Exacerbations and Pseudomonas aeruginosa colonization are associated with altered lung structure and function in primary ciliary dyskinesia.

BACKGROUND: Recurrent bacterial infections of the respiratory tract are one of the major clinical features of the primary ciliary dyskinesia (PCD), a rare genetic disease due to malfunctioning of motile cilia. Chronic infections and persistent inflammation of the respiratory system result in progressive lung disease. Aim of the study was to highlight the main factors associated with clinical, functional and anatomical deterioration in PCD patients. METHODS: We retrospectively analyzed data from 58 patients with PCD, 37 adults and 21 children. The demographic and clinical data, forced expiratory volume at 1 s (FEV1) and forced vital capacity (FVC), sputum microbiology and imaging results (chest CT scores-modified Bhalla) were recorded. Patients were stratified according to the number of exacerbations (< 2/year vs ≥ 2/year) and chronic Pseudomonas aeruginosa (PA) colonization. The possible correlations between lung function and chest CT scores were assessed; we also evaluated the correlation between these parameters and the severity scores for bronchiectasis (BSI, FACED and e-FACED). RESULTS: Chest CT scores showed a significant correlation with FEV1 (p = 0.0002), age (p <  0.0001), BMI (p = 0.0002) and number of lung lobes involved (p <  0.0001). PA colonization had an overall prevalence of 32.6%: no significant difference in FEV1 between PA colonized and non-colonized patients was found (p = 0.70), while chest CT score was significantly worse in chronic PA colonized patients (p = 0.009). Patients with a high number of exacerbation (≥ 2/year) were older (p = 0.01), had lower FEV1 (p = 0.03), greater number of lobes involved (p < 0.001) and worse CT score than patients with low number of exacerbations (p = 0.001); they also had higher prevalence of PA chronic bronchial infection (33.3% versus 13.6%, p = 0.10). Multivariable linear regression analyses adjusted for gender, age and BMI showed positive associations between PA colonization and number of exacerbations with severity of disease (number of lobes involved, CT score, BSI, FACED, and e-FACED). CONCLUSIONS: In our PCD population the number of exacerbations (≥ 2/year) and PA colonization were the two most relevant factors associated with severity of disease.

Association of severe COVID-19 outcomes with radiological scoring and cardiomegaly: findings from the COVID-19 inpatients database, Japan.

PURPOSE: We aimed to characterize novel coronavirus infections based on imaging [chest X-ray and chest computed tomography (CT)] at the time of admission. MATERIALS AND METHODS: We extracted data from 396 patients with laboratory-confirmed COVID-19 who were managed at 68 hospitals in Japan from January 25 to September 2, 2020. Case patients were categorized as severe (death or treatment with invasive ventilation during hospitalization) and non-severe groups. The imaging findings of the groups were compared by calculating odds ratios (ORs) and 95% confidence intervals (95% CIs), adjusted for sex, age, and hospital size (and radiographic patient positioning for cardiomegaly). Chest X-ray and CT scores ranged from 0 to 72 and 0 to 20, respectively. Optimal cut-off values for these scores were determined by a receiver-operating characteristic (ROC) curve analysis. RESULTS: The median age of the 396 patients was 48 years (interquartile range 28-65) and 211 (53.3%) patients were male. Thirty-two severe cases were compared to 364 non-severe cases. At the time of admission, abnormal lesions on chest X-ray and CT were mainly observed in the lower zone/lobe. Among severe cases, abnormal lesions were also seen in the upper zone/lobe. After adjustment, the total chest X-ray and CT score values showed a dose-dependent association with severe disease. For chest X-ray scores, the area under the ROC curve (AUC) was 0.91 (95% CI = 0.86-0.97) and an optimal cut-off value of 9 points predicted severe disease with 83.3% sensitivity and 84.7% specificity. For chest CT scores, the AUC was 0.94 (95% CI = 0.89-0.98) and an optimal cut-off value of 11 points predicted severe disease with 90.9% sensitivity and 82.2% specificity. Cardiomegaly was strongly associated with severe disease [adjusted OR = 24.6 (95% CI = 3.7-166.0)]. CONCLUSION: Chest CT and X-ray scores and the identification of cardiomegaly could be useful for classifying severe COVID-19 on admission.

Predicting disease progression in cystic fibrosis.

INTRODUCTION: Progressive lung disease is the major cause of morbidity and mortality in patients with cystic fibrosis (CF). Methods of correctly predicting the future progression of lung disease in patients with CF are essential for directing aggressive treatment to prevent loss of lung function and end stage respiratory failure. Areas covered: This review addresses predictors of respiratory disease progression in patients with CF. We searched Web of Science and Medline, with no restriction on publication date, with the search terms 'cystic fibrosis' and 'disease progression', 'lung function decline', 'prognosis', 'prediction/predictive', 'prediction/prognostic scores', 'risk factors', 'outcome measures/endpoints/disease surrogate', 'longitudinal/long term', 'statistical model', and 'survival'. Expert commentary: Forced expiratory volume in 1 sec (FEV1) and rate of FEV1 decline, remain the most significant predictors of mortality in patients with CF while CT scores and airway secretion biomarkers are the main predictors of early CF lung disease. Comprehensive scores incorporating clinical, lung function, imaging and laboratory data will become essential in the future for predicting disease progression and for use in clinical trials. Early interventions may delay the progression of structural lung disease.