Background: Early onset neonatal sepsis (EOS) is a public health problem; antibiotic treatment is often unnecessary and can increase morbimortality. EOS risk calculator are available that allows limiting the use of antibiotics.
Objective: To compare the patterns of antibiotic use and hospitalization time in infant newborns (NB) ≥ 34 weeks of gestational age (GA) in a historical cohort attended from November 2017 to April 2018 vs. a prospective cohort from November 2018 to April 2019, before and after implementing the use of an EOS risk calculator, respectively.
Material And Methods: Ambispective, observational, longitudinal, analytical study in infants NB ≥ 34 GA attended before and after implementing the use of an EOS risk calculator. The patterns of antibiotic´s use were compared. Simple frequencies and proportions, means and standard deviations or medians with ranges, Mann-Whitney U Test and Chi square test with SPSS V. 20.0 statistical package were used; considering significant values of p < 0.05.
Results: Thirty patients were included, 15 NB for each period, the gestational age average was 36.8 ± 2.3 GA. there was no statistically significant difference in the frequency of diagnosis of EOS with blood culture or days of hospital stay. Antibiotics were beginning in all the infants attended before the implementation of the EOS risk calculator, unlike 46.7% of the infants after its implementation (p = 0.001).
Conclusions: The EOS risk calculator is an easy tool to use, and demonstrated to be useful in decreasing unnecessary use of antibiotics.
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Sci Rep
January 2025
Department of Orthopedic Surgery, Beijing Chao-Yang Hospital, Capital Medical University, GongTiNanLu 8#, Chaoyang District, Beijing, 100020, China.
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Department of Allergy and Clinical Immunology, Department of Respiratory and Critical Care Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China; Guangzhou National Laboratory, Guangzhou, Guangdong, China. Electronic address:
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Department of Botany and Microbiology, College of Science, King Saud University, P.O. Box.2455, Riyadh, 11451, Saudi Arabia.
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Honeybee Research Institute, Jiangxi Agricultural University, Nanchang 330045, China.
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