Predicting Mortality and Intestinal Failure in Neonates with Surgical Necrotizing Enterocolitis

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1 Predicting Mortality and Intestinal Failure in Neonates with Surgical Necrotizing Enterocolitis Darshna Bhatt MHA DO, Curtis Travers MPH, Ravi M. Patel MD MSc, Julia Shinnick MD, Kelly Arps MD, Sarah Keene, MD, Mehul V. Raval MD MS Affiliations: Division of Neonatology, Department of Pediatrics, Emory University School of Medicine, Children s Healthcare of Atlanta, Atlanta, GA, USA; Biostatistical Core, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Division of Pediatric Surgery, Department of Surgery, Emory University School of Medicine, Children s Healthcare of Atlanta, Atlanta, GA, USA

2 Disclosures Speaker: Dr. Mehul V. Raval, MD, MS Dr. Raval has documented that he has nothing to disclose.

3 NEC is BAD 10% of NICU deaths Surgical NEC = ~50% mortality SBS & intestinal failure (IF) Existing risk prediction models Neu and Walker. NEJM (2011) Richardson DK et al. Journal of Peds (2001) Medlock S et al. PLoS ONE (2011) Zupancic JA et al Pediatrics (2007) Stey A et al. Pediatrics. (2015) The ideal prediction model should: Be simple to use with a small set of inputs that are easily accessible preoperatively Be appropriately validated and calibrated

4 Objectives The primary purpose of this study was to evaluate and compare existing tools in the prediction of death or IF in patients with surgical NEC A secondary aim was to derive and validate a novel hybrid model to predict death or IF

5 Methods Retrospective, observational cohort study (9/09-5/15) Inclusion criteria: 1) gestational age < 37 weeks 2) diagnosis of NEC requiring surgical intervention Exclusion criteria: 1) diagnosis of spontaneous intestinal perforation (SIP) 2) or congenital intestinal anomalies The primary outcome was death or IF 1) All cause in-hospital mortality 2) IF = failure to full enteral feeds 90d post op Duro D et al. The Journal of Pediatrics (2010) Kelleher J et al. (2013)

6 Methods Data collection All variables collected were measured before surgery Physiologic parameters were obtained within 3 hours before surgery Statistical Analysis Logistic regression modelling was used Discrimination was assessed using the AUC Hybrid model: Variables with bivariate p-values < 0.1 were considered candidate variables Backward step-wise selection used to create model Model validation & calibration Hosmer DW et al. Statistics In Medicine (1997)

7 Sample Selection for Derivation Model 520 patients identified in hospital database using ICD-9 codes (9/01-5/15) Gestational Age, weeks (IQR) Derivation cohort (n =147) 27.1 ( ) Validation cohort (n= 76) 27.0 ( ) P value duplicate patients Birthweight, g (IQR) 940 ( ) 880 ( ) charts examined for confirming diagnosis of surgical NEC 147 patients met inclusion criteria 329 patients excluded 140 Other (incorrectly coded- suspicion/ concern for NEC) 70 Medical NEC (no surgical intervention) 101 Spontaneous Intestinal Perforations 2 Omphaloceles 16 Gastroschisis Male 60% 54% 0.39 Antenatal Steroids (>1 doses) 67% 58% 0.19 Exp Lap 92% 82% Primary Drain 8% 18% 0.02 Mortality or IF 64% 70% 0.39 Mortality 38% 36% 0.71 IF 35% 34% 0.86

8 8 Models VON-RA Model SNAPPE-II Model NSQIP-P Model Hybrid Model Ge/stational age Gestational age (squared) multiple gestation/ singleton gestation Outborn status Apgar score 1 min Apgar score 5 min Gender Cesarean delivery Presence of a congenital anomaly Mean blood pressure Temperature PO 2 /FiO 2 Lowest serum ph Multiple seizures Urine output Preterm Small for gestational age Birthweight Mode of delivery Case type Nutritional supplement Dialysis Cardiac risk factors Apgar score 1 min Apgar score 5 min Inotrope use 24hrs pre-op Blood transfusion 48hours prior to op procedure Hepatobiliary disease Hereditary bleeding disorder Intracranial hemorrhage Systemic sepsis Apgar score 1 min Inotrope use Mean blood pressure Sepsis

9 AUC

10 Observed Probabilities Observed Probabilities Observed vs Predicted Probabilities for Death or IF Calibration Plots (derivation cohort) & (validation cohort) Predicted Probabilities Predicted Probabilities

11 Conclusions Prediction of death or IF among infants with surgical NEC is possible using existing prediction tools and, to a greater extent, using a newly proposed hybrid model Our hybrid model utilizes four pre-operative variables: Apgar score at 1 minute Inotrope use Mean arterial pressure Sepsis

12 Next Steps The proposed hybrid model can be used to provide risk-adjusted comparisons of surgical outcomes among centers This tool may help centers understand how their surgical outcomes among infants with NEC compare to other centers by providing less biased comparisons We are currently in the process of validating this tool at additional tertiary care centers