African American race is associated with worse sleep quality in heavy smokers.

STUDY OBJECTIVES: To examine the association of self-identified race with sleep quality in heavy smokers. METHODS: We studied baseline data from 1965 non-Hispanic White and 462 African American participants from SPIROMICS with ≥ 20 pack-years smoking history. We first examined the Pittsburgh Sleep Quality Index's (PSQI) internal consistency and item-total correlation in a population with chronic obstructive pulmonary disease. We then used staged multivariable regression to investigate the association of race and sleep quality as measured by the PSQI) The first model included demographics, the second added measures of health status, and the third, indicators of socioeconomic status. We next explored the correlation between sleep quality with 6-minute walk distance and St. George's Respiratory Questionnaire score as chronic obstructive pulmonary disease-relevant outcomes. We tested for interactions between self-identified race and the most important determinants of sleep quality in our conceptual model. RESULTS: We found that the PSQI had good internal consistency and item-total correlation in our study population of heavy smokers with and without chronic obstructive pulmonary disease. African American race was associated with increased PSQI in univariable analysis and after adjustment for demographics, health status, and socioenvironmental exposures (P = .02; 0.44 95%CI: .06 to .83). Increased PSQI was associated with higher postbronchodilator forced expiratory volume in 1 second and lower household income, higher depressive symptoms, and female sex. We identified an interaction wherein depressive symptoms had a greater impact on PSQI score for non-Hispanic White than African American participants (P for interaction = .01). CONCLUSIONS: In heavy smokers, self-reported African American race is independently associated with worse sleep quality. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: Study of COPD Subgroups and Biomarkers (SPIROMICS); URL: https://clinicaltrials.gov/ct2/show/NCT01969344; Identifier: NCT01969344. CITATION: Baugh AD, Acho M, Arhin A, et al. African American race is associated with worse sleep quality in heavy smokers. J Clin Sleep Med. 2023;19(8):1523-1532.

Impact of a Mechanical Ventilation Curriculum on Respiratory Therapist Recognition of Patient-Ventilator Asynchrony.

BACKGROUND: Respiratory therapists (RTs) play a crucial role in managing mechanically ventilated patients, such as addressing patient-ventilator asynchronies that may contribute to patient harm. Waveform analysis is integral to the evaluation of patient-ventilator asynchronies; despite this, no published studies have assessed the ability of practicing RTs to interpret ventilator waveform abnormalities. METHODS: The study took place between June 2017-February 2019. Eighty-six RTs from 2 academic medical centers enrolled in a one-day mechanical ventilation course. The scores of 79 first-time attendees were included in the analysis. Prior to and following the course, RTs were asked to identify abnormalities on a 5-question, multiple-choice ventilator waveform exam. They were also asked to provide a self-assessment of their ventilator management skills on a 1 (complete novice) to 5 (expert) scale. RESULTS: Initial scores were low but improved after one day of ventilator instruction (19.4 ± 17.1 vs 29.6 ± 19.0, P < .001). No significant difference was noted in mean confidence levels between the pre- and post-course assessments (3.8 ± 0.9 vs 3.8 ± 1.0, P = .56). RTs with fewer years of clinical experience (0-10 y) had a statistically significant improvement in their post-course test scores relative to their pre-course scores (0-5 y: 12.5 ± 10.1 to 46.0 ± 10.8, P < .001; 6-10 y: 18.7 ± 15.8 to 32.1 ± 16.7, P = .02), whereas those with > 11 y of clinical experience did not (11-20 y: 22.4 ± 15.5 to 27.4 ± 19.0, P = .44; 21+ y: 19.6 ± 22.1 to 15.3 ± 13.8, P = .50). CONCLUSIONS: RTs may benefit from additional training in ventilator waveform interpretation, especially early in their clinical training. More work is needed to determine the optimal length and content of a mechanical ventilation curriculum for RTs.

How I Teach Auto-PEEP: Applying the Physiology of Expiration.

Teaching complex topics in mechanical ventilation can prove challenging for clinical educators, both at the bedside and in the classroom setting. Some of these topics, such as the topic of auto-positive end-expiratory pressure (auto-PEEP), consist of complicated physiological principles that can be difficult to convey in an organized and intuitive manner. In this entry of "How I Teach," we provide an approach to teaching the concept of auto-PEEP to senior residents and fellows working in the intensive care unit. We offer a framework for educators to effectively present the concepts of auto-PEEP to learners, either at the bedside or in the classroom setting, by summarizing key concepts and including concrete examples of the educational techniques we use. This framework includes specific content we emphasize, how to present this content using a variety of educational resources, assessing learner understanding, and how to modify the topic on the basis of location, time, or resource constraints.

ATS Core Curriculum 2020. Adult Critical Care Medicine.

The American Thoracic Society Core Curriculum updates clinicians annually in adult and pediatric pulmonary disease, medical critical care, and sleep medicine, in a 3- to 4-year recurring cycle of topics. These topics will be presented at the 2020 International Conference. Below is the adult critical care medicine core including complications of chemotherapy, acute-on-chronic liver failure, alcohol withdrawal syndrome, mechanical circulatory support, direct oral anticoagulants, upper gastrointestinal hemorrhage, and vasopressor selection.

Impact of Novel Multiinstitutional Curriculum on Critical Care Fellow Ventilator Knowledge.

Background: Management of mechanical ventilation (MV) is a curricular milestone for trainees in pulmonary critical care medicine (PCCM) and critical care medicine (CCM) fellowships. Though recognition of ventilator waveform abnormalities that could result in patient complications is an important part of management, it is unclear how well fellows recognize these abnormalities.Objective: To study proficiency of ventilator waveform analysis among first-year fellows enrolled in a MV course compared with that of traditionally trained fellows.Methods: The study took place from July 2016 to January 2019, with 93 fellows from 10 fellowship programs completing the waveform examination. Seventy-three fellows participated in a course during their first year of fellowship, with part I occurring at the beginning of fellowship in July and part II occurring after 6 months of clinical work. These fellows were given a five-question ventilator waveform examination at multiple time points throughout the two-part course. Twenty fellows from three other fellowship programs who were in their first, second, or third year of fellowship and who did not participate in this course served as the control group. These fellows took the waveform examination a single time, at a median of 23 months into their training.Results: Before the course, scores were low but improved after 3 days of education at the beginning of the fellowship (18.0 ± 1.6 vs. 45.6 ± 3.0; P < 0.0001). Scores decreased after 6 months of clinical rotations but increased to their highest levels after part II of the course (33.7 ± 3.1 for part II pretest vs. 77.4 ± 2.4 for part II posttest; P < 0.0001). After completing part I at the beginning of fellowship, fellows participating in the course outperformed control fellows, who received a median of 23 months of traditional fellowship training at the time of testing (45.6 ± 3.0 vs. 25.3 ± 2.7; P < 0.0001). There was no difference in scores between PCCM and CCM fellows. In anonymous surveys, the fellows also rated the mechanical ventilator lectures highly.Conclusion: PCCM and CCM fellows do not recognize common waveform abnormalities at the beginning of fellowship but can be trained to do so. Traditional fellowship training may be insufficient to master ventilator waveform analysis, and a more intentional, structured course for MV may help fellowship programs meet the curricular milestones for MV.