Comparison of Clinical Measures Among Interstitial Lung Disease (ILD) Patients with Usual Interstitial Pneumonia (UIP) Patterns on High-Resolution Computed Tomography.

PURPOSE: Idiopathic Pulmonary Fibrosis is a progressive and fatal interstitial lung disease (ILD) characterized by a typical radiographic or histologic usual interstitial pneumonia (UIP) pattern. In 2018, diagnostic categories of UIP based on computed tomography patterns were revised by the Fleischner Society. The study aimed to describe differences in comorbidities and spirometry in ILD patients that were characterized by high-resolution computed tomography (HRCT) images as having a typical, probable, indeterminate, and alternative diagnosis of UIP. METHODS: We retrospectively studied 80 ILD patients from 2017 to 2019. Typical UIP was defined using the Fleischner Society diagnostic criteria for IPF. Atypical UIP was reached by consensus after a multidisciplinary clinical-radiological-pathological review of patient data. Baseline characteristics, comorbidities, and spirometry were compared among the four subgroups. RESULTS: Among 80 patients, 59% were male, 61% had a history of smoking, and the mean age was 67.7 ± 10 years (SD). A typical UIP pattern was more frequently observed among patients with chronic obstructive pulmonary disease (COPD) (p < 0.001) and pulmonary hypertension (p = 0.03). Of 30 patients with COPD, 14 had emphysema, while 10 had IPF. After adjusting for forced expiratory volume in one second (FEV1) in liters, change of FEV1% from baseline to 6-12 months, age, and sex, only COPD remained significantly associated with typical UIP (p = 0.018). Tobacco use was not significantly associated with any radiographic type (p = 0.199). CONCLUSION: Typical UIP was prevalent among COPD/emphysema patients. Although smoking has a strong association with IPF, we did not find a significant association with smoking and typical UIP in our cohort.

Advances in Targeted Therapy for Progressive Fibrosing Interstitial Lung Disease.

Progressive fibrosing interstitial lung disease (PF-ILD) has been redefined as a new clinical syndrome that shares similar genetics, pathophysiology, and natural history to idiopathic pulmonary fibrosis (IPF). IPF is the most common form of idiopathic interstitial pneumonias, which is progressive in nature and is associated with significant mortality. Therapies targeting an inflammatory and/or immune response have not been consistently effective or well tolerated in patients with IPF. The two antifibrotic drugs approved for IPF treatment, nintedanib and pirfenidone, have been shown to reduce lung function decline in PF-ILD. Novel uses of antifibrotic therapy are emerging due to a paucity of evidence-based treatments for multiple ILD subtypes. In this review, we describe the current body of knowledge on antifibrotic therapy and immunomodulators in PF-ILD, drawing from experience in IPF where appropriate.

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.

Prevalence and Predictors of Deep Vein Thrombosis in Critically Ill Medical Patients Who Underwent Diagnostic Duplex Ultrasonography.

INTRODUCTION: Deep vein thrombosis (DVT) is a recognized but preventable cause of morbidity and mortality in the medical intensive care unit (MICU). We examined the prevalence and risk factors for DVT in MICU patients who underwent diagnostic venous duplex ultrasonography (DUS) and the potential effect on clinical outcomes. METHODS: This is a retrospective study examining prevalence of DVT in 678 consecutive patients admitted to a tertiary care level academic MICU from July 2014 to 2015. Patients who underwent diagnostic DUS were included. Potential conditions of interest were mechanical ventilation, hemodialysis, sepsis, Sequential Organ Failure Assessment (SOFA) scores, central venous catheters, prior DVT, and malignancy. Primary outcomes were pulmonary embolism, ICU length of stay, and mortality. Additionally, means of thromboprophylaxis was compared between the groups. Multivariable logistic regression analysis was utilized to determine predictors of DVT occurrence. RESULTS: Of the 678 patients, 243 (36%) patients underwent DUS to evaluate for DVT. The prevalence of DVT was 16% (38) among tested patients, and a prior history of DVT was associated with DVT prevalence (P < .01). Between cases and controls, there were no significant differences in central venous catheters, mechanical ventilation, hemodialysis, sepsis, SOFA scores, malignancy, and recent surgery. Patients receiving chemical prophylaxis had fewer DVTs compared to persons with no prophylaxis (14% vs 29%; P = .01) and persons with dual chemical and mechanical prophylaxis (P = 0.1). Fourteen percent of patients tested had documented DVT while on chemoprophylaxis. There were no significant differences in ICU length of stay (P = .35) or mortality (P = .34). CONCLUSIONS: Despite the appropriate use of universal thromboprophylaxis, critically ill nonsurgical patients still demonstrated high rates of DVT. A history of DVT was the sole predictor for development of proximal DVT on DUS testing. Dual chemical and mechanical prophylaxis does not appear to be superior to single-chemical prophylaxis in DVT prevention in this population.

Comparison of body adiposity index (BAI) and BMI with estimations of % body fat in clinically severe obese women.

OBJECTIVE: Body adiposity index (BAI), a new surrogate measure of body fat (hip circumference/(height(1.5) - 18)), has been proposed as an alternative to body mass index (BMI). We compared BAI with BMI, and each of them with laboratory measures of body fat-derived from bioimpedance analysis (BIA), air displacement plethysmography (ADP), and dual-energy X-ray absorptiometry (DXA) in clinically severe obese (CSO) participants. DESIGN AND METHODS: Nineteen prebariatric surgery CSO, nondiabetic women were recruited (age = 32.6 ± 7.7 SD; BMI = 46.5 ± 9.0 kg/m(2) ). Anthropometrics and body fat percentage (% fat) were determined from BIA, ADP, and DXA. Scatter plots with lines of equality and Bland-Altman plots were used to compare BAI and BMI with % fat derived from BIA, ADP, and DXA. BAI and BMI correlated highly with each other (r = 0.90, P < 0.001). RESULTS: Both BAI and BMI correlated significantly with % fat from BIA and ADP. BAI, however, did not correlate significantly with % fat from DXA (r = 0.42, P = 0.08) whereas BMI did (r = 0.65, P = 0.003). BMI was also the single best predictor of % fat from both BIA (r(2) = 0.80, P < 0.001) and ADP (r(2) = 0.65, P < 0.001). The regression analysis showed that the standard error of the estimate (SEE), or residual error around the regression lines, was greater for BAI comparisons than for BMI comparisons with BIA, ADP, and DXA. Consistent with this, the Bland and Altman plots indicated wider 95% confidence intervals for BAI difference comparisons than for BMI difference comparisons for their respective means for BIA, ADP, and DXA. CONCLUSIONS: Thus, BAI does not appear to be an appropriate proxy for BMI in CSO women.