Early Detection of Sepsis and NEC Using Serial Vital Sign Trends (HR, SpO₂, RR) on Standard NICU Monitors in Preterm Neonates
Sepsis and NEC Using Serial Vital Sign Trends on Standard NICU Monitors
DOI:
https://doi.org/10.54393/pjhs.v6i8.3470Keywords:
Preterm Neonates, Neonatal Sepsis, Necrotizing Enterocolitis, Vital Signs, Heart Rate, Respiratory Rate, Oxygen Saturation, NICU Monitoring, Early DetectionAbstract
Preterm neonates are at high risk for sepsis and necrotizing enterocolitis (NEC), but early signs are often subtle, delaying diagnosis and worsening outcomes. Objectives: To evaluate whether trends in routinely monitored heart rate (HR), respiratory rate (RR), and oxygen saturation (SpO₂) predict sepsis and NEC and to examine their association with NICU stay, mortality, and discharge outcomes. Methods: A prospective observational cohort study was conducted among 103 preterm infants (<37 weeks’ gestation) admitted to a tertiary NICU with continuous multi-parameter monitoring. HR, RR, and SpO₂ trends were compared between infants with sepsis/NEC and those who remained stable. Outcomes were analyzed using t-tests, Mann–Whitney U tests, Chi-square tests, and logistic regression. Cox regression identified mortality predictors, and Kaplan–Meier curves compared survival between groups. Results: Sepsis occurred in 22.3% and NEC in 7.8% of neonates. Female infants had lower odds of sepsis/NEC (adjusted OR = 0.23, 95% CI: 0.07–0.74, p=0.013). Sepsis/NEC was linked to longer NICU stay (21.6 ± 6.8 vs 11.9 ± 4.4 days, p<0.001) and higher mortality (30.4% vs 10.0%, p=0.014). Cox regression confirmed sepsis/NEC as an independent predictor of mortality (HR = 0.084, p=0.005). Conclusions: Routine vital sign trends alone were insufficient for early detection, but their association with adverse outcomes underscores the potential of enhanced monitoring and predictive modeling to enable earlier recognition and improved survival.
References
Kariniotaki C, Thomou C, Gkentzi D, Panteris E, Dimitriou G, Hatzidaki E. Neonatal Sepsis: A Comprehensive Review. Antibiotics. 2024 Dec; 14(1): 6. doi: 10.3390/antibiotics14010006. DOI: https://doi.org/10.3390/antibiotics14010006
Saleem S, Tikmani SS, Goudar SS, Hwang K, Dhaded S, Guruprasad G et al. Neonatal Mortality Among Preterm Infants Admitted to Neonatal Intensive Care Units in India and Pakistan: A Prospective Study. BJOG: An International Journal of Obstetrics and Gynaecology. 2023 Nov; 130: 68-75. doi: 10.1111/1471-0528.17581. DOI: https://doi.org/10.1111/1471-0528.17581
Oliveira SR, Lopes C, Basilio AB. Early Onset Sepsis: Clinical Observation or Risk Factors Approach? Journal de Pediatria. 2025 May; 101(3): 375-80. doi: 10.1016/j.jped.2024.10.007. DOI: https://doi.org/10.1016/j.jped.2024.10.007
Ofek Shlomai N, Tayeb M, Abu Omar R, Eventov Friedman S. Changes in the Incidence and Severity of NEC Over the Last Decade: A Single-Center Study. Journal of Clinical Medicine. 2025 May; 14(10): 3551. doi: 10.3390/jcm14103551. DOI: https://doi.org/10.3390/jcm14103551
Mithal LB, Becker ME, Ling-Hu T, Goo YA, Otero S, Kremer A et al. Cord Blood Proteomics Identifies Biomarkers of Early-Onset Neonatal Sepsis. Journal of Clinical Investigation Insight. 2025 Jun. doi: 10.1172/jci.insight.193826. DOI: https://doi.org/10.1172/jci.insight.193826
Raturi A and Chandran S. Neonatal Sepsis: Aetiology, Pathophysiology, Diagnostic Advances and Management Strategies. Clinical Medicine Insights: Pediatrics. 2024 Sep; 18: 11795565241281337. doi: 10.1177/11795565241281337. DOI: https://doi.org/10.1177/11795565241281337
Kurul S, Fiebig K, Flint RB, Reiss IK, Küster H, Simons SH et al. Knowledge Gaps in Late-Onset Neonatal Sepsis in Preterm Neonates: A Roadmap for Future Research. Pediatric Research. 2022 Jan; 91(2): 368-79. doi: 10.1038/s41390-021-01721-1. DOI: https://doi.org/10.1038/s41390-021-01721-1
Stocker M, Fillistorf L, Carra G, Giannoni E. Early Detection of Neonatal Sepsis and Reduction of Overall Antibiotic Exposure: Towards Precision Medicine. Archives de Pédiatrie. 2024 Nov; 31(8): 480-3. doi: 10.1016/j.arcped.2024.10.003. DOI: https://doi.org/10.1016/j.arcped.2024.10.003
Oladokun RE, Alao MA, Ogunbosi BO, Bello OE, Ude I, Obasi A et al. Trends in Identification, Etiology, and Resistance Profiles of Bacterial Isolates and Appropriate Therapy for Neonatal Sepsis in Low-and Middle-Income Countries: A Narrative Review. Current Pediatrics Reports. 2023 Dec; 11(4): 214-21. doi: 10.1007/s40124-023-00297-0. DOI: https://doi.org/10.1007/s40124-023-00297-0
Feng B, Zhang Z, Wei Q, Mo Y, Luo M, Jing L et al. A Prediction Model for Neonatal Necrotizing Enterocolitis in Preterm and Very Low Birth Weight Infants. Frontiers in Pediatrics. 2023 Oct; 11: 1242978. doi: 10.3389/fped.2023.1242978. DOI: https://doi.org/10.3389/fped.2023.1242978
Sullivan BA and Fairchild KD. Vital Signs as Physiomarkers of Neonatal Sepsis. Pediatric Research. 2022 Jan; 91(2): 273-82. doi: 10.1038/s41390-021-01709-x. DOI: https://doi.org/10.1038/s41390-021-01709-x
Honoré A, Forsberg D, Adolphson K, Chatterjee S, Jost K, Herlenius E. Vital Sign‐Based Detection of Sepsis in Neonates Using Machine Learning. Acta Paediatrica. 2023 Apr; 112(4): 686-96. doi: 10.1111/apa.16660. DOI: https://doi.org/10.1111/apa.16660
Garstman AG, Rodriguez Rivero C, Onland W. Early Detection of Late Onset Sepsis in Extremely Preterm Infants Using Machine Learning: Towards an Early Warning System. Applied Sciences. 2023 Aug; 13(16): 9049. doi: 10.3390/app13169049. DOI: https://doi.org/10.3390/app13169049
Verhoeven R, Kupers T, Brunsch CL, Hulscher JB, Kooi EM. Using Vital Signs for the Early Prediction of Necrotizing Enterocolitis in Preterm Neonates with Machine Learning. Children. 2024 Nov; 11(12): 1452. doi: 10.3390/children11121452. DOI: https://doi.org/10.3390/children11121452
Yang Y, Zhou S, Liu X, Zhang Y, Lin L, Zheng C, Zhong X. Ultrasound Combined with Serological Markers for Predicting Neonatal Necrotizing Enterocolitis: A Machine Learning Approach. Frontiers in Pediatrics. 2025 Jul; 13: 1606571. doi: 10.3389/fped.2025.1606571. DOI: https://doi.org/10.3389/fped.2025.1606571
Narasimha Rao KV, Dadabada PK, Jaipuria S. A Systematic Literature Review of Predictive Analytics Methods for Early Diagnosis of Neonatal Sepsis. Discover Public Health. 2024 Sep; 21(1): 96. doi: 10.1186/s12982-024-00219-5. DOI: https://doi.org/10.1186/s12982-024-00219-5
Rahman J, Brankovic A, Tracy M, Khanna S. Exploring Computational Techniques in Preprocessing Neonatal Physiological Signals for Detecting Adverse Outcomes: Scoping Review. Interactive Journal of Medical Research. 2024 Aug; 13(1): e46946. doi: 10.2196/46946. DOI: https://doi.org/10.2196/46946
Williams E, Ascherl R, Gaertner VD, Sibrecht G, Kurul S, Herrmann ML et al. Future Perspectives of Heart Rate and Oxygenation Monitoring in the Neonatal Intensive Care Unit–A Narrative Review. Journal of Clinical Monitoring and Computing. 2025 Jun: 1-5. doi: 10.1007/s10877-025-01310-1. DOI: https://doi.org/10.1007/s10877-025-01310-1
Krbec BA, Zhang X, Chityat I, Brady-Mine A, Linton E, Copeland D et al. Emerging Innovations in Neonatal Monitoring: A Comprehensive Review of Progress and Potential for Non-Contact Technologies. Frontiers in Pediatrics. 2024 Oct; 12: 1442753. doi: 10.3389/fped.2024.1442753. DOI: https://doi.org/10.3389/fped.2024.1442753
Sullivan BA and Fairchild KD. Heart Rate Analysis in Neonatal Sepsis: A Complex Equation. Pediatric Research. 2025 Jan; 97(1): 35-7. doi: 10.1038/s41390-024-03548-y. DOI: https://doi.org/10.1038/s41390-024-03548-y
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Pakistan Journal of Health Sciences

This work is licensed under a Creative Commons Attribution 4.0 International License.
This is an open-access journal and all the published articles / items are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For comments




