scholarly journals Clinical features and prognostic factors of early-onset sepsis: a 7.5-year experience in one neonatal intensive care unit

2019 ◽  
Vol 62 (1) ◽  
pp. 36-41
Author(s):  
Se Jin Kim ◽  
Ga Eun Kim ◽  
Jae Hyun Park ◽  
Sang Lak Lee ◽  
Chun Soo Kim
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Prognostic Factors ◽  
Neonatal Intensive Care Unit ◽  
Clinical Features ◽  
Early Onset ◽  
Neonatal Intensive Care ◽  
Early Onset Sepsis

scholarly journals Comparision of Clinical and Laboratory Parameters in Culture Proven and Unproven Early Onset Sepsis in NICU

2015 ◽  
Vol 11 (4) ◽  
pp. 310-314 ◽  
Author(s):  
S Shrestha ◽  
S Dhongol Singh ◽  
NC Shrestha ◽  
RPB Shrestha ◽  
SK Madhup
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Blood Culture ◽  
Laboratory Test ◽  
Neonatal Intensive Care Unit ◽  
Early Onset ◽  
Neonatal Intensive Care ◽  
Study Groups ◽  
Early Onset Sepsis ◽  
Culture Positive

Backgroud Early onset sepsis remains a major cause for neonatal morbidity and mortality.Objectives The aim of this study was to describe and compare the clinical and laboratory characteristics of neonates in neonatal intensive care unit with culture positive and negative early onset sepsis and verify if there were any differences between the groups.Methods A one year comparative prospective study was conducted from January 2011 to January 2012 in neonatal intensive care unit (NICU), Dhulikhel Hospital, Kathmandu University Hospital (KUH).Results Out of 215 cases of suspected neonatal sepsis, 192 (89.30%) cases of early onset sepsis were admitted in neonatal intensive care unit. Out of which 82 cases (42.7%) had blood culture positive and 110( 57.3%) had culture negative but compatible with features of clinical sepsis. There were no cases of culture proven meningitis and urinary tract infections.The clinical characteristic did not show any statistical differences between the study groups except for seizure which was found to be high in culture positive cases (p= 0.041). The hospital stay in neonatal intensive care unit was significantly longer (p=0.02) in culture positive cases. As for the laboratory test there were no differences found between the two study groups except cases of meningitis was more in culture proven early onset sepsis (p=0.00). The overall mortality in early onset sepsis was 36.95%. The higher mortality of 64.7% was seen in culture positive cases but statistically not significant.Conclusion Clinical manifestation and laboratory test were insufficient to distinguish between neonatal infection with blood culture positive and negative sepsis, hence both culture positive and negative cases should be treated promptly and equally.Kathmandu Univ Med J 2013; 11(4): 310-314

scholarly journals Machine Learning Approaches to Predict In-Hospital Mortality among Neonates with Clinically Suspected Sepsis in the Neonatal Intensive Care Unit

2021 ◽  
Vol 11 (8) ◽  
pp. 695
Author(s):  
Jen-Fu Hsu ◽  
Ying-Feng Chang ◽  
Hui-Jun Cheng ◽  
Chi Yang ◽  
Chun-Yuan Lin ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Neonatal Intensive Care Unit ◽  
Clinical Features ◽  
Neonatal Intensive Care ◽  
Learning Approaches ◽  
Suspected Sepsis ◽  
Test Sets

Background: preterm and critically ill neonates often experience clinically suspected sepsis during their prolonged hospitalization in the neonatal intensive care unit (NICU), which can be the initial sign of final adverse outcomes. Therefore, we aimed to utilize machine learning approaches to predict neonatal in-hospital mortality through data-driven learning. Methods: a total of 1095 neonates who experienced clinically suspected sepsis in a tertiary-level NICU in Taiwan between August 2017 and July 2020 were enrolled. Clinically suspected sepsis was defined based on clinical features and laboratory criteria and the administration of empiric antibiotics by clinicians. The variables used for analysis included patient demographics, clinical features, laboratory data, and medications. The machine learning methods used included deep neural network (DNN), k-nearest neighbors, support vector machine, random forest, and extreme gradient boost. The performance of these models was evaluated using the area under the receiver operating characteristic curve (AUC). Results: the final in-hospital mortality of this cohort was 8.2% (90 neonates died). A total of 765 (69.8%) and 330 (30.2%) patients were randomly assigned to the training and test sets, respectively. Regarding the efficacy of the single model that most accurately predicted the outcome, DNN exhibited the greatest AUC (0.923, 95% confidence interval [CI] 0.953–0.893) and the best accuracy (95.64%, 95% CI 96.76–94.52%), Cohen’s kappa coefficient value (0.74, 95% CI 0.79–0.69) and Matthews correlation coefficient value (0.75, 95% CI 0.80–0.70). The top three most influential variables in the DNN importance matrix plot were the requirement of ventilator support at the onset of suspected sepsis, the feeding conditions, and intravascular volume expansion. The model performance was indistinguishable between the training and test sets. Conclusions: the DNN model was successfully established to predict in-hospital mortality in neonates with clinically suspected sepsis, and the machine learning algorithm is applicable for clinicians to gain insights and have better communication with families in advance.

scholarly journals Sepsis profile and outcome of preterm neonates admitted to neonatal intensive care unit of Cairo University Hospital

2021 ◽  
Vol 69 (1) ◽  
Author(s):  
Khaled Salama ◽  
Amira Gad ◽  
Sarah El Tatawy
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Neonatal Intensive Care Unit ◽  
Neonatal Sepsis ◽  
Scoring System ◽  
Neonatal Intensive Care ◽  
Late Onset ◽  
University Hospital ◽  
Preterm Neonates ◽  
Early Onset Sepsis

Abstract Background This study demonstrates the experience of the neonatal intensive care unit (NICU) of a tertiary referral center in Egypt in management of prematures with neonatal sepsis. This retrospective study included preterm neonates admitted to NICU with clinical and/or laboratory diagnosis of sepsis. Blood culture was done followed by antimicrobial susceptibility testing for positive cases. Neonates with sepsis were classified into early onset sepsis (EOS) and late onset sepsis (LOS). Hematological scoring system (HSS) for detection of sepsis was calculated. Results The study included 153 cases of neonatal sepsis; 63 (41.2%) EOS and 90 (58.8%) LOS. The majority of the neonates had very low or moderately low birth weight (90.9%). All neonates received first-line antibiotics in the form of ampicillin-sulbactam, and gentamicin. Second-line antibiotics were administered to 133 neonates (86.9%) as vancomycin and imipenem-cilastatin. Mortalities were more common among EOS group (p < 0.017). Positive blood cultures were detected in 61 neonates (39.8%) with a total number of 66 cultures. The most commonly encountered organisms were Klebsiella MDR and CoNS (31.8% each). Klebsiella MDR was the most predominant organism in EOS (28.9%), while CoNS was the most predominant in LOS (39.2%) The detected organisms were divided into 3 families; Enterobacteriaceae, non-fermenters, and Gram-positive family. There 3 families were 100% resistant to ampicillin. The highest sensitivity in Enterobacteriaceae and Non-fermenters was for colistin and polymyxin-B. An HSS of 3–8 had a sensitivity and specificity of 62.3% and 57.6%, respectively for diagnosis of culture-proven sepsis. Conclusion Neonatal sepsis was encountered in 21.5% of admitted preterm neonates; LOS was more common (58.8%). Mortality was 51.6%. Klebsiella MDR and CoNS were the most commonly encountered organisms in both EOS and LOS. The isolated families were 100% resistant to ampicillin. The hematological scoring system (HSS) showed limited sensitivity for detection of sepsis.

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