Which Factors Predict Hospital Length-of-Stay for Children Admitted to the Neonatal Intensive Care Unit and Pediatric Ward? A Hospital-Based Prospective Study (original) (raw)
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Frontiers in Pediatrics, 2022
Background: In spite of recent advances in health care, neonatal sepsis is still one of the major causes of morbidity and mortality in neonates and is an ongoing major global public health challenge. Its incidence of mortality varies from health institution to health institution and within the same health institution at varied times and depends on predisposing factors. So the aim of this study was to determine the time to death and its predictors among neonates admitted with neonatal sepsis. Methods: An institutional based retrospective cohort study was conducted among 500 randomly selected neonatal charts. The data was entered using Epi data version 3.1, and exported to and analyzed at STATA version 14. Bivariable and multivariable cox regression analysis were conducted to identify predictors of mortality. Association was summarized using adjusted hazard ratio (AHR) and statistical signi cances were declared at 95% CI and P-value <0.05. Proportionality assumption was tested by global test based on Schoenfeld residuals analysis. Results: During the follow up time, 58 (11.6%) neonates were died with neonatal sepsis while the rest were censored. In this study the overall death incidence rate was 20.5 per 1000 neonate days.
BMC Pregnancy and Childbirth
Background: The first one month of life; the neonatal period is the most risky time for child survival. In Ethiopia, neonatal mortality is unacceptably high, and the trend in reduction is slower as compared to infant and child mortality. The magnitude and associated factors of neonatal mortality in a tertiary care facility were not well documented. Therefore, the aim of this study was to determine neonatal mortality and predictors among neonates admitted to neonatal intensive care unit of Wolaita Sodo University Teaching and Referral Hospital, South Ethiopia. Methods: A retrospective cohort study design was done among neonates admitted to neonatal intensive care unit of a University Teaching and Referral Hospital from 2015 to 2017. Data were collected using data extraction checklist from the medical registry. The main outcome was the occurrence of death within the first four weeks. The survival time was calculated in days between the date of admission and the date of death. Kaplan-Meier survival was used to depict the pattern of death in 28 days and Cox-Proportional model was used to identify the predictors of the neonatal mortality. Results: A total of 964 neonates which contributed to 5889 neonates-days were included in the study. There were 159 neonatal deaths during the follow-up time. Overall, the neonatal mortality incidence was 27 per 1000 neonates-days. Predictors of neonatal mortality were: multiple birth, mothers who did not attend antenatal care visits, neonates born by cesarean section, not initiated breast feeding within 1 h of birth, neonates resuscitated, hyaline membrane disease and perinatal asphyxia. Conclusion: Neonatal mortality at neonatal intensive care unit was high. Managing neonatal complications, initiating breast feeding within 1 h of birth, promoting antenatal care visits, improving quality of services and ensuring continuum of care are recommended to increase survival of neonates.
2019
Background: The first month is the most crucial period for child survival. Neonatal mortality is stagnated in sub-Saharan Africa including Ethiopia. And the trend in reduction is slower than infant and child mortality. The facilities-based cause and predictor of neonatal death in the neonatal intensive care unit were not well documented in this study setting. Hence the aim of this study was to determine the cause and predictors of neonatal mortality among neonates admitted in neonatal intensive care units in eastern Ethiopia. Method: Facilities-based prospective follow-up study was conducted among neonates admitted in neonatal intensive care units of public hospitals in eastern Ethiopia from November to December 2018. Data were collected using pre-tested, structured questionnaire and follow-up checklist. The main outcomes, cause of death was set by senior pediatricians and residents. Epi-Data 3.1 and SPSS 25 version software were used for entry and analysis. Binary logistic regressi...
PLOS ONE, 2022
Background In 2019, 2.4 million neonates died globally, with most deaths occurring in low-resource settings. Despite the introduction of neonatal intensive care units (NICUs) in these settings, neonatal mortality remains high, and caring for sick neonates around the clock can be challenging due to limited staff and resources. Objective To evaluate whether neonatal intensive care admissions during daytime and overnight hours affects in-hospital neonatal mortality. Methods A retrospective case-control study was conducted using 2016 chart data at a University hospital in Ethiopia. Cases were defined as neonates who died in the NICU, and controls were defined as neonates who survived. Overnight hours were defined as 17:00 to 07:59, and day hours were defined as 08:00 to 16:59. Univariate and multivariate logistic regressions were used to investigate the relationship between time of admission and mortality, along with perinatal characteristics. Results A total of 812 neonates, 207 cases ...
SVOA Paediatrics, 2022
Background: Neonatal period is the most vulnerable time for the survival of newborns. Despite many efforts done to improve the outcome of neonates admitted to hospitals; it doesn't show satisfactory progress. The study aimed to assess the pattern, causes of admission, and factors associated with treatment outcomes. Methods: facility-based cross-sectional study design was conducted among 707 randomly selected neonates from March 1 to 31, 2020. Data were extracted from medical records using a checklist adapted from the national neonatal registration book. The data were inserted into Epi-data version 3.1 and then exported into SPSS window version 22 for analysis. Bivariate and multivariate analyses were done to identify the association between independent variables and the outcome variable. Results: From 698 admitted neonates during the 2 years period, 594 of them were improved and 104 of them were not improved. Neonatal sepsis, hypothermia, and low birth weight were the leading causes of admission to the hospital.
Pediatric Health, Medicine and Therapeutics
Background: Neonatal mortality includes all deaths of neonate occurring before the 28th day of life. Neonatal mortality has been declining over two decades in Sub-Saharan Africa, including Ethiopia. The foremost causes of death are preventable and treatable. Regardless, recognizing the predictors may be a crucial step in lowering neonatal mortality. However, evidences on the survival status of neonates and/or neonatal death predictors were limited in Ethiopia, particularly in the study area. Thus, this study aimed to answer these questions. Methods: An institution-based retrospective cohort study was done among 380 Neonates admitted to the Neonatal Intensive Care Unit at Bombe Primary Hospital from January 1, 2018, to December 31, 2019. Bivariable and multivariable Cox regression analyses were conducted to identify predictors of mortality. Association was summarized using adjusted hazard ratio (AHR), and statistical significances were declared at 95% CI and P-value <0.05. Proportionality assumption was tested by a global test based on Schoenfeld residuals analysis.
Abstract Background: The larger fraction of infant mortality is that of neonatal; and early neonatal death is the most significant contributor of neonatal mortality as a whole. There are various factors which may be associated with early neonatal mortality and they have been the reasons for the wide variation in mortality rates among the health facilities reporting. Objective: This study was made to assess the independent predictors of early neonatal mortality. Methods: From 2001 through 2005, a total of 3789 live born neonates, who were admitted to the neonatal intensive care unit of Tikur Anbessa Hospital, were included in this study. Variables were classified into two: Socio economic/reproductive factors and maternal/newborn factors. Predictors were assessed using a multivariable binary logistic regression. Variables with a p-value of <0.05 were entered into a multivariable logistic model. Results: From the socio-economic/reproductive variables: age less than one day (AOR=2.53...
Background: The first month is the most crucial period for child survival and neonatal mortality continues to remain high with little improvement over the years in Sub-Saharan Africa including Ethiopia. This region shows the least progress to reducing this high mortality rate and it continues to be a significant public health issue. The facilities-based cause and predictors of neonatal death in the neonatal intensive care unit are not well documented in this study setting. Hence, the aim of this study was to determine the cause and predictors of neonatal mortality among infants admitted to the neonatal intensive care units in Eastern Ethiopia. Method: Facilities-based prospective follow-up study was conducted among neonates admitted to the neonatal intensive care units of public hospitals in Eastern Ethiopia from November to December 2018. Data was collected using a pre-tested, structured questionnaire and a follow-up checklist. The main outcomes and cause of death was set by pediat...
Research Square (Research Square), 2020
Background Pediatric intensive care unit (PICU) tremendously improves the success of saving patients having potentially life-threatening illness. An accurate estimate of lives saved through pediatric critical care intervention is important to evaluate the quality of the health care system. Data on pediatric critical care in developing countries remain scarce yet is much needed to improve clinical practices and outcomes. This study aimed to determine the incidence and predictors of mortality in the pediatric intensive care unit in the study setting. Method An institution based prospective cohort study was conducted from February 2018 to July 2019. We collected data by interview, chart and registration book review. Life table was used to estimate the cumulative survival of patients and Log rank test was used to compare survival curves between different categories of the explanatory variables. Survival trend over the follow up time was described using the Kaplan Meier graph. Bivariate and multivariate Cox proportional hazard model were used to identify predictors. Result Based on the 10 th version of international classi cations of disease (ICD) of WHO, neurologic disorders (22.7%) infectious disease (18.8%) and environmental hazards (11.8%) account for the top three diagnoses. The median observation time was 3 days with IQR of 1 to 6 days. Of the total of 313 participants, 102 (32.6%) died during the follow-up time. This gives the incidence of mortality of 6.9 deaths per 100 person day observation. Caregivers' occupation of government-employed (AHR=0.35,