Glioblastoma multiforme (GBM) is the most common and malignant brain tumor with poor prognosis. The heterogeneous and aggressive nature of GBMs increases the difficulty of current standard treatment. The presence of GBM stem cells and the blood brain barrier (BBB) further contribute to the most important compromise of chemotherapy and radiation therapy. Current suggestions to optimize GBM patients’ outcomes favor controlled targeted delivery of chemotherapeutic agents to GBM cells through the BBB using nanoparticles and monoclonal antibodies. Nanotechnology and nanocarrier-based drug delivery have recently gained attention due to the characteristics of biosafety, sustained drug release, increased solubility, and enhanced drug bioactivity and BBB penetrability. In this review, we focused on recently developed nanoparticles and emerging strategies using nanocarriers for the treatment of GBMs. Current studies using nanoparticles or nanocarrier-based drug delivery system for treatment of GBMs in clinical trials, as well as the advantages and limitations, were also reviewed.

It is unknown whether neonatal ventilator-associated pneumonia (VAP) caused by multidrug-resistant (MDR) pathogens and inappropriate initial antibiotic treatment is associated with poor outcomes after adjusting for confounders. Methods: We prospectively observed all neonates with a definite diagnosis of VAP from a tertiary level neonatal intensive care unit (NICU) in Taiwan between October 2017 and March 2020. All clinical features, therapeutic interventions, and outcomes were compared between the MDR–VAP and non-MDR–VAP groups. Multivariate regression analyses were used to investigate independent risk factors for treatment failure. Results: Of 720 neonates who were intubated for more than 2 days, 184 had a total of 245 VAP episodes. The incidence rate of neonatal VAP was 10.1 episodes/per 1000 ventilator days. Ninety-six cases (39.2%) were caused by MDR pathogens. Neonates with MDR–VAP were more likely to receive inadequate initial antibiotic therapy (51.0% versus 4.7%; p < 0.001) and had delayed resolution of clinical symptoms (38.5% versus 25.5%; p = 0.034), although final treatment outcomes were comparable with the non-MDR–VAP group. Inappropriate initial antibiotic treatment was not significantly associated with worse outcomes. The VAP-attributable mortality rate and overall mortality rate of this cohort were 3.7% and 12.0%, respectively. Independent risk factors for treatment failure included presence of concurrent bacteremia (OR 4.83; 95% CI 2.03–11.51; p < 0.001), septic shock (OR 3.06; 95% CI 1.07–8.72; p = 0.037), neonates on high-frequency oscillatory ventilator (OR 4.10; 95% CI 1.70–9.88; p = 0.002), and underlying neurological sequelae (OR 3.35; 95% CI 1.47–7.67; p = 0.004). Conclusions: MDR–VAP accounted for 39.2% of all neonatal VAP in the neonatal intensive care unit (NICU), but neither inappropriate initial antibiotics nor MDR pathogens were associated with treatment failure. Neonatal VAP with concurrent bacteremia, septic shock, and underlying neurological sequelae were independently associated with final worse outcomes.

Background: Early identification of critically ill neonates with poor outcomes can optimize therapeutic strategies. We aimed to examine whether machine learning (ML) methods can improve mortality prediction for neonatal intensive care unit (NICU) patients on intubation for respiratory failure. Methods: A total of 1734 neonates with respiratory failure were randomly divided into training (70%, n = 1214) and test (30%, n = 520) sets. The primary outcome was the probability of NICU mortality. The areas under the receiver operating characteristic curves (AUCs) of several ML algorithms were compared with those of the conventional neonatal illness severity scoring systems including the NTISS and SNAPPE-II. Results: For NICU mortality, the random forest (RF) model showed the highest AUC (0.939 (0.921–0.958)) for the prediction of neonates with respiratory failure, and the bagged classification and regression tree model demonstrated the next best results (0.915 (0.891–0.939)). The AUCs of both models were significantly better than the traditional NTISS (0.836 (0.800–0.871)) and SNAPPE-II scores (0.805 (0.766–0.843)). The superior performances were confirmed by higher accuracy and F1 score and better calibration, and the superior and net benefit was confirmed by decision curve analysis. In addition, Shapley additive explanation (SHAP) values were utilized to explain the RF prediction model. Conclusions: Machine learning algorithms increase the accuracy and predictive ability for mortality of neonates with respiratory failure compared with conventional neonatal illness severity scores. The RF model is suitable for clinical use in the NICU, and clinicians can gain insights and have better communication with families in advance.

Background: Multidrug-resistant (MDR) pathogens have emerged as an important issue in neonatal intensive care units (NICUs), especially in critically ill neonates with severe respiratory failure. We aimed to investigate neonatal healthcare-associated infections (HAIs) caused by MDR pathogens and the impacts of inappropriate initial antibiotic therapy on the outcomes. Methods: We retrospectively analyzed all cases of HAIs in neonates with severe respiratory failure in a tertiary-level NICU in Taiwan between January 2014 and May 2020. All clinical features, microbiology, therapeutic interventions, and outcomes were compared between the MDR-HAI and non-MDR HAI groups. Multivariate regression analyses were used to investigate independent risk factors for sepsis-attributable mortality. Results: A total of 275 critically ill neonates with severe respiratory failure who had HAIs were enrolled. Ninety-five cases (34.5%) were caused by MDR pathogens, and 141 (51.3%) cases had positive bacterial cultures from multiple sterile sites. In this cohort, the MDR-HAI group was more likely to receive inappropriate initial antibiotic therapy (51.0% versus 4.7%, respectively; p < 0.001) and exhibit delayed control of the infectious focus (52.6% versus 37.8%, respectively; p = 0.021) compared with the non-MDR HAI group. The sepsis-attributable and final in-hospital rates were 21.8% and 37.1%, respectively, and they were comparable between the MDR-HAI and non-MDR HAI groups. Empirically broad-spectrum antibiotics were prescribed in 76.7% of cases, and inappropriate initial antibiotic treatment was not significantly associated with worse outcomes. Independent risk factors for sepsis-attributable mortality in neonates with severe respiratory failure included the presence of septic shock (OR: 3.61; 95% CI: 1.54–8.46; p = 0.003), higher illness severity (OR: 1.33; 95% CI: 1.04–1.72; p = 0.026), and neonates with bronchopulmonary dysplasia (OR: 2.99; 95% CI: 1.47–6.09; p = 0.003). Conclusions: MDR pathogens accounted for 34.5% of all neonatal HAIs in the NICU, but neither MDR pathogens nor inappropriate initial antibiotics were associated with final adverse outcomes. Because the overuse of broad-spectrum antibiotics has emerged as an important issue in critically ill neonates, the implementation of antimicrobial stewardship to promote the appropriate use of antimicrobials is urgently needed.

Background: Streptococcus agalactiae (also known as group B streptococcus, GBS) is associated with high mortality and morbidity rates in infants, especially those with complicated GBS sepsis, defined as those with meningitis, severe sepsis and/or septic shock. We aimed to characterize the clinical and molecular characteristics and risk factors for adverse outcomes of neonates with invasive GBS diseases. Methods: From 2003 to 2020, all neonates with invasive GBS diseases who were hospitalized in a tertiary-level neonatal intensive care unit (NICU) were enrolled. The GBS isolates underwent serotyping, multilocus sequence typing (MLST) and antibiotic susceptibility testing. We compared cases of complicated GBS sepsis with uncomplicated GBS bacteremia. Results: During the study period, a total of 188 neonates (aged less than 6 months old) with invasive GBS diseases were identified and enrolled. Among them, 119 (63.3%) had uncomplicated GBS bacteremia and 69 (36.7%) neonates had complicated GBS sepsis, including meningitis (25.5%, n = 48) and severe sepsis or septic shock. Among neonates with complicated GBS sepsis, 45 (65.2%) had neurological complications, and 21 (42.0%) of 50 survivors had neurological sequelae at discharge. The overall final mortality rate was 10.1% (19 neonates died). Type III/ST-17 GBS isolates accounted for 56.5% of all complicated GBS sepsis and 68.8% of all GBS meningitis, but this strain was not significantly associated with worse outcomes. The antimicrobial resistance rate among the invasive GBS isolates was obviously increasing in the past two decades. After multivariate logistic regression analysis, neonates with thrombocytopenia and respiratory failure were independently associated with final adverse outcomes. Conclusions: a total of 36.7% of all neonatal invasive GBS diseases were associated with complicated sepsis with/without meningitis. Given the high mortality and morbidity rates in neonates with complicated GBS sepsis, further studies for early identification of specific strains, risk factors or genetic mechanisms that will cause complicated GBS sepsis are urgently needed in the future.

Background Ventilator associated pneumonia (VAP) caused by more than one microorganisms is not uncommon and may be potentially challenging, but the relevant data is scarce in ventilated neonates. We aimed to investigate the clinical characteristics and outcomes of polymicrobial VAP in the neonatal intensive care unit (NICU). Methods All neonates with definite diagnosis of VAP from a tertiary level neonatal intensive care unit (NICU) in Taiwan between October 2017 and September 2020 were prospectively observed and enrolled for analyses. All clinical features, therapeutic interventions and outcomes were compared between the polymicrobial VAP and monomicrobial VAP episodes. Multivariate regression analyses were used to find the independent risk factors for treatment failure. Results Among 236 episodes of neonatal VAP, 60 (25.4%) were caused by more than one microorganisms. Polymicrobial VAP episodes were more likely to be associated with multidrug-resistant pathogens (53.3% versus 34.7%, P = 0.014), more often occurred in later days of life and in neonates with prolonged intubation and underlying bronchopulmonary dysplasia. Otherwise most clinical characteristics of polymicrobial VAP were similar to those of monomicrobial VAP. The therapeutic responses and treatment outcomes were also comparable between these two groups, although modification of therapeutic antibiotics were significantly more common in polymicrobial VAP episodes than monomicrobial VAP episodes (63.3% versus 46.2%; P < 0.001). None of any specific pathogens was significantly associated with worse outcomes. Instead, it is the severity of illness, including presence of concurrent bacteremia, septic shock, and requirement of high-frequency oscillatory ventilator and underlying neurological sequelae that are independently associated with treatment failure. Conclusions Polymicrobial VAP accounted for 25.4% of all neonatal VAP in the NICU, and frequently occurred in neonates with prolonged intubation and underlying bronchopulmonary dysplasia. In our cohort, most clinical features, therapeutic responses and final outcomes of neonates with monomicrobial and polymicrobial VAP did not differ significantly.

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Background: Ventilator associated pneumonia (VAP) caused by more than one microorganisms is not uncommon and may be potentially challenging, but the relevant data is scarce in ventilated neonates. We aimed to investigate the clinical characteristics and outcomes of polymicrobial VAP in the neonatal intensive care unit (NICU).Methods: All neonates with definite diagnosis of VAP from a tertiary level neonatal intensive care unit (NICU) in Taiwan between October 2017 and September 2020 were prospectively observed and enrolled for analyses. All clinical features, therapeutic interventions and outcomes were compared between the polymicrobial VAP and monomicrobial VAP episodes. Multivariate regression analyses were used to find the independent risk factors for treatment failure. Results: Among 236 episodes of neonatal VAP, 60 (25.4%) were caused by more than one microorganisms. Polymicrobial VAP episodes were more likely to be associated with multidrug-resistant pathogens (53.3% versus 34.7%, P = 0.014), more often occurred in later days of life and in neonates with prolonged intubation and underlying bronchopulmonary dysplasia. Otherwise most clinical characteristics of polymicrobial VAP were similar to those of monomicrobial VAP. The therapeutic responses and treatment outcomes were also comparable between these two groups, although modification of therapeutic antibiotics were significantly more common in polymicrobial VAP episodes than monomicrobial VAP episodes (63.3% versus 46.2%; P<0.001). None of any specific pathogens was significantly associated with worse outcomes. Instead, it is the severity of illness, including presence of concurrent bacteremia, septic shock, and requirement of high-frequency oscillatory ventilator and underlying neurological sequelae that are independently associated with treatment failure.Conclusions: Polymicrobial VAP accounted for 25.4% of all neonatal VAP in the NICU, and frequently occurred in neonates with prolonged intubation and underlying bronchopulmonary dysplasia. In our cohort, most clinical features, therapeutic responses and final outcomes of neonates with monomicrobial and polymicrobial VAP did not differ significantly.