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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 8  |  Issue : 2  |  Page : 186-190

Score for neonatal acute physiology perinatal extension II in predicting neonatal mortality in the neonatal intensive care unit


1 Department of Pediatrics, Ekta Institute of Child Health, Raipur, Chhattisgarh, India
2 Department of Community Medicine, Government Medical College, Shahdol, Madhya Pradesh, India

Date of Submission18-May-2020
Date of Decision25-Jul-2020
Date of Acceptance04-Aug-2020
Date of Web Publication23-Dec-2020

Correspondence Address:
Dr. Vikas Gupta
Department of Community Medicine, Government Medical College, Shahdol, Madhya Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/amhs.amhs_102_20

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  Abstract 


Background and Aim: Very low birth weight (VLBW) neonates constitute approximately 4%–7% of all live births and their mortality is very high (50%). There has been an effort in recent times to develop the severity score for the illness like score for neonatal acute physiology perinatal extension II (SNAPPE-II) score so that it is possible to prevent, particularly aiming the improvement of newborn children care. The study aimed to determine the validity of SNAPPE-II in predicting the VLBW neonates' mortality risk in the neonatal intensive care unit (NICU) at teaching hospital of Raipur, Chhattisgarh. Materials and Methods: This was a hospital-based prospective study carried out among all premature newborns weighing <1500 g and more than 26 weeks admitted to the NICU with a sample size of 129. The variables of SNAPPE-II score were prospectively recorded within 12 h of admission, and their outcome was monitored till 28 days postbirth period. All tests were performed at a 5% level of significance. Results: The SNAPPE II score of the dead neonates was significantly higher than the surviving neonates (43.6 ± 17.25 vs. 18.2 ± 13.09; P < 0.001), and the receiver operating characteristics (ROC) showed that discriminating ability of SNAPPE-II score was 0.857 (good). The best cutoff for SNAPPE II score in predicting neonatal mortality on charting the ROC was 31. Conclusion: The present study was conducted to specifically design to evaluate the validity of SNAPPE II score as predictor of neonatal mortality in VLBW infants and helps in prioritizing them so we can intervene and prevent mortality in these neonates.

Keywords: Neonatal intensive care unit, prospective, score for neonatal acute physiology perinatal-II, very low birth weight


How to cite this article:
Bagri N, Panika RK, Gupta V, Nathani IK. Score for neonatal acute physiology perinatal extension II in predicting neonatal mortality in the neonatal intensive care unit. Arch Med Health Sci 2020;8:186-90

How to cite this URL:
Bagri N, Panika RK, Gupta V, Nathani IK. Score for neonatal acute physiology perinatal extension II in predicting neonatal mortality in the neonatal intensive care unit. Arch Med Health Sci [serial online] 2020 [cited 2021 Jan 27];8:186-90. Available from: https://www.amhsjournal.org/text.asp?2020/8/2/186/304704




  Introduction Top


The WHO defines very low birth weight (VLBW) as birth weight <1500 g at birth irrespective of the gestational age.[1] VLBW neonates constitute approximately 4%–7% of all live births, and their mortality is very high as around 50%.[2] In general, VLBW babies who require intensive care are preterm and they contribute to the major workload of special newborn care units Score for Acute Neonatal Physiology (SNAP).[3] It is acknowledged that the prospect of the survival of this population of infant is closely related to various factors, and investigators all over the world have been searching for factors (clinical and physiological) which could help in the prediction of mortality in VLBW neonates.[4] These predictors include maternal factors (maternal medical illness, significant obstetric problems, use of antenatal steroids, etc.), birth weight, gestational age, Apgar scores, and respiratory distress syndrome.[5] As neonatal intensive care has lagged behind that of measures for adult and pediatric intensive care for the development of illness severity indices, an effort by Richardson in 1993 led to the development of “score for acute neonatal physiology” (SNAP), which is an organ system physiology-based illness severity index, derived from 34 routine clinical tests and vital signs within the first 24 hours of neonate admission. SNAP perinatal extension (SNAPPE) was later developed and provides a simple additive point score to generate mortality risks, such as birth weight, Apgar scores, and small for gestational age. SNAP was cumbersome to use because of the number and complexity of items. Therefore, Richardson et al., in 2001, simplified the score and developed the second generation of SNAPPE, derived from six physiological variables and three variables of perinatal mortality risks, and also shortened the observation time from 24 h to 12 h of admission.[6],[7],[8] With the identification of such a scoring system, it is possible to prevent, particularly aiming the improvement of newborn children care. Here, the neonatal intensive care unit (NICU) is one of the most effective tools to reduce the country's newborn mortality.[9] Furthermore, the patterns of neonatal mortality are useful indicators of the quality of obstetrical and neonatal care in a particular setting, and their assessment ensures the estimation of the quality of health care.[10] Therefore, we proposed this study to determine the validity of SNAPPE-II in predicting the VLBW neonates' mortality risk in the NICU at teaching hospital of Raipur, Chhattisgarh. This should inform public health authorities on the current burden of neonatal mortality in order to tailor control interventions to curb this burden.


  Materials and Methods Top


Study design and setting

This was a hospital-based prospective cohort study carried out from June 2018 to May 2019 (1 year) in the NICU, Department of Paediatrics, Ekta Institute of Child Health, Raipur.

Study population

The source and study population for this study were all premature newborns weighing <1500 g and more than 26 weeks admitted to the NICU, Department of Paediatrics, Ekta Institute of Child Health, Raipur, from the 1-year period, i.e., June 2018–May 2019. We excluded neonates with the presence of lethal congenital malformation, death within 12 h of life, Leaving Against Medical Advise (LAMA), and extramural newborns.

Sample size with justification

Even though we included all premature VLBW newborns consecutively admitted to the NICU of Ekta Institute of Child Health during the study period, we checked the adequacy of the sample size based on our objectives and accordingly, the minimum required sample size was calculated using sample size formula, n = (Np [1-p])/([d2/Z21-a/2] × [N-1] + p × [1-p]) by considering the following statistical assumptions: N = 200 as population size (number of patients of birth weight <1500 g admitted to Ekta Hospital in a year), P = 36.9% as prevalence of mortality in birth weight <1500, d = 5% as margin of error, and Z1-a/2 = 1.96 at 95% confidence interval.[11] This calculation yielded a sample size requirement of 129 neonates.

Data collection

Ethical committee and scientific committee clearance were taken. Parents of the children were explained about the purpose of the study and ensured strict confidentiality. Written informed consents were obtained before the study. The variable SNAPPE-II score was collected prospectively by doctors as well as trained nurses on the basis of recommended physiological and clinical factors [Table 1], within the first 12 h of admission in the NICU after stabilization.[12] The final score was computed as the arithmetic sum of points assigned to each item, and the worst score within the first 12 h of admission was analyzed. We monitored their outcome till 28 days postbirth period. When the neonates were discharged before 28 days, weekly phone calls were undertaken to monitor the newborn outcomes at home [Figure 1].
Table 1: Score for neonatal acute physiology perinatal extension II[12]

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Figure 1: Flowchart identifying the study population (n= 129)

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Data analysis

Data obtained were compiled systematically in Microsoft Excel 2010 spreadsheet and master table was prepared. The data set was subdivided and distributed meaningfully; the data were presented in the form of graphs and tables. Statistical analyses were performed using a personal computer with the Statistical Package for the Social Sciences Software IBM SPSS Statistics for Windows, Version 16.0 (IBM Corp. Armonk, NY, USA). Categorical data were presented as percentages (%) and continuous data were presented as mean ± standard deviation or median with interquartile range. A bivariate analysis using the Chi-square test or Fisher exact test, where appropriate, was performed to evaluate differences between groups for categorized variables, and independent sample t-test was performed to evaluate differences between groups for continuous variables. The power of the SNAPPE II score to predict the neonatal mortality was evaluated by means of receiver operating characteristics (ROC) curve. The optimal cutoff score to predict mortality was determined by visual inspection of the curve at a level that combined maximum sensitivity and optimal specificity. All tests were performed at a 5% level of significance; thus, an association was significant if P < 0.05.


  Results Top


A total of 129 participants fulfilling the inclusion criteria were enrolled in to the study and 45.75% were male and 54.25% were female, and mortality is higher among males as compared to the females (P < 0.05) [Table 2]. clearly evident that the dead neonates had significantly less weight than those neonates who survived (P < 0.001). The infants who died in the neonatal period were considerably more premature than the survivors, and this difference was highly significant (P < 0.001).
Table 2: Distribution of score for neonatal acute physiology perinatal extension.II variables among the study participants (n=129)

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Two groups showed a significant difference with respect to the temperature in the first 24 h. The urine output in the first 24 h was different in both the groups (P < 0.001). The dead neonates were shown to be significantly more acidotic in the first 24 h of life, as compared to the survivor's group. The present study showed that the infants who died in the early neonatal period had significantly lower PO2/FiO2 [Table 2]. The mean of SNAPPE II score was 25.1 ± 18.22. The SNAPPE II score of the dead neonates was significantly higher than the surviving neonates (43.6 ± 17.25 vs. 18.2 ± 13.09; P < 0.001).

[Figure 2] shows the ROC of SNAPPE II score in predicting mortality among very low birth neonates. It shows that the discriminating ability was 0.857 (good). The best cutoff for SNAPPE II score in predicting neonatal mortality on charting the ROC was 31 with sensitivity and specificity as 76.6% and 88.4%, respectively, with a significant P < 0.001.
Figure 2: Receiver operating characteristics curve for score for neonatal acute physiology perinatal extension II score for prediction of mortality among study participants

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  Discussion Top


The present study was specifically designed to evaluate the validity of the SNAPPE II score as predictor of neonatal mortality. Great care was taken in methodology to ensure the accuracy and reproducibility of the observations. The survival of VLBW babies admitted to the SNCUs in India is generally lower than in the developed country with wide variations in the performance of SNCUs in our country itself. By considering the effects on the outcome of pre-NICU admission risk factors, the severity of illness, and the intensive care effectiveness, our study may help to understand the reason for the existence of these differences.

Male gender has been cited as a major risk factor for neonatal mortality in the studies by Lim et al. and Basiri et al., and numerous hypotheses have been proposed to explain the biological plausibility of the differences in the mortality existing between the two sexes, and similar findings were obtained in the present study on univariate analysis.[13],[14]

Among the neonatal physiologic alterations, the mean arterial blood pressure, temperature, ratio PO2/FiO2, serum pH, and urine output showed a statistically or clinically significant difference among the two groups of neonates. Similar results were shown in the studies by Marshall et al., Narayanan et al., and Aiken.[8],[15],[16]

The SNAPPE II was designed primarily as a measurement of illness severity, a major but not the only component on mortality risks. A prognostic score was considered valid in the population if the low score patients survive, on the contrary patients with higher score will not survive.[12] Our study showed that the SNAPPE II value of the nonsurvivals was higher significantly than the survivals. Overall, it correlated well with the outcome with higher score predicting higher mortality. The ROC showed that SNAPPE II has a better performance in predicting the mortality (0.857). Similar observations made by Harsha and Archana and Muktan et al., where ROC SNAPPE II in predicting admission mortality was having area under the curve as 0.849 and 0.917, respectively.[17],[18],[19]

A prognostic tool was considered good if it has sensitivity, specificity, positive, and negative predictive value >90%, or if the statistic test of McNemar showed P > 0.05 and P < 0.05. However, studies that look for the optimum value of the diagnostic test to establish the best cutoff point are very rare. Based on that, SNAPPE II scores >31 were considered as the best cutoff point in predicting neonatal mortality. The cutoff obtained in various studies done by Niranjan et al., Ucar et al., Groenendaal et al., Reid et al., Mesquita Ramirez et al., and Prentice et al. varied.[19],[20],[21],[22],[23],[24]

From this finding, we can conclude that more neonatal survival interventions should be targeted toward the immediate and early neonatal periods. This finding aligns with the studies of Wang et al., Sharma and Gaur, and Hornik et al., which shows that up to half of all deaths occur in the first 24 h of life, and 75% occur in the 1st week, with the 48 h immediately following birth cited as the most crucial time for newborn. Moreover, the variables for SNAPPE-II can be collected by well-trained nurses apart from doctors. Furthermore, the SNAPPE II score method helps in counseling the parents regarding the severity of illness and the probable treatment cost involved.[25],[26],[27]

The main limitation of our study is that it is a single-center study, though the findings obtained can still be generalized because they portray similar etiologies of neonatal hospital mortality observed in other parts of states as shown in studies by Rachuri et al., Harsha and Archana, and Niranjan et al.[17],[19],[28] The merits of this study include only VLBW neonates, also due to its prospective cohort design, and robust statistical methods to provide a contribution of level II scientific evidence to the scarcity of data on neonatal hospital mortality in the Indian setting.[25] The correlation of the individual variables of the SNAPPE II score (mean arterial blood pressure, temperature, ratio PO2/FiO2, serum pH, and urine output) with the mortality was not reflected in the studies conducted by Harsha et al. and Niranjan et al., but the present study showed that the above variables in the SNAPPE II score were independent predictors of mortality and were statistically significant.[17],[19]


  Conclusion Top


The present study was specifically designed to evaluate the validity of SNAPPE II score as predictor of neonatal mortality in VLBW infants at Ekta Institute of Child Health, Raipur, and it was concluded that SNAPPE II is a measurement of illness severity that correlates well with the neonatal outcome at the NICU. SNAPPE II scores of more than 31 are associated with higher mortality. This study identifies the importance of SNAPPE-II with mortality in VLBW neonates and helps in prioritizing it so we can intervene and prevent mortality in these neonates. There is, therefore, a need that such infants require care at centers with adequately trained staff with appropriately developed support infrastructure.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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Lim JW, Chung SH, Kang DR, Kim CR. Risk factors for cause-specific mortality of very-low-birth-weight infants in the Korean neonatal network. J Korean Med Sci 2015;30 Suppl 1:S35-44.  Back to cited text no. 13
    
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Harsha SS, Archana BR. SNAPPE-II (Score for Neonatal Acute Physiology with Perinatal Extension-II) in predicting mortality and morbidity in NICU. J Clin Diagn Res 2015;9:SC10-2.  Back to cited text no. 17
    
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