Unlabelled: Alveolar-pleural fistulas (APF) are a clinical entity that represents a diagnostic and therapeutic challenge.
Objective: The objective of this work is to design a diagnostic algorithm for the anatomical detection of APF in patients who are not candidates for surgical treatment.
Method: Prospective non-randomized study of 47 patients. Diagnostic procedures were performed: (a) prior to bronchoscopy: computed axial tomography (CT) and implantation of electronic pleural drainage system (EPD) and (b) endoscopic: endobronchial occlusion (EO) by balloon, selective endobronchial oxygen insufflation (OI) (2l) and selective bronchography (BS) (instillation of iodinated radiological contrast using continuous fluoroscopy).
Results: The sample was predominantly male (81%). The diagnostic methods revealed: (a) Determination of the anatomical location of APF by CT in 15/46 patients (31.9% of sample), and variations in the pattern (intermittent or continuous air leak) and quantification after drug administration sedatives using EPD, (b) endoscopic: anatomical determination of APF was achieved in 57.1, 81 and 63.4% respectively using EO, OI and BS. The combination of the diagnostic tests allowed us to determine the anatomical location of the APF in 91.5% of the sample. No complications were recorded in 85.1% of cases.
Conclusions: The diagnosis of APF by flexible bronchoscopy is a useful method, with an adequate safety and efficacy profile. The proposed diagnostic algorithm includes the use of EPD and performing a CT scan. Regarding endoscopic diagnosis: in case of continuous air leak, the first option is OE; and if the leak is intermittent, we recommend endobronchial OI, with BS as a secondary option (respective sensitivity 81% vs 63.4% and complications 8.1% vs 7.3%).
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.arbres.2024.06.015 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Evaluation of a Deep Learning Denoising Algorithm for Dose Reduction in Whole-Body Photon-Counting CT Imaging: A Cadaveric Study.
Acad Radiol
January 2025
Department of Radiology, University Hospital Tuebingen, Hoppe-Seyler-Str. 3, 72076 Tuebingen, Germany (R.D., J.M.B., B.S., J.M., S.G., P.K., S.W., J.H., K.N., S.A., A.B.).
Rationale And Objectives: Photon Counting CT (PCCT) offers advanced imaging capabilities with potential for substantial radiation dose reduction; however, achieving this without compromising image quality remains a challenge due to increased noise at lower doses. This study aims to evaluate the effectiveness of a deep learning (DL)-based denoising algorithm in maintaining diagnostic image quality in whole-body PCCT imaging at reduced radiation levels, using real intraindividual cadaveric scans.
Materials And Methods: Twenty-four cadaveric human bodies underwent whole-body CT scans on a PCCT scanner (NAEOTOM Alpha, Siemens Healthineers) at four different dose levels (100%, 50%, 25%, and 10% mAs).
The Clinical Utility of Incorporating Next-Generation Sequencing Results in the Management Algorithm of Pancreatic Cysts.
Gastrointest Endosc
January 2025
Division of Digestive and Liver Diseases, University of Texas Southwestern Medical Center, Dallas, TX. Electronic address:
Background & Aims: Pancreatic cysts often pose challenges in predicting malignant progression. Next-generation sequencing has become an appealing ancillary diagnostic test. The diagnostic performance is well characterized, but the impact on clinical management remains unclear.
View Article and Find Full Text PDFLong-term outcome and risk stratification in compensated advanced chronic liver disease after HCV-cure.
Hepatology
February 2025
Department of Medicine III, Division of Gastroenterology and Hepatology, Medical University of Vienna, Vienna, Austria.
Background And Aims: Around 750,000 patients per year will be cured of HCV infection until 2030. Those with compensated advanced chronic liver disease remain at risk for hepatic decompensation and de novo HCC. Algorithms have been developed to stratify risk early after cure; however, data on long-term outcomes and the prognostic utility of these risk stratification algorithms at later time points are lacking.
View Article and Find Full Text PDFDevelopment and Validation of a Novel Model to Discriminate Idiosyncratic Drug-Induced Liver Injury and Autoimmune Hepatitis.
Liver Int
February 2025
Liver Research Center, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Background And Aim: Discriminating between idiosyncratic drug-induced liver injury (DILI) and autoimmune hepatitis (AIH) is critical yet challenging. We aim to develop and validate a machine learning (ML)-based model to aid in this differentiation.
Methods: This multicenter cohort study utilised a development set from Beijing Friendship Hospital, with retrospective and prospective validation sets from 10 tertiary hospitals across various regions of China spanning January 2009 to May 2023.
Novel Strategies for the Treatment of Lung Cancer: An In-depth Analysis of the Use of Immunotherapy, Precision Medicine, and Artificial Intelligence to Improve Prognoses.
Curr Med Chem
January 2025
Shree S K Patel College of Pharmaceutical Education and Research, Ganpat University, Mahesana, Gujarat, 384012, India.
Therapeutic hurdles persist in the fight against lung cancer, although it is a leading cause of cancer-related deaths worldwide. Results are still not up to par, even with the best efforts of conventional medicine, thus new avenues of investigation are required. Examining how immunotherapy, precision medicine, and AI are being used to manage lung cancer, this review shows how these tools can change the game for patients and increase their chances of survival.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!