Objective: To develop models and a graphical tool for predicting survival to discharge without major morbidity for infants with a gestational age (GA) at birth of 22-32 weeks using infant information at birth.
Design: Retrospective cohort study.
Setting: Canadian Neonatal Network data for 2003-2008 were utilised.
Patients: Neonates born between 22 and 32 weeks gestation admitted to neonatal intensive care units in Canada.
Main Outcome Measure: Survival to discharge without major morbidity defined as survival without severe neurological injury (intraventricular haemorrhage grade 3 or 4 or periventricular leukomalacia), severe retinopathy (stage 3 or higher), necrotising enterocolitis (stage 2 or 3) or chronic lung disease.
Results: Of the 17 148 neonates who met the eligibility criteria, 65% survived without major morbidity. Sex and GA at birth were significant predictors. Birth weight (BW) had a significant but non-linear effect on survival without major morbidity. Although maternal information characteristics such as steroid use, improved the prediction of survival without major morbidity, sex, GA at birth and BW for GA predicted survival without major morbidity almost as accurately (area under the curve: 0.84). The graphical tool based on the models showed how the GA and BW for GA interact, to enable prediction of outcomes especially for small and large for GA infants.
Conclusion: This graphical tool provides an improved and easily interpretable method to predict survival without major morbidity for very preterm infants at the time of birth. These curves are especially useful for small and large for GA infants.
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http://dx.doi.org/10.1136/archdischild-2011-300143 | DOI Listing |
JMIR Public Health Surveill
January 2025
School of Public Health, National Defense Medical Center, Taipei City, Taiwan.
Background: Japanese encephalitis (JE) is a zoonotic parasitic disease caused by the Japanese encephalitis virus (JEV), and may cause fever, nausea, headache, or meningitis. It is currently unclear whether the epidemiological characteristics of the JEV have been affected by the extreme climatic conditions that have been observed in recent years.
Objective: This study aimed to examine the epidemiological characteristics, trends, and potential risk factors of JE in Taiwan from 2008 to 2020.
J Occup Med Toxicol
January 2025
Indian Council of Medical Research-National Institute for Implementation Research on Non-Communicable Diseases, Jodhpur, 342005, India.
Background: Silicosis remains a major occupational health challenge in India. This review systematically examines the prevalence, risk factors, regional differences, and diagnostic tools specific to India's high-risk industries. Additionally, it assesses policy gaps and offers insights from diverse clinical and qualitative studies, aiming to inform targeted public health interventions and support the development of effective occupational health policies.
View Article and Find Full Text PDFCrit Care
January 2025
Department of Intensive Care Unit, The First Hospital of China Medical University, Shenyang, China.
Background: The role that sleep patterns play in sepsis risk remains poorly understood.
Objectives: The objective was to evaluate the association between various sleep behaviours and the incidence of sepsis.
Methods: In this prospective cohort study, we analysed data from the UK Biobank (UKB).
BMC Public Health
January 2025
Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Background: Non-communicable diseases (NCDs) have become a major public health concern in Iraq, playing a significant role in the country's morbidity and mortality rates. To offer a thorough overview of the patterns and the overall impact of NCDs on public health, this study aims to map the trends in the incidence, prevalence, and mortality rates of NCDs in Iraq between 2003 and 2021.
Methods: Data from the Global Burden of Disease (GBD) Study 2021 were utilized.
BMC Infect Dis
January 2025
Department of Respiratory Medicine, Anting Hospital of Jiading District, 1060 Hejing Road, Anting Town, Jiading District, Shanghai, 201805, China.
Background: Respiratory tract infections (RTIs) are one of the leading causes of morbidity and mortality worldwide. The increase in antimicrobial resistance in respiratory pathogens poses a major challenge to the effective management of these infections.
Objective: To investigate the distribution of major pathogens of RTIs and their antimicrobial resistance patterns in a tertiary care hospital and to develop a mathematical model to explore the relationship between pathogen distribution and antimicrobial resistance.
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