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Correlation between perfusion index and the severity of disease in early neonates / 中国小儿急救医学
Article em Zh | WPRIM | ID: wpr-930848
Biblioteca responsável: WPRO
ABSTRACT
Objective:To analyze the role of perfusion index(PI)in assessing the severity of neonatal illnesses.Methods:A total of 502 newborns admitted to the Department of Neonatology within 24 hours of birth at Xinxiang Central Hospital from October 2018 to July 2019 were recruited.Neonatal critical illness score(NCIS)was graded within 24 hours of admission, and newborns were categorized into non-critical(NCIS>90 scores), critical(NCIS 70-90 scores)and extremely critical(NCIS<70 scores). PI was monitored in all newborns within 24 hours of birth in a resting state.A total of 502 PIs were recorded, including 341 cases of non-critical, 110 cases of critical and 51 cases of extremely critical.Results:The medium PI [ M( P25, P75)] of newborns in non-critical, critical and extremely critical groups were 1.80(1.40, 2.60), 0.96(0.74, 1.43)and 0.65(0.41, 1.10), respectively.PI values in extremely critical group was significantly lower than those in critical group and non-critical group( P<0.05). The medium PI [ M( P25, P75)] of full-term newborns, moderate/late preterm newborns and extremely/very preterm newborns were 1.70(1.20, 2.70), 1.60(1.10, 2.30) and 1.35(0.80, 2.30), respectively.PI in full-term newborns was significantly higher than those in moderate/late preterm newborns and extremely/very preterm newborns( P<0.05). PI was moderately positively correlated with NCIS in newborns( r=0.791, P<0.01). The area under the receiver operating characteristic curve of NCIS predicted by PI value was 0.846, and the prediction sensitivity and specificity were 85.0% and 70.8% when PI was 0.56. Conclusion:PI is correlated with NCIS in newborns, which is able to reflect the severity of neonatal illnesses.A low PI indicates severe conditions of neonatal illnesses.
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Texto completo: 1 Base de dados: WPRIM Tipo de estudo: Prognostic_studies Idioma: Zh Ano de publicação: 2022 Tipo de documento: Article
Texto completo: 1 Base de dados: WPRIM Tipo de estudo: Prognostic_studies Idioma: Zh Ano de publicação: 2022 Tipo de documento: Article