{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:09:06Z","timestamp":1783901346589,"version":"3.55.0"},"reference-count":19,"publisher":"Walter de Gruyter GmbH","issue":"3","license":[{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Predicting the outcome of neonatal critical patients remains elusive. The multiple factors of maternal state of health (infections, diabetes, gestosis), the placental situation (premature rupture of membranes) as well as multiple factors from the baby (small for gestational age, low Apgar score, low birth infections, mechanical ventilation, hypoglycaemia hyperglycamiea) render the approach to treatment of each patient individual and the outcome uncertain. Several approaches and scales are developed in order to assess the mortality risk in those rather complicated situations.<\/jats:p>\n                  <jats:p>We used the CRIB-II scale to assess the mortality risk in 80 patients delivered in a large tertiary level hospital with more than 4,000 deliveries yearly. The patients were stratified according to all the neonatal risk factors and comorbidities. The CRIB-II scale identified well the mortality rates, but not the outcomes. A large and well-balanced cohort of patients followed for a longer period is required to discern in detail the importance of CRIB-II scale in predicting outcomes in high-risk new-borns. This could serve as an assistance to personalized approach to severely sick children. In addition, it is a valuable method in comparing outcomes in different NICUs and outcomes in different times in the same NICU, thus rendering possible improvements in the same unit and among several NICU departments.<\/jats:p>","DOI":"10.2478\/prilozi-2020-0046","type":"journal-article","created":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T07:28:26Z","timestamp":1608622106000},"page":"59-64","source":"Crossref","is-referenced-by-count":3,"title":["The CRIB II (Clinical Risk Index for Babies II) Score in Prediction of Neonatal Mortality"],"prefix":"10.2478","volume":"41","author":[{"given":"Orhideja","family":"Stomnaroska","sequence":"first","affiliation":[{"name":"University Clinic for Gynecology and Obstetrics , Medical Faculty Skopje , Skopje , RN Macedoniaa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dragan","family":"Danilovski","sequence":"additional","affiliation":[{"name":"Institute for Epidemiology and Biostatistics , Medical Faculty Skopje , Skopje , RN Macedonia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2020,12,8]]},"reference":[{"key":"2026071215245469301_j_prilozi-2020-0046_ref_001_w2aab3b7c14b1b6b1ab1ab1Aa","unstructured":"1. 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; 574 (7778): 353\u2013358.10.1038\/s41586-019-1545-0"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_002_w2aab3b7c14b1b6b1ab1ab2Aa","doi-asserted-by":"crossref","unstructured":"2. 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 Pediatr. 2018; 172(3): 269\u2013277. Free PMC article.10.1001\/jamapediatrics.2017.4402","DOI":"10.1001\/jamapediatrics.2017.4402"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_003_w2aab3b7c14b1b6b1ab1ab3Aa","doi-asserted-by":"crossref","unstructured":"3. Richardson DK, Tarnow-Mordi WO, Escobar GJ. Neonatal Risk Scoring Systems. Can They Predict Mortality and Morbidity? Clin Perinatol 1998; 25(3): 591\u2013611.","DOI":"10.1016\/S0095-5108(18)30099-X"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_004_w2aab3b7c14b1b6b1ab1ab4Aa","doi-asserted-by":"crossref","unstructured":"4. Richardson DK, Corcoran JD, Escobar GJ, et al. SNAP-II and SNAPPE-II: simplified newborn illness severity and mortality risk scores. J Pediatr 2001; 138: 92\u2013100.10.1067\/mpd.2001.109608","DOI":"10.1067\/mpd.2001.109608"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_005_w2aab3b7c14b1b6b1ab1ab5Aa","doi-asserted-by":"crossref","unstructured":"5. Garg B, Sharma D, Farahbakhsh N. Assessment of sickness severity of illness in neonates: review of various neonatal illness scoring systems. J Matern Fetal Neonatal Med. 2018; 31(10): 1373\u20131380.10.1080\/14767058.2017.1315665","DOI":"10.1080\/14767058.2017.1315665"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_006_w2aab3b7c14b1b6b1ab1ab6Aa","doi-asserted-by":"crossref","unstructured":"6. McLeod JS, Menon A, Matusko N, Weiner GM, Gadepalli S, Barks J, Mychaliska GB, Perrone EE Comparing mortality risk models in VLBW and preterm infants: systematic review and meta-analysis. Journal of Perinatology (40), 695\u2013703(2020).10.1038\/s41372-020-0650-0","DOI":"10.1038\/s41372-020-0650-0"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_007_w2aab3b7c14b1b6b1ab1ab7Aa","doi-asserted-by":"crossref","unstructured":"7. Parry G, Tucker J, Tarnow-Mordi WO. CRIB-II: an update of the clinical risk index for babies score. Lancet 2003; 361: 1789\u20131791.10.1016\/S0140-6736(03)13397-1","DOI":"10.1016\/S0140-6736(03)13397-1"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_008_w2aab3b7c14b1b6b1ab1ab8Aa","doi-asserted-by":"crossref","unstructured":"8. Manktelow BN, Draper ES, Field DJ. Predicting neonatal mortality among very preterm infants: a comparison of three versions of the CRIB score. Arch Dis Child Fetal Neonatal Ed. 2010; 95(1): F9\u2013F13.10.1136\/adc.2008.14801519608556","DOI":"10.1136\/adc.2008.148015"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_009_w2aab3b7c14b1b6b1ab1ab9Aa","unstructured":"9. How to Create and Interpret a ROC Curve in SPSS https:\/\/www.statology.org\/roc-curve-spss\/"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_010_w2aab3b7c14b1b6b1ab1ac10Aa","unstructured":"10. The Area Under an ROC Curve http:\/\/gim.unmc.edu\/dxtests\/roc3.htm"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_011_w2aab3b7c14b1b6b1ab1ac11Aa","unstructured":"11. Stomnaroska O. Neonatal hypoglycaemia in children with high and normal risk: incidence, aetiology, therapeutics and prognosis. Doctoral thesis, Medical Faculty Skopje, University Saints Cyril and Methodius, 2017."},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_012_w2aab3b7c14b1b6b1ab1ac12Aa","doi-asserted-by":"crossref","unstructured":"12. 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; 108(3): 172\u20138.10.1159\/00043341426278218","DOI":"10.1159\/000433414"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_013_w2aab3b7c14b1b6b1ab1ac13Aa","unstructured":"13. Marete IK, Wasunna AO, Otieno PA.East Afr Med J. Clinical risk index for babies (CRIB) II score as a predictor of neonatal mortality among low birth weight babies at Kenyatta National Hospital. 2011; 88(1): 18\u201323."},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_014_w2aab3b7c14b1b6b1ab1ac14Aa","doi-asserted-by":"crossref","unstructured":"14. Jae Hyun Park, Yun Sil Chang, So Yoon Ahn, Se In Sung, Won Soon Park.. Predicting Mortality in Extremely Low Birth Weight Infants: Comparison between Gestational Age, Birth Weight, Apgar Score, CRIB II Score, Initial and Lowest Serum Albumin Levels. PLoS One 2018; 13(2): e0192232.10.1371\/journal.pone.0192232581100829438382","DOI":"10.1371\/journal.pone.0192232"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_015_w2aab3b7c14b1b6b1ab1ac15Aa","doi-asserted-by":"crossref","unstructured":"15. Buhrer C, Grimmer I, Metze B, Obladen M. The CRIB (Clinial Risk Index for Babies) score and neurodevelopmental impairment at one year corrected age in very low birth weight infants. Intensive Care Med. 2000; 26: 325\u20139.10.1007\/s00134005115710823390","DOI":"10.1007\/s001340051157"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_016_w2aab3b7c14b1b6b1ab1ac16Aa","unstructured":"16. Ezz-Eldin ZM, Hamid TAA, Youssef MRL, Nabil HED.. Clinical Risk Index for Babies (CRIB II) Scoring System in Prediction of Mortality in Premature Babies. 2015; 9(6): SC08\u201311."},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_017_w2aab3b7c14b1b6b1ab1ac17Aa","doi-asserted-by":"crossref","unstructured":"17. B\u00fchrer C, Metze B, Obladen M. CRIB, CRIB-II, Birth Weight or Gestational Age to Assess Mortality Risk in Very Low Birth Weight Infants? Acta Paediatr 2008; 97(7): 899\u2013903.","DOI":"10.1111\/j.1651-2227.2008.00793.x"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_018_w2aab3b7c14b1b6b1ab1ac18Aa","doi-asserted-by":"crossref","unstructured":"18. Reid S, Bajuk B, Lui K, Sullivan EA, NSW, ACT Neonatal Intensive Care Units Audit Group PSN. Comparing CRIB-II and SNAPPE-II as mortality predictors for very preterm infants. J Paediatr Child Health. 2014; 51: 524\u201328.10.1111\/jpc.1274225266790","DOI":"10.1111\/jpc.12742"},{"key":"2026071215245469301_j_prilozi-2020-0046_ref_019_w2aab3b7c14b1b6b1ab1ac19Aa","doi-asserted-by":"crossref","unstructured":"19. Ja\u0161i\u010d M, Dessardo NS, Dessardo S, Rukavina KM. CRIB II score versus gestational age and birth weight in preterm infant mortality prediction: who will win the bet? SIGNA VITAE 2016; 11(1): 172\u2013181.","DOI":"10.22514\/SV111.052016.12"}],"container-title":["PRILOZI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/content.sciendo.com\/view\/journals\/prilozi\/41\/3\/article-p59.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/reference-global.com\/pdf\/10.2478\/prilozi-2020-0046","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T23:36:43Z","timestamp":1783899403000},"score":1,"resource":{"primary":{"URL":"https:\/\/reference-global.com\/article\/10.2478\/prilozi-2020-0046"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,1]]},"references-count":19,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,12,8]]},"published-print":{"date-parts":[[2020,11,1]]}},"alternative-id":["10.2478\/prilozi-2020-0046"],"URL":"https:\/\/doi.org\/10.2478\/prilozi-2020-0046","relation":{},"ISSN":["1857-8985","1857-9345"],"issn-type":[{"value":"1857-8985","type":"electronic"},{"value":"1857-9345","type":"print"}],"subject":[],"published":{"date-parts":[[2020,11,1]]}}}