Computed Tomography of Bronchiectasis

Naidich, David P.; McCauley, Dorothy I.; Khouri, Nagi F.; Stitik, Frederick P.; Siegelman, Stanley S.

doi:10.1097/00004728-198206000-00001

Cited by 403 publications

(187 citation statements)

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“…The presence of bronchiectasis was based on criteria published by NAIDICH et al [18]. The extent of the bronchiectasis was evaluated according to the number of pulmonary lobes and segments affected, with the lingula and middle lobe considered as independent lobes.…”

Section: Construction Cohort N=397mentioning

confidence: 99%

Multidimensional approach to non-cystic fibrosis bronchiectasis: the FACED score

et al. 2013

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Bronchiectasis is a multidimensional disease and, therefore, its severity or prognosis cannot be adequately quantified by analysing one single variable. The objective of the present study was to develop a multidimensional score that classifies the severity of bronchiectasis according to its prognosis. This is an observational multicentre study including 819 patients diagnosed with non-cystic fibrosis bronchiectasis using high-resolution computed tomography. 397 subjects were selected at random to construct the score while the remaining 422 were used for its validation. The outcome was 5-year all-cause mortality after radiological diagnosis. A logistic regression analysis was used to select the variables included in the final score.The final seven-point score incorporated five dichotomised variables: forced expiratory volume in 1 s % predicted (F, cut-off 50%, maximum value 2 points); age (A, cut-off 70 years, maximum value 2 points); presence of chronic colonisation by Pseudomonas aeruginosa (C, dichotomic, maximum value 1 point); radiological extension (E, number of lobes affected, cut-off two lobes, maximum value 1 point); and dyspnoea (D, cut-off grade II on the Medical Research Council scale, maximum value 1 point) to construct the FACED score. The validation cohort confirmed the score's validity.We conclude that this easy-to-use multidimensional grading system proved capable of accurately classifying the severity of bronchiectasis according to its prognosis. @ERSpublications An easy-to-use multidimensional grading system accurately classifies bronchiectasis severity according to prognosis

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Section: Construction Cohort N=397mentioning

confidence: 99%

Multidimensional approach to non-cystic fibrosis bronchiectasis: the FACED score

et al. 2013

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“…The study included individuals diagnosed with bronchiectasis based on the HRCT findings 24 who were clinically stable (absence of respiratory infection in the 4 weeks preceding the study), had no history of smoking, and were ≥18 years of age. Individuals with a history or diagnosis of asthma or a pleural or cardiovascular disease were excluded, as were the patients who had been subjected to a lung resection or used oral corticosteroids in the 4 weeks preceding the study.…”

Section: Patientsmentioning

confidence: 99%

Impact of Different Etiologies of Bronchiectasis on the Pulmonary Function Tests

Lopes

Camilo

Menezes

et al. 2014

Clinical Medicine & Research

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“…The slight respiratory motion shifts a given longitudinally oriented pulmonary vessel during the scan, so that in the image, the vessel appears in two different locations. The resultant double, parallel lines look like the thickened bronchial walls that occur with bronchiectasis [2] (Fig. 1 A).…”

Section: Methodsmentioning

confidence: 98%