Exacerbations Among Patients With Asthma Are Largely Dependent on the Presence of Multimorbidity

BACKGROUND AND OBJECTIVE

Comorbidities can influence asthma control and promote asthma exacerbations (AEs). However, the impact of multimorbidity in AEs, assessed based on long-term follow-up of patients with asthma of different degrees of severity, has received little attention in real-life conditions. To describe the epidemiological and clinical characteristics and predictors of AEs in patients who had presented at least 1 AE in the previous year in the MEchanism of Genesis and Evolution of Asthma (MEGA) cohort.

METHODS

The work-up included a detailed clinical examination, pulmonary function testing, fractional exhaled nitric oxide (FeNO), blood counts, induced sputum, skin prick-tests, asthma questionnaires, and assessment of multimorbidity. The number of moderate-severe AEs in the preceding year was registered for each patient.

RESULTS

The study population comprised 486 patients with asthma (23.7% mild, 35% moderate, 41.3% severe). Disease remained uncontrolled in 41.9%, and 47.3% presented ≥1 moderate-severe AE, with a mean (SD) annual exacerbation rate of 0.47 (0.91) vs 2.11 (2.82) in mild and severe asthma, respectively. Comorbidity was detected in 56.4% (66.6% among those with severe asthma). Bronchiectasis, chronic rhinosinusitis with nasal polyps, atopy, psychiatric illnesses, hyperlipidemia, and hypertension were significantly associated with AEs. No associations were found for FeNO, blood eosinophils, or total serum IgE. Sputum eosinophilia and a high-T2 inflammatory pattern were significantly associated with AEs. Multivariable regression analysis showed a significant association with asthma severity, uncontrolled disease, and low prebronchodilator FEV1/FVC.

CONCLUSION

Our study revealed a high frequency of AE in the MEGA cohort. This was strongly associated with multimorbidity, asthma severity, poor asthma control, airflow obstruction, higher sputum eosinophils, and a very high-T2 inflammatory pattern.

Improvement in Olfaction in Patients With CRSwNP and Severe Asthma Taking Anti-IgE and Anti-IL-5 Biologics: A Real-Life Study

BACKGROUND AND OBJECTIVES

Chronic rhinosinusitis with nasal polyps (CRSwNP), which is characterized by partial loss of smell (hyposmia) or total loss of smell (anosmia), is commonly associated with asthma and/or nonsteroidal anti-inflammatory drug-exacerbated respiratory disease (N-ERD). CRSwNP worsens disease severity and quality of life. The objective of this real-world study was to determine whether biological treatments prescribed for severe asthma can improve olfaction in patients with CRSwNP. A further objective was to compare the improvement in in olfaction in N-ERD and non-N-ERD subgroups.

METHODS

We performed a multicenter, noninterventional, retrospective, observational study of 206 patients with severe asthma and CRSwNP undergoing biological treatment (omalizumab, mepolizumab, benralizumab, or reslizumab).

RESULTS

Olfaction improved after treatment with all 4 monoclonal antibodies (omalizumab [35.8%], mepolizumab [35.4%], reslizumab [35.7%], and benralizumab [39.1%]), with no differences between the groups. Olfaction was more likely to improve in patients with atopy, more frequent use of short-course systemic corticosteroids, and larger polyp size. The proportion of patients whose olfaction improved was similar between the N-ERD (37%) and non-N-ERD (35.7%) groups.

CONCLUSIONS

This is the first real-world study to compare improvement in olfaction among patients undergoing long-term treatment with omalizumab, mepolizumab, reslizumab, or benralizumab for severe asthma and associated CRSwNP. Approximately 4 out of 10 patients reported a subjective improvement in olfaction (with nonsignificant differences between biologic drugs). No differences were found for improved olfaction between the N-ERD and non-N-ERD groups.

An Experimental Assessment of Depth Estimation in Transparent and Translucent Scenes for Intel RealSense D415, SR305 and L515

RGB-D cameras have become common in many research fields since these inexpensive devices provide dense 3D information from the observed scene. Over the past few years, the RealSense™ range from Intel^® has introduced new, cost-effective RGB-D sensors with different technologies, more sophisticated in both hardware and software. Models D415, SR305, and L515 are examples of successful cameras launched by Intel^® RealSense™ between 2018 and 2020. These three cameras are different since they have distinct operating principles. Then, their behavior concerning depth estimation while in the presence of many error sources will also be specific. For instance, semi-transparent and scattering media are expected error sources for an RGB-D sensor. The main new contribution of this paper is a full evaluation and comparison between the three Intel RealSense cameras in scenarios with transparency and translucency. We propose an experimental setup involving an aquarium and liquids. The evaluation, based on repeatability/precision and statistical distribution of the acquired depth, allows us to compare the three cameras and conclude that Intel RealSense D415 has overall the best behavior namely in what concerns the statistical variability (also known as precision or repeatability) and also in what concerns valid measurements.

EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos

Deep learning techniques hold promise to develop dense topography reconstruction and pose estimation methods for endoscopic videos. However, currently available datasets do not support effective quantitative benchmarking. In this paper, we introduce a comprehensive endoscopic SLAM dataset consisting of 3D point cloud data for six porcine organs, capsule and standard endoscopy recordings, synthetically generated data as well as clinically in use conventional endoscope recording of the phantom colon with computed tomography(CT) scan ground truth. A Panda robotic arm, two commercially available capsule endoscopes, three conventional endoscopes with different camera properties, two high precision 3D scanners, and a CT scanner were employed to collect data from eight ex-vivo porcine gastrointestinal (GI)-tract organs and a silicone colon phantom model. In total, 35 sub-datasets are provided with 6D pose ground truth for the ex-vivo part: 18 sub-datasets for colon, 12 sub-datasets for stomach, and 5 sub-datasets for small intestine, while four of these contain polyp-mimicking elevations carried out by an expert gastroenterologist. To verify the applicability of this data for use with real clinical systems, we recorded a video sequence with a state-of-the-art colonoscope from a full representation silicon colon phantom. Synthetic capsule endoscopy frames from stomach, colon, and small intestine with both depth and pose annotations are included to facilitate the study of simulation-to-real transfer learning algorithms. Additionally, we propound Endo-SfMLearner, an unsupervised monocular depth and pose estimation method that combines residual networks with a spatial attention module in order to dictate the network to focus on distinguishable and highly textured tissue regions. The proposed approach makes use of a brightness-aware photometric loss to improve the robustness under fast frame-to-frame illumination changes that are commonly seen in endoscopic videos. To exemplify the use-case of the EndoSLAM dataset, the performance of Endo-SfMLearner is extensively compared with the state-of-the-art: SC-SfMLearner, Monodepth2, and SfMLearner. The codes and the link for the dataset are publicly available at https://github.com/CapsuleEndoscope/EndoSLAM. A video demonstrating the experimental setup and procedure is accessible as Supplementary Video 1.

Assessing Adherence by Combining the Test of Adherence to Inhalers With Pharmacy Refill Records

BACKGROUND AND OBJECTIVE

The Global Initiative for Asthma (GINA) recommends the concurrent use of self-report and pharmacy refill data to assess treatment adherence. However, clinical evidence to support this combined approach is limited. Objective: To determine nonadherence to inhaler medication based on a validated questionnaire (Test of Adherence to Inhalers; TAI) and prescription refill data in a community sample of patients with chronic obstructive pulmonary disease (COPD) or asthma. Secondarily, we sought to determine the degree of concordance between these two measures.

METHODS

Cross-sectional, observational multicenter study in patients with asthma or COPD. Sociodemographic and clinical data were obtained from clinical records. Refill data were retrieved from electronic pharmacy databases. Participants completed the 12-item TAI during a single visit as part of routine care. Nonadherence was defined as TAI <50 or <80% pharmacy refill rate (PRR) in the previous 6 months.

RESULTS

A total of 816 patients (mean age, 60) were included. Nonadherence rates were 58.1% (TAI) and 28.6% (PRR) compared with 64.6% for the combined data (P<.0001). Concordance between the 2 measures was weak (к=0.205).

CONCLUSIONS

These findings confirm the GINA recommendations, indicating that concomitant use of the TAI and pharmacy refill data identifies a higher percentage of nonadherent asthma or COPD patients than either instrument alone.

Cattle breed-variation in infestation by the horn fly Haematobia irritans

A study was carried out to assess the resistance of pure and cross-bred groups of cattle to the horn fly Haematobia irritans (Linnaeus) (Diptera: Muscidae) in northern Argentina. Pure-bred cattle were Criolla, Iberian Bos taurus Linnaeus (Artiodactyla: Bovidae) and Nellore, Bos indicus Linnaeus (Artiodactyla: Bovidae). Cross-bred cattle were Hereford, British B. taurus (34%) X Nellore (66%) and Hereford (66%) X Nellore (34%). All were heifers and animals were maintained in two groups, each containing a mixture of pure and cross-breeds. The lowest fly numbers were found on Criolla heifers and the highest on Hereford X Nellore cross-breeds. However, it could not be determined from this study whether this was a consequence of breed and/or size, as Criolla heifers were lighter than the corresponding Hereford X Nellore heifers. Fly numbers on the heifers followed an approximately negative binomial distribution. However, the ranking of individual animals in their level of infestation within subgroups was not consistent. Hence, culling the most infested heifers on any given date would at best give only a small improvement in H. irritans control.