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Abstract Background This study analyzed the relationship between vancomycin area under the concentration-time curve (AUC) and acute kidney injury (AKI) reported across recent studies. Methods A systematic review of PubMed, Medline, Scopus, and compiled references was conducted. We included randomized cohort and case-control studies that reported vancomycin AUCs and risk of AKI (from 1990 to 2018). The primary outcome was AKI, defined as an increase in serum creatinine of ≥0.5 mg/L or a 50% increase from baseline on ≥2 consecutive measurements. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Primary analyses compared the impact of AUC cutpoint (greater than ~650 mg × hour/L) and AKI. Additional analysis compared AUC vs trough-guided monitoring on AKI incidence. Results Eight observational studies met inclusion/exclusion criteria with data for 2491 patients. Five studies reported first-24-hour AUCs (AUC0-24) and AKI, 2 studies reported 24- to 48-hour AUCs (AUC24-48) and AKI, and 2 studies reported AKI associated with AUC- vs trough-guided monitoring. AUC less than approximately 650 mg × hour/L was associated with decreased AKI for AUC0-24 (OR, 0.36 [95% CI, .23–.56]) as well as AUC24-48 (OR, 0.45 [95% CI, .27–.75]). AKI associated with the AUC monitoring strategy was significantly lower than trough-guided monitoring (OR, 0.68 [95% CI, .46–.99]). Conclusions AUCs measured in the first or second 24 hours and lower than approximately 650 mg × hour/L may result in a decreased risk of AKI. Vancomycin AUC monitoring strategy may result in less vancomycin-associated AKI. Additional investigations are warranted. This meta-analysis identifies a clear exposure–response relationship (ie, area under the curve threshold greater than ~650 mg × hour/L) for vancomycin and acute kidney injury (AKI). It also suggests that area under the concentration-time curve monitoring strategies can potentially decrease the risk of AKI.

Abstract Background Detection of active pulmonary tuberculosis on chest radiographs (CRs) is critical for the diagnosis and screening of tuberculosis. An automated system may help streamline the tuberculosis screening process and improve diagnostic performance. Methods We developed a deep learning–based automatic detection (DLAD) algorithm using 54c221 normal CRs and 6768 CRs with active pulmonary tuberculosis that were labeled and annotated by 13 board-certified radiologists. The performance of DLAD was validated using 6 external multicenter, multinational datasets. To compare the performances of DLAD with physicians, an observer performance test was conducted by 15 physicians including nonradiology physicians, board-certified radiologists, and thoracic radiologists. Image-wise classification and lesion-wise localization performances were measured using area under the receiver operating characteristic (ROC) curves and area under the alternative free-response ROC curves, respectively. Sensitivities and specificities of DLAD were calculated using 2 cutoffs (high sensitivity [98%] and high specificity [98%]) obtained through in-house validation. Results DLAD demonstrated classification performance of 0.977–1.000 and localization performance of 0.973–1.000. Sensitivities and specificities for classification were 94.3%–100% and 91.1%–100% using the high-sensitivity cutoff and 84.1%–99.0% and 99.1%–100% using the high-specificity cutoff. DLAD showed significantly higher performance in both classification (0.993 vs 0.746–0.971) and localization (0.993 vs 0.664–0.925) compared to all groups of physicians. Conclusions Our DLAD demonstrated excellent and consistent performance in the detection of active pulmonary tuberculosis on CR, outperforming physicians, including thoracic radiologists. A deep learning–based algorithm outperformed radiologists in detecting active pulmonary tuberculosis on chest radiographs and thus may play an important role in diagnosis and screening of tuberculosis in select situations, contributing to the reduction of the high burden of tuberculosis worldwide.

Of patients with pneumonia coming from the community, 18% are immunocompromised. Specific immunocompromised states are associated with specific microbiology, which has to be taken into consideration when choosing empirical therapy. Abstract Background The correct management of immunocompromised patients with pneumonia is debated. We evaluated the prevalence, risk factors, and characteristics of immunocompromised patients coming from the community with pneumonia. Methods We conducted a secondary analysis of an international, multicenter study enrolling adult patients coming from the community with pneumonia and hospitalized in 222 hospitals in 54 countries worldwide. Risk factors for immunocompromise included AIDS, aplastic anemia, asplenia, hematological cancer, chemotherapy, neutropenia, biological drug use, lung transplantation, chronic steroid use, and solid tumor. Results At least 1 risk factor for immunocompromise was recorded in 18% of the 3702 patients enrolled. The prevalences of risk factors significantly differed across continents and countries, with chronic steroid use (45%), hematological cancer (25%), and chemotherapy (22%) the most common. Among immunocompromised patients, community-acquired pneumonia (CAP) pathogens were the most frequently identified, and prevalences did not differ from those in immunocompetent patients. Risk factors for immunocompromise were independently associated with neither Pseudomonas aeruginosa nor non–community-acquired bacteria. Specific risk factors were independently associated with fungal infections (odds ratio for AIDS and hematological cancer, 15.10 and 4.65, respectively; both P = .001), mycobacterial infections (AIDS; P = .006), and viral infections other than influenza (hematological cancer, 5.49; P < .001). Conclusions Our findings could be considered by clinicians in prescribing empiric antibiotic therapy for CAP in immunocompromised patients. Patients with AIDS and hematological cancer admitted with CAP may have higher prevalences of fungi, mycobacteria, and noninfluenza viruses.

Neisseria gonorrhoeae and Neisseria meningitidis are closely-related bacteria that cause a significant global burden of disease. Control of gonorrhoea is becoming increasingly difficult, due to widespread antibiotic resistance. While vaccines are routinely used for N. meningitidis, no vaccine is available for N. gonorrhoeae. Recently, the outer membrane vesicle (OMV) meningococcal B vaccine, MeNZB, was reported to be associated with reduced rates of gonorrhoea following a mass vaccination campaign in New Zealand. To probe the basis for this protection, we assessed the cross-reactivity to N. gonorrhoeae of serum raised to the meningococcal vaccine Bexsero, which contains the MeNZB OMV component plus 3 recombinant antigens (Neisseria adhesin A, factor H binding protein [fHbp]-GNA2091, and Neisserial heparin binding antigen [NHBA]-GNA1030). A bioinformatic analysis was performed to assess the similarity of MeNZB OMV and Bexsero antigens to gonococcal proteins. Rabbits were immunized with the OMV component or the 3 recombinant antigens of Bexsero, and Western blots and enzyme-linked immunosorbent assays were used to assess the generation of antibodies recognizing N. gonorrhoeae. Serum from humans immunized with Bexsero was investigated to assess the nature of the anti-gonococcal response. There is a high level of sequence identity between MeNZB OMV and Bexsero OMV antigens, and between the antigens and gonococcal proteins. NHBA is the only Bexsero recombinant antigen that is conserved and surfaced exposed in N. gonorrhoeae. Bexsero induces antibodies in humans that recognize gonococcal proteins. The anti-gonococcal antibodies induced by MeNZB-like OMV proteins could explain the previously-seen decrease in gonorrhoea following MeNZB vaccination. The high level of human anti-gonococcal NHBA antibodies generated by Bexsero vaccination may provide additional cross-protection against gonorrhoea.

Abstract Background The known relationship between the gestational age at maternal primary infection an the outcome of congenital CMV is based on small, retrospective studies conducted between 1980 and 2011. They reported that 32% and 15% of cases had sequelae following a maternal primary infection in the first and second or the third trimester, respectively. We aimed to revisit this relationship prospectively between 2011 and 2017, using accurate virological tools. Methods We collected data on women with a primary infection and an infected child aged at least 1 year at the time of analysis. An accurate determination of the timing of the primary infection was based upon serial measurements of immunoglobulin (Ig) M and IgG and on IgG avidity in sera collected at each trimester. The case outcome was assessed according to a structured follow-up between birth and 48 months. Results We included 255 women and their 260 fetuses/neonates. The dating of the maternal infection was prospective in 86% of cases and retrospective in 14%. At a median follow-up of 24 months, the proportion of sensorineural hearing loss and/or neurologic sequelae were 32.4% (95% confidence interval [CI] 23.72–42.09) after a maternal primary infection in the first trimester, 0 (95% CI 0–6.49) after an infection in the second trimester, and 0 (95% CI 0–11.95) after an infection in the third trimester (P < .0001). Conclusions These results suggest that a cytomegalovirus infection can be severe only when the virus hits the fetus in the embryonic or early fetal period. Recent guidelines recommend auditory follow-ups for at least 5 years for all infected children. This raises parental anxiety and generates significant costs. We suggest that auditory and specialized neurologic follow-ups may be recommended only in cases of a maternal infection in the first trimester. In this study, only children infected after a maternal primary infection in the first trimester had sequelae at follow-up. For women with seroconversion in the second or third trimester, the risk returns to the baseline associated with any pregnancy.

Abstract Background Despite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. Therefore, we aimed to develop a highly sensitive metagenomic next-generation sequencing (mNGS) assay capable of evaluating the pulmonary microbiome and identifying diverse pathogens in the lungs of immunocompromised children. Methods We collected 41 lower respiratory specimens from 34 immunocompromised children undergoing evaluation for pulmonary disease at 3 children’s hospitals from 2014–2016. Samples underwent mechanical homogenization, parallel RNA/DNA extraction, and metagenomic sequencing. Sequencing reads were aligned to the National Center for Biotechnology Information nucleotide reference database to determine taxonomic identities. Statistical outliers were determined based on abundance within each sample and relative to other samples in the cohort. Results We identified a rich cross-domain pulmonary microbiome that contained bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Samples with bacterial outliers had significantly depressed alpha-diversity (median, 0.61; interquartile range [IQR], 0.33–0.72 vs median, 0.96; IQR, 0.94–0.96; P < .001). Potential pathogens were detected in half of samples previously negative by clinical diagnostics, demonstrating increased sensitivity for missed pulmonary pathogens (P < .001). Conclusions An optimized mNGS assay for pulmonary microbes demonstrates significant inoculation of the lower airways of immunocompromised children with diverse bacteria, fungi, and viruses. Potential pathogens can be identified based on absolute and relative abundance. Ongoing investigation is needed to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised children with pulmonary disease. Pulmonary infections in immunocompromised children frequently evade detection by current clinical diagnostics. We optimized metagenomic sequencing of pulmonary pathogens in immunocompromised children and show that metagenomic RNA sequencing identified pulmonary pathogens in approximately half of patients with negative clinical diagnostics.