Development and application of a deep learning-based comprehensive early diagnostic model for chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a frequently diagnosed yet treatable condition, provided it is identified early and managed effectively. This study aims to develop an advanced COPD diagnostic model by integrating deep learning and radiomics features. METHODS: We utilized a dataset comprising CT images from 2,983 participants, of which 2,317 participants also provided epidemiological data through questionnaires. Deep learning features were extracted using a Variational Autoencoder, and radiomics features were obtained using the PyRadiomics package. Multi-Layer Perceptrons were used to construct models based on deep learning and radiomics features independently, as well as a fusion model integrating both. Subsequently, epidemiological questionnaire data were incorporated to establish a more comprehensive model. The diagnostic performance of standalone models, the fusion model and the comprehensive model was evaluated and compared using metrics including accuracy, precision, recall, F1-score, Brier score, receiver operating characteristic curves, and area under the curve (AUC). RESULTS: The fusion model exhibited outstanding performance with an AUC of 0.952, surpassing the standalone models based solely on deep learning features (AUC = 0.844) or radiomics features (AUC = 0.944). Notably, the comprehensive model, incorporating deep learning features, radiomics features, and questionnaire variables demonstrated the highest diagnostic performance among all models, yielding an AUC of 0.971. CONCLUSION: We developed and implemented a data fusion strategy to construct a state-of-the-art COPD diagnostic model integrating deep learning features, radiomics features, and questionnaire variables. Our data fusion strategy proved effective, and the model can be easily deployed in clinical settings. TRIAL REGISTRATION: Not applicable. This study is NOT a clinical trial, it does not report the results of a health care intervention on human participants.

Intensive Intervention Improves Outcomes for Chronic Obstructive Pulmonary Disease Patients: A Medical Consortium-Based Management.

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality. Strategies involving multidimensional approaches for the treatment of COPD are needed. This study aimed to evaluate the efficiency of medical consortium-based management for COPD. Patients were grouped in accordance with whether the hospitals they went to were under the medical consortium. We enrolled 141 COPD patients in the management group and 147 COPD patients in the control group. There was no predetermined sex and disease severity inclusion or exclusion criteria. Patients in the control group were managed by standard care, while patients in the management group were managed with intensive medical intervention jointly by specialists in the hospital and general practitioners and healthcare workers in community health centers. There was no difference in the basal demographics between the two groups. The basal condition of the management group was worse than that of the control group, demonstrated by a higher CAT score and a lower pulmonary function index. Half-year intensive intervention decreased CAT score from 17.28 to 15.62 and the Barthel ADL index from 73 to 60 in the management group, which was associated with better pulmonary rehabilitation, pursed-lip breathing, oxygen usage, and medicine regularity. The benefits became more obvious after one-year intensive intervention in the management group. There was a difference in mMRC grades and smoking cessation between the two groups. This study shows that a one-year intensive intervention improves the patients' health status and pulmonary function, suggesting that our medical consortium-based management is effective in the treatment of COPD.

Risk factors for antibiotic resistance and mortality in patients with bloodstream infection of Escherichia coli.

This study aimed to investigate the risk factors for bloodstream infection (BSI) caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (E. coli) and related mortality. The clinical data of 388 patients with E. coli BSI were analyzed. Blood cultures were performed and the antimicrobial susceptibility profiles of the resulting isolates were determined. Four single-nucleotide polymorphisms (rs231775, rs12343816, rs16944, and rs2233406) were genotyped using real-time PCR. ESBL were detected by disk diffusion confirmatory testing. Univariate and multivariate regression analyses were applied to identify the risk factors for ESBL-producing isolates and the BSI-induced mortality. The prevalence of ESBL-producing E. coli in BSI patients was 40.98%. E. coli isolates were commonly susceptible to carbapenem and ß-lactam/ß-lactamase inhibitor combinations. The major ESBL genes were CTX-M-14, CTX-M-55, CTX-M-15, and CTX-M-27. The proportion of CTX-M-15 was significantly higher in patients over 70 years and those receiving stomach tube catheterization. Nosocomial infection, biliary tract infection, stomach tube catheterization, and previous cephalosporin administration were independent risk factors for ESBL-producing isolates. ESBL positivity, nosocomial infection, and cancer were independent risk factors of mortality. Two genetic polymorphisms associated with inflammation activation, rs231775 A allele and rs2233406 T allele, significantly increased the mortality risk of E. coli BSI with a risk ratio (95% CI) of 1.93 (1.05-3.55) and 4.38 (2.07-9.29), respectively. For patients with nosocomial infection, biliary tract infection, and cancer, the monitor of BSI and antibiotic susceptibility should be enhanced. The invasive procedures should be minimized. rs231775 and rs2233406 are promising prognostic markers for E. coli BSI patients.

Multiple endo bronchial lipoma: a rare case report.

BACKGROUND: Endobronchial lipoma is an extremely rare benign tumor, which is generally located in the first three subdivisions of the tracheobronchial tree. According to the existing literature, all endobronchial lipomas are single (one per patient). Here, we report a rare case in which the patient presented with two endobronchial lipomas in the same patient, and underwent a bronchoscopic tumor resection in the left main bronchus and the left lower bronchus. Both tumors were pathologically confirmed as endobronchial lipoma. CASE PRESENTATION: A 52-year-old Chinese man presented at the clinic reporting a mild cough with yellow color sputum and exertional dyspnea for 2 weeks. He was a heavy smoker (45 pack-years). Chest auscultation demonstrated faint wheezing in left lower lobe. Computed tomography (CT) revealed two low-density endobronchial masses located in the middle segment of the left main bronchus and the posterior basilar segmental bronchus of the left lower lobe. The neoplasms measured a CT-attenuation value of -70HU, -98HU in density with air trapping and atelectasis in the segmental bronchus of the left lower lobe. The patient underwent interventional bronchoscopic management to remove the neoplasms by using an electrosurgical snare, cryotherapy, and electrocautery. The locations of the neoplasms were confirmed at the left main bronchus and the superior segment of the left lower lobe during bronchoscopic intervention. Histopathological examination confirmed that both tissues were consistent with lipomas. After 18 months of follow-up, the patient was free of symptoms and CT revealed that bronchiectasia remained in the superior segment of the left lower lobe; however, no mass lesion was present in the left bronchus. CONCLUSIONS: This case suggests that an endobronchial lipoma can present as multiple lesions, and both proximal and distal types can simultaneously occur in the same patient. Thus, these findings help us further understand the biology of endobronchial lipomas.