Document Type : original article
Authors
1 General Physician, Faculty of Medicine, Arak University of Medical Sciences, Arak, Iran.
2 Associate Professor of Pediatric, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
3 Assistant professor of Neonatal, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
4 Assistant Professor of Biostatistics, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
5 Bachelor of Public Health, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
Abstract
Background: Survival of infants admitted to the NICU does not depend exclusively on birth weight and gestational age, but on other perinatal factors and physiological conditions of individual infants, especially the severity of their illness. Therefore, scoring systems are needed to assess the risk of adverse outcomes for each premature infant. In this study, the accuracy of Crib-II was investigated to predict the mortality of premature babies admitted to the NICU.
Methods: 140 babies admitted to the NICU, meeting the selection criteria (gestational age less than 32 weeks or weight less than 1500 grams) were included in the study. The required data for the Crib-II tool (gender, gestational age, birth weight, initial temperature of the baby, and base excess) were collected and analyzed using SPSS software version 23.
Results: In this study, 45% (63 infants) were female and 55% (77 infants) were male, with a mortality rate of 30.7%. The average gestational age was 30.17±2.14 weeks, the average birth weight was 1856.52±583.18 grams, the average initial rectal temperature was 36.92±0.52 °C, the average base excess was -8.54±7.09 mmol/L, the average Crib-II score was 5.15±4.43, and the area under the roc curve with a cut point of 6.5 was 0.96. Also, the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio were 96%, 93%, 98%, 95%, 97%, 46.5, and 0.07, respectively.
Conclusion: Based on our observations in this study, the Crib-II index has a high value in predicting the mortality of premature babies. It was able to correctly predict 96% of the deaths of premature babies, which indicates the high value of this index.
Keywords
- Cutland CL, Lackritz EM, Mallett-Moore T, Bardají A, Chandrasekaran R, Lahariya C, et al. Low birth weight: Case definition & guidelines for data collection, analysis, and presentation of maternal immunization safety data. Vaccine. 2017 Dec 12;35(48Part A):6492.
- Waldemar A. Prematurity and Intrauterine Growth Restriction. Robert M Kliegman, Stanton. Nelson textbook of pediatrics. Philadelphia: Saunders; 2011.
- Bettiol H, Barbieri MA, da Silva AA. Epidemiology of preterm birth: current trends. Revista brasileira de ginecologia e obstetricia: revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia. 2010 Feb;32(2):57-60.
- Villar J, Papageorghiou AT, Knight HE, Gravett MG, Iams J, Waller SA, et al. The preterm birth syndrome: a prototype phenotypic classification. American journal of obstetrics and gynecology. 2012; 206(2):119-23.
- Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. The lancet. 2008; 371(9606):75-84.
- Helenius K, Sjörs G, Shah PS, Modi N, Reichman B, Morisaki N, et al. Survival in very preterm infants: an international comparison of 10 national neonatal networks. Pediatrics. 2017 Dec 1;140(6).
- Patel RM, Kandefer S, Walsh MC, Bell EF, Carlo WA, Laptook AR, et al. Causes and timing of death in extremely premature infants from 2000 through 2011. New england journal of medicine. 2015 Jan 22;372(4):331-40.
- Reid S, Bajuk B, Lui K, Sullivan EA, NSW, ACT Neonatal Intensive Care Units Audit Group P. Comparing CRIB‐II and SNAPPE‐II as mortality predictors for very preterm infants. Journal of pediatrics and child health. 2015; 51(5):524-8.
- Dorling JS, Field DJ, Manktelow B. Neonatal disease severity scoring systems. Archives of Disease in Childhood-Fetal and Neonatal Edition. 2005 Jan 1;90(1):F11-6.
- Garg B, Sharma D, Farahbakhsh N. Assessment of sickness severity of illness in neonates: review of various neonatal illness scoring systems. The Journal of Maternal-Fetal & Neonatal Medicine. 2018 May 19;31(10):1373-80.
- Richardson DK, Tamow-Mordi WO, Escobar GJ. Neonatal risk scoring systems: can they predict mortality and morbidity?. Clinics in perinatology. 1998 Sep 1;25(3):591-608.
- Richardson DK, Corcoran JD, Escobar GJ, Lee SK. SNAP-II and SNAPPE-II: simplified newborn illness severity and mortality risk scores. The Journal of pediatrics. 2001 Jan 1;138(1):92-100.
- McLeod JS, Menon A, Matusko N, Weiner GM, Gadepalli SK, Barks J, et al. Comparing mortality risk models in VLBW and preterm infants: systematic review and meta-analysis. Journal of Perinatology. 2020 May;40(5):695-703.
- Parry G, Tucker J, Tarnow-Mordi W. CRIB II: an update of the clinical risk index for babies score. The Lancet. 2003 May 24;361(9371):1789-91.
- Manktelow BN, Draper ES, Field DJ. Predicting neonatal mortality among very preterm infants: a comparison of three versions of the CRIB score. Archives of Disease in Childhood-Fetal and Neonatal Edition. 2010 Jan 1;95(1):F9-13.
- Mohkam M, Afjeii A, Payandeh P, Zadkarami M, Kazemian M, Fakhraii H, et al. A comparison of CRIB, CRIB II, SNAP, SNAPII and SNAP-PE scores for prediction of mortality in critically ill neonates. 2011.
- Harsha SS, Archana BR. SNAPPE-II (score for neonatal acute physiology with perinatal extension-II) in predicting mortality and morbidity in NICU. Journal of clinical and diagnostic research: JCDR. 2015 Oct;9(10):SC10.
- Narkhede S. Understanding auc-roc curve. Towards data science. 2018 Jun 26;26(1):220-7.
- Burstein R, Henry NJ, Collison ML, Marczak LB, Sligar A, Watson S, et al. Mapping 123 million neonatal, infant and child deaths between 2000 and 2017. Nature. 2019 Oct 17;574(7778):353-8.
- Howell EA, Janevic T, Hebert PL, Egorova NN, Balbierz A, Zeitlin J. Differences in morbidity and mortality rates in black, white, and Hispanic very preterm infants among New York City hospitals. JAMA pediatrics. 2018 Mar 1;172(3):269-77.
- Stomnaroska O. Neonatal hypoglycaemia in children with high and normal risk: incidence, etiology, therapeutics and prognosis. Doctotal thesis, Medical Faculty Skopje, University Sts Cyril and Methodius. 2017.
- Guenther K, Vach W, Kachel W, Bruder I, Hentschel R. Auditing neonatal intensive care: is PREM a good alternative to CRIB for mortality risk adjustment in premature infants?. Neonatology. 2015 Sep 1;108(3):172-8.
- Akbar N, Sarwar S, Sajid M, Hayat M, Hassan A, Wasim A. The accuracy of clinical risk index for babies (CRIB-II) for predicting mortality of severely-ill preterm neonates. Annals of Punjab Medical College. 2020 Mar 31;14(1):54-7.
- Qasim S, Zahid S, Islam A, Anwar M, Siddique S, Rafique A. Clinical Risk Index Score (CRIB II) as a Predictor of Neonatal Mortality among Premature Babies. Pakistan Journal of Medical & Health Sciences. 2022 Sep 4;16(08):70-.
- Rehman A, Hamid MH. Accuracy of CRIB II Score in Predicting the Neonatal Mortality in very Preterm Babies. Pakistan Journal of Medical & Health Sciences. 2022 Apr 18;16(03):564-.
- Baumer JH, Wright D, Mill T. Illness severity measured by CRIB score: a product of changes in perinatal care?. Archives of Disease in Childhood-Fetal and Neonatal Edition. 1997 Nov 1;77(3):F211-5.
- Khanna R, Taneja V, Singh SK, Kumar N, Sreenivas V, Puliyel JM. The clinical risk index of babies (CRIB) score in India. The Indian Journal of Pediatrics. 2002 Nov;69:957-60.
- Gagliardi L, Cavazza A, Brunelli A, Battaglioli M, Merazzi D, Tandoi F, et al. Assessing mortality risk in very low birthweight infants: a comparison of CRIB, CRIB-II, and SNAPPE-II. Archives of Disease in Childhood-Fetal and Neonatal Edition. 2004 Sep 1;89(5):F419-22.