Score For Neonatal Acute Physiology Research Articles

Association between maternal stress and premature milk cortisol, milk IgA, and infant health: a cohort study.

Maternal stress is pervasive in the neonatal intensive care unit (NICU). Maternal stress is associated with changes in human milk (HM) immunomodulatory agents, which may impact neonatal health. We sought to determine the association between maternal stress, HM immunoglobulin A (IgA) and cortisol, and to assess how these milk components correlate with infant immune and neurodevelopmental outcomes. We then compared how these associations persist over time. The study design involved a cohort study of exclusively breastfeeding mothers and their singleton moderately preterm (28-34 weeks) infants admitted to the NICU. We collected maternal serum, maternal saliva, and first-morning whole milk samples, and administered maternal stress questionnaires at 1 and 5 weeks postpartum. We analyzed the samples for HM IgA (using a customized immunoassay in skim milk) and for HM and salivary cortisol (using a chemiluminescent immunoassay). Infant illness was assessed using the Score for Neonatal Acute Physiology II (SNAP II) and SNAP II with Perinatal Extension (SNAPPE II), and infant neurodevelopment were assessed using the Test of Infant Motor Performance. We analyzed changes in HM IgA and cortisol over time using paired t-tests. Furthermore, we performed correlation and regression analyses after adjusting for gestational age (GA), corrected GA, and infant days of life. In our study, we enrolled 26 dyads, with a mean maternal age of 28.1 years, consisting of 69% white, 19% Black, and 8% Hispanic. Cortisol: Salivary and HM cortisol were closely associated in week 1 but not in week 5. Though mean salivary cortisol remained stable over time [2.41 ng/mL (SD 2.43) to 2.32 (SD 1.77), p = 0.17], mean HM cortisol increased [1.96 ng/mL (SD 1.93) to 5.93 ng/mL (SD 3.83), p < 0.001]. Stress measures were inversely associated with HM cortisol at week 1 but not at week 5. IgA: HM IgA decreased over time (mean = -0.14 mg/mL, SD 0.53, p < 0.0001). High maternal stress, as measured by the Parental Stressor Scale: neonatal intensive care unit (PSS:NICU), was positively associated with HM IgA at week 5 (r = 0.79, P ≤ 0.001). Higher IgA was associated with a lower (better) SNAP II score at week 1 (r = -0.74, p = 0.05). No associations were found between maternal stress, salivary cortisol, HM cortisol, or HM IgA and neurodevelopment at discharge (as assessed using the TIMP score). Furthermore, these relationships did not differ by infant sex. Maternal stress showed associations with HM cortisol and HM IgA. In turn, HM IgA was associated with lower measures of infant illness.

Neonatal mortality risk assessment using SNAPPE-2 score in a neonatal intensive care unit in moderate-to-late preterm Newborns

Background: In 1993, Richardson et al. introduced the score for neonatal acute physiology (SNAP), a 34-parameter system predicting mortality and morbidity in neonates. To enhance simplicity, it was later refined to nine parameters and renamed SNAP-II. Additionally, a perinatal extension known as SNAP Perinatal Extension, Version II (SNAPPE-II) was developed for broader applicability. Objectives: To determine the validity of SNAPPE-II in predicting the outcome in terms of mortality in premature babies of gestational age between 32 and 36 weeks in a tertiary care neonatal intensive care unit (NICU) of Cheluvamba Hospital, Mysore, Karnataka. Materials and Methods: The diagnostic study was conducted in the NICU of a tertiary care center in Mysore, India. The sample size of 138 subjects was calculated using a formula, and simple random sampling was used. The study included newborns with gestational ages between 32 and 36 weeks, and data was collected within 48 h of birth as per the proforma. The study assessed the correlation between the SNAPPE II score and mortality rate in babies admitted to the NICU. Data were analyzed using various statistical methods. Results: This study finds that the SNAPPE-II score has a moderate ability to distinguish between those newborns who will end up with mortality and those who will survive, as indicated by an area under ROC curve of 0.724, and has moderate diagnostic accuracy as indicated by a Youden index of 0.3974. The associated criterion for the SNAPPE-II score is &gt;57, indicating newborns are more likely to have mortality. Conclusion: The SNAPPE-II score can be used to predict neonatal mortality rates in moderate-to-late preterm babies of gestational age between 32 and 36 weeks.

Improving Prediction of Survival for Extremely Premature Infants Born at 23 to 29 Weeks Gestational Age in the Neonatal Intensive Care Unit: Development and Evaluation of Machine Learning Models.

Infants born at extremely preterm gestational ages are typically admitted to the neonatal intensive care unit (NICU) after initial resuscitation. The subsequent hospital course can be highly variable, and despite counseling aided by available risk calculators, there are significant challenges with shared decision-making regarding life support and transition to end-of-life care. Improving predictive models can help providers and families navigate these unique challenges. Machine learning methods have previously demonstrated added predictive value for determining intensive care unit outcomes, and their use allows consideration of a greater number of factors that potentially influence newborn outcomes, such as maternal characteristics. Machine learning-based models were analyzed for their ability to predict the survival of extremely preterm neonates at initial admission. Maternal and newborn information was extracted from the health records of infants born between 23 and 29 weeks of gestation in the Medical Information Mart for Intensive Care III (MIMIC-III) critical care database. Applicable machine learning models predicting survival during the initial NICU admission were developed and compared. The same type of model was also examined using only features that would be available prepartum for the purpose of survival prediction prior to an anticipated preterm birth. Features most correlated with the predicted outcome were determined when possible for each model. Of included patients, 37 of 459 (8.1%) expired. The resulting random forest model showed higher predictive performance than the frequently used Score for Neonatal Acute Physiology With Perinatal Extension II (SNAPPE-II) NICU model when considering extremely preterm infants of very low birth weight. Several other machine learning models were found to have good performance but did not show a statistically significant difference from previously available models in this study. Feature importance varied by model, and those of greater importance included gestational age; birth weight; initial oxygenation level; elements of the APGAR (appearance, pulse, grimace, activity, and respiration) score; and amount of blood pressure support. Important prepartum features also included maternal age, steroid administration, and the presence of pregnancy complications. Machine learning methods have the potential to provide robust prediction of survival in the context of extremely preterm births and allow for consideration of additional factors such as maternal clinical and socioeconomic information. Evaluation of larger, more diverse data sets may provide additional clarity on comparative performance.

Mortality Risk Assessment by SNAP-II and SNAPPE-II among Very Low Birth Weight Newborns- An Observational Study

Introduction: Very Low Birth Weight (VLBW) babies are those with a birth weight of less than 1500 gm and require special care, attention, and resources. However, despite all efforts, their mortality rate remains high. Proper assessment of these neonates is crucial to identify high-risk cases and take early steps to reduce mortality. In addition to technical advances in neonatal care, severity scores have been developed to predict neonatal mortality. Richardson developed the Score for Neonatal Acute Physiology (SNAP-II) and SNAP with Perinatal Extension (SNAPPE-II) as scoring systems for predicting mortality in the Neonatal Intensive Care Unit (NICU). Aim: To assess the usefulness of SNAP-II and SNAPPE-II as predictors of mortality in VLBW neonates. Materials and Methods: This was an observational cross-sectional study involving 145 VLBW neonates admitted to the NICU of North Bengal Medical College and Hospital (NBMCH) from May 2019 to April 2020. Relevant data were collected to assess the mortality risk scores SNAP-II and SNAPPE-II. The outcome of discharge or death was recorded. Data entry was performed using MS excel and analysed using Statistical Package for Social Sciences (SPSS) version 20.0. The relationship between newborn survival and SNAP-II or SNAPPE-II final scores was determined using the Mann- Whitney U test, and the relationship between survival and various SNAP-II and SNAPPE-II score categories was determined using Fisher’s-Exact Test. A p-value of less than 0.05 was considered statistically significant. An ROC curve was generated to determine the best cutoff score for predicting mortality. Results: The mean scores of SNAP-II and SNAPPE-II were higher in babies who expired compared to those who survived. The mean (±SD) SNAP-II scores were 8.96 (±13.865) for survived newborns and 41.08 (±23.174) for expired newborns. The mean (±SD) SNAPPE-II scores were 20.01 (±14.54) for survived newborns and 48.85 (±25.02) for expired newborns. The optimal cutoff values for SNAP-II and SNAPPE-II in predicting mortality were 31.5 and 36, respectively. The sensitivity and specificity of SNAP-II were 83.0% and 89.1%, while for SNAPPE-II they were 69.8% and 89.1%, respectively. Conclusion: The mean SNAP-II and SNAPPE-II scores were higher among expired VLBW neonates compared to those who survived. A SNAP-II score of 31.5 and SNAPPE-II score of 36 were associated with higher mortality, indicating that both scores are effective predictors of mortality regardless of Gestational Ages (GA) and birth weight.

Comparing different scoring systems for predicting mortality risk in preterm infants: a systematic review and network meta-analysis.

This study aimed to compare the predictive values of eight scoring systems (Neonatal Critical Illness Score [NCIS], Neonatal Therapeutical Intervention Score System [NTISS], Clinical Risk Index for Babies [CRIB], Clinical Risk Index for Babies II [CRIB-II], Score for Neonatal Acute Physiology Perinatal Extension [SNAPPE], Score for Neonatal Acute Physiology Perinatal Extension II [SNAPPE-II], Score for Neonatal Acute Physiology [SNAP], and Score for Neonatal Acute Physiology II [SNAP-II]) for the mortality risk among preterm infants. The Embase, PubMed, Chinese Biomedical Database, Web of Science, and Cochrane Library databases were searched to collect studies that compared different scoring systems in predicting the mortality risk in preterm infants from database inception to March 2023. Literature screening, data extraction, and bias risk assessment were independently conducted by two researchers. Subsequently, the random-effects model was used for the network meta-analysis. A total of 19 articles were included, comprising 14,377 preterm infants and 8 scoring systems. Compared to CRIB-II, NCIS, NTISS, SNAP-II, and SNAPPE-II, CRIB demonstrated better predictive efficiency for preterm infant mortality risk (P < 0.05). Relative to CRIB, CRIB-II, and SNAPPE, SNAP-II had worse predictive efficiency for preterm infant mortality risk (P < 0.05). The surface under the cumulative ranking curve of the eight scoring systems was as follows: CRIB (0.980) > SNAPPE (0.718) >SNAP (0.534) >CRIB-II (0.525) >NTISS (0.478) >NCIS (0.422) >SNAPPE-II (0.298) >SNAP-II (0.046). The CRIB scoring system showed the highest accuracy in predicting preterm infant mortality risk and was simple to perform. Therefore, CRIB selection can be prioritized in clinical practice. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=434731, PROSPERO (CRD42023434731).

A novel application to develop illness severity scores for predicting mortality and morbidities in a Neonatal Intensive Care Unit (NICU)

The first hundred days of child life is considered the most critical phase of its physical development and its health. Neonates who are critically sick are kept under observation in a Neonatal Intensive Care Unit (NICU) for continuous monitoring of their health conditions. Classifying infants on the first day of admission based on illness severity score would help neonatologist in understanding the prognosis and better management of neonates at NICU. Illness severity scoring systems with a Score for Neonatal Acute Physiology (SNAP) and its variants was proposed to classify neonates based on its prognosis. A novel risk stratification module was developed which allowed neonatologist to design and develop an illness severity scoring system using the Richardson defined method. The SNAP I, modified SNAP I and SNAP II for the study population at study site was validated on 230 preterm neonates diagnosed with respiratory distress syndrome (RDS), apnea and sepsis as a retrospective study. All the scores predicted mortality with statistical significance, with improved accuracy performance (+ 15 to 25%) was seen with proposed modified SNAP I. The proposed modified SNAP I score was found to be most accurate compared to SNAP I and SNAP II for predicting the mortality and also other outcome measures such as severity of respiratory distress syndrome (RDS) (70%), presence of apnea (65%) and sepsis (80%) for the study population. Results obtained were strong indication of the need for scoring system where the variables as well as their range could be altered based on study population and NICU involved for the study.

Support vector machines in neonatal mortality detection: a comprehensive scoping review with disease-specific emphasis

Neonatal mortality is a widely significant problem since diseases such as sepsis, apnea and jaundice have claimed the lives of 2.3 million neonates in 2021. As such, better tools need to be developed to reduce its rate. While traditional methods like Clinical risk index (CRIB) and Score for neonatal acute physiology (SNAP) have proven helpful in predicting neonatal mortality, there is a need for more efficient measures. One such approach is support vector machine (SVM), a supervised machine-learning algorithm that is primarily used for classification. SVM can perform both linear and non-linear classification; it conducts the latter with the assistance of the kernel trick and functions such as polynomial, gaussian, RBF and sigmoid functions. This narrative review aims to explore the potential and limitations of SVM in predicting major global causes of neonatal mortality. We searched through articles employing SVM to predict different diseases and symptoms such as sepsis, seizures, fetal heart rate, low birth weight, hypoxic-ischemic encephalopathy, apnea, jaundice and neonatal respiratory distress syndrome, and concluded that while SVM has its merits and has shown promising results in many aspects, it also has its demerits such as requiring an extensive training time to achieve higher accuracy and precision.

Pattern of Inflammatory Markers and Use of Antibiotics in Meconium Aspiration Syndrome: A Retrospective Cohort Study.

Objectives To study the pattern of inflammatory markers in meconium aspiration syndrome (MAS) and their correlation with illness severity/antibiotic usage. Study design This is a retrospective analysis of neonates who were admitted with MAS and had inflammatory markers done during the first week of life. Results Seventy-six neonates with MAS were identified. White cell count (WCC), absolute neutrophil count (ANC), and immature to total neutrophil count (I/T) ratiopeaked at 12 and CRP (43.75 mg/dl) at 48 hours of life (HOL). Neonates needing nasal cannula oxygen had lower CRP at 12 (p=0.035) and 24 HOL (p=0.046). There was no correlation between CRP at 48 HOL and score for neonatal acute physiology and perinatal extension II (SNAPPE-II; R2 0.0004). High CRP at 24 HOL was associated with longer duration of antibiotics (p<0.001) despite no correlation with the blood cultures. Conclusion MAS was associated with inflammatory markers peaking at 12 to 48 HOL; however, antibiotics should not be determined based on them as their correlation for illness severity or blood culture is poor.

Addition of platelet-lymphocyte ratio to risk factors to improve the early prediction of acute kidney injury and mortality in critically ill neonates.

To determine whether early neutrophil, lymphocyte, and platelet ratio (NLPR), neutrophillymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR), calculated based on easily available parameters in complete blood count, are associated with the development of acute kidney injury (AKI) and mortality during neonatal intensive care unit (NICU) stay, and to evaluate whether these ratios could act as a predictor of AKI and mortality in neonates. The pooled data of 442 critically ill neonates from our previously published prospective observational studies of urinary biomarkers were analyzed. Complete blood count (CBC) was measured on NICU admission. The clinical outcomes included AKI developed during the first 7 days after admission and NICU mortality. Of the neonates, 49 developed AKI and 35 died. The association of the PLR, but not NLPR and NLR, with AKI and mortality remained significant after adjustment for potential confounders including birth weight and illness severity as assessed by the score for neonatal acute physiology (SNAP). The area under the curve (AUC) of the PLR for predicting AKI and mortality was 0.62 (P=0.008) and 0.63 (P=0.010), respectively, with additional predictive value when combined with other perinatal risk factors. The combination of PLR with birth weight, SNAP, and serum creatinine (SCr) had an AUC of 0.78 (P<0.001) in predicting AKI, and its combination with birth weight and SNAP had an AUC of 0.79 (P<0.001) in predicting mortality. Low PLR on admission is associated with increased risk for AKI and NICU mortality. Although the PLR alone is not predictive of AKI and mortally, it adds predictive value to other risk factors for AKI prediction in critically ill neonates.

Feeding practices of preterm low birthweight infants up to six onths: a comparison between Kangaroo and Conventional care.

To compare feeding practices of low birthweight(LBW) infants, according to type of care received during and after hospital discharge: Kangaroo Care(KC) and Conventional Care(CC). Prospective cohort study was conducted at a university hospital (Brazil) between 2019 and 2021. The sample consisted of 65 LBW infants (weight≤1,800grams)-46 in KC and 19 in CC. KC includes breastfeeding(BF) guidance and support to parents at hospital and after discharge. Data collection was performed at hospital discharge, and at the 4 th and 6 th month of corrected gestational age(CGA). Consumption of twenty-seven foods was analyzed in the last two periods of the follow-up and expressed in relative frequency. Three indicators were analyzed: exclusive breastfeeding(EBF); mixed BF; and introduction of liquid and solid foods. Groups had similar health characteristics, except for the weight at hospital discharge and SNAPPE II score, that were lower in KC group. We found higher frequency of EBF among KC at hospital discharge (CC=5.3% vs KC=47.8%; p=0.001). The higher frequency of mixed BF was observed in KC at 4 months of CGA (CC=5.6%vsKC=35.0%; p=0.023), and at 6 months of CGA (CC=0.0%vsKC=24.4%; p=0.048). Consumption of solid foods (4 th month of CGA=25.9%, 6 th month of CGA=91.2%) and liquids (4 th month of CGA=77.6%;6 th month of CGA=89.5%) were similar between groups. In KC, SNAPPE II scores were lower and frequency of EBF was higher at hospital discharge and frequency of mixed BF was higher over six months. Early supply of infant formula, liquid and solid foods were similar in both groups.

Diagnostic and prognostic values of miR181b-5p and miR21-5p for neonatal sepsis risk and their link to SNAP II score and disease mortality.

Neonatal sepsis is a lethal syndrome that necessitates prompt treatment to avoid disease complications. As a result, biomarkers that may either differentiate sepsis early or predict the outcome of sepsis are essential. The goal of this research was to find out the clinical weight of using miR181b-5p and miR21-5p expression levels as diagnostic and prognostic new genetic markers for neonatal sepsis. A total of 60 neonates with sepsis and 60 healthy neonates were involved in this study. Laboratory tests include complete blood count (CBC), random blood sugar (RBS), arterial blood gases (ABG), and serum C-reactive protein (CRP). Neonates with sepsis were assessed by the Score for Neonatal Acute Physiology II (SNAP II). The serum fold changes of the target miRNAs were determined using qRT-PCR and the 2-ΔΔCt equation. The relative serum level of miR181b-5p was [ median (IQR)=0.2509 (0.0009-4.11)] and for miR21-5p was [median (IQR)=0.07 (0.007-7.16)] which were significantly downregulated in patients with neonatal sepsis compared to controls (p<0.001 each). There was a strong significant positive correlation between miR181b-5p and miR21-5p with r=0.718 and p<0.001. MiR181b-5p and miR21-5p were significantly negatively correlated with total leucocytic count (TLC), lymphocytic count, and CRP. While they were both positively correlated to the SNAP II score. Obvious association between higher expressions of target genes and higher SNAP II score groups. After a following-up period, twenty-two (36.7%) neonates died, while 38 (63.3%) of the babies became better and were released from the hospital. We reported that miR-181-5p, miR21-5p, SNAP II score and CRP were significantly higher in non-survivors than survivors. Only miR181b-5p, miR21-5p, and SNAP II were predictive factors of septic mortality. MiR181b-5p and miR21-5p are diagnostic and prognostic biomarkers of neonatal sepsis.

Determination of the strength of SNAPPE II score (Score for Neonatal Acute Physiology with Perinatal Extension-II) to predict neonatal mortality in a neonatal intensive care unit of tertiary care hospital: A prospective observational study

Determination of the strength of SNAPPE II score (Score for Neonatal Acute Physiology with Perinatal Extension-II) to predict neonatal mortality in a neonatal intensive care unit of tertiary care hospital: A prospective observational study

Triage Policies at U.S. Hospitals with Pediatric Intensive Care Units

Objectives To characterize the prevalence and content of pediatric triage policies. Methods We surveyed and solicited policies from U.S. hospitals with pediatric intensive care units. Policies were analyzed using qualitative methods and coded by 2 investigators. Results Thirty-four of 120 institutions (28%) responded. Twenty-five (74%) were freestanding children’s hospitals and 9 (26%) were hospitals within a hospital. Nine (26%) had approved policies, 9 (26%) had draft policies, 5 (14%) were developing policies, and 7 (20%) did not have policies. Nineteen (68%) institutions shared their approved or draft policy. Eight (42%) of those policies included neonates. The polices identified 0 to 5 (median 2) factors to prioritize patients. The most common factors were short- (17, 90%) and long- (14, 74%) term predicted mortality. Pediatric scoring systems included Pediatric Logistic Organ Dysfunction-2 (12, 63%) and Score for Neonatal Acute Physiology and Perinatal Extensions-II (4, 21%). Thirteen (68%) policies described a formal algorithm. The most common tiebreakers were random/lottery (10, 71%) and life cycles (9, 64%). The majority (15, 79%) of policies specified the roles of triage team members and 13 (68%) precluded those participating in patient care from making triage decisions. Conclusions While many institutions still do not have pediatric triage policies, there appears to be a trend among those with policies to utilize a formal algorithm that focuses on short- and long-term predicted mortality and that incorporates age-appropriate scoring systems. Additional work is needed to expand access to pediatric-specific policies, to validate scoring systems, and to address health disparities.

Association between pulmonary hemorrhage and CPAP failure in very preterm infants.

BackgroundPulmonary hemorrhage (PH) in neonates is a life-threatening respiratory complication. We aimed to analyze the perinatal risk factors and morbidity with PH among very preterm infants in a large multicenter study.MethodsThis was a multicenter case–control study based on a prospective cohort. Participants included 3,680 in-born infants with a gestational age at 24–32 weeks (birth weight <1,500 g) who were admitted between January 1, 2019, and October 31, 2021. All infants were divided into two groups, namely, the PH and no-PH groups, at a ratio of 1:2 according to the following factors: gestational age (GA), birth weight (BW), and the Score for Neonatal Acute Physiology with Perinatal extension II (SNAPPE II). Perinatal factors and outcomes were compared between the two groups by logistic regression analyses.ResultsA total of 3,680 infants were included in the study, and the number of identified cases of PH was 262 (7.1%). The incidence was 16.9% (136/806) for neonates with extremely low BW (BW < 1,000 g) infants. The multivariate analysis showed that CPAP failure (OR 2.83, 95% CI 1.57, 5.08) was significantly associated with PH. PH was associated with a high likelihood of death (OR 3.81, 95% CI 2.67, 5.43) and bronchopulmonary dysplasia (BPD) (≥grade II) (OR 1.58, 95% CI 1.00, 2.48).ConclusionsIn this multicenter case–control study based on a prospective cohort, PH to be common among VLBW infants. PH is associated with significant morbidity and mortality, and perinatal management, especially CPAP failure. Respiratory management strategies to decrease the risk of PH should be optimized.

Value of red cell distribution width-to-platelet ratio as a predictor for morbidity and mortality in neonatal intensive care unit.

Scoring neonatal acute physiology is significant for improving the survival rate of neonates in neonatal intensive care units (NICU). Red blood cell distribution width to platelet ratio (RPR) has been used to evaluate physiology of multiple diseases. However, the value of RPR as a predictor for morbidity and mortality in NICU remains unclear. The score for neonatal acute physiology and perinatal extension II (SNAPE-II) was used to evaluate the physiology and separate neonates into Mild (n = 45), Moderate (n = 45) and Severe (n = 45) groups. White blood cell count (WBC), procalcitonin (PCT) and C-reactive protein (CRP) in cord blood were examine. Spearman's correlation and receiver operating characteristic analysis were performed to demonstrated the correlations of these indicators. There was a positive correlation between the SNAPE-II scores and RPR in neonates in NICU. The WBC, PCT and CRP levels increased with the upregulation of SNAPE-II scores in neonates in NICU and there were positive correlations between RPR and WBC, PCT and CRP, respectively. RPR could be used as a supplementary predictor for the evaluation of neonatal morbidity and mortality in NICU beside SNAPE-II.

Neurodevelopmental Outcomes of Infants at

To evaluate changes in mortality or significant neurodevelopmental impairment (NDI) in children born at <29weeks of gestation in association with national quality improvement initiatives. This longitudinal cohort study included children born at 220/7 to 286/7weeks of gestation who were admitted to Canadian neonatal intensive care units between 2009 and 2016. The primary outcome was a composite rate of death or significant NDI (Bayley Scales of Infant and Toddler Development, Third Edition score <70, severe cerebral palsy, blindness, or deafness requiring amplification) at 18-24months corrected age. To evaluate temporal changes, outcomes were compared between epoch 1 (2009-2012) and epoch 2 (2013-2016). aORs were calculated for differences between the 2 epochs accounting for differences in patient characteristics. The 4426 children included 1895 (43%) born in epoch 1 and 2531 (57%) born in epoch 2. Compared with epoch 1, in epoch 2 more mothers received magnesium sulfate (56% vs 28%), antibiotics (69% vs 65%), and delayed cord clamping (37% vs 31%) and fewer infants had a Score for Neonatal Acute Physiology, version II >20 (31% vs 35%) and late-onset sepsis (23% vs 27%). Death or significant NDI occurred in 30% of children in epoch 2 versus 32% of children in epoch 1 (aOR, 0.86; 95% CI, 0.75-0.99). In epoch 2, there were reductions in the need for hearing aids or cochlear implants (1.4% vs 2.6%; aOR, 0.50; 95% CI, 0.31-0.82) and in blindness (0.6% vs.1.4%; aOR, 0.38; 95% CI, 0.18-0.80). Among preterm infants born at <29weeks of gestation, composite rates of death or significant NDI and rates of visual and hearing impairment were significantly lower in 2013-2016 compared with 2009-2012.

Multiple organ dysfunction syndrome prediction in newborn children

There are several directions for predicting multiple organ dysfunction syndrome (MODS), but almost all of them are poorly tested in neonatology. This review is presented to indicate the problem of the condition severity objectification of newborns and the possibility of predicting the development of MODS. Scales for assessing the severity of MODS in critically ill children have been developed and used since the end of the last century, but their validation in the newborns faces certain difficulties. Prognostic nosospecific scales: NICHD (National Institute of Child Health and Human Development) calculator, CRIB II (Clinical Risk Index for Babies), SNAPPE-II (Score for Neonatal Acute Physiology with Perinatal Extension II) are used in neonatology, however their comparison in this category of patients has not been carried out.Theoretical and practical issues of the short-term and long-term prediction of the MODS onset and its outcomes in newborns is a promising area of neonatology, since it allows a doctor to be warned about an impending catastrophe and opens a “window of opportunity” for timely correction of treatment tactics and complications prevention. Obtaining different phenotypes of critical illness and predicting their outcomes in children may have good predictive potential, but such studies have not been conducted in newborns. A promising direction in predicting MODS is the identification of biomarkers of inflammation, among which endocan, cluster of differentiation 64, cluster of differentiation molecules 11b, “pancreatic stone protein” (PSP), soluble intercellular adhesionmolecule-1 (sICAM-1), progranulin, neopterin, resistin (FIZZ3, presepsin (PSP)) carry a good potential, but their effectiveness in neonatology is still to be investigated.Thus, the prediction of MODS in children and newborns remains an unresolved problem. At the same time, several promising scientific directions are actively being developed today, which may lead to a significant breakthrough in predicting MODS in neonatology.

Assessment of the diagnostic ability of RIFLE classification and neutrophil gelatinase-associated lipocalin biomarker in detecting acute kidney injury in newborns at the intensive care unit

Introduction/Objective. This study was designed to demonstrate the association of the RIFLE classification and neutrophil gelatinase-associated lipocalin (NGAL) in predicting of newborns with acute kidney injury (AKI). Methods. This was a prospective study. We included 100 newborns suspected of having a kidney injury. These newborns were admitted to the intensive care unit (ICU) at the University Clinic of Pediatrics from the period of two years. The severity of the disease was determined by RIFLE classification. The biochemical marker NGAL was included in this study because it is an early biomarker of AKI in newborns. The statistical processing of the material was by methods of descriptive statistics. Results. The prevalence rate of AKI was 6.25%, but according to the RIFLE classification the prevalence was 8.7%. According to RIFLE classification, we reported ?risk? in 36%, ?injury? in 50% and ?failure? in 14% of newborns with AKI. In newborns with perinatal asphyxia, kidney injury was seen in 34% and 30%, making perinatal asphyxia the most common predisposing factor. The difference in average value of the score for neonatal acute physiology with perinatal extension in newborns with AKI and the control group without AKI was confirmed significant (p &lt; 0.001). Also, there was a significant difference (p &lt; 0.001) between serum creatinine and urinary NGAL values, on the day they were admitted to the ICU. Conclusion. In newborns hospitalized in the ICU, AKI is a serious condition. We could identify kidney injury and follow up the progression of the disease by using RIFLE classification. The need for early diagnosis of kidney injury, in a period when the disease is not clinically manifest, in the first hours of its occurrence, is provided by NGAL.

Platelet glycoprotein VI genetic polymorphism T13254C in neonatal sepsis

Background Neonatal sepsis is a global burden, being a leading cause of neonatal morbidity and mortality worldwide. Platelet glycoprotein VI (GPVI) affects sepsis at multiple stages of the inflammatory response. The expression of the GPVI receptor is genetically determined, thus influencing the coagulation processes. The authors focused in this study on the role of platelet GPVI genetic polymorphism T13254C (rs1613662) in neonatal sepsis in relation to other risk factors, laboratory tests, sepsis progression, and outcome. Methods The authors studied 50 neonates with early-onset sepsis. The authors detected platelet GPVI T13254C polymorphism using the TaqMan allelic discrimination method by the real-time polymerase chain reaction technique. Results The results showed that GPVI mutant polymorphic group was associated with higher D-dimer levels (P=0.032). Moreover, septic neonates with mutant homozygous type showed poor survival (P=0.047). However, GPVI mutant polymorphic types were not significantly related to other demographic, laboratory data, and different scoring systems, such as sepsis-induced coagulopathy score, International Society on Thrombosis and Hemostasis score, and Score for Neonatal Acute Physiology. Conclusion The authors found a relation between platelet GPVI T13254C polymorphism and D-dimer levels, hence suggesting a relation with neonatal sepsis-associated coagulopathy, which might further affect patients’ outcome.

Comparative Performance of Four Established Neonatal Disease Scoring Systems in Predicting In-Hospital Mortality and the Potential Role of Thromboelastometry.

Background: To compare the prognostic accuracy of the most commonly used indexes of mortality over time and evaluate the potential of adding thromboelastometry (ROTEM) results to these well-established clinical scores. Methods: The study population consisted of 473 consecutive term and preterm critically-ill neonates. On the first day of critical illness, modified Neonatal Multiple Organ Dysfunction (NEOMOD) scoring system, Score for Neonatal Acute Physiology (SNAP II), Perinatal extension of SNAP (SNAPPE), and SNAPPE II, were calculated and ROTEM standard extrinsically activated (EXTEM) assay was performed simultaneously. Time-to-event methodology for competing-risks was used to assess the performance of the aforementioned indexes in predicting in-hospital mortality over time. Time-dependent receiver operator characteristics curves for censored observation were compared across indexes. The addition of EXTEM parameters to each index was tested in terms of discrimination capacity. Results: The modified NEOMOD score performed similarly to SNAPPE. Both scores performed significantly better than SNAP II and SNAPPE II. Amplitude recorded at 10 min (A10) was the EXTEM parameter most strongly associated with mortality (A10 < 37 mm vs. ≥37 mm; sHR = 5.52; p < 0.001). Adding A10 to each index apparently increased the prognostic accuracy in the case of SNAP II and SNAPPE II. However, these increases did not reach statistical significance. Conclusion: Although the four existing indexes considered showed good to excellent prognostic capacity, modified NEOMOD and SNAPPE scores performed significantly better. Though larger studies are needed, adding A10 to well-established neonatal severity scores not including biomarkers of coagulopathy might improve their prediction of in-hospital mortality.