Review of Non-Bacterial Infections in Respiratory Medicine: Viral Pneumonia

Viral Pneumonia during the COVID-19 Pandemic, 2019-2021 Evoking Needs for SARS-CoV-2 and Additional Vaccinations

Coronaviruses can cause pneumonia, with clinical symptoms that may be similar to the symptoms of other viral pneumonias. To our knowledge, there have been no reports regarding cases of pneumonia caused by coronaviruses and other viruses among hospitalized patients in the past 3 years before and during coronavirus disease 2019 (COVID-19). Here, we analysed the causes of viral pneumonia among hospitalized patients during the coronavirus disease 2019 (COVID-19) pandemic (2019-2021). Between September 2019 and April 2021, patients hospitalized at Shuang Ho Hospital in north Taiwan with a diagnosis of pneumonia were enrolled in this study. Age, sex, onset date, and season of occurrence were recorded. Respiratory tract pathogens were identified with molecular detection using the FilmArray^® platform from nasopharyngeal swabs. In total, 1147 patients (128 patients aged <18 years and 1019 patients aged ≥18 years) with pneumonia and identified respiratory tract pathogens were assessed. Among the 128 children with pneumonia, the dominant viral respiratory pathogen was rhinovirus (24.2%), followed by respiratory syncytial virus (RSV; 22.7%), parainfluenza virus (1 + 2 + 3 + 4) (17.2%), adenovirus (12.5%), metapneumovirus (9.4%), coronavirus (1.6%), and influenza virus (A + B) (1.6%). Among the 1019 adults with pneumonia, the dominant viral respiratory pathogen was rhinovirus (5.0%), followed by RSV (2.0%), coronavirus (2.0%), metapneumovirus (1.5%), parainfluenza virus (1 + 2 + 3 + 4) (1.1%), adenovirus (0.7%), and influenza virus (A + B) (0%). From 2019-2021, older patients (aged >65 years) with pneumonia tested positive for coronavirus most commonly in autumn. Coronavirus was not detected during summer in children or adults. Among children aged 0-6 years, RSV was the most common viral pathogen, and RSV infection occurred most often in autumn. Metapneumovirus infection occurred most often in spring in both children and adults. In contrast, influenza virus was not detected in patients with pneumonia in any season among children or adults from January 2020 to April 2021. Among all patients with pneumonia, the most common viral pathogens were rhinovirus in spring, adenovirus and rhinovirus in summer, RSV and rhinovirus in autumn, and parainfluenza virus in winter. Among children aged 0-6 years, RSV, rhinovirus, and adenovirus were detected in all seasons during the study period. In conclusion, the proportion of pneumonia cases caused by a viral pathogen was higher in children than the proportion in adults. The COVID-19 pandemic period evoked a need for SARS-CoV-2 (severe acute respiratory disease coronavirus 2) vaccination to prevent the severe complications of COVID-19. However, other viruses were also found. Vaccines for influenza were clinically applied. Active vaccines for other viral pathogens such as RSV, rhinovirus, metapneuomoccus, parainfluenza, and adenovirus may need to be developed for special groups in the future.

Pneumonia Detection Using Enhanced Convolutional Neural Network Model on Chest X-Ray Images

Pneumonia, caused by microorganisms, is a severely contagious disease that damages one or both the lungs of the patients. Early detection and treatment are typically favored to recover infected patients since untreated pneumonia can lead to major complications in the elderly (>65 years) and children (<5 years). The objectives of this work are to develop several models to evaluate big X-ray images (XRIs) of the chest, to determine whether the images show/do not show signs of pneumonia, and to compare the models based on their accuracy, precision, recall, loss, and receiver operating characteristic area under the ROC curve scores. Enhanced convolutional neural network (CNN), VGG-19, ResNet-50, and ResNet-50 with fine-tuning are some of the deep learning (DL) algorithms employed in this study. By training the transfer learning model and enhanced CNN model using a big data set, these techniques are used to identify pneumonia. The data set for the study was obtained from Kaggle. It should be noted that the data set has been expanded to include further records. This data set included 5863 chest XRIs, which were categorized into 3 different folders (i.e., train, val, test). These data are produced every day from personnel records and Internet of Medical Things devices. According to the experimental findings, the ResNet-50 model showed the lowest accuracy, that is, 82.8%, while the enhanced CNN model showed the highest accuracy of 92.4%. Owing to its high accuracy, enhanced CNN was regarded as the best model in this study. The techniques developed in this study outperformed the popular ensemble techniques, and the models showed better results than those generated by cutting-edge methods. Our study implication is that a DL models can detect the progression of pneumonia, which improves the general diagnostic accuracy and gives patients new hope for speedy treatment. Since enhanced CNN and ResNet-50 showed the highest accuracy compared with other algorithms, it was concluded that these techniques could be effectively used to identify pneumonia after performing fine-tuning.

Identification and quantification of nine compounds in Fangwen Jiuwei decoction by liquid chromatography-mass spectrometry

Fangwen Jiuwei Decoction is a traditional Chinese medicine preparation for the treatment of pneumonia developed by Shenzhen Bao'an Chinese Medicine Hospital, which shows remarkable clinical responses. Qualitative and quantitative analyses of the main active compounds are crucial for the quality control of traditional Chinese medicine prescription in clinical application. In this study, we identified nine active compounds essential for the pharmacological effects of Fangwen Jiuwei Decoction based on the analysis of the Network Pharmacology and relevant literature. Moreover, these compounds can interact with several crucial drug targets in pneumonia based on molecular docking. We applied high-performance liquid chromatography-tandem mass spectrometry method was established these nine active ingredients' qualitative and quantitative detections. The possible cleavage pathways of nine active components were determined based on secondary ions mass spectrometry. The results of high-performance liquid chromatography-tandem mass spectrometry were further validated, which show a satisfactory correlation coefficient (r > 0.99), recovery rate (≥93.31%), repeatability rate (≤5.62%), stability (≤7.95%), intra-day precision (≤6.68%), and inter-day precision (≤9.78%). The limit of detection was as low as 0.01 ng/ml. In this study, we established a high-performance liquid chromatography-tandem mass spectrometry method to qualitatively and quantitatively analyze the chemical components in the Fangwen Jiuwei Decoction extract.

Prepandemic viral community-acquired pneumonia: Diagnostic sensitivity and specificity of nasopharyngeal swabs and performance of clinical severity scores

The objectives of this work were to assess the diagnostic sensitivity and specificity of nasopharyngeal (NP) swabs for viral community-acquired pneumonia (CAP) and the performance of pneumonia severity index (PSI) and CURB-65 severity scores in the viral CAP in adults. A prospective observational cohort study of consecutive 341 hospitalized adults with CAP was performed between January 2018 and March 2020. Demographics, comorbidities, symptoms/signs, analytical data, severity scores, antimicrobials, and outcomes were recorded. Blood, NP swabs, sputum, and urine samples were collected at admission and assayed by multiplex real time-PCR, bacterial cultures, and Streptococcus pneumoniae and Legionella pneumophila antigens detection, to determine the etiologies and quantify the viral load. The etiology was identified in 174 (51.0%) patients, and in 85 (24.9%) it was viral, the most frequent rhinovirus and influenza virus. The sensitivity of viral detection in sputum (50.7%) was higher than in NP swabs (20.9%). Compared with sputum, the positive predictive value and specificity of NP swabs for viral diagnosis were 95.8% and 96.9%, respectively. Performance of PSI and CURB-65 scores in all CAP with etiologic diagnosis were as expected, with mortality associated with higher values, but they were not associated with mortality in patients with viral pneumonia. NP swabs have lower sensitivity but high specificity for the diagnosis of viral CAP in adults compared with sputum, reinforcing the use NP swabs for the diagnostic etiology work-up. The PSI and CURB-65 scores did not predict mortality in the viral CAP, suggesting that they need to be updated scores based on the identification of the etiological agent.

Mapping theme trends and recognizing hot spots in viral pneumonia: a bibliometric analysis of global research

BACKGROUND

The challenges that viral pneumonia poses to the global public health system remain daunting. In this study, an analysis of publications on viral pneumonia over the past two decades was conducted. Through this work, we hope to provide inspiration for future research on viral pneumonia.

METHODS

We extracted all of the English publications relevant to viral pneumonia published during 1999-2019 from Web of Science. GraphPad Prism, CiteSpace, and VOSviewer were used to collect and analyze the publication trends in related fields.

RESULTS

We identified 2,006 publications with 62,155 citations as of February 16, 2021. The United States accounted for the largest number of publications (34.2%), with the highest number of citations (27,616) and the highest h-index (78). China ranked second in the number of publications. Ctr Dis Control & Prevent proved to be the center of research cooperation. Clinical Infectious Diseases included the most papers published relating to the topic of viral pneumonia. Chan KH published the most papers in this field (25), while an article from Fouchier RAM presented the highest citation frequency (1,275).

CONCLUSIONS

According to the bibliometric analysis database and related software results, the United States dominates the field of viral pneumonia research. The key term extracted by VOSviewer has shifted to "Diagnosis and management", indicating a new trend for viral pneumonia research.

Incidence and disease burden of community-acquired pneumonia in southeastern China: data from integrated medical resources

Community-acquired pneumonia (CAP) is a lower respiratory tract infection. It is one of the commonest infectious diseases and the third leading cause of death worldwide. However, the epidemiological profiles of CAP in southeastern China are unknown. Data of inpatients and outpatients diagnosed with CAP from January 1, 2015 to December 31, 2020 were obtained from the National Healthcare Big Data in Fuzhou (Fuzhou Database). This database covers medical data from 37 hospitals and 159 community health service stations. The incidence rate, treatment pattern, and direct medical costs of CAP were assessed using clinical data. A total of 8,156,237 patients were enrolled, with a mean age of 33.72 ± 20.88 years. The overall incidence rate of CAP was 3.13 (95% confidence interval [CI]: 3.11-3.15) per 1000 person-years (PY), with 15.97 (95% CI: 15.85-16.08) per 1000 PY in children below 5 years old and 2.62 (95% CI: 2.57-2.66) per 1000 PY in the elderly ≥60 years. The cost per outpatient was $242.83 ± 341.62, and the cost per inpatient was $4,530.4 ± 9,151.68. The three most used therapeutic drugs in patients with CAP are cefotaxime, moxifloxacin, and azithromycin. In addition, despite the ability of both imported and domestic pneumococcal conjugate vaccines to reduce the incidence rate of CAP, the current vaccination coverage rates were relatively low. We suggest that more attention should be paid to the disease burden of CAP, especially due to its great economic burden in China.

Network-based pharmacology to predict the mechanism of Ginger and Forsythia combined treatment of viral pneumonia

BACKGROUND

Viral pneumonia (VP) is a common inflammatory disease caused by a virus in the upper respiratory tract. However, current treatment options for pneumonia are limited because of the strong infectivity and lack of research.

METHOD

Based on various databases, the mechanisms of Ginger and Forsythia were predicted by network pharmacology. The possible active ingredients of Ginger and Forsythia were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and screened by pharmacokinetic parameters. Their possible targets were predicted by the TCMSP database. The VP-related targets were collected from the GeneCards and OMIM databases. The compound-target-disease network was visualized by Cytoscape 3.7.1. In addition, the protein functional annotation and identification of signalling pathways of possible targets were performed with Gene Ontology (GO) and KEGG enrichment analysis. Molecular docking was finally employed for in silico simulation matching between representative Ginger and Forsythia compounds and their core genes.

RESULTS

Twenty-eight active ingredients of Ginger and Forsythia were found and 30 common targets for the combined treatment of VP were obtained. The enrichment analysis of GO functions and KEGG pathways included 186 GO function entries and 56 KEGG pathways. Molecular docking showed that the main ingredients can closely bind three targets (CASP3, JUN, and ESR1). Thus, Ginger and Forsythia play significant roles in the prevention and treatment of VP, and this study showed their mechanism was "multicomponent, multitarget, and multipathway" for the prevention and treatment of VP.

CONCLUSION

We successfully predicted the active components and targets of Ginger and Forsythia for prevention and treatment of VP. This may systematically clarify its mechanism of action and provide a direction for future research.

Laboratory Tests and Outcome for Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 causes coronavirus disease 2019 (COVID-19) and poses substantial challenges for healthcare systems. With a vastly expanding number of publications on COVID-19, clinicians need evidence synthesis to produce guidance for handling patients with COVID-19. In this systematic review and meta-analysis, we examine which routine laboratory tests are associated with severe COVID-19 disease.

CONTENT

PubMed (Medline), Scopus, and Web of Science were searched until March 22, 2020, for studies on COVID-19. Eligible studies were original articles reporting on laboratory tests and outcome of patients with COVID-19. Data were synthesized, and we conducted random-effects meta-analysis, and determined mean difference (MD) and standard mean difference at the biomarker level for disease severity. Risk of bias and applicability concerns were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2.

SUMMARY

45 studies were included, of which 21 publications were used for the meta-analysis. Studies were heterogeneous but had low risk of bias and applicability concern in terms of patient selection and reference standard. Severe disease was associated with higher white blood cell count (MD, 1.28 ×109/L), neutrophil count (MD, 1.49 ×109/L), C-reactive protein (MD, 49.2 mg/L), lactate dehydrogenase (MD, 196 U/L), D-dimer (standardized MD, 0.58), and aspartate aminotransferase (MD, 8.5 U/L); all p < 0.001. Furthermore, low lymphocyte count (MD -0.32 × 109/L), platelet count (MD -22.4 × 109/L), and hemoglobin (MD, -4.1 g/L); all p < 0.001 were also associated with severe disease. In conclusion, several routine laboratory tests are associated with disease severity in COVID-19.

Non-influenza respiratory viruses in adult patients admitted with influenza-like illness: a 3-year prospective multicenter study

PURPOSE

To describe the burden, and characteristics, of influenza-like illness (ILI) associated with non-influenza respiratory viruses (NIRV).

METHODS

We performed a prospective, multicenter, observational study of adults admitted with ILI during three influenza seasons (2012-2015). Patients were screened for picornavirus, respiratory syncytial virus (RSV), coronavirus, human metapneumovirus, adenovirus, bocavirus, parainfluenza virus, and influenza, by PCR on nasopharyngeal samples. We excluded patients coinfected with NIRV and influenza.

RESULTS

Among 1421 patients enrolled, influenza virus was detected in 535 (38%), and NIRV in 215 (15%), mostly picornavirus (n = 61), RSV (n = 53), coronavirus 229E (n = 48), and human metapneumovirus (n = 40). In-hospital mortality was 5% (NIRV), 4% (influenza), and 5% (no respiratory virus). As compared to influenza, NIRV were associated with age (median, 73 years vs. 68, P = 0.026), chronic respiratory diseases (53% vs. 45%, P = 0.034), cancer (14% vs. 9%, P = 0.029), and immunosuppressive drugs (21% vs. 14%, P = 0.028), and inversely associated with diabetes (18% vs. 25%, P = 0.038). On multivariable analysis, only chronic respiratory diseases (OR 1.5 [1.1-2.0], P = 0.008), and diabetes (OR 0.5 [0.4-0.8], P = 0.01) were associated with NIRV detection.

CONCLUSIONS

NIRV are common in adults admitted with ILI during influenza seasons. Outcomes are similar in patients with NIRV, influenza, or no respiratory virus.

Acute respiratory failure among lung transplant adults requiring intensive care: Changing spectrum of causative organisms and impact of procalcitonin test in the diagnostic workup

BACKGROUND

The aim was to identify the causing organisms and assess the association of procalcitonin (PCT) with bacterial pneumonia within 24 hours of intensive care unit admission (ICU-A) among lung transplant (LT) adult recipients.

METHODS

Secondary analysis from a prospective cohort study. All LT adults admitted to ICU for acute respiratory failure (ARF) over 5 years were included. Patients were followed until hospital discharge or death.

RESULTS

Fifty-eight consecutive LT patients were enrolled. The most important cause of ICU-A due to ARF was pneumonia 29 (50%) followed by acute rejection 3 (5.2%) and bronchiolitis obliterans syndrome exacerbation 3 (5.2%). Microorganisms were isolated from 22/29 cases with pneumonia (75.9%): 17 (77.2%) bacterial, 4 (18.2%) viral, 1 (4.5%) Aspergillus fumigates, with Pseudomonas aeruginosa being the most common cause (45.5%) of pneumonia, with 10 patients presenting chronic colonization by P aeruginosa. Median [Interquartile range (IQR)] PCT levels within 24 hours after admission were higher in pneumonia (1.5 µg/L; IQR:0.3-22.0), than in non-pneumonia cases (0.2 µg/L; IQR:0.1-0.7) (P = .019) and PCT levels within 24 hours helped to discriminate bacterial pneumonia (8.2 µg/L; IQR:0.2-43.0) from viral pneumonia and non-pneumonia cases (0.2 µg/L; IQR:0.1-0.7). The overall negative predictive value for bacterial pneumonia was 85.1%, increasing to 91.6% among episodes after 6 months of LT.

CONCLUSIONS

Causes of severe pneumonia in LT are changing, with predominant role of P aeruginosa and respiratory viruses. PCT ≤ 0.5 μg/L within 24 hours helps to exclude bacterial pneumonia diagnosis in LT adults requiring ICU-A. A negative PCT test allows antimicrobial de-escalation and requires an alternative diagnostic to bacterial pneumonia.

Influenza species and subtypes circulation among hospitalized patients in Laleh hospital during two influenza seasonal (2016-2017 and 2017-2018) using a multiplex Real Time-Polymerase Chain Reaction

The introduction of polymerase chain reaction (PCR) techniques has improved the detection of respiratory viruses, particularly with the use of multiplex real-time technique with the capability of simultaneous detection of various pathogens in a single reaction. The aim of this study was to apply the above technology for the diagnosis of influenza infections and at the same time to differentiate between common flu species between hospitalized patients in Laleh hospital (Iran) between two flu seasons (2016-2017 and 2017-2018). Different respiratory specimens were collected from 540 patients from a period of December 2016 to May 2018 and were sent to the laboratory for molecular diagnosis. RNAs were extracted and subsequently, a multiplex real time PCR identifying flu A, flu B and typing flu A (H1N1) was carried out. The mean age of patients was 47.54±23.96. 216 (40%) and 321 (60%) of subjects were male and female, respectively. 219 out of 540 (40.5%) were positive for influenza infection including flu A (n=97, 44.3%), flu A (H1N1) (n=45, 20.7%) and flu B (n=77, 35%). Flu A was the dominant species on 2016-2017 and flu B was the major species on 2017-2018. Flu A (H1N1) was comparable in both time periods. Flu infections were most frequently diagnosed in age groups 21-40. Flu-positive patients suffered more from body pain and sore throat than flunegative patients with significant statistical difference (P values <0.001). The mean duration of hospitalization was shorter for flu-positive patients (P value = 0.016). Application of multiplex real time PCR could facilitate the influenza diagnosis in a short period of time, benefiting patients from exclusion of bacterial infections and avoiding unnecessary antibiotic therapy. Influenza diagnosis was not achieved in up to 60% of flu-like respiratory infections, suggesting the potential benefit of adopting the same methodology for assessing the involvement of other viral or/and bacterial pathogens in those patients.

Biomarkers in Pneumonia-Beyond Procalcitonin

Pneumonia is the leading infectious cause of mortality worldwide and one of the most common lower respiratory tract infections that is contributing significantly to the burden of antibiotic consumption. Due to the complexity of its pathophysiology, it is widely accepted that clinical diagnosis and prognosis are inadequate for the accurate assessment of the severity of the disease. The most challenging task for a physician is the risk stratification of patients with community-acquired pneumonia. Herein, early diagnosis is essential in order to reduce hospitalization and mortality. Procalcitonin and C-reactive protein remain the most widely used biomarkers, while interleukin 6 has been of particular interest in the literature. However, none of them appear to be ideal, and the search for novel biomarkers that will most sufficiently predict the severity and treatment response in pneumonia has lately intensified. Although our insight has significantly increased over the last years, a translational approach with the application of genomics, metabolomics, microbiomics, and proteomics is required to better understand the disease. In this review, we discuss this rapidly evolving area and summarize the application of novel biomarkers that appear to be promising for the accurate diagnosis and risk stratification of pneumonia.

Use of an innovative and non-invasive device for virologic sampling of cough aerosols in patients with community and hospital acquired pneumonia: a pilot study

BACKGROUND

The aetiology of lower respiratory tract infections is challenging to investigate. Despite the wide array of diagnostic tools, invasive techniques, such as bronchoalveolar lavage (BAL), are often required to obtain adequate specimens. PneumoniaCheckTM is a new device that collects aerosol particles from cough, allowing microbiological analyses. Up to now it has been tested only for bacteria detection, but no study has investigated its usefulness for virus identification.

METHODS

In this pilot study we included 12 consecutive patients with pneumonia. After testing cough adequacy via a peak flow meter, a sampling with PneumoniaCheckTM was collected and a BAL was performed in each patient. Microbiological analyses for virus identification were performed on each sample and concordance between the two techniques was tested (sensitivity, specificity and positive/negative predictive values), taking BAL results as reference.

RESULTS

BAL was considered adequate in 10 patients. Among them, a viral pathogen was identified by PneumoniaCheckTM 6 times, each on different samples, whereas BAL allowed to detect the presence of a virus on 7 patients (14 positivities). Overall, the specificity for PneumoniaCheckTM to detect a virus was 100%, whereas the sensitivity was 66%. When considering only herpes viruses, PneumoniaCheckTM showed a lower sensitivity, detecting a virus in 1/4 of infected patients (25%).

CONCLUSIONS

In this pilot study PneumoniaCheckTM showed a good correlation with BAL for non-herpes virologic identification in pneumonia patients, providing excellent specificity. Further studies on larger population are needed to confirm these results and define its place in the panorama of rapid diagnostic tests for lower respiratory tract infections.