Molecular Distance to Health Transcriptional Score and Disease Severity in Children Hospitalized With Community-Acquired Pneumonia

Correlation between fat-soluble vitamin levels and inflammatory factors in paediatric community-acquired pneumonia: A prospective study

Community-acquired pneumonia (CAP) is a common respiratory disease in children. This prospective cohort study of 110 children with CAP and 100 healthy children investigated the relationship between the levels of vitamin A, D and E and inflammatory markers, such as tumour necrosis factor (TNF-a), interleukin-1 (IL-1), interleukin-10 (IL-10), neutrophils (NE) and C-reactive protein (CRP), in CAP. The haemoglobin, leukocyte concentration, NE, monocytes and CRP concentration in the CAP group showed significant differences (P < 0.05). The levels of vitamin A, D and E in the CAP group were lower than those in the control group, while the levels of TNF-a and IL-1 were higher than in the control group; the differences were statistically significant (P < 0.05). The IL-10 levels showed no significant differences (P > 0.05). Pearson analysis revealed that the vitamin A, D and E levels were all correlated with the TNF-a, IL-10 and CRP levels (P < 0.05). The vitamin A, D and E levels of the CAP children were lower than those of the healthy children. Thus, the content of fat-soluble vitamins is correlated with the secretion of TNF-a and IL-10. The research provides a new direction for the prevention, diagnosis and treatment of CAP.

Construction and external validation of a scoring prediction model for mortality risk within 30 days of community-acquired pneumonia in children admitted to the pediatric intensive care unit: A multicenter retrospective case-control study

In this study, we constructed and validated a scoring prediction model to identify children admitted to the pediatric intensive care unit (PICU) with community-acquired pneumonia (CAP) at risk for early death. Children with CAP who were admitted to the PICU were included in the training set and divided into death and survival groups according to whether they died within 30 days of admission. For univariate and multifactorial analyses, demographic characteristics, vital signs at admission, and laboratory test results were collected separately from the 2 groups, and independent risk factors were derived to construct a scoring prediction model. The ability of the scoring model to predict CAP-related death was validated by including children with CAP hospitalized at 3 other centers during the same period in the external validation set. Overall, the training and validation sets included 296 and 170 children, respectively. Univariate and multifactorial analyses revealed that procalcitonin (PCT), lactate dehydrogenase (LDH), activated partial thromboplastin time (APTT), and fibrinogen (Fib) were independent risk factors. The constructed scoring prediction model scored 2 points each for PCT ≥ 0.375 ng/mL, LDH ≥ 490 U/L, and APTT ≥ 31.8 s and 1 point for Fib ≤ 1.78 g/L, with a total model score of 0-7 points. When the score was ≥ 5 points, the sensitivity and specificity of mortality diagnosis in children with CAP were 72.7% and 87.5%, respectively. In the external validation set, the sensitivity, specificity, and accuracy of the scoring model for predicting the risk of CAP-related death were 64.0%, 92.4%, and 88.2%, respectively. Constructing a scoring prediction model is worth promoting and can aid pediatricians in simply and rapidly evaluating the risk of death in children with CAP, particularly those with complex conditions.

Pneumonia-Plus: a deep learning model for the classification of bacterial, fungal, and viral pneumonia based on CT tomography

OBJECTIVES

This study aims to develop a deep learning algorithm, Pneumonia-Plus, based on computed tomography (CT) images for accurate classification of bacterial, fungal, and viral pneumonia.

METHODS

A total of 2763 participants with chest CT images and definite pathogen diagnosis were included to train and validate an algorithm. Pneumonia-Plus was prospectively tested on a nonoverlapping dataset of 173 patients. The algorithm's performance in classifying three types of pneumonia was compared to that of three radiologists using the McNemar test to verify its clinical usefulness.

RESULTS

Among the 173 patients, area under the curve (AUC) values for viral, fungal, and bacterial pneumonia were 0.816, 0.715, and 0.934, respectively. Viral pneumonia was accurately classified with sensitivity, specificity, and accuracy of 0.847, 0.919, and 0.873. Three radiologists also showed good consistency with Pneumonia-Plus. The AUC values of bacterial, fungal, and viral pneumonia were 0.480, 0.541, and 0.580 (radiologist 1: 3-year experience); 0.637, 0.693, and 0.730 (radiologist 2: 7-year experience); and 0.734, 0.757, and 0.847 (radiologist 3: 12-year experience), respectively. The McNemar test results for sensitivity showed that the diagnostic performance of the algorithm was significantly better than that of radiologist 1 and radiologist 2 (p < 0.05) in differentiating bacterial and viral pneumonia. Radiologist 3 had a higher diagnostic accuracy than the algorithm.

CONCLUSIONS

The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist and reduce the risk of misdiagnosis. The Pneumonia-Plus is important for appropriate treatment and avoiding the use of unnecessary antibiotics, and provide timely information to guide clinical decision-making and improve patient outcomes.

CLINICAL RELEVANCE STATEMENT

Pneumonia-Plus algorithm could assist in the accurate classification of pneumonia based on CT images, which has great clinical value in avoiding the use of unnecessary antibiotics, and providing timely information to guide clinical decision-making and improve patient outcomes.

KEY POINTS

• The Pneumonia-Plus algorithm trained from data collected from multiple centers can accurately identify bacterial, fungal, and viral pneumonia. • The Pneumonia-Plus algorithm was found to have better sensitivity in classifying viral and bacterial pneumonia in comparison to radiologist 1 (5-year experience) and radiologist 2 (7-year experience). • The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist.

Clinical, Laboratory, and Radiographic Features Can Help Predict Mycoplasma pneumoniae Lower Respiratory Tract Infection in Children

Mycoplasma pneumoniae (Mp) is a common cause of lower respiratory tract infection (LRTI) in children that is difficult to distinguish from LRTI of other etiologies. We aimed to determine if a combination of clinical, laboratory, and chest radiographic features can help identify patients at higher risk of Mp LRTI. We reviewed medical charts of children referred to our tertiary hospital with suspected acute mycoplasmal LRTI. Pharyngeal swabs obtained from patients were tested by Mp PCR. We compared epidemiological and clinical data of children with positive and negative Mp PCR results. In addition, a multivariable logistic regression analysis was performed to predict Mp LRTI based on the patient's age, duration of symptoms, presence of extrapulmonary manifestations, laboratory findings, and chest radiographic findings. We included 65 children with Mp PCR-negative and 49 with Mp PCR-positive LRTI and no viral co-detection. Children with Mp LRTI were older (median age 5.8 vs. 2.2 years, p < 0.001), had a longer duration of symptoms on referral (median 7 vs. 4 days, p < 0.001), and lower median WBC (9.9 vs. 12.7 × 10⁹/L, p < 0.001). On chest radiograph, unilateral infiltrates were more frequently observed in the Mp PCR-positive group (57.5% vs. 24.1%, p = 0.001). Age, duration of symptoms, and chest radiographic findings had the highest predictive value for Mp LRTI in a multivariable logistic regression model. Our analysis suggests that a combination of clinical, laboratory, and chest radiographic features can be used to assess the likelihood of Mp LRTI and assist in decision-making for which children need further tests or macrolide antibiotic treatment.

Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort

A new era of human postmortem tissue research has emerged thanks to the development of 'omics technologies that measure genes, proteins, and spatial parameters in unprecedented detail. Also newly possible is the ability to construct polygenic scores, individual-level metrics of genetic risk (also known as polygenic risk scores/PRS), based on genome-wide association studies, GWAS. Here, we report on clinical, educational, and brain gene expression correlates of polygenic scores in ancestrally diverse samples from the Human Brain Collection Core (HBCC). Genotypes from 1418 donors were subjected to quality control filters, imputed, and used to construct polygenic scores. Polygenic scores for schizophrenia predicted schizophrenia status in donors of European ancestry (p = 4.7 × 10^-8, 17.2%) and in donors with African ancestry (p = 1.6 × 10^-5, 10.4% of phenotypic variance explained). This pattern of higher variance explained among European ancestry samples was also observed for other psychiatric disorders (depression, bipolar disorder, substance use disorders, anxiety disorders) and for height, body mass index, and years of education. For a subset of 223 samples, gene expression from dorsolateral prefrontal cortex (DLPFC) was available through the CommonMind Consortium. In this subgroup, schizophrenia polygenic scores also predicted an aggregate gene expression score for schizophrenia (European ancestry: p = 0.0032, African ancestry: p = 0.15). Overall, polygenic scores performed as expected in ancestrally diverse samples, given historical biases toward use of European ancestry samples and variable predictive power of polygenic scores across phenotypes. The transcriptomic results reported here suggest that inherited schizophrenia genetic risk influences gene expression, even in adulthood. For future research, these and additional polygenic scores are being made available for analyses, and for selecting samples, using postmortem tissue from the Human Brain Collection Core.

Transcript host-RNA signatures to discriminate bacterial and viral infections in febrile children

Traditional laboratory markers, such as white blood cell count, C-reactive protein, and procalcitonin, failed to discriminate viral and bacterial infections in children. The lack of an accurate diagnostic test has a negative impact on child's care, limiting the ability of early diagnosis and appropriate management of children. This, on the one hand, may lead to delayed recognition of sepsis and severe bacterial infections, which still represent the leading causes of child morbidity and mortality. On the other hand, this may lead to overuse of empiric antibiotic therapies, particularly for specific subgroups of patients, such as infants younger than 90 days of life or neutropenic patients. This approach has an adverse effect on costs, antibiotic resistance, and pediatric microbiota. Transcript host-RNA signatures are a new tool used to differentiate viral from bacterial infections by analyzing the transcriptional biosignatures of RNA in host leukocytes. In this systematic review, we evaluate the efficacy and the possible application of this new diagnostic method in febrile children, along with challenges in its implementation. Our review support the growing evidence that the application of these new tools can improve the characterization of the spectrum of bacterial and viral infections and optimize the use of antibiotics in children. IMPACT: Transcript host RNA signatures may allow to better characterize the spectrum of viral, bacterial, and inflammatory illnesses in febrile children and can be used with traditional diagnostic methods to determine if and when to start antibiotic therapy. This is the first review on the use of transcript RNA signatures in febrile children to distinguish viral from bacterial infections. Our review identified a wide variability of target populations and gold standards used to define sepsis and SBIs, limiting the generalization of our findings.

Host transcriptional signatures as predictive markers of infection in children

PURPOSE OF REVIEW

Analyses of the host transcriptional response to infection has proved to be an alternative diagnostic strategy to standard direct pathogen detection. This review summarizes the value of applying blood and mucosal transcriptome analyses for the diagnosis and management of children with viral and bacterial infections.

RECENT FINDINGS

Over the years, studies have validated the concept that RNA transcriptional profiles derived from children with infectious diseases carry a pathogen-specific biosignature that can be qualitatively and quantitively measured. These biosignatures can be translated into a biologically meaningful context to improve patient diagnosis, as seen in children with tuberculosis, rhinovirus infections, febrile infants and children with pneumonia; understand disease pathogenesis (i.e. congenital CMV) and objectively classify patients according to clinical severity (i.e. respiratory syncytial virus).

SUMMARY

The global assessment of host RNA transcriptional immune responses has improved our understanding of the host-pathogen interactions in the clinical setting. It has shown the potential to be used in clinical situations wherein our current diagnostic tools are inadequate, guiding the diagnosis and classification of children with infectious diseases.

Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test

OBJECTIVES

Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test.

DESIGN

Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results.

SETTING

Four U.S. emergency departments.

PATIENTS

Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis.

INTERVENTIONS

Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes.

MEASUREMENTS AND MAIN RESULTS

Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance.

CONCLUSIONS

The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.

Mycoplasma pneumoniae Genotypes and Clinical Outcome in Children

Factors leading to the wide range of manifestations associated with Mycoplasma pneumoniae infection are unclear. We investigated whether M. pneumoniae genotypes are associated with specific clinical outcomes. We compared M. pneumoniae loads and genotypes of children with mucocutaneous disease to those of children with pneumonia, family members with upper respiratory tract infection (URTI), and carriers from a prospective cohort study (n = 47; 2016 to 2017) and to those of other children with mucocutaneous disease from a case series (n = 7; 2017 to 2020). Genotyping was performed using macrolide resistance determination, P1 subtyping, multilocus variable-number tandem-repeat analysis (MLVA), and multilocus sequence typing (MLST). Comparisons were performed with a pairwise Wilcoxon rank sum test and a Fisher exact test with corrections for multiple testing, as appropriate. M. pneumoniae loads did not statistically differ between patients with mucocutaneous disease and those with pneumonia or carriers. Macrolide resistance was detected in 1 (1.9%) patient with mucocutaneous disease. MLVA types from 2016 to 2017 included 3-5-6-2 (n = 21 [46.7%]), 3-6-6-2 (n = 2 [4.4%]), 4-5-7-2 (n = 14 [31.1%]), and 4-5-7-3 (n = 8 [17.8%]), and they correlated with P1 subtypes and MLST types. MLVA types were not associated with specific outcomes such as mucocutaneous disease, pneumonia, URTI, or carriage. They were almost identical within families but varied over geographic location. MLVA types in patients with mucocutaneous disease differed between 2016 to 2017 (3-5-6-2, n = 5 [62.5%]) and 2017 to 2020 (4-5-7-2, n = 5 [71.4%]) (P = 0.02). Our results suggest that M. pneumoniae genotypes may not determine specific clinical outcomes.

Pathogenetic profiling of COVID-19 and SARS-like viruses

The novel coronavirus (2019-nCoV) has recently emerged, causing COVID-19 outbreaks and significant societal/global disruption. Importantly, COVID-19 infection resembles SARS-like complications. However, the lack of knowledge about the underlying genetic mechanisms of COVID-19 warrants the development of prospective control measures. In this study, we employed whole-genome alignment and digital DNA-DNA hybridization analyses to assess genomic linkage between 2019-nCoV and other coronaviruses. To understand the pathogenetic behavior of 2019-nCoV, we compared gene expression datasets of viral infections closest to 2019-nCoV with four COVID-19 clinical presentations followed by functional enrichment of shared dysregulated genes. Potential chemical antagonists were also identified using protein-chemical interaction analysis. Based on phylogram analysis, the 2019-nCoV was found genetically closest to SARS-CoVs. In addition, we identified 562 upregulated and 738 downregulated genes (adj. P ≤ 0.05) with SARS-CoV infection. Among the dysregulated genes, SARS-CoV shared ≤19 upregulated and ≤22 downregulated genes with each of different COVID-19 complications. Notably, upregulation of BCL6 and PFKFB3 genes was common to SARS-CoV, pneumonia and severe acute respiratory syndrome, while they shared CRIP2, NSG1 and TNFRSF21 genes in downregulation. Besides, 14 genes were common to different SARS-CoV comorbidities that might influence COVID-19 disease. We also observed similarities in pathways that can lead to COVID-19 and SARS-CoV diseases. Finally, protein-chemical interactions suggest cyclosporine, resveratrol and quercetin as promising drug candidates against COVID-19 as well as other SARS-like viral infections. The pathogenetic analyses, along with identified biomarkers, signaling pathways and chemical antagonists, could prove useful for novel drug development in the fight against the current global 2019-nCoV pandemic.

Prediction value of procalcitonin combining CURB-65 for 90-day mortality in community-acquired pneumonia

Background: Due to its high mortality rate, immediate and reliable severity assessment and accurate prediction of prognosis at hospital admission is critical for the management of community-acquired pneumonia (CAP) patients.Methods: Consecutive patients with primary diagnosis of CAP and hospitalized at our hospital from January 2013 to December 2015 were screened for this retrospective study. Demographic information, clinical and laboratory examination, severity model scoring, and 90-day outcomes were studied. Area under the curve (AUC) of receiver operating characteristic curve (ROC) was analyzed to compare the predictive value of different prognostic scoring methods.Results: 2099 CAP patients with a median age of 60 (IQR 44.0-73.0) years-old were included in this study. Median length of stay was 10 days (IQR 8.0-13.0). The all-cause 90-day mortality was found in 2.19% (46/2099) of all patients. PCT was identified as an independent predictor for the prognosis of CAP patients. CURB-65 in combination with PCT outperformed other predictive methods in 90-day mortality with the optimal AUC of 0.900 and Youden's Index of 0.706.Conclusions: PCT is a good marker for the assessment of severity and 90-day mortality of CAP patients. The combination of PCT and CURB-65 was more accurate than other prognostic models in predicting 90-day mortality.

High ratio of C-reactive protein/procalcitonin predicts Mycoplasma pneumoniae infection among adults hospitalized with community acquired pneumonia

There is limited data on serum biomarkers in distinguishing Mycoplasma pneumoniae (MP) from Streptococcus pneumoniae (SP) and viral pneumoniae (VP) etiologies of community-acquired pneumonia (CAP). A retrospective study of inpatients diagnosed with CAP at the First Affiliated Hospital of Dali University (Dali, Yunnan, China) between January 2018 and June 2020 was conducted. The demographic, clinical and laboratory data of the patients with CAP were analyzed. Univariate analyses identified predictors for MP infections. The discriminative power of C-reactive protein (CRP), procalcitonin (PCT), CRP/PCT and CRP/PCT >350 μg/ng was assessed by area under the curve (AUC) of the receiver operating characteristic (ROC) curves. A total of 552 CAP patients, including 247 (44.7%) with MP, 152 (27.6%) with SP and 153 (27.7%) with influenza A and B viruses, were enrolled. When comparing MP with SP, cough and CRP/PCT >350 μg/ng (odds ratio [OR]) 2.88, p < .001) were predictors for MP. CRP/PCT >350 μg/ng had 76% sensitivity and 100% specificity (AUC = 0.89, p < .001, 95% confidence interval [CI]:0.81-0.94) to predict MP infections. Furthermore, similar results were again obtained when comparing MP with VP. CRP/PCT >350 μg/ng present better information (OR: 4.70; AUC = 0.92, p < .001, 87% sensitivity and 100% specificity). In addition, comparing MP and non-MP (SP and VP combined), CRP/PCT >350 μg/ng exhibited excellent performance (AUC = 0.90, 95%CI 0.83-0.95, p < .001, 76% sensitivity and 100% specificity). CRP/PCT ratio may be a potential index to distinguish MP-CAP from non-MP-CAP.

Improved Diagnostics Help to Identify Clinical Features and Biomarkers That Predict Mycoplasma pneumoniae Community-acquired Pneumonia in Children

BACKGROUND

There are no reliable signs or symptoms that differentiate Mycoplasma pneumoniae (Mp) infection in community-acquired pneumonia (CAP) from other etiologies. Additionally, current diagnostic tests do not reliably distinguish between Mp infection and carriage. We previously determined that the measurement of Mp-specific immunoglobulin M antibody-secreting cells (ASCs) by enzyme-linked immunospot assay allowed for differentiation between infection and carriage. Using this new diagnostic test, we aimed to identify clinical and laboratory features associated with Mp infection.

METHODS

This is a prospective cohort study of children, 3-18 years of age, with CAP from 2016 to 2017. Clinical features and biomarkers were compared between Mp-positive and -negative groups by Mann-Whitney U test or Fisher exact test, as appropriate. Area under the receiver operating characteristic curve (AUC) differences and optimal thresholds were determined by using the DeLong test and Youden J statistic, respectively.

RESULTS

Of 63 CAP patients, 29 were Mp-positive (46%). Mp positivity was statistically associated with older age (median, 8.6 vs 4.7 years), no underlying disease, family with respiratory symptoms, prior antibiotic treatment, prolonged prodromal respiratory symptoms and fever, and extrapulmonary (skin) manifestations. Lower levels of C-reactive protein, white blood cell count, absolute neutrophil count, and procalcitonin (PCT), specifically PCT <0.25 μg/L, were statistically associated with Mp infection. A combination of age >5 years (AUC = 0.77), prodromal fever and respiratory symptoms >6 days (AUC = 0.79), and PCT <0.25 μg/L (AUC = 0.81) improved diagnostic performance (AUC = 0.90) (P = .05).

CONCLUSIONS

A combination of clinical features and biomarkers may aid physicians in identifying patients at high risk for Mp CAP.

Blood genome expression profiles in infants with congenital cytomegalovirus infection

Congenital CMV infection (cCMVi) affects 0.5–1% of all live births worldwide, making it the leading cause of sensorineural hearing loss (SNHL) in childhood. The majority of infants with cCMVi have normal hearing at birth, but are at risk of developing late-onset SNHL. Currently, we lack reliable biomarkers to predict the development of SNHL in these infants. Here, we evaluate blood transcriptional profiles in 80 infants with cCMVi (49 symptomatic, 31 asymptomatic), enrolled in the first 3 weeks of life, and followed for 3 years to assess emergence of late-onset SNHL. The biosignatures of symptomatic and asymptomatic cCMVi are indistinguishable, suggesting that immune responses of infants with asymptomatic and symptomatic cCMVi are not different. Random forest analyses of initial samples in infants with cCMVi, irrespective of their clinical classification, identify a 16-gene classifier signature associated with the development of SNHL with 92% accuracy, suggesting its potential value as a biomarker.

Congenital CMV infection can result in sensorineural hearing loss, but predicting this outcome is not yet possible. Here, the authors show that while blood gene expression profiles are not substantially different between symptomatic and asymptomatic infants with congenital CMV infection, a 16-gene signature is identified and able to predict late-onset hearing loss in these children.

Baseline and Disease-Induced Transcriptional Profiles in Children with Sickle Cell Disease

Acute chest syndrome (ACS) is a significant cause of morbidity and mortality in sickle cell disease (SCD), but preventive, diagnostic, and therapeutic options are limited. Further, ACS and acute vasoccclusive pain crises (VOC) have overlapping features, which causes diagnostic dilemmas. We explored changes in gene expression profiles among patients with SCD hospitalized for VOC and ACS episodes to better understand ACS disease pathogenesis. Whole blood RNA-Seq was performed for 20 samples from children with SCD at baseline and during a hospitalization for either an ACS (n = 10) or a VOC episode (n = 10). Respiratory viruses were identified from nasopharyngeal swabs. Functional gene analyses were performed using modular repertoires, IPA, Gene Ontology, and NetworkAnalyst 3.0. The VOC group had a numerically higher percentage of female, older, and hemoglobin SS participants compared to the ACS group. Viruses were detected in 50% of ACS cases and 20% of VOC cases. We identified 3004 transcripts that were differentially expressed during ACS episodes, and 1802 transcripts during VOC episodes. Top canonical pathways during ACS episodes were related to interferon signaling, neuro-inflammation, pattern recognition receptors, and macrophages. Top canonical pathways in patients with VOC included IL-10 signaling, iNOS signaling, IL-6 signaling, and B cell signaling. Several genes related to antimicrobial function were down-regulated during ACS compared to VOC. Gene enrichment nodal interactions demonstrated significantly altered pathways during ACS and VOC. A complex network of changes in innate and adaptive immune gene expression were identified during both ACS and VOC episodes. These results provide unique insights into changes during acute events in children with SCD.

Biomarkers and Disease Severity in Children With Community-Acquired Pneumonia

BACKGROUND

Host biomarkers predict disease severity in adults with community-acquired pneumonia (CAP). We evaluated the association of the white blood cell (WBC) count, absolute neutrophil count (ANC), C-reactive protein (CRP), and procalcitonin with the development of severe outcomes in children with CAP.

METHODS

We performed a prospective cohort study of children 3 months to 18 years of age with CAP in the emergency department. The primary outcome was disease severity: mild (discharged from the hospital), mild-moderate (hospitalized but not moderate-severe or severe), moderate-severe (eg, hospitalized with receipt of intravenous fluids, supplemental oxygen, complicated pneumonia), and severe (eg, intensive care, vasoactive infusions, chest drainage, severe sepsis). Outcomes were examined within the cohort with suspected CAP and in a subset with radiographic CAP.

RESULTS

Of 477 children, there were no statistical differences in the median WBC count, ANC, CRP, or procalcitonin across severity categories. No biomarker had adequate discriminatory ability between severe and nonsevere disease (area under the curve [AUC]: 0.53-0.6 for suspected CAP and 0.59-0.64 for radiographic CAP). In analyses adjusted for age, antibiotic use, fever duration, and viral pathogen detection, CRP was associated with moderate-severe disease (odds ratio 1.12; 95% confidence interval, 1.0-1.25). CRP and procalcitonin revealed good discrimination of children with empyema requiring chest drainage (AUC: 0.83) and sepsis with vasoactive infusions (CRP AUC: 0.74; procalcitonin AUC: 0.78), although prevalence of these outcomes was low.

CONCLUSIONS

WBC count, ANC, CRP, and procalcitonin are generally not useful to discriminate nonsevere from severe disease in children with CAP, although CRP and procalcitonin may have some utility in predicting the most severe outcomes.

The distribution characteristics of intestinal microbiota in children with community-acquired pneumonia under five Years of age

Pneumonia is the leading cause of morbidity and mortality in children under five years of age worldwide. Over the past decades, studies have shown that the upper respiratory pathogens are closely related to the occurrence of pneumonia. However, the co-occurrence of gut microbiome dysbiosis may have clinical manifestation in the prognosis of childhood pneumonia. The aim of the present study is to investigate the differences in gut microbial communities between children's diagnosed community-acquired pneumonia (CAP) under five compared to healthy controls in Inner Mongolia. Fecal samples were collected from children with CAP and healthy controls (<5 years old) and the genomic microbiome 16S rRNA was amplified using the hypervariable V4 region and subjected to MiSeq Illumina sequencing, and then analyzed for microbiota composition and phenotype. Finally functional profiling was performed by KEGG pathways analyses. Our results revealed a gut microbiota dysbiosis in children with CAP. Distinct gut microbiome composition and structure were associated with childhood CAP between two age categories compared to healthy controls. In addition, the phylogenic phenotype's prediction was found to be significantly different between the groups. The prominent genera in age group of 0-3 were Bifidobacterium and Enterococcus. On the contrary, Escherichia-Shigella, Prevotella, Faecalibacterium and Enterobacter were remarkably decreased in most of the fecal samples from CAP patients in age group of 0-3 compared to the control. At the genus level, the CAP children in the age group of 4-5 showed an increase in the abundance of Escherichia/Shigella, Bifidobacterium, Streptococcus and Psychrobacter and, a decrease in the abundance of Faecalibacterium, Bacteroides, Lachnospiraceae and Ruminococcus compared with the matched healthy controls. Moreover, CAP children in both age groups exhibited distinct profiles in the KEGG functional analysis. Our data revealed that the gut microbiota differ between CAP patients and health children and certain gut microbial species are associated with CAP. Further research to identify specific microbial species which may contribute to the development CAP are merited. In addition, rectification of microbiota dysbiosis may provide supplemental benefits for treatment of the childhood CAP.

Blood biomarkers differentiating viral versus bacterial pneumonia aetiology: a literature review

Background and objectives

The goal of this literature review is to compare current studies regarding the accuracy of different serum markers in differentiating viral from bacterial pneumonia in the pediatric population with what is employed in the medical settings at present. Currently there is still a lack of significant research, that would give us evaluation on biomarkers benefits towards getting a definite diagnosis of pneumonia. Finding out the potential of biomarkers to differentiate between viral and bacterial pneumonia is also important because knowing the exact pathogen would prevent irrational use of antibiotics. At present, irrational, broad-spectrum antibiotic use and increasing antibiotic resistance in microorganisms are still one of the greatest challenges in clinical settings. The use of biomarkers in clinical practice would not only facilitate accurate diagnosis, but would also help to reduce the amount of antibiotics overuse.

Materials and methods

Literature search conducted on Medline and Google Scholar using a combination of terms. Articles that were in English and within ten years of the search date were manually sorted according to inclusion and exclusion criteria. Results: Initial search returned n = 13,408. After activating filters, n = 140 were identified of which n = 12 included for literature review.

Conclusions

Rise or drop in the concentration of a single marker is not accurate enough for predicting viral/bacterial community acquired pneumonia. This is because there is overlapping to a varying extent depending on the marker cut-off values, detection methods, analyses, the desired specificity, and sensitivity. Furthermore, the presence of mixed infection makes almost all markers suboptimal to be used universally. New markers such as MxA1 and HMGB1 gave promising results. However, to replicate a similar testing condition in a clinical environment may not be practical. Another approach is to make use of more than one marker and combine with clinical signs and symptoms. This may not be cost-effective in many clinical settings; nevertheless, in many studies, marker combination greatly improved the predictive power.

Utility of predictive tools for risk stratification of elderly individuals with all-cause acute respiratory infection

PURPOSE

A number of scoring tools have been developed to predict illness severity and patient outcome for proven pneumonia, however, less is known about the utility of clinical prediction scores for all-cause acute respiratory infection (ARI), especially in elderly subjects who are at increased risk of poor outcomes.

METHODS

We retrospectively analyzed risk factors and outcomes of individuals ≥ 60 years of age presenting to the emergency department with a clinical diagnosis of ARI.

RESULTS

Of 276 individuals in the study, 40 had proven viral infection and 52 proven bacterial infection, but 184 patients with clinically adjudicated ARI (67%) remained without a proven microbial etiology despite extensive clinical (and expanded research) workup. Patients who were older, had multiple comorbidities, or who had proven bacterial infection were more likely to require hospital and ICU admission. We identified a novel model based on 11 demographic and clinical variables that were significant risk factors for ICU admission or mortality in elderly subjects with all-cause ARI. As comparators, a modified PORT score was found to correlate more closely with all-cause ARI severity than a modified CURB-65 score (r, 0.54, 0.39). Interestingly, modified Jackson symptom scores were found to inversely correlate with severity (r, - 0.34) but show potential for differentiating viral and bacterial etiologies.

CONCLUSIONS

Modified PORT, CURB-65, Jackson symptom scores, and a novel ARI scoring tool presented herein all offer predictive ability for all-cause ARI in elderly subjects. Such broadly applicable scoring metrics have the potential to assist in treatment and triage decisions at the point of care.

Blood circRNAs as biomarkers for the diagnosis of community-acquired pneumonia

Circular RNAs (circRNAs) have been reported as effective diagnostic and therapeutic biomarkers in many diseases, but the potential of using this easy-to-monitor and highly stable materials for diagnosing Community-acquired pneumonia (CAP) remains unexplored. Here, aiming to identify potential CAP-related circRNAs in peripheral blood and seeking to deepen the understanding of how circRNA-miRNA-mRNA regulatory networks may contribute to CAP, we applied microarrays profiling analysis and identified 8296 differentially expressed (DE) circRNAs between patients with CAP (n = 6) and healthy controls (n = 6). Subsequently, we validated the accumulation trends for the top 100 DE circRNAs based on qPCR in an independent validation cohort (30 patients vs 30 controls), and ultimately identified a panel of four circRNAs that perform extremely well as sensitive and specific biomarkers for diagnosing CAP: hsa_circ_0018429 (area under the curve [AUC] = 0.8216), hsa_circ_0026579 (AUC = 0.7733), hsa_circ_0125357 (AUC = 0.7730), and hsa_circ_0099188 (AUC = 0.6978); combined as a panel (AUC = 0.8776). In addition, hsa_circ_0026579 exhibited good performance in differentiating viral from bacterial or mixed infection, with an AUC of 0.863. We also identified 10 miRNAs that most likely to interact with these four circRNAs, and then predicted 205 mRNA target genes. The KEGG pathway enrichment analysis suggested highly plausible functional implications related to inflammation and to virus-infection-related signaling pathways (such as HTLV-1 infection and hepatitis B infection). Thus, we generated a genetic network of potential CAP-related regulatory interactions that should inform future hypothesis-driven research into the causes and potential treatment of this widespread and frequently fatal disease.

Investigating Pneumonia Etiology Among Refugees and the Lebanese population (PEARL): A study protocol

Background: Community-acquired pneumonia (CAP), a leading cause of mortality, mainly affects children in developing countries. The harsh circumstances experienced by refugees include various factors associated with respiratory pathogen transmission, and clinical progression of CAP. Consequently, the etiology of CAP in humanitarian crisis situations may differ to that of settled populations, which would impact appropriate case management. Therefore, the Pneumonia Etiology Among Refugees and the Lebanese population (PEARL) study was initiated with the objective of identifying the causal pathogenic microorganisms in the respiratory tract of children and adults from both the refugee and host country population presenting with signs of CAP during a humanitarian crisis.

Methods: PEARL, a prospective, multicentric, case-control study, will be conducted at four primary healthcare facilities in Tripoli and the Bekaa valley over 15 months (including two high-transmission seasons/winters). Sociodemographic and medical data, and biological samples will be collected from at least 600 CAP cases and 600 controls. Nasopharyngeal swabs, sputum, urine and blood samples will be analyzed at five clinical pathology laboratories in Lebanon to identify the bacterial and viral etiological agents of CAP. Transcriptomic profiling of host leukocytes will be performed.

Conclusions: PEARL is an original observational study that will provide important new information on the etiology of pneumonia among refugees, which may improve case management, help design antimicrobial stewardship interventions, and reduce morbidity and mortality due to CAP in a humanitarian crisis.

Cytokines in the Respiratory Airway as Biomarkers of Severity and Prognosis for Respiratory Syncytial Virus Infection: An Update

The human respiratory syncytial virus (hRSV) is one of the most important causes of upper and lower respiratory tract infections in children and the main cause of bronchiolitis worldwide. Disease manifestations caused by hRSV may vary from mild to severe, occasionally requiring admission and hospitalization in intensive care units. Despite the high morbidity rates associated to bronchiolitis, treatment options against hRSV are limited and there are no current vaccination strategies to prevent infection. Importantly, the early identification of high-risk patients can help improve disease management and prevent complications associated with hRSV infection. Recently, the characterization of pro- and anti-inflammatory cytokine patterns produced during hRSV-related inflammatory processes has allowed the identification of potential prognosis biomarkers. A suitable biomarker should allow predicting the severity of the infection in a simple and opportune manner and should ideally be obtained from non-invasive samples. Among the cytokines associated with hRSV disease severity, IL-8, interferon-alpha (IFN-alpha), and IL-6, as well as the Th2-type cytokines thymic stromal lymphopoietin (TSLP), IL-3, and IL-33 have been highlighted as molecules with prognostic value in hRSV infections. In this review, we discuss current studies that describe molecules produced by patients during hRSV infection and their potential as biomarkers to anticipate the severity of the disease caused by this virus.