Home Monitoring of Asthma Exacerbations in Children and Adults With Use of an AI-Aided Stethoscope.

PURPOSE: The advent of new medical devices allows patients with asthma to self-monitor at home, providing a more complete picture of their disease than occasional in-person clinic visits. This raises a pertinent question: which devices and parameters perform best in exacerbation detection? METHODS: A total of 149 patients with asthma (90 children, 59 adults) participated in a 6-month observational study. Participants (or parents) regularly (daily for the first 2 weeks and weekly for the next 5.5 months, with increased frequency during exacerbations) performed self-examinations using 3 devices: an artificial intelligence (AI)-aided home stethoscope (providing wheezes, rhonchi, and coarse and fine crackles intensity; respiratory and heart rate; and inspiration-to-expiration ratio), a peripheral capillary oxygen saturation (SpO2) meter, and a peak expiratory flow (PEF) meter and filled out a health state survey. The resulting 6,029 examinations were evaluated by physicians for the presence of exacerbations. For each registered parameter, a machine learning model was trained, and the area under the receiver operating characteristic curve (AUC) was calculated to assess its utility in exacerbation detection. RESULTS: The best single-parameter discriminators of exacerbations were wheezes intensity for young children (AUC 84% [95% CI, 82%-85%]), rhonchi intensity for older children (AUC 81% [95% CI, 79%-84%]), and survey answers for adults (AUC 92% [95% CI, 89%-95%]). The greatest efficacy (in terms of AUC) was observed for a combination of several parameters. CONCLUSIONS: The AI-aided home stethoscope provides reliable information on asthma exacerbations. The parameters provided are effective for children, especially those younger than 5 years of age. The introduction of this tool to the health care system might enhance asthma exacerbation detection substantially and make remote monitoring of patients easier.

Is the Relationship Between Breastfeeding and Childhood Risk of Asthma and Obesity Mediated by Infant Antibiotic Treatment?

BACKGROUND: Studies of the protective effect of breastfeeding on asthma have not brought unequivocal results, and thus this issue remains controversial. Antibiotic use, known to increase asthma risk, may be involved in this relationship. The objective of this study was to assess the influence of breastfeeding duration on obesity and asthma risk in childhood and to test a mediating role of antibiotic use in infancy. SUBJECTS AND METHODS: A cross-sectional anthropometric and questionnaire study was conducted on 1,277 schoolchildren 8 years of age. Data on weight status, asthma, breastfeeding duration, antibiotic administration in infancy, socioeconomic status, and lifestyle were analyzed. Multivariate standard and logistic regression and mediation analyses, controlling for confounders, were applied. RESULTS: Total duration of breastfeeding was negatively related to the child's body mass index (p=0.038), fat percentage (p=0.030), and obesity risk (p=0.032). Dropping the variable of antibiotic use from the model made the breastfeeding duration a significant predictor of low asthma risk (p=0.027). Antibiotic treatment mediated the relationship between breastfeeding duration and asthma risk (Sobel's z=-2.61, p=0.009). CONCLUSIONS: Our findings support protective effects of longer duration of breastfeeding against obesity and asthma. We propose a new mechanism for a relationship between breastfeeding and asthma: shorter breastfeeding compromises infant health and thereby leads to antibiotic treatment, which in turn increases the risk of asthma.