[Pulmonary nodules and pneumonia : A diagnostic guideline]

[Analysis of Salivary Microbiota Characteristics in Patients With Pulmonary Nodules: A Prospective Nonrandomized Concurrent Controlled Trial]

Objective

To uncover and identify the differences in salivary microbiota profiles and their potential roles between patients with pulmonary nodules (PN) and healthy controls, and to propose new candidate biomarkers for the early warning of PN.

Methods

16S rRNA amplicon sequencing was performed with the saliva samples of 173 PN patients, or the PN group, and 40 health controls, or the HC group, to compare the characteristics, including diversity, community composition, differential species, and functional changes of salivary microbiota in the two groups. Random forest algorithm was used to identify salivary microbial markers of PN and their predictive value for PN was assessed by area under the curve (AUC). Finally, the biological functions and potential mechanisms of differentially-expressed genes in saliva samples were preliminarily investigated on the basis of predictive functional profiling of Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2).

Results

The α diversity and β diversity of salivary microbiota in the PN group were higher than those in the HC group (P<0.05). Furthermore, there were significant differences in the community composition and the abundance of oral microorganisms between the PN and the HC groups (P<0.05). Random forest algorithm was applied to identify differential microbial species. Porphyromonas, Haemophilus, and Fusobacterium constituted the optimal marker sets (AUC=0.79, 95% confidence interval: 0.71-0.86), which can be used to effectively identify patients with PN. Bioinformatics analysis of the differentially-expressed genes revealed that patients with PN showed significant enrichment in protein/molecular functions involved in immune deficiency and redox homeostasis.

Conclusion

Changes in salivary microbiota are closely associated with PN and may induce the development of PN or malignant transformation of PN, which indicates the potential of salivary microbiota to be used as a new non-invasive humoral marker for the early diagnosis of PN.

B-mode ultrasound and contrast-enhanced ultrasound for evaluation of pneumonia: A pictorial essay

Due to their often peripheral pleural-based location, pneumonias can be visualised by B-mode ultrasound. Therefore, sonography can be used as an alternative imaging modality to chest X-ray in suspected cases of pneumonia. Depending on the clinical background of the patient, and various underlying pathological mechanisms, a heterogeneous pattern of pneumonia is seen in both B-mode lung ultrasound and contrast-enhanced ultrasound. Here, we describe the spectrum of sonographic manifestations of pneumonic/inflammatory consolidation on B-mode lung ultrasound and contrast-enhanced ultrasound.

Examining the Definition of Ventilator-Associated Pneumonia in the Trauma Setting: A Single-Center Analysis

Background: Ventilator associated pneumonia (VAP) is defined by the American College of Surgeons Trauma Quality Improvement Program (ACS TQIP) using laboratory findings, pathophysiologic signs/symptoms, and imaging criteria. However, many critically ill trauma patients meet the non-specific laboratory and sign/symptom thresholds for VAP, so the TQIP designation of VAP depends heavily upon imaging evidence. We hypothesized that physician opinions widely vary regarding chest radiograph findings significant for VAP. Patients and Methods: The TQIP Spring 2021 Benchmark Report (BR) was used to identify 14 patients with VAP at an academic Level 1 Trauma Center. Critically ill trauma patients (n = 7) who spent at least four days intubated and met TQIP's laboratory and sign/symptom thresholds for VAP but did not appear as VAPs on the BR comprised the control group. For each deidentified patient, four successive chest radiographic images were compiled and arranged chronologically. Cases and controls were randomly arranged in digital format. Blinded physicians (n = 27) were asked to identify patients with VAP based solely on imaging evidence. Results: Radiographic evidence of VAP was highly subjective (Krippendorff α = 0.134). Among physicians of the same job description, inter-rater reliability remained low (α = 0.137 for trauma attending physicians; α = 0.141 for trauma fellows; α = 0.271 for radiologists). When majority judgment was compared to the TQIP BR, there was disagreement between the two tests (Cohen κ = ^-0.071; sensitivity, 64.3%; specificity, 28.6%). Conclusions: Current definitions of VAP rely on subjective imaging interpretation and ignore the reality that there are numerous explanations for opacities on CXR. The inconsistency of physicians' imaging interpretation and protean physiologic findings for VAP in trauma patients should preclude the current definition of VAP from being used as a quality improvement metric in TQIP.