Atypical Pneumonia: Definition, Causes, and Imaging Features

Pulmonary Infection

Pneumonia is a significant cause of morbidity and mortality in the community and hospital settings. Bacterial, viral, mycobacterial, and fungal pathogens are all potential causative agents of pulmonary infection. Chest radiographs and computed tomography are frequently utilized in the assessment of pneumonia. Learning the imaging patterns of different potential organisms allows the radiologist to formulate an appropriate differential diagnosis. An organism-based approach is used to discuss the imaging findings of different etiologies of pulmonary infection.

Imaging in pulmonary infections of immunocompetent adult patients

Pneumonia is a clinical syndrome characterised by fever, cough and alveolar infiltration of purulent fluid, caused by infection with a microbial pathogen. It can be caused by infections with bacteria, viruses or fungi, but a causative organism is identified in less than half of cases. The most common type of pneumonia is community-acquired pneumonia, which is caused by infections acquired outside the hospital. Current guidelines for pneumonia diagnosis require imaging to confirm the clinical suspicion of pneumonia. Thus, imaging plays an important role in both the diagnosis and management of pneumonia, with each modality having specific advantages and limitations. Chest radiographs are commonly used but have limitations in terms of sensitivity and specificity. Lung ultrasound shows high sensitivity and specificity. Computed tomography scans offer higher diagnostic accuracy but involve higher radiation doses. Radiological patterns, including lobar, lobular and interstitial pneumonia, provide valuable insights into causative pathogens and treatment decisions. Understanding these radiological patterns is crucial for accurate diagnosis. In this review, we will summarise the most important aspects pertaining to the role of imaging in pneumonia and will highlight the imaging characteristics of the most common causative organisms.

NEAT1 in inflammatory infectious diseases: An integrated perspective on molecular modulation

The long non-coding RNA (lncRNA), NEAT1, has emerged as a central figure in the intricate network of molecular regulators in inflammatory infectious diseases (IIDs). The review initiates a comprehensive exploration of NEAT1's multifaceted roles and molecular interactions in the context of these complex diseases. The study begins by acknowledging the global health burden of IIDs, underscoring the urgency for innovative insights into their pathogenesis and therapeutic avenues. NEAT1 is introduced as a pivotal lncRNA with growing relevance in immune responses and inflammatory processes. The core of this review unravels the NEAT1 landscape, elucidating its involvement in the modulation of immune signalling pathways, regulation of inflammatory cytokines, and interactions with various immune cells during infection. It explores NEAT1's role in orchestrating immune responses and balancing host defence mechanisms with the risk of immunopathology. Furthermore, the review underscores the clinical significance of NEAT1 in infectious diseases, discussing its associations with disease severity, prognosis, and potential as a diagnostic and therapeutic target. It provides insights into ongoing research endeavours aimed at harnessing NEAT1 for innovative disease management strategies, including developing RNA-based therapeutics. Concluding on a forward-looking note, the review highlights the broader implications of NEAT1 in the context of emerging infectious diseases and the possibility for precision medicine approaches that leverage NEAT1's regulatory capacities. In summary, this review illuminates the pivotal role of NEAT1 in IIDs by navigating its complex landscape, offering profound insights into its implications for disease pathogenesis and the development of targeted therapies.

First report of an outbreak of "Q" fever IN an abattoir from Argentina

In late October 2021, one of the veterinarians and the occupational physician of a bovine and swine abattoir from Entre Ríos Province, Argentina were alerted about workers with atypical pneumonia symptoms, raising suspicious of a possible Q fever outbreak. An outbreak epidemiological investigation was carried out. Analysis was based on the description of the study population, according to gender, age, symptoms, and position within the abattoir, as well as on outbreak epidemic curve and its probable origin. Cases of Q fever in the workers were confirmed by serology. Measurements of the association between the evaluated variables and the risk of exposure were investigated and calculated as attack rates. The outbreak occurred between October and November 2021, symptomatically affecting 11 workers, out of a total exposed population of 49 individuals. The index case was a 33-year-old male who started with symptoms on 27 October 2021, and the outbreak extended for at least 17 days. Workers in the clean zone of the slaughter floor had a 4.68 times higher risk of contracting Q fever than people located in other areas. Importantly, two pregnant cows were slaughtered a few days before the outbreak began, which could have been the origin of the outbreak. The present study demonstrates the urgent need to consider Q fever when diagnosing abortive diseases of ruminants in Argentina, as well as in zoonotic disease epidemiological surveillance to inform all actors of the health system.

Microbial Landscape and Antibiotic-Susceptibility Profiles of Microorganisms in Patients with Bacterial Pneumonia: A Comparative Cross-Sectional Study of COVID-19 and Non-COVID-19 Cases in Aktobe, Kazakhstan

This cross-sectional study investigated the microbial landscape and antibiotic-resistance patterns in patients with bacterial pneumonia, with a focus on the impact of COVID-19. Sputum samples from individuals with bacterial pneumonia, including coronavirus disease 2019-positive polymerase chain reaction (COVID-19-PCR+), COVID-19-PCR- and non-COVID-19 patients, were analyzed. Surprisingly, the classic etiological factor of bacterial pneumonia, Streptococcus pneumoniae, was rarely isolated from the sputum samples. Furthermore, the frequency of multidrug-resistant pathogens was found to be higher in non-COVID-19 patients, highlighting the potential impact of the pandemic on antimicrobial resistance. Strains obtained from COVID-19-PCR+ patients exhibited significant resistance to commonly used antibiotics, including fluoroquinolones and cephalosporins. Notably, the ESKAPE pathogens, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterobacter cloacae, and Enterobacter aerogenes, were identified among the isolated microorganisms. Our findings underscore the urgent need for infection control measures and responsible antibiotic use in healthcare settings, as well as the importance of enhancing pneumonia diagnostics and implementing standardized laboratory protocols.

A Rare Case of Community-Acquired Pneumonia Only Presenting With Diarrhea, Abdominal Pain, and Fever: A Case Report

Legionnaires' disease is an atypical pneumonia caused by Legionella pneumophila (L. pneumophila) pneumonia that features slow onset, nonproductive cough, fatigue, headache, sore throat, myalgias, and malaise. It can be difficult to diagnose, as it presents with extrapulmonary symptoms, and delay in treatment can be fatal. Here, we present the case of a previously healthy 32-year-old Caucasian male with Legionnaires disease who only presented to the clinic with abdominal pain and diarrhea. The patient did not have any pulmonary symptoms at the initial presentation. This presentation did not fit the diagnostic tools available for Legionnaires' disease, including a validated clinical prediction rule, which ruled out L. pneumophila infection with a sensitivity of 97% and a negative predictive value of 99.4%. Due to the complaint of abdominal pain, a flat/upright abdominal X-ray was ordered, which includes a chest X-ray. Upon analyzing the chest X-ray, a right lower lobe consolidation was identified, prompting an L. pneumophila urinary test to be added to the lab orders. This case represents the difficulties in diagnosing Legionnaires' disease due to the diverse clinical complexities of presentations, which may solely involve abdominal complaints.

Diagnostic Yield of CT Pulmonary Angiogram in the Diagnosis of Pulmonary Embolism and Its Predictive Factors

Introduction Computed tomography pulmonary angiography (CTPA) is the reference investigation of choice to diagnose pulmonary embolism (PE). Nevertheless, the use of CTPA should be weighed against its risks, such as radiation and contrast-induced nephropathy. We aim to assess the yield of CTPA in diagnosing PE at a tertiary centre in Malaysia. We also identify predictive factors associated with the yield of CTPA in this cohort. Methods This was a cross-sectional study involving all patients who had had CTPA done at Hospital Tengku Ampuan Afzan, Kuantan, Malaysia, from January 1, 2021, to November 30, 2021. All patients' records were retrieved and reviewed. CTPA images were retrieved from the Radiology Information System (RIS) and Picture Archiving and Communication System (PACS). They were double-reviewed by the authors, with the initial reports redacted from reporting radiologists to prevent reporting bias. The predictive factors were determined using simple logistic regression and multiple logistic regression. Results A total of 351 CTPAs were reviewed, of which 93 were found to be positive for PE, giving rise to an overall CTPA yield of 26.5%. Upon simple logistic regression, factors such as gender, discipline, history of trauma, presence of COVID-19 infection, and pneumonia were found to be associated with positive CTPA. Upon multiple logistic regression, male patients were found to have a higher chance of positive CTPA results. On the other hand, patients with COVID-19 infection and pneumonia have a lower chance of positive results in CTPA. Conclusion The yield of CTPA in diagnosing PE at our institution was acceptable at 26.5%. Upon multiple logistic regression, patients with COVID-19 infection and pneumonia were more likely to have a negative CTPA result, highlighting the need for clinicians to be more prudent in requesting CTPAs in these patients.

Identification and comparison of Chlamydia psittaci, Legionella and Mycoplasma pneumonia infection

INTRODUCTION

Conventional etiological detection and pathogenic antibody methods make it challenging to identify the atypical pathogens among the community-acquired pneumonia (CAP). Metagenomic next-generation sequencing (mNGS) could rapidly detect all potentially infectious diseases and identifies novel or potential pathogens.

METHODS

Eighteen patients diagnosed with atypical CAP were enrolled in this retrospective study, including nine Chlamydia psittaci pneumonia (C. p), four Legionella pneumonia (L. p) and five Mycoplasma pneumonia (M. p). We simultaneously tested bronchoalveolar lavage fluid (BALF) samples for conventional microbiological methods and mNGS, and blood specimens were analysed. We also collected and compared baseline and clinical characteristics and treatment responses.

RESULTS

Patients with C. p and L. p had similar symptoms, including fever, cough, headache, dyspnoea, asthenia, shivering and headache, compared with M. p, whose symptoms were slight. C. p and L. p usually showed multiple lobar distributions with pleural effusion. Serologic testing indicated that L. p had higher levels of white blood cells (WBCs), neutrophils, C-reactive protein (CRP), procalcitonin (PCT), alanine aminotransferase (ALT), lactate dehydrogenase (LDH) and creatinine compared with M. p and L. p (p < 0.05). However, patients with C. p had lower levels of albumin (p < 0.05), and M. p had a minimum risk of cardiac volume loads (p < 0.05). CD4/CD8 ratio, lymphocytes, aspartate aminotransferase (AST), creatine kinase (CK), cell counting of BALF and coagulation had no difference (p < 0.05). Pathogenic IgM assay showed that 4/5 cases were positive for M. p and no positive detection for C. p and L. p infection. We timely adjusted the antibiotics according to the final mNGS results. Eventually, 16/18 patients recovered fully. Conditions of L. p patients were worse than those of C. p patients, and those of M. p patients were the least.

CONCLUSION

Early application of mNGS detection increased the atypical pathogenic identification, improved the prognosis and made up for the deficiency of conventional detection methods.

Are ELISA and PCR Discrepancies in the Identification of Chlamydia pneumoniae Caused by the Presence of "Chlamydia-Related Bacteria"?

Chlamydia are Gram-negative, intracellular pathogens colonizing the epithelial mucosa. They cause primarily atypical pneumonia and have recently been associated with chronic diseases. Diagnostics rely almost exclusively on serological methods; PCR tests are used rarely because in patients with positive ELISA, it is nearly impossible to identify chlamydial DNA. To understand this issue, we elaborated a reliable and sensitive nested PCR method (panNPCR) for identifying all Chlamydiales species, not only in sputa, but also in clotted blood. Sequencing of the PCR product revealed that 41% of positive sputa samples and 66% of positive blood samples were not infected by Chlamydia but with "Chlamydia-related bacteria" such as Rhabdochlamydia sp., Parachlamydia sp., Protochlamydia sp., Neochlamydia sp., Mesochlamydia elodeae and lacustris, Piscichlamydia salmonis, and Estrella lausannensis. Consequently, we propose that there might be more than four human pathogenic Chlamydia species. We did not find any clear correlation between increased levels of antibodies and the presence of their DNA. Chlamydialles DNA was found in sputa samples from individuals positive for IgG or IgA but not in blood samples. Thus, elevated IgG and IgA levels are not reliable markers of chronic infection, and the presence of persistent forms should be proved by panNPCR. Apparently, the differences between ELISA and DNA amplification results have three main methodological reasons. The first one is the threshold occurrence of chlamydial genetic material in sputum and blood. The second one is the fact that a significant part of the samples can have DNA with sequences different from those of other species of the order Chlamydiales. The third one is the high background characteristic for ELISA, the absence of paired sera, and the vague interpretation of the gray zone.

Four-Year Environmental Surveillance Program of Legionella spp. in One of Palermo’s Largest Hospitals

Legionella is a ubiquitous bacterium that lives in freshwater environments and colonizes human-made water systems. Legionella pneumophila is the most virulent species, and risk factors for Legionnaires’ disease include increasing age, smoking, chronic diseases, and immunodeficiency. For this reason, it is very important to assess and monitor hospital water systems in order to prevent legionellosis. We have monitored a large hospital in Palermo for four years. To determine the presence of microorganisms, according to national guidelines, we used the culture method, which is considered the gold standard for Legionella detection. Sampling was divided into five macro-areas, and a total of 251 samples were collected during the period of investigation, 49% of which were Legionella spp.-positive and 51% were Legionella spp.-negative. Positive samples with L. pneumophila. sgr 2-15 were most frequent in the Underground (55.6%, p = 0.0184), Medicine (42.9%, p = 0.0184) and Other (63.2%, p = 0.002) areas; while positive samples for L. pneumophila sgr 1 were less frequent in the Underground (0.0%, p = 0.0184) and Surgery areas (4.5%, p = 0.033), and for Legionella anisa, were less frequent in the Medicine (4.1%, p = 0.021), Oncohematology (0.0%, p = 0.0282), and Other (0.0%, p = 0.016) areas. Finally, no significant differences were observed among the areas for each isolate considered. The surveillance carried out in these years demonstrates the importance of monitoring, which allows us to analyze the conditions of hospital facilities and, therefore, prevent Legionella spp. infections.

Deep diagnostic agent forest (DDAF): A deep learning pathogen recognition system for pneumonia based on CT

BACKGROUND

Even though antibiotics agents are widely used, pneumonia is still one of the most common causes of death around the world. Some severe, fast-spreading pneumonia can even cause huge influence on global economy and life security. In order to give optimal medication regimens and prevent infectious pneumonia's spreading, recognition of pathogens is important.

METHOD

In this single-institution retrospective study, 2,353 patients with their CT volumes are included, each of whom was infected by one of 12 known kinds of pathogens. We propose Deep Diagnostic Agent Forest (DDAF) to recognize the pathogen of a patient based on ones' CT volume, which is a challenging multiclass classification problem, with large intraclass variations and small interclass variations and very imbalanced data.

RESULTS

The model achieves 0.899 ± 0.004 multi-way area under curves of receiver (AUC) for level-I pathogen recognition, which are five rough groups of pathogens, and 0.851 ± 0.003 AUC for level-II recognition, which are 12 fine-level pathogens. The model also outperforms the average result of seven human readers in level-I recognition and outperforms all readers in level-II recognition, who can only reach an average result of 7.71 ± 4.10% accuracy.

CONCLUSION

Deep learning model can help in recognition pathogens using CTs only, which might help accelerate the process of etiological diagnosis.