Analysis on the Health of Newborns in Three Hospitals, 2008-2024

Overview

The objective of this observational study is to analyze the factors associated with neonatal morbidity and mortality in three hospitals in Quito, Ecuador, from January 2022 to December 2023. The primary question to be addressed is: What perinatal factors are associated with neonatal morbidity and mortality in neonates admitted to HGOIA, HGDC, and HGONA hospitals? The participants will be neonates whose complete medical records are registered in the Perinatal Information System (SIP) and the Maternal-Perinatal Clinical Record (HCMP) databases during the study period. Data will be retrospectively collected from the mentioned databases, evaluating variables such as birth weight, gestational age, congenital anomalies, neonatal complications, and maternal factors such as age and medical conditions. The analysis will include prevalence calculations, variable associations through logistic regression, and the development of neonatal growth curves. Statistical software such as R will be used for data analysis, and the results will be compared to national and international standards.

Detailed Description of the Study This retrospective observational study aims to analyze the factors associated with neonatal morbidity and mortality in three hospitals in Quito, Ecuador: the Hospital Gineco Obstétrico Isidro Ayora (HGOIA), the Hospital General Docente de Calderón (HGDC), and the Hospital Gineco Obstétrico Pediátrico de Nueva Aurora Luz Elena Arismendi (HGONA). The study spans the period from January 2022 to December 2023 and utilizes secondary data obtained from the Perinatal Information System (SIP) and the Maternal-Perinatal Clinical Record (HCMP). Background and Rationale: The analysis of perinatal factors related to neonatal morbidity and mortality is crucial to improving neonatal care standards and reducing mortality rates. According to the Ecuadorian Ministry of Public Health, the main causes of neonatal mortality in 2020 included prematurity, respiratory distress syndrome, and congenital anomalies, among others. This study seeks to identify and quantify risk and protective factors in the neonatal population admitted to the three mentioned hospitals, enabling the design of more effective interventions. Methodology: A cross-sectional design with retrospective data collection will be utilized. The study participants will include all neonates recorded in the SIP and HCMP databases during the specified period. Data will encompass perinatal variables such as birth weight, gestational age, congenital anomalies, neonatal complications, and maternal conditions (e.g., age, comorbidities). Procedures: Data Collection: Extraction of relevant information from the SIP and HCMP databases. Identification and removal of duplicate or incomplete records. Organization of variables using an operationalization chart detailing dimensions, indicators, and measurement scales. Statistical Analysis: Bivariate and multivariate analyses will be conducted using logistic regression models to evaluate associations between variables. Odds ratios (OR) with 95% confidence intervals will be calculated. Neonatal growth curves stratified by sex and gestational age will be generated. R software will be used for all statistical analyses. Expected Outcomes: Identification of risk and protective factors associated with neonatal morbidity and mortality. Characterization of intrauterine growth disorders, prematurity complications, and congenital anomalies in the studied population. Comparison of indicators across the three hospitals to identify significant differences and design improvement strategies. Limitations: Potential biases are anticipated, including errors in clinical record documentation and incomplete data. These limitations will be addressed through thorough data cleaning and exclusion of inconsistent records. Expected Impact: The findings will contribute to the development of evidence-based neonatal clinical care protocols and guidelines, aiming to reduce morbidity and mortality rates in participating hospitals and serve as a model for other institutions in the country.