosis. Understanding these pathways can guide the development of prognostic and treatment pathways.\u003c/p\u003e","manuscriptTitle":"Targeted RNA sequencing identified gene expression profiles linked to severe necrosis and mortality in preterm infants with surgical necrotizing enterocolitis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 10:36:31","doi":"10.21203/rs.3.rs-7244063/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a0ae82e-367e-4d2b-ae39-6fc18d6b8bb3","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52364520,"name":"Epigenetics \u0026 Genomics"}],"tags":[],"updatedAt":"2025-07-31T10:36:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-31 10:36:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7244063","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7244063","identity":"rs-7244063","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}