Impact of Bronchiectasis on COPD Severity and Alpha-1 Antitrypsin Deficiency as a Risk Factor in Individuals with a Heavy Smoking History.

Rationale: Bronchiectasis is common among those with heavy smoking histories, but risk factors for bronchiectasis, including alpha-1 antitrypsin deficiency, and its implications for COPD severity are uncharacterized in such individuals. Objectives: To characterize the impact of bronchiectasis on COPD and explore alpha-1antitrypsin as a risk factor for bronchiectasis. Methods: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) participants (N=914; ages 40-80 years; ≥20-pack-year smoking) had high-resolution computed tomography (CT) scans interpreted visually for bronchiectasis, based on airway dilation without fibrosis or cicatrization. We performed regression-based models of bronchiectasis with clinical outcomes and quantitative CT measures. We deeply sequenced the gene encoding -alpha-1 antitrypsin, SERPINA1, in 835 participants to test for rare variants, focusing on the PiZ genotype (Glu366Lys, rs28929474). Measurements and Main Results: We identified bronchiectasis in 365 (40%) participants, more frequently in women (45% versus 36%, p=0.0045), older participants (mean age=66[standard deviation (SD)=8.3] versus 64[SD=9.1] years, p=0.0083), and those with lower lung function (forced expiratory volume in 1 second [FEV1 ] percentage predicted=66%[SD=27] versus 77%[SD=25], p<0.0001; FEV1 to forced vital capacity [FVC] ratio=0.54[0.17] versus 0.63[SD=0.16], p<0.0001). Participants with bronchiectasis had greater emphysema (%voxels ≤-950 Hounsfield units, 11%[SD=12] versus 6.3%[SD=9], p<0.0001) and parametric response mapping functional small airways disease (26[SD=15] versus 19[SD=15], p<0.0001). Bronchiectasis was more frequent in the combined PiZZ and PiMZ genotype groups compared to those without PiZ, PiS, or other rare pathogenic variants (N=21 of 40 [52%] versus N=283 of 707[40%], odds ratio [OR]=1.97; 95% confidence interval [CI]=1.002, 3.90, p=0.049), an association attributed to White individuals (OR=1.98; 95%CI = 0.9956, 3.9; p=0.051). Conclusions: Bronchiectasis was common in those with heavy smoking histories and was associated with detrimental clinical and radiographic outcomes. Our findings support alpha-1antitrypsin guideline recommendations to screen for alpha-1 antitrypsin deficiency in an appropriate bronchiectasis subgroup with a significant smoking history.

Factors Affecting Patient Adherence to Lung Cancer Screening.

OBJECTIVES: The National Lung Screening Trial (NLST) demonstrated a 20% reduction in mortality with low-dose computed tomography (CT) for lung cancer screening (LCS). The NLST found the greatest benefit to LCS for patients who underwent annual screening for a full 3-year follow-up period. The adherence to serial imaging in the NLST was 95%. METHODS: We conducted a prospective study of 268 patients who presented for LCS and who were not enrolled in a research study to determine the adherence to recommended follow-up imaging and biopsy at a single center. We evaluated the correlations among sociodemographic characteristics, Lung Imaging and Reporting Data System, and adherence. RESULTS: Only 48% of the patient population received recommended follow-up (either imaging or biopsy) after their referent LCS. Patients with abnormal LCS (Lung Imaging and Reporting Data System 3 or 4) were more likely to adhere to the recommended follow-up (additional imaging or biopsy) compared with those with negative screens. Sex, ethnicity, smoking status, and household income were not correlated with adherence to screening and biopsy. CONCLUSIONS: The benefits from LCS observed in the NLST may be undermined by low adherence to follow-up screening. Studies targeting LCS patients to bolster adherence to follow-up are needed.

Effects of deep sedation on sleep in critically ill medical patients on mechanical ventilation.

Atypical EEG patterns not consistent with standard sleep staging criteria have been observed in medical intensive care unit (ICU) patients. Our aim was to examine the relationship between sleep architecture and sedation in critically ill mechanically ventilated patients pre- and post-extubation. We performed a prospective observational repeated measures study where 50 mechanically ventilated patients with 31 paired analyses were examined at an academic medical centre. The sleep efficiency was 58.3 ± 25.4% for intubated patients and 45.6 ± 25.4% for extubated patients (p = .02). Intubated patients spent 76.33 ± 3.34% of time in non-rapid eye movement (NREM) sleep compared to 64.66 ± 4.06% of time for extubated patients (p = .02). REM sleep constituted 1.36 ± 0.67% of total sleep time in intubated patients and 2.06 ± 1.09% in extubated patients (p = .58). Relative sleep atypia was higher in intubated patients compared to extubated patients (3.38 ± 0.87 versus 2.79 ± 0.42; p < .001). Eleven patients were sedated with propofol only, 18 patients with fentanyl only, 11 patients with fentanyl and propofol, and 10 patients had no sedation. The mean sleep times on "propofol", "fentanyl", "propofol and fentanyl," and "no sedation" were 6.54 ± 0.64, 4.88 ± 0.75, 6.20 ± 0.75 and 4.02 ± 0.62 hr, respectively. The sigma/alpha values for patients on "propofol", "fentanyl", "propofol and fentanyl" and "no sedation" were 0.69 ± 0.04, 0.54 ± 0.01, 0.62 ± 0.02 and 0.57 ± 0.02, respectively. Sedated patients on mechanical ventilation had higher sleep efficiency and more atypia compared to the same patients following extubation. Propofol was associated with higher sleep duration and less disrupted sleep architecture compared to fentanyl, propofol and fentanyl, or no sedation.

Spirometry in Hospitalized Patients with Acute Exacerbation of COPD Accurately Predicts Post Discharge Airflow Obstruction.

Purpose: Objective documentation of airflow obstruction is often lacking inhospitalized patients treated for acute exacerbation of chronic obstructive pulmonary disease (AECOPD). The utility of spirometry performed in hospitalized patients to identify airflow obstruction, and thus a diagnosis of COPD, is unclear. Our aim was to compare inpatient spirometry, performed during an AECOPD, with outpatient spirometry. Methods: A retrospective analysis of data from patients enrolled in an AECOPD care plan was performed. As part of the plan, patients underwent inpatient spirometry to establish a COPD diagnosis and outpatient clinic spirometry within 4 weeks of hospital discharge to confirm it. Data analyzed included forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), slow vital capacity (SVC) and FEV1/ vital capacity (VC). Obstruction was defined by FEV1/VC<0.70. Results: A total of 159 patients (mean age 63.2 +/- 10.5 years) had corresponding in- and outpatient spirometry. The median days between inpatient and outpatient spirometry was 12 (interquartile range [IQR] 9-16). Inpatient spirometry had a sensitivity of 94%, specificity of 24%, positive predictive value of 83% and negative predictive value of 53% for predicting outpatient obstruction. The area under curve for using inpatient spirometry was 0.82. The mean difference between inpatient and outpatient FEV1 was 0.44 +/- 0.03 liters or 17.3 +/- 1.13 % predicted (p<0.0001) for FEV1. Conclusions: Inpatient spirometry accurately predicts outpatient airflow obstruction, thus providing an opportunity to identify patients admitted with suspected AECOPD who have no prior spirometric documentation.

Impact of Obesity on Outcomes in a Multiethnic Cohort of Medical Intensive Care Unit Patients.

PURPOSE: To examine the association of obesity with in-hospital mortality and complications during critical illness. METHODS: We performed a retrospective analysis of a multiethnic cohort of 699 patients admitted to medical intensive care unit between January 2010 and May 2011 at Mount Sinai St. Luke's and Mount Sinai West Hospitals, tertiary care centers in New York City. Multivariate logistic regression analysis was used to evaluate the association between obesity (body mass index [BMI] ≥ 30] and in-hospital mortality. Subgroup analysis was performed in elderly patients (age ≥65 years). RESULTS: Compared to normal BMI, obese patients had lower in-hospital mortality (24.4% vs 17.6%, P = .04). On multivariate analysis, obesity was independently associated with lower in-hospital mortality (odds ratio [OR]: 0.49, 95% confidence interval [CI]: 0.27-0.89, P = .018). There was no significant difference in rates of mechanical ventilation, reintubation, and vasopressor requirement across BMI categories. In subgroup analysis, elderly obese patients did not display lower in-hospital mortality (adjusted OR: 0.85, 95% CI: 0.40-1.82, P = .68). CONCLUSION: Our study supports the hypothesis that obesity is associated with decreased mortality during critical illness. However, this finding was not observed among elderly obese patients. Further studies should explore the interaction between age, obesity, and outcomes in critical illness.