Improving management of neonatal infections

Metagenomic Next-Generation Sequencing for the Diagnosis of Neonatal Infectious Diseases

Infectious diseases pose a fatal risk to neonates. Timely and accurate pathogen detection is crucial for proper clinical diagnosis and therapeutic strategies. Limited sample volumes from neonatal patients seriously hindered the accurate detection of pathogens. Here, we unravel that metagenomic next-generation sequencing (mNGS) of cell-free DNA (cfDNA) and RNA can achieve unbiased detection of trace pathogens from different kinds of body fluid samples and blood samples. We enrolled 168 neonatal patients with suspected infections from whom blood samples (n = 153), cerebrospinal fluid samples (n = 127), and respiratory tract samples (RTSs) (including bronchoalveolar lavage fluids, sputa, and respiratory secretions) (n = 51) were collected and analyzed using mNGS. High rates of positivity (70.2%; 118/168) of mNGS were observed, and the coincidence rate against the final clinical diagnosis in positive mNGS cases reached 68.6% (81/118). The most common causative pathogens were Klebsiella pneumoniae (n = 12), Escherichia coli (n = 12), and Streptococcus pneumoniae (n = 8). mNGS using cfDNA and RNA can identify microbes that cannot be detected by conventional methods in different body fluid and blood samples, and more than 50% of these microbes were identified as causative pathogens. Further local polynomial regression fitting analysis revealed that the best timing for mNGS detection ranged from 1 to 3 days after the start of continuous antimicrobial therapy. Diagnosed and guided by mNGS results, the therapeutic regimens for 86 out of 117 neonatal patients were changed, most of whom (80/86) completely recovered and were discharged, while 44 out of 86 patients completely or partially stopped unnecessary medication. Our findings highlight the importance of mNGS in detecting causative DNA and RNA pathogens in infected neonatal patients. IMPORTANCE To the best of our knowledge, this is the first report on evaluating the performance of mNGS using cfDNA and RNA from body fluid and blood samples for diagnosing neonatal infections. mNGS of RNA and cfDNA can achieve the unbiased detection and identification of trace pathogens from different kinds of neonatal body fluid and blood samples with a high total coincidence rate (226/331; 68.3%) against final clinical diagnoses by sample. The best timing for mNGS detection in neonatal infections ranged from 1 to 3 days, rather than 0 days, after the start of continuous antimicrobial therapy. Our findings highlight the importance of mNGS in detecting causative DNA and RNA pathogens, and the extensive application of mNGS for the diagnosis of neonatal infections can be expected.

Clinical and laboratory factors associated with neonatal sepsis mortality at a major Vietnamese children's hospital

Sepsis is a major cause of neonatal mortality and children born in low- and middle-income countries (LMICs) are at greater risk of severe neonatal infections than those in higher-income countries. Despite this disparity, there are limited contemporaneous data linking the clinical features of neonatal sepsis with outcome in LMICs. Here, we aimed to identify factors associated with mortality from neonatal sepsis in Vietnam. We conducted a prospective, observational study to describe the clinical features, laboratory characteristics, and mortality rate of neonatal sepsis at a major children's hospital in Ho Chi Minh City. All in-patient neonates clinically diagnosed with probable or culture-confirmed sepsis meeting inclusion criteria from January 2017 to June 2018 were enrolled. We performed univariable analysis and logistic regression to identify factors independently associated with mortality. 524 neonates were recruited. Most cases were defined as late-onset neonatal sepsis and were hospital-acquired (91.4% and 73.3%, respectively). The median (IQR) duration of hospital stay was 23 (13-41) days, 344/524 (65.6%) had a positive blood culture (of which 393 non-contaminant organisms were isolated), and 69/524 (13.2%) patients died. Coagulase-negative staphylococci (232/405; 57.3%), Klebsiella spp. (28/405; 6.9%), and Escherichia coli (27/405; 6.7%) were the most isolated organisms. Sclerema (OR = 11.4), leukopenia <4,000/mm3 (OR = 7.8), thrombocytopenia <100,000/mm3 (OR = 3.7), base excess < -20 mEq/L (OR = 3.6), serum lactate >4 mmol/L (OR = 3.4), extremely low birth weight (OR = 3.2), and hyperglycaemia >180 mg/dL (OR = 2.6) were all significantly (p<0.05) associated with mortality. The identified risk factors can be adopted as prognostic factors for the diagnosis and treatment of neonatal sepsis and enable early risk stratification and interventions appropriate to reduce neonatal sepsis in LMIC settings.