Evaluation of Neonatal Mortality Rate and the Impact on Transparency

2008 ◽  
Vol 23 (2) ◽  
pp. e17
Author(s):  
Joy J. Higgins
Keyword(s):  
Mortality Rate ◽  
Neonatal Mortality ◽  
Neonatal Mortality Rate ◽  
The Impact

The Mortality of Extremely Premature Infants and the Impact on the Overall Neonatal Mortality Rate [20C]

2016 ◽  
Vol 127 ◽  
pp. 31S
Author(s):  
Horatio S. Falciglia ◽  
William K. Brady ◽  
Ronald Merkel ◽  
Vickie Glover ◽  
Angela N. Fellner
Keyword(s):  
Mortality Rate ◽  
Neonatal Mortality ◽  
Premature Infants ◽  
Neonatal Mortality Rate ◽  
The Impact

scholarly journals Neonatal Mortality is Modulated by Gestational Age, Birthweight and Fetal Heart Rate Abnormalities in the Low Resource Setting in Tanzania – a Five Year Review 2015-2019

2021 ◽  
Author(s):  
Aisa Shayo ◽  
Pendo Mlay ◽  
Emily Ahn ◽  
Hussein Kidanto ◽  
Michael Espiritu ◽  
...  
Keyword(s):  
Heart Rate ◽  
Mortality Rate ◽  
Neonatal Mortality ◽  
Fetal Heart Rate ◽  
Fetal Heart ◽  
Delivery Room ◽  
Moderate Hypothermia ◽  
Neonatal Mortality Rate ◽  
Low Resource ◽  
The Impact

Abstract Background Neonatal mortality (NM) remains a significant problem in low resource settings. Birth asphyxia (BA) and prematurity contribute significantly to NM. The study objectives were to determine first, the overall NM as well as yearly neonatal mortality rate from 2015 to 2019. Second, the impact of decreasing GA (<37 weeks) and BW (<2500 grams) on NM. Third, the contribution of intrapartum and delivery room (DR) factors and in particular fetal heart rate abnormalities (FHRT) on NM <7 days. Methods Retrospective cohort study. Labor and delivery room data were obtained from 2015 to 2019 and included BW, GA, fetal heart rate (FHRT) abnormalities, bag mask ventilation (BMV) during resuscitation, initial temperature, antenatal steroids use. Outcome was binary i.e. either death < 7 days or survival. Analysis included t tests, odds ratios (OR) and multiple logistic regression Results The overall neonatal mortality rate was 18/1000 livebirths over the five years. NM was significantly higher for newborns <37 versus ≥37 weeks, OR 10.5 (p<0.0001) and BW <2500 versus ≥2500g OR 9.9 (p<0.0001). For infants <1000g / <28 weeks, the neonatal mortality rate was ~ 588/1000 livebirths. Variables associated with NM included BW - odds of death decreased by 0.55 for every 500g increase in weight, by 0.89 for every week increase in GA, NM increased 6.8-fold with BMV, 2.6-fold with abnormal FHRT, 2.2 fold with no antenatal corticosteroid (ACS), 2.6-fold with moderate hypothermia (all <0.0001). Conclusion NM rates was predominantly modulated by decreasing BW and GA, with smaller/ less mature newborns 10-fold more likely to die. NM in term newborns is strongly associated with FHRT abnormalities and when coupled with respiratory depression suggests BA. In smaller newborns, lack of ACS and moderate hypothermia were additional contributing factors. A composite perinatal approach is essential to achieve a sustained reduction in NM.

scholarly journals The Impact of Special Care Newborn Unit on Routine Neonatal Care Practices and Survival of Neonates in 250-Bed General Hospital, Sirajganj

2018 ◽  
Vol 30 (2) ◽  
pp. 65-68
Author(s):  
Md Imdadul Haque ◽  
Laila Shamima Sharmin ◽  
Md Sanaul Haque Mia ◽  
Md Rafiqul Islam ◽  
SMQ Hasan
Keyword(s):  
Mortality Rate ◽  
General Hospital ◽  
Neonatal Mortality ◽  
Neonatal Care ◽  
Special Care ◽  
Tertiary Level ◽  
Neonatal Mortality Rate ◽  
District Hospitals ◽  
Care Practices ◽  
The Impact

To address the high infant and neonatal mortality rate in Bangladesh, government has adopted policy to ensure care for neonates from community to tertiary level of health care delivery system. Our country has achieved 4 MDG targets well before 2015. However the pace of reduction of neonatal mortality is much lower than that of older children. For that reason government of Bangladesh through Ministry of Health and Family Welfare established Special Care Neonatal Unit (SCNU) at secondary and tertiary level facilities to improve management of sick newborn. The aim of this study was to evaluate the impact of creating SCNU at district hospitals on newborn care practices and to evaluate the contribution of SCNU in improved neonatal survival. It was an observational study conducted from May 2016 to October 2016at 250-bed General Hospital, Sirajganj. Hospital database was accessed to note the number of neonatal admissions, number of referral to higher centers and neonatal mortality. A questionnaire was prepared to interview mothers of children admitted in SCNU and general pediatric ward. A total of 355 mothers were interviewed. There was a significant reduction in neonatal mortality rate after the establishment of SCNU. There was also significant improvement in the knowledge and awareness among mothers regarding various aspects of neonatal care because of the SCNU.TAJ 2017; 30(2): 65-68

IMPACT OF NEONATAL INTENSIVE CARE

PEDIATRICS ◽  
1996 ◽  
Vol 97 (2) ◽  
pp. 215-215
Author(s):  
Student
Keyword(s):  
Intensive Care ◽  
Birth Weight ◽  
Mortality Rate ◽  
Neonatal Mortality ◽  
Neonatal Intensive Care ◽  
Neonatal Mortality Rate ◽  
Total Reduction ◽  
Weight Groups

Neonates who weighed &gt; 1.5 kg at birth were the major contributors to the overall reduction in the neonatal mortality rate (NMR); approximately two thirds of total reduction in the NMR between 1960 and 1980 and 52.6% of the total reduction between 1980 and 1986 occurred in the &gt; 1.5-kg birth weight groups.

scholarly journals Infant mortality: comparison between two birth cohorts from Southeast and Northeast, Brazil

2004 ◽  
Vol 38 (6) ◽  
pp. 773-779 ◽  
Author(s):  
Valdinar S Ribeiro ◽  
Antônio A M Silva ◽  
Marco A Barbieri ◽  
Heloisa Bettiol ◽  
Vânia M F Aragão ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Neonatal Mortality ◽  
Protective Factor ◽  
Infant Mortality Rate ◽  
Northeast Brazil ◽  
Birth Cohorts ◽  
Neonatal Mortality Rate ◽  
Live Births

OBJECTIVE: To obtain population estimates and profile risk factors for infant mortality in two birth cohorts and compare them among cities of different regions in Brazil. METHODS: In Ribeirão Preto, southeast Brazil, infant mortality was determined in a third of hospital live births (2,846 singleton deliveries) in 1994. In São Luís, northeast Brazil, data were obtained using systematic sampling of births stratified by maternity unit (2,443 singleton deliveries) in 1997-1998. Mothers answered standardized questionnaires shortly after delivery and information on infant deaths was retrieved from hospitals, registries and the States Health Secretarys' Office. The relative risk (RR) was estimated by Poisson regression. RESULTS: In São Luís, the infant mortality rate was 26.6/1,000 live births, the neonatal mortality rate was 18.4/1,000 and the post-neonatal mortality rate was 8.2/1,000, all higher than those observed in Ribeirão Preto (16.9, 10.9 and 6.0 per 1,000, respectively). Adjusted analysis revealed that previous stillbirths (RR=3.67 vs 4.13) and maternal age <18 years (RR=2.62 vs 2.59) were risk factors for infant mortality in the two cities. Inadequate prenatal care (RR=2.00) and male sex (RR=1.79) were risk factors in São Luís only, and a dwelling with 5 or more residents was a protective factor (RR=0.53). In Ribeirão Preto, maternal smoking was associated with infant mortality (RR=2.64). CONCLUSIONS: In addition to socioeconomic inequalities, differences in access to and quality of medical care between cities had an impact on infant mortality rates.

scholarly journals Density Estimation of Neonatal Mortality Rate Using Empirical Bayes Deconvolution with Poisson Distributed Surrogate in Central Java Province Indonesia

2020 ◽  
pp. 206-212
Author(s):  
Fevi Novkaniza ◽  
Khairil Anwar Notodiputro ◽  
I Wayan Mangku ◽  
Kusman Sadik
Keyword(s):  
Mortality Rate ◽  
Neonatal Mortality ◽  
Density Estimation ◽  
Poisson Distribution ◽  
Empirical Bayes ◽  
Prior Density ◽  
Neonatal Mortality Rate ◽  
Neonatal Deaths ◽  
Central Java ◽  
Central Java Province

This article is concerned with the density estimation of Neonatal Mortality Rate (NMR) in Central Java Province, Indonesia. Neonatal deaths contribute to 73% of infant deaths in Central Java Province. The number of neonatal deaths for 35 districts/municipalities in Central Java Province is considered as Poisson distributed surrogate with NMR as the rate of Poisson distribution. It is assumed that each number of neonatal deaths by district/municipality in Central Java Province were realizations of unobserved NMR, which come from unknown prior density. We applied the Empirical Bayes Deconvolution (EBD) method for estimating the unknown prior density of NMR based on Poisson distributed surrogate. We used secondary data from the Health Profiles of Central Java Province, Indonesia, in 2018. The density estimation of NMR by the EBD method showed that the resulting prior estimate is relatively close to the Gamma distribution based on Poisson surrogate. This is implying that the suitability of the obtained prior density estimation as a conjugate prior for Poisson distribution.

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