Respirology最新文献

Background and objective: The effects of the volume mismatch between the airway and lung vasculature on exacerbation in chronic obstructive pulmonary disease (COPD) is uncertain. We aimed to examine the association between an increased volume ratio of the airway to lung blood vessels (AVR) and exacerbations, regardless of visually assessed bronchiectasis (modified Reiff [mReiff] score) and extrapulmonary vasculature on computed tomography (CT), in patients with COPD during a 5-year follow-up period.

Methods: Participants were recruited from the Hokkaido COPD Cohort Study (original, N = 96) and Kyoto University cohort (validation, N = 130). CT-derived indices of the airway and vasculature, mReiff scores, and ratio of pulmonary artery diameter to aorta diameter (PA/Ao) were evaluated. The Kaplan-Meier method with log-rank tests was used to compare the high (highest quartile) and low (other quartiles) groups, while multivariable Cox proportional hazards models explored the factors associated with the time to first exacerbation.

Results: The high AVR group showed a shorter time to first exacerbation than the low AVR group in analyses of both all patients and those without visual bronchiectasis. High AVR was significantly associated with exacerbations [Hazard ratio [95% confidence interval]: original, 3.85 [1.17, 12.6]; validation, 2.01 [1.15, 3.52]), irrespective of mReiff scores and PA/Ao in all patients. The lung-volume-corrected airway or blood vessel volumes did not correlate with the time to first exacerbation.

Conclusion: High AVR was associated with a shorter time to first exacerbation, complementary to mReiff score and PA/Ao, suggesting that AVR is a novel CT-derived predictor of exacerbation in COPD.

Background and objective: In recent decades, artificial intelligence has seen significant development in various fields of medicine, including interventional pulmonology. The study aims to evaluate the diagnostic performance of innovative approaches to detect lung cancer on biopsy sample images (Rapid On-Site Evaluation, ROSE) compared to the diagnostic gold standard.

Methods: We conducted a multicentric study, comparing remote anatomopathological evaluation (E-ROSE) and machine learning algorithms (AI-ROSE) reliability in diagnosing lung cancer, evaluating 277 biopsy sample images, 25 of which were doubtful; to compare them with the definitive histological examination performed by the pathologist.

Results: E-ROSE achieved a diagnostic accuracy of 95.5%, with a sensitivity of 99.0% and specificity of 88.7%, including doubtful cases respectively 91.4%, 97.1%, and 81%. AI-ROSE showed a sensitivity of 96.4% and a specificity of 78.9%, with an accuracy of 92.5%. Including the doubtful cases, the best model achieved an accuracy of 85%, sensitivity of 97.4%, and specificity of 75.4%. The discriminative ability of the tests was compared both for positive/negative cases, showing Area Under ROC Curve (AUC) of 93.9% for E-ROSE and 87.6% for AI-ROSE; while including doubtful, AUC was 89.1% for E-ROSE and 86.4% for AI-ROSE.

Conclusions: The study suggests that the application of innovative methods such as E-ROSE and AI-ROSE could provide valuable support to interventional pulmonologists in the diagnostic process.

Background and objective: Patients diagnosed with benign central airway stenosis who are ineligible for surgical intervention require airway stents. The high complication rates associated with conventional silicone and metallic stents have led to the development of new devices with lower complication rates and easier insertion and removal. This paper presents our results, including the indications, patient characteristics, and outcomes.

Methods: We reviewed patients who underwent bronchoscopy for airway stenosis due to a benign cause between January 2015 and February 2023 in the interventional pulmonology unit of a tertiary university hospital. The causes and locations of stenosis, outcomes, and complications were analysed in patients who received a minimum of one biodegradable (BD) stent. All procedures were performed under general anaesthesia using a rigid bronchoscope.

Results: A total of 136 BD stents were implanted at 22 airway sites in 18 patients, with a median age of 56. Thirteen patients, three with prior metal stents and 10 with prior silicone stents, had a history of non-BD stent usage. Twelve procedures (54.5%) used bronchial stents, whereas 10 procedures (45.4%) used tracheal stents. The median duration of BD stent use was 10.6 months (range: 0.1-72.0 months). Early complications included one moderate granulation formation and two dislocations that necessitated stent fixation: one using clips and the other sutured to an additional stent.

Conclusion: The study indicates that BD stents are both safe and feasible for treating benign stenosis, offering a safer alternative to silicone and metallic stents while providing personalised treatment for patients.

Background and objective: Acute exacerbations of COPD (AECOPD) worsen outcomes, yet they are often underreported. The 14-item EXACT diary has been validated for trial use-the five-item CERT checklist is patient-centered. We compared the two tools' accuracy and early-warning performance for AECOPD.

Methods: This prospective study examined 63 COPD patients who completed EXACT and CERT daily. Two metrics were used for CERT: total score and binary (positive if ≥ 2 items were rated as moderate/severe). AECOPD patients were bootstrap matched to a non-exacerbator. Linear mixed-effects models assessed score differences on the day of AECOPD diagnosis and the previous days.

Results: Twelve patients developed clinically confirmed AECOPD. On the day of AECOPD diagnosis, all tools discriminated AECOPD (AUC: EXACT 0.90, CERT total score 0.88, and CERT binary 0.87; p < 0.01). At optimal thresholds, sensitivities ranged from 81% to 87%, and specificities ranged from 93% to 95%. One day before the AECOPD diagnosis, the CERT total score (5.9 vs. 1.4; p = 0.006) and the CERT binary outcome (70.4% vs. 9.3%; p = 0.009) significantly distinguished impending exacerbations. However, the EXACT score did not (39.6% vs. 34.3%; p = 0.186). The CERT total score yielded an AUC of 0.86 (sensitivity 83%, specificity 86%), and the binary rating achieved a specificity of 91% and a sensitivity of 70% one day before diagnosis.

Conclusion: Both EXACT and CERT can accurately detect AECOPD at the time of diagnosis. However, patients were able to recognise worsening symptoms one day before an AECOPD diagnosis when using the CERT.

Trial registration: clinicaltrials.gov (NCT04140097).