The
blood count is an easily achievable routine exam and will it have specifics in
the event of a neonatal bacterial infection? Hence, the present study with the objective of determining the profile of the
hemogram of newborns hospitalized for early bacterial neonatal infection. Material and methods: This was a cross-sectional study that took place
from June 27 to September 03, 2016 in the
neonatology department of teaching hospital Gabriel Toure. Included were all neonates
hospitalized for early neonatal bacterial infection (ENBI) and who had a blood
count. Results: We included 227 patients,
64.8% of whom were premature. The sex ratio was 1.4. The infants were less than
24 hours old in 93.6% of the cases. The mean hemoglobin level was 16.435 g/dl [8.8 - 22.26]. Erythrocytopenia was found in 18.5% of cases. Anemia was present in 17%
of newborns. The
average leukocyte was 15.228·103/mm3 [1.4 - 72]. Hyperleukocytosis
and leukopenia were found in 12.32% and 6.6% respectively. Neutropenia
and lymphopenia were present in 14.5% and 30.8%. There was a correlation between leukocytosis of
negative blood cultures (23/27) (p = 0.030). For Neutrophils, neutrophilia
was more observed in term neonates and neutropenia in premature infants (p = 0.03). Monocytosis was present in 13.6% of cases. One quarter (25.5%) of newborns had thrombocytopenia. Conclusion: Hematological variations
did not allow a specific profile of newborns hospitalized for early neonatal bacterial infection to be identified.

/pdf/hematological-profile-of-newborns-hospitalized-for-neonatal-3x8wpgu8vu.pdf

Hematological Profile of Newborns Hospitalized for Neonatal Bacterial Infection in the Neonatology of the Pediatric Department of Gabriel Toure Teaching Hospital Bamako, Mali

AI in Pathology: What could possibly go wrong?

: Background : As per World Health Organization (WHO), sepsis is a leading cause of hospitalization and death in children in developing countries.The rapidly changing bacteriologic profile of childhood sepsis warrants the need for an ongoing review of the etiopathogenesis and drug susceptibility pattern of causative agents. Objectives: To find out the etiological profile and antibiotic sensitivity pattern of the pathogens causing pediatric sepsis in a tertiary care teaching hospital of Central India. Materials and Methods : This is a cross-sectional study. 194 clinical samples were collected from inpatients ranging in age from >1 month to 15 years. Isolation and identification of pathogens were done using Standard microbiological techniques. Antimicrobial susceptibility testing was performed by the standard Kirby Bauer disc diffusion method and interpreted as per CLSI guidelines. Results :Out of the total 87 blood culture isolates majority were Gram Positive cocci (70%); with Staphylococcus aureus (53%) being the most predominant organism. The GPC isolates showed high susceptibility towards Vancomycin, Linezolid, Piperacillin tazobactam, and Tetracyclines. Methicillin resistance was reported in 38% of Staphylococcus aureus isolates. 40% of Enterococcus isolates exhibited High-level Aminoglycoside resistance.Enterobacteriaceae isolates exhibited high susceptibility towards Carbapenems, Colistin, Piperacillin tazobactum& Ceftazidime clavulanate. 40% of E.coli isolates & 50% of K.pneumoniae isolates were found to be Extended- spectrum β lactamase ( ESBL) producers. Non-fermenters exhibited high sensitivity towards Meropenem, Colistin, Piperacillin tazobactam, Amikacin. Conclusions : The present study has provided much-needed information on the local antimicrobial profile of the prevailing pathogens causing pediatric sepsis which will be helpful in guiding their management.

Microbiological profile of Pediatric sepsis in a tertiary care teaching hospital of Central India

The aim of the present study was to identify the incidence of sepsis among neonates admitted at Beni-Suef University Hospital during the period of the study, to identify different organisms responsible for sepsis and the serum level of CD14 (presepsin) was investigated as a biomarker of sepsis. All neonates suspected with sepsis during the time of the study admitted in neonatal intensive care unit at Beni-Suef University Hospital were screened for sepsis by blood culture and presepsin levels were investigated. The incidence of sepsis was 32.4%. Presepsin marker had a significant role in prediction of presence of sepsis, at a cut off value of 2300 or more of presepsin, it can predict the presence of sepsis with sensitivity of (94.29%), specificity of (88.6%), positive predictive value (89.2%) and negative predictive value (93.9%)

Evaluation of serum levels of CD14 in neonatal sepsis and its correlation with type of infection in Beni-Suef University Hospital

Background: Neonatal sepsis is a common condition among neonates particularly in developing countries. Treatment of neonatal sepsis is with antibiotics, which have huge benefits when indications are clear. However, widespread utilisation of antibiotics over the years has been reported to favour the emergence of antibiotic resistance. In this study, we aimed at assessing antibiotic resistance and associated factors for neonatal sepsis at a selected children’s hospital in Zambia.
Method: We conducted a retrospective cross-sectional study from January, 2018 to December, 2019. Data was collected from files of all admitted neonates and the microbiology blood culture register. Analysis of factors associated with antibiotic resistance was done by logistic regression using STATA software, version 14 and statistical tests were done using 5% significance level and 95% confidence intervals. 
Results: Out of the 172 blood cultures analysed, 61.0% (105/172) were male admitted with suspected neonatal sepsis. The median age at admission was 4 (2 - 12) days old and 69.8% (120/172) were positive blood cultures. Commonly isolated bacteria causing neonatal sepsis were Enterobacter (29.2%), E. coli (19.2%) and Staphylococcus (13.3%). Resistance of isolated bacteria towards Penicillins ranged from 80% to 100% and to third generation cephalosporins from 50% to 70% and these were the most commonly resistant antibiotics. An increase in the duration of empirical treatment was more likely (AOR= 1.12, CI: 1.01 - 1.23) to be associated with antibiotic resistance for neonatal sepsis and this finding was statistically significant.
Conclusion: Increased duration of empirical treatment in hospital was a positive predictor for antibiotic resistance. Early detection of bacteria causing sepsis and sensitive antibiotics via blood culture and drug sensitivity testing would probably reduce the rate of antibiotic resistance.

/pdf/antibiotic-resistance-and-associated-factors-for-neonatal-3p8r3twkuc.pdf

Antibiotic Resistance and Associated Factors for Neonatal Sepsis at a Selected Children’s Hospital in Zambia

Background: Neonatal sepsis one of the most common cause for neonatal mortality and morbidity in developing countries Group B Streptococci being the most common organism in developed countries, whereas CONS and Gram negative bacteria frequently encountered organisms in developing countries It is advisable to have an individualised institutional protocol based on their own culture reports to reduce the antibiotic resistance  Methods: A prospective observational study was conducted from September 2016- February 2017, at the Department of Paediatrics, SVS Medical College and Hospital, Mahabubnagar, Telangana, India The study included 65 neonates admitted in our NICU A questionnaire was filled by mothers after taking consent Data was Collected data was analysed Results: In present study, we found that CONS were the most commonly isolated organisms followed by Klebsiella  Conclusions: Neonatal sepsis creates a significant burden due to its impact on neonatal mortality and long-term morbidity Following proper hand washing techniques with minimal handling in intensive care units will reduce neonatal sepsis from opportunistic infections

/pdf/clinico-bacteriological-profile-of-neonatal-sepsis-in-rural-1zrpjiss2x.pdf

Clinico-bacteriological profile of neonatal sepsis in rural tertiary care hospital

<h3>Introduction</h3> CT angiography (CTA), the modality of choice for detection of intracranial aneurysms (IA), is widely available at all care levels. Implementing deep learning algorithms (DLA) in the radiologists’ workflow could result in higher detection rates, particularly in smaller centers. We present results of multicenter pre-clinical experience with a new IA detection DLA. <h3>Methods</h3> A DLA was developed at Site 1 to predict the existence and locations of IAs &gt;2 mm in 3D head CTA volumes. It localizes IAs using an improved 3D UNet to regress the bounding boxes of suspicious locations. IA presence is confirmed by a multi-resolution 3D DenseNet at each suspicious location. The model was trained on 436 studies and tested on 696 studies from site 1. To validate robustness against protocol variability, it was retrospectively tested on 337 volumes (149 positives, 188 negatives) from 4 additional sites with various types of scanners. A neuroradiologist/trained fellow from each site annotated bounding boxes around the IAs with 3DSlicer. The model’s performance was assessed by comparing its predicted aneurysm locations to the annotated boxes. <h3>Results</h3> The model achieved a lesion-level sensitivity of 0.72 (95% CI: 0.66 - 0.75) with 1.4 false positives per volume (FPPV, 95% CI: 1.22 - 1.57). Sensitivity ranged 0.84 (1.72 FPPV) - 0.67 (1.40 FPPV) amongst 5 sites. Performance variation was secondary to testing on images from scanners the model had not been trained on (unseen). Removing unseen scanners, the model achieved sensitivity of 0.77 (95% CI: 0.68 - 0.84) with 1.51 FPPV (95% CI: 1.24 - 1.82). Patient-level area under curves (AUCs) on the external sites were comparable to that of site 1 dataset, which was 0.88 (95% CI: 0.84 - 0.92). The model performed better in the detection of internal carotid and anterior communicating artery IAs &gt; 3 mm. <h3>Conclusions</h3> This DLA for IA detection showed robust performance in detecting IAs &gt; 3 mm. DLAs may reliably help detection of IAs on CTA, particularly in the community practices less familiar with intracranial vascular imaging. Different scanners can lead to performance variability. This can be avoided by training with data from different scanners. <h3>Disclosures</h3> <b>D. Wu:</b> 1; C; National Institute of Health. <b>E. Orru’:</b> None. <b>S. Ferraciolli:</b> None. <b>A. Ashok:</b> 1; C; NIHR Academic Clinical Fellowship. <b>A. Sorby-Adams:</b> None. <b>M. Guindy:</b> None. <b>D. Montes:</b> None. <b>A. Medina:</b> None. <b>G. Bianco:</b> None. <b>J. Kaggie:</b> 1; C; NIHR Cambridge BRC. <b>D. Rabina:</b> None. <b>O. Ashush:</b> None. <b>X. Han:</b> None. <b>Y. Baror:</b> None. <b>M. Patel:</b> 4; C; Rhino HealthTech Inc. <b>I. Dayan:</b> 4; C; Rhino HealthTech Inc.. <b>J. Romero:</b> None. <b>R. González:</b> 1; C; National Institute of Health. 2; C; MR Access, Inc.. 4; C; MR Access, Inc.. <b>C. Wald:</b> None. <b>F. Kitamura:</b> 2; C; MD.ai, GE Healthcare. <b>P. Kuriki:</b> None. <b>T. Matys:</b> 1; C; NIHR Cambridge BRC. 2; C; NHS. <b>Q. Li:</b> 1; C; National Institute of Health. 

/pdf/e-107-multi-center-study-of-a-deep-learning-model-for-eqbin8mv.pdf

E-107 Multi-center study of a deep learning model for intracranial aneurysm detection in computed tomography angiography

Background: COVID-19 infection adversely affects all nephron segments to cause acute kidney injury (AKI), leading to greater mortality. Methods: A retrospective analysis was conducted of patients (age >18 years) with COVID-19-related AKI admitted at a quaternary-level multispeciality hospital between September 2020 and April 2021. Data regarding various clinical, radiological, biochemical and haematological parameters were analysed and their association with clinical outcomes concerning mortality or survival was determined. Results: We included 67 patients (46 males) with a mean age of 68.2 ± 12.17 years, of whom 45 patients were haemodynamically unstable, and 52 had hypoxaemia at the time of presentation. Overall, 53% of the cases were discharged from the hospital and 46% succumbed to the illness; females had higher mortality (67%, P = 0.024). The mean neutrophil/lymphocyte ratio (P = 0.014), HbA1c (P = 0.011), LDH (P = 0.002), D-dimer (P = 0.034) and C-reactive protein (P = 0.001) levels at admission were higher in patients with unfavourable outcomes. Increased mortality was present in patients who had a higher clinical category of illness (P = 0.014), advanced AKI stage (P = 0.001), haemodynamic instability at presentation (P < 0.001), required some form of KRT (P = 0.009), oxygen (P = 0.047), ventilatory (P = 0.028) or inotropic support (P = <0.001), were on calcium channel blockers at the time of admission (P = 0.024) or required antifungal agents (P = 0.003) or insulin therapy (P = 0.041). Conclusions: Female COVID-19 patients with AKI, presenting with advanced disease and chest pain, having preexisting comorbidities, had increased mortality. Keywords: COVID-19, acute kidney injury, Severe Acute Respiratory Syndrome, coronavirus

A. Ashok

Papers

Clinico-bacteriological profile of neonatal sepsis in rural tertiary care hospital

E-107 Multi-center study of a deep learning model for intracranial aneurysm detection in computed tomography angiography

Factors associated with unfavourable outcomes in COVID-19 patients with acute kidney injury: A single centre retrospective observational study