Relationship between air pollution exposure and the progression of idiopathic pulmonary fibrosis in Madrid: Chronic respiratory failure, hospitalizations, and mortality. A retrospective study.

Introduction: Air pollution has a significant impact on the morbidity and mortality of various respiratory diseases. However, this has not been widely studied in diffuse interstitial lung diseases, specifically in idiopathic pulmonary fibrosis. Objective: In this study we aimed to assess the relationship between four major air pollutants individually [carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), and nitrogen oxides (NOx)] and the development of chronic respiratory failure, hospitalization due to respiratory causes and mortality in patients with idiopathic pulmonary fibrosis. Methods: We conducted an exploratory retrospective panel study from 2011 to 2020 in 69 patients with idiopathic pulmonary fibrosis from the pulmonary medicine department of a tertiary hospital. Based on their geocoded residential address, levels of each pollutant were estimated 1, 3, 6, 12, and 36 months prior to each event (chronic respiratory failure, hospital admission and mortality). Data was collected from the air quality monitoring stations of the Community of Madrid located <3.5 km (2.2 miles) from each patient's home. Results: The increase in average values of CO [OR 1.62 (1.11-2.36) and OR 1.84 (1.1-3.06)], NO2 [OR 1.64 (1.01-2.66)], and NOx [OR 1.11 (1-1.23) and OR 1.19 (1.03-1.38)] were significantly associated with the probability of developing chronic respiratory failure in different periods. In addition, the averages of NO2, O3, and NOx were significantly associated with the probability of hospital admissions due to respiratory causes and mortality in these patients. Conclusion: Air pollution is associated with an increase in the probability of developing chronic respiratory failure, hospitalization due to respiratory causes and mortality in patients with idiopathic pulmonary fibrosis.

Air pollution exposure and its effects on idiopathic pulmonary fibrosis: clinical worsening, lung function decline, and radiological deterioration.

Introduction: Major urban pollutants have a considerable influence on the natural history of lung disease. However, this effect is not well known in idiopathic pulmonary fibrosis (IPF). Aim: This study aimed to investigate the effects of air pollution on clinical worsening, lung function, and radiological deterioration in patients with IPF. Methods: This exploratory retrospective cohort study included 69 patients with IPF, monitored from 2011 to 2020. Data on air pollution levels, including carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter ≤ 2.5 µM (PM2.5), ozone (O3), and nitrogen oxides (NOx), were collected from the nearest air quality monitoring stations (<3.5 km from the patients' homes). Patient outcomes such as clinical worsening, lung function decline, and radiological deterioration were assessed over various exposure periods (1, 3, 6, 12, and 36 months). The statistical analyses were adjusted for various factors, including age, sex, smoking status, and treatment. Results: There was an association between higher O3 levels and an increased likelihood of clinical worsening over 6 and 36 months of exposure (odds ratio [OR] and 95% confidence interval [CI] = 1.16 [1.01-1.33] and OR and 95% CI = 1.80 [1.07-3.01], respectively). Increased CO levels were linked to lung function decline over 12-month exposure periods (OR and 95% CI 1.63 = [1.01-2.63]). Lastly, radiological deterioration was significantly associated with higher CO, NO2, and NOx levels over 6-month exposure periods (OR and 95% CI = 2.14 [1.33-3.44], OR and 95% CI = 1.76 [1.15-2.66] and OR and 95% CI = 1.16 [1.03-1.3], respectively). Conclusion: This study suggests that air pollution, specifically O3, CO, NO2, and NOx, could affect clinical worsening, lung function, and radiological outcomes in patients with IPF. These findings highlight the potential role of air pollution in the progression of IPF, emphasizing the need for further research and air quality control measures to mitigate its effects on respiratory health.

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performance with respect to human reader severity assessment and whole lung radiomics. We propose a deep learning based scheme to automatically segment the different lesion subtypes in nonenhanced CT scans. The automatic lesion quantification was used to predict clinical outcomes. The proposed technique has been independently tested in a multicentric cohort of 103 patients, retrospectively collected between March and July of 2020. Segmentation of lesion subtypes was evaluated using both overlapping (Dice) and distance-based (Hausdorff and average surface) metrics, while the proposed system to predict clinically relevant outcomes was assessed using the area under the curve (AUC). Additionally, other metrics including sensitivity, specificity, positive predictive value and negative predictive value were estimated. 95% confidence intervals were properly calculated. The agreement between the automatic estimate of parenchymal damage (%) and the radiologists' severity scoring was strong, with a Spearman correlation coefficient (R) of 0.83. The automatic quantification of lesion subtypes was able to predict patient mortality, admission to the Intensive Care Units (ICU) and need for mechanical ventilation with an AUC of 0.87, 0.73 and 0.68 respectively. The proposed artificial intelligence system enabled a better prediction of those clinically relevant outcomes when compared to the radiologists' interpretation and to whole lung radiomics. In conclusion, deep learning lesion subtyping in COVID-19 pneumonia from noncontrast chest CT enables quantitative assessment of disease severity and better prediction of clinical outcomes with respect to whole lung radiomics or radiologists' severity score.

Effect of Sex Differences on Computed Tomography Findings in Adults With Cystic Fibrosis: A Multicenter Study.

BACKGROUND: The survival of women with cystic fibrosis (CF) is lower than that of men by approximately 5 years. While various factors have been put forward to account for this discrepancy, no specific reasons have been established. Our hypothesis was that anatomical-structural involvement is more pronounced in women with CF than in men and that this is reflected in thoracic HRCT findings. MATERIAL AND METHODS: We performed a prospective multicentre study, in which adult patients were consecutively included over 18 months. Chest HRCT was performed, and findings were scored by 2 thoracic radiologists using the modified Bhalla system. We also studied respiratory function, applied the CFQR 14+ questionnaire, and collected clinical variables. RESULTS: Of the 360 patients followed up in the participating units, 160 were eventually included. Mean age was 28 years, and 47.5% were women. The mean±SD global score on the modified Bhalla score was 13.7±3.8 in women and 15.2±3.8 in men (p=0.024). The highest scores were observed for sacculations, bronchial generations, and air trapping in women. Women had lower BMI, %FEV1, %FVC, and %DLCO. Similarly, the results for the respiratory domain in CFQR 14+ were worse in women, who also had more annual exacerbations. CONCLUSIONS: This is the first study to provide evidence of the implication of sex differences in HRCT findings in patients with CF. Women with CF present a more severe form of the disease that results in more frequent exacerbations, poorer functional and nutritional outcomes, deterioration of quality of life, and greater structural damage.

Predictive value of the modified Bhalla score for assessment of pulmonary exacerbations in adults with cystic fibrosis.

OBJECTIVES: The objective of this study was to analyze the predictive value of the modified Bhalla score in high-resolution computed tomography (HRCT) for assessment of pulmonary exacerbations (PEx) in cystic fibrosis (CF) patients. We also describe the relationship between this score and pulmonary function test results. METHODS: We performed a multicenter and prospective study where adult patients with CF were included consecutively over 18 months. All patients underwent HRCT with acquisition in inspiration and expiration. The results were analyzed by an expert radiologist who assigned a modified Bhalla score value. Lung function was also assessed, and clinical variables were collected. Follow-up lasted approximately 1 year, and PEx were registered. RESULTS: The study population comprised 160 subjects selected from 360 CF patients monitored in the participating CF units. The mean age was 28 years, 47.5% were women, and mean forced expiratory volume in 1 s (FEV1) was 67.5%. The mean global modified Bhalla score was 14.5 ± 0.31 points. Pulmonary function test (PFT) results and the modified Bhalla score correlated well, mainly forced vital capacity (FVC) and FEV1. We constructed a statistical model based on the overall Bhalla score to predict the number of PEx. CONCLUSIONS: The overall modified Bhalla score can predict future PEx in CF patients. This useful tool can help to prevent PEx in higher risk patients. KEY POINTS: • Pulmonary function test results and the modified Bhalla score correlated well with FVC and FEV1. • The total modified Bhalla score can predict the number of exacerbations in adult CF patients. • Our findings highlight the need to establish a unified protocol for chest HRCT during the follow-up of adult patients with CF in order to anticipate possible complications and determine their impact on pulmonary function.

Caso de atresia bronquial / A case of bronchial atresia

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MR imaging of isolated right subclavian artery.

We report the MRI findings in a 3-week-old boy with D-transposition of the great arteries and an abnormal origin of the right subclavian artery from the pulmonary artery. This anomaly of the subclavian arteries is called isolation. It is infrequent in patients with a right aortic arch, but exceedingly rare in those with a left aortic arch. This is a unique report of the MRI findings in this congenital abnormality of the aortic arch.

Endovascular stent-graft treatment of thoracic aortic disease.

Aneurysmal diseases of the thoracic aorta are life-threatening conditions. In such cases, stent-graft treatment has been proposed as an alternative to surgery. The morbidity and mortality associated with endovascular repair are significantly lower than those associated with open surgery. In the largest surgical series, the mortality ranged from 5% to 20%. In studies of endovascular repair, the 30-day mortality was 0%-20% and the periprocedural stroke rate was 0%-7%. Often, open surgery is prohibited in patients with these high-risk lesions; thus, in many cases endovascular treatment is the only alternative. Thoracic aortic diseases that can be treated with endovascular stent-graft placement include aneurysms, dissection, traumatic rupture, traumatic pseudoaneurysms, intramural hematoma, penetrating atherosclerotic ulcers, and aortic rupture. Thorough preprocedure imaging is essential for selecting patients, choosing the stent-graft devices, and planning the intervention. Prerequisites for endovascular stent-graft placement are an adequate neck for graft attachment and adequate vascular access. When the ascending aorta or aortic arch is involved, surgical and endovascular procedures can be combined and performed simultaneously, allowing treatment of a wider range of cases. An experienced interdisciplinary team is needed to manage such cases.