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Background: Patients with COPD are at high risk of lung cancer developing, but no validated predictive biomarkers have been reported to identify these patients. Molecular profiling of exhaled breath by electronic nose (eNose) technology may qualify for early detection of lung cancer in patients with COPD., Research Question: Can eNose technology be used for prospective detection of early lung cancer in patients with COPD?, Study Design and Methods: BreathCloud is a real-world multicenter prospective follow-up study using diagnostic and monitoring visits in day-to-day clinical care of patients with a standardized diagnosis of asthma, COPD, or lung cancer. Breath profiles were collected at inclusion in duplicate by a metal-oxide semiconductor eNose positioned at the rear end of a pneumotachograph (SpiroNose; Breathomix). All patients with COPD were managed according to standard clinical care, and the incidence of clinically diagnosed lung cancer was prospectively monitored for 2 years. Data analysis involved advanced signal processing, ambient air correction, and statistics based on principal component (PC) analysis, linear discriminant analysis, and receiver operating characteristic analysis., Results: Exhaled breath data from 682 patients with COPD and 211 patients with lung cancer were available. Thirty-seven patients with COPD (5.4%) demonstrated clinically manifest lung cancer within 2 years after inclusion. Principal components 1, 2, and 3 were significantly different between patients with COPD and those with lung cancer in both training and validation sets with areas under the receiver operating characteristic curve of 0.89 (95% CI, 0.83-0.95) and 0.86 (95% CI, 0.81-0.89). The same three PCs showed significant differences (P < .01) at baseline between patients with COPD who did and did not subsequently demonstrate lung cancer within 2 years, with a cross-validation value of 87% and an area under the receiver operating characteristic curve of 0.90 (95% CI, 0.84-0.95)., Interpretation: Exhaled breath analysis by eNose identified patients with COPD in whom lung cancer became clinically manifest within 2 years after inclusion. These results show that eNose assessment may detect early stages of lung cancer in patients with COPD., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Obstructive Sleep Apnea (OSA) is recognized as an increasing health risk, leading to daytime sleepiness and various medical conditions, such as hypertension and heart failure. Polysomnography (PSG), the gold standard to diagnose OSA, is a resource-intensive and expensive investigation confined to the hospital.Portable home monitoring, i.e. pulse oximetry, may become an acceptable OSA screening method. The novel nasal pulse oximeter sensor (Xhale Alar) adds the possibility of combining pulse oximetry (SpO2) with airflow analysis by an integrated thermistor, which might increase the diagnostic accuracy.In the Alar pilot study, 39 adults were measured during an overnight PSG recording together with the Alar sensor. This study aims to investigate the additional value of an airflow signal compared to SpO2 analysis in OSA screening. Both time and spectral features were extracted from SpO2 and airflow signals recorded with the Alar sensor. Leave one out cross-validation was used to develop Random Forest models in screening for apnea-hypopnea index (AHI) thresholds 5 and 10. Using both AHI ≥ 5 and AHI ≥ 10 as the diagnostic cutoff, the airflow signal shows respectively an AUC of 89% and 80% compared to 78% and 77% with SpO2 analysis, showing a higher performance using an airflow signal in screening adults for OSA.

A noncontact mapping system (EnSite) was used for electroanatomical mapping of the bladder simultaneously with pressure flow study in three women with lower urinary tract symptoms. We selected the periods of obvious detrusor activity. Data were processed to remove baseline drift, and an envelope of electrovesicography (EVG) data was created. The correlation coefficient for the correlation between between the EVG envelope and the detrusor pressure (Pdet) was calculated. Bladder geometry was successfully created in all 3 patients. Simultaneous recording of EVG and pressure flow data was successful in 1 patient. Scatter plots were made of the highest correlation coefficient, showing a positive correlation between the Pdet and the envelope, and negative correlation between abdominal pressure (Pabd) and the envelope. Minimal electrical activity could be observed. Significant weak to moderate correlation coefficients were found for the correlations between Pdet and EVG and between Pabd and EVG.