The biological plausibility of this signature of neonatal sepsis was justified in the similar signature of fetal distress established by obstetric practices in fetal heart rate monitoring37. Thus, the group developed mathematical algorithms to detect these visually-recognized patterns in the heart rate time series and used multivariable logistic regression modeling to translate those patterns into the risk of imminent sepsis.

One of these infants has clinical deterioration requiring intubation the next day, at which point antibiotics are started. An artificial intelligence (AI) system for early detection of neonatal sepsis has been implemented in a level IV NICU. An automated algorithm incorporates analysis of heart ...

August 1, 2024 - Diagnosing early-onset neonatal sepsis in low-resource settings: development of a multivariable prediction model.

Neonatal complications such as NEC(27) and bronchopulmonary dysplasia (BPD)(28) were identified according to parent study protocol and widely used benchmarks. Specifically, an episode of NEC was defined as clinical and radiographic evidence of NEC (pneumatosis intestinalis) treated with antibiotics and bowel rest. Based on NICHD definitions for premature infants, episodes of culture-proven sepsis occurring <72 hours of life were considered early onset and excluded from analysis.

October 31, 2024 - LB Mithal, R Yogev, HL Palac, D Kaminsky, I Gur, KK. Mestan · Vital signs analysis algorithm detects inflammatory response in premature infants with late onset sepsis and necrotizing enterocolitis

November 27, 2024 - Recognizing sepsis early in critically ill infants continues to be a significant challenge in neonatology. Physiologic markers such as the heart rate characteristic, combined with better understanding of baseline risks, and increasingly sophisticated ML approaches have yielded increasingly accurate algorithms to support sepsis recognition efforts.

Twenty-five maternal and neonatal ... morbidity, Catheter, and Mechanical ventilation) were used to for the learning procedure with the Levenberg-Marquardt optimization algorithm and sepsis estimation as the output of the model....

September 8, 2026 - Real-time predictive analytics represents one of the most promising applications of AI in neonatal care. Unlike conventional diagnostic approaches based on intermittent clinical assessment, AI-driven early warning systems can continuously process streaming physiological data and dynamically update sepsis risk as new information becomes available [18]. Such systems may support clinicians by identifying early signs of deterioration [8], while recent work has increasingly focused on translating predictive algorithms into clinical decision support systems for late-onset sepsis and other critical neonatal conditions [34].

January 7, 2025 - This study proposes a machine learning algorithm utilizing electronic medical record (EMR) data from Mbarara Regional Referral Hospital (MRRH) to enhance early detection and treatment of neonatal sepsis.

July 24, 2020 - Twenty-five maternal and neonatal ... Mechanical ventilation) were used to for the learning procedure with the Levenberg-Marquardt optimization algorithm and sepsis estimation as the output of the model....

September 12, 2021 - Nearest-neighbor and logistic regression analyses of clinical and heart rate characteristics in the early diagnosis of neonatal sepsis. Med Decis Making. 2010; 30(2): 258-266. ... 37Zimmet AM, Sullivan BA, Moorman JR, Lake DE, Ratcliffe SJ. Trajectories of the heart rate characteristics index, a physiomarker of sepsis in premature infants, predict Neonatal ICU mortality.

Time-domain features from heart rate, respiratory rate and oxygen saturation values were calculated and demographic factors included. Sepsis prediction was performed using Naïve Bayes algorithm in a maximum a posteriori framework up to 24 h ...

July 4, 2024 - It does not utilize deep learning techniques like Convolutional Neural Networks (CNNs). In our research, we assessed the effectiveness of the custom machine learning algorithm in identifying neonatal sepsis using important metrics such as accuracy, specificity, sensitivity, and precision.

October 29, 2021 - In the article, “Vital signs as physiomarkers of neonatal sepsis” by Sullivan and Fairchild,4 the authors have reviewed “signature” patterned pathophysiologic changes in heart rate, respiration, and oxygen saturation (SpO2) that occur with neonatal sepsis. The authors make a strong argument to integrate and utilize highly advanced real-time bioengineering/computational tools that read and incorporate the routine bedside vital signs into machine learning models. The advanced analytics and the predictive algorithm that is derived from continuous vital sign monitoring data can further assist clinicians with early recognition of sepsis, especially in intensive care units (ICUs).

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3 weeks ago - In NICUs, researchers have developed machine learning models that combine continuously monitored data, including heart rate and oxygen saturation, to identify infants at increased risk of sepsis before clinical signs appear.

However, early onset neonatal sepsis/meningitis or pneumonia has been found to occur in only about 1 baby per 100 colonized mothers. Following is the algorithm used at UTMB for prevention of EOS in babies born to mothers with chorioamnionitis or colonized with GBS.

Key risk factors strongly associated with neonatal sepsis, including low birth weight, prematurity, perinatal history, premature rupture of membranes (PROM), C-reactive protein (CRP), procalcitonin (PCT), white blood cell count (WBC), platelet count (PLT), and respiratory or circulatory difficulties, are commonly included in these studies.

January 23, 2018 - The early localized bowel inflammation, bacterial penetration, and tissue destruction is often difficult to identify until signs of abdominal distension, bloody stool, bowel perforation, or clinical deterioration appear, often accompanied by sepsis [15]. Thus, development of more reliable and specific methods to predict and exclude LOS and/or NEC in preterm infants is essential to improve neonatal outcomes.