Antimicrobial resistance is a rigorous health issue around the world. Because of the short turn-around-time and broad pathogen spectrum, culture-independent metagenomic next-generation sequencing (mNGS) is a powerful and highly efficient tool for clinical pathogen detection. The increasing question is whether mNGS is practical in the prediction of antimicrobial susceptibility. This review summarizes the current mNGS-based antimicrobial susceptibility testing technologies. The critical determinants of mNGS-based antibacterial resistance prediction have been comprehensively analyzed, including antimicrobial resistance databases, sequence alignment tools, detection tools for genomic antimicrobial resistance determinants, as well as resistance prediction models. The clinical challenges for mNGS-based antibacterial resistance prediction have also been reviewed and discussed.
Objective To analyze the benign-malignant outcomes of pulmonary nodules in surgical patients and their influencing factors, and provide evidence and ideas for optimizing and improving the integrated management model of pulmonary nodules. Methods From October to December 2023, a convenience sampling method was used to select patients who underwent lung surgery at West China Hospital, Sichuan University between July 2022 and June 2023 for this study. The malignancy rate of postoperative pathological results of pulmonary nodules and its influencing factors were analyzed using univariate analysis and multiple logistic regression. Results A total of 4600 surgical patients with pulmonary nodules were included, with a malignancy rate of 88.65% (4078/4600) and a benign rate of 11.35% (522/4600). Univariate analysis showed significant differences in malignancy rates among different genders, ages, methods of pulmonary nodule detection, and smoking histories (P<0.05); however, no significant difference was found regarding place of birth or family history of lung cancer (P>0.05). Multiple logistic regression analysis indicated that females [odds ratio (OR)=1.533, 95% confidence interval (CI) (1.271, 1.850)], older age groups [61-75 vs. ≤30 years: OR=1.640, 95%CI (1.021, 2.634); >75 vs. ≤30 years: OR=2.690, 95%CI (1.062, 6.814)], and pulmonary nodules detected during physical examinations [OR=1.286, 95%CI (1.064, 1.554)] were high-risk factors for malignancy, with statistical significance (P<0.05). Conclusion In the integrated management of pulmonary nodules, it is crucial not to overlook females or older patients, as they may be more significant influencing factors than smoking; furthermore, lung examinations are effective means of early detection of malignant lung tumors and are worth promoting and popularizing.
Whipple’s disease is a multisystemic disease caused by Tropheryma (T.) whipplei that primarily affects the gastrointestinal tract. In literature, T. whipplei can also cause pulmonary infections. The detection of T. whipplei depends on nucleic acid-based test. With the application of next-generation sequencing (NGS), cases with T. whipplei detected from respiratory tract samples by NGS are increasingly found but there is lack of recognized diagnostic criteria for these cases. Within the context, we propose a grading diagnostic scheme for the situation that T. whipplei is detected from respiratory tract samples, based on clinical experience and diagnostic thinking, and referring to the international classifications of invasive fungal infections. The scheme comprises five levels: confirmed, probable, possible, impossible, and excluded. There were 26 such cases from West China Hospital of Sichuan University and we used our diagnostic scheme to define probable in 6 cases, possible in 9 cases, impossible in 8 cases, and excluded in 3 cases. Based on this, we also propose specific suggestions for sample collection and testing, patient management, and further research directions. These recommendations are preliminary based on the existing cases from West China Hospital of Sichuan University and therefore needs to be verified, modified, optimized, and even reconstructed when more clinical evidence and further clinical studies become available.
Lung cancer is the malignant tumor with the highest incidence and mortality rate in China. Early diagnosis and treatment are key to improving the survival rate and reducing the mortality rate for lung cancer patients. This article introduces the integrated management model for patients with pulmonary nodules/lung cancer developed by West China Hospital of Sichuan University based on “internet plus” and health service team of treatment, nursing, and care. The Integrated Care Management Center has established a multidisciplinary team, using internet platforms and artificial intelligence tools to develop a whole life cycle health service system for patients with pulmonary nodules/lung cancer, which is from the screening of high-risk population for lung cancer, the intelligent risk stratification and follow-up management of pulmonary nodules, the subsequent standardized diagnosis and treatment of lung cancer and comorbidity management, until the patient’s demise. After the implementation of this model, the malignancy rate in surgically treated patients with pulmonary nodules reached 85.08%, and the patient satisfaction score was 95.76. This model provides a new idea and reference for the innovation of chronic disease service model and the management of pulmonary nodules and lung cancer.
Objective By using metagenomic next-generation sequencing (mNGS), we aimed to analyze the microbes characteristics of lower respiratory tract of patients with pulmonary infection, so as to improve the further understanding of clinical etiological characteristics of patients with pulmonary infection. Methods A total of 840 patients with suspected pulmonary infection were enrolled from August 2020 to October 2021 in West China Hospital of Sichuan University. mNGS was used to detect the microbiome of bronchoalveolar lavage fluid of all patients, and the microbial characteristics of lower respiratory tract of all patients were retrospectively analyzed. Results A total of 840 patients were enrolled, of which 743 were positive for microbiome, with bacterial infection accounting for 35.13% (261/743). Acinetobacter baumannii accounted for 18.98% (141/743), followed by Streptococcus pneumoniae (14.13%, 105/743), Klebsiella pneumoniae (13.46%, 100/743), Enterococcus faecium (12.11%, 90/743) and Mycobacterium tuberculosis complex (11.98%, 89/743). Acinetobacter baumannii had the highest average reads (2607.48). In addition, some specific pathogens were detected, such as 9 cases of Chlamydia psittaci. The main fungal infections were Candida albicans (12.38%, 92/743), Pneumocystis jirovecii (9.02%, 67/743) and Aspergillus fumigatus (7.40%, 55/743), among which the average reads of Pneumocystis jirovecii was higher (141.86) than Candida albicans and Aspergillus fumigatus. In addition, some special pathogens were also detected, such as a case of Talaromyces marneffei. The main viral infections included human β herpevirus 5 (17.90%, 133/743), human γ herpevirus 4 (17.36%, 129/743), human β herpevirus 7 (16.15%, 120/743) and human α herpevirus 1 (13.59%, 101/743), among which the average reads of human herpesvirus type 1 (367.27) was the highest. Parasitic infection was least, with only 2 cases of Echinococcus multilocularis, 2 cases of Angiostrongylus cantonensis, 2 cases of Dermatophagoides pteronyssinus and 1 case of Dermatophagoides farinae, which were mainly infected with bacteria and viruses. In addition, a total of 407 patients were diagnosed with mixed infection, of which virus and bacteria mixed infection was the most (22.61%, 168/743). The distribution of microorganisms in different seasons also has certain characteristics. For example, bacteria (Acinetobacter baumannii) were most frequently detected in autumn and winter, while viruses (human gamma-herpesvirus type 4) were most frequently detected in spring and summer. Conclusions In the lower respiratory tract of patients with pulmonary infection, the main gram-negative bacteria are Acinetobacter baumannii and Klebsiella pneumoniae, while the main gram-positive bacteria are Streptococcus pneumoniae, Enterococcus faecium and Mycobacterium tuberculosis complex; the main fungi are Candida albicans, Pneumocystis jirovecii and Aspergillus fumigatus; the main viruses are human β herpevirus 5, human γ herpevirus 4 and human β herpevirus 7. However, parasites are rarely detected and have no obvious characteristics. Bacterial infection and bacterial virus mixed infection are the main co-infections; the microbial characteristics of autumn and winter are different from those of spring and summer. In addition, attention should be paid to special pathogenic microorganisms, such as Chlamydia psittaci and Talaromyces marneffei. These characteristics could be used as reference and basis for the pathogenic diagnosis of pulmonary infection.