The analysis of lung sounds in infants and children with a history of wheezing/asthma using an automatic procedure.

BACKGROUND: Lung sound analysis parameters have been reported to be useful biomarkers for evaluating airway condition. We developed an automatic lung sound analysis software program for infants and children based on lung sound spectral curves of frequency and power by leveraging machine learning (ML) technology. METHODS: To put this software program into clinical practice, in Study 1, the reliability and reproducibility of the software program using data from younger children were examined. In Study 2, the relationship between lung sound parameters and respiratory flow (L/s) was evaluated using data from older children. In Study 3, we conducted a survey using the ATS-DLD questionnaire to evaluate the clinical usefulness. The survey focused on the history of wheezing and allergies, among healthy 3-year-old infants, and then measured lung sounds. The clinical usefulness was evaluated by comparing the questionnaire results with the results of the new lung sound parameters. RESULTS: In Studies 1 and 2, the parameters of the new software program demonstrated excellent reproducibility and reliability, and were not affected by airflow (L/s). In Study 3, infants with a history of wheezing showed lower FAP0 and RPF75p (p < 0.001 and p = 0.025, respectively) and higher PAP0 (p = 0.001) than healthy infants. Furthermore, infants with asthma/asthma-like bronchitis showed lower FAP0 (p = 0.002) and higher PAP0 (p = 0.001) than healthy infants. CONCLUSIONS: Lung sound parameters obtained using the ML algorithm were able to accurately assess the respiratory condition of infants. These parameters are useful for the early detection and intervention of childhood asthma.

Long-term clinical observation of patients with heterozygous KIF1A variants.

KIF1A-related disorders (KRDs) encompass recessive and dominant variants with wide clinical variability. Recent genetic investigations have expanded the clinical phenotypes of heterozygous KIF1A variants. However, there have been a few long-term observational studies of patients with heterozygous KIF1A variants. A retrospective chart review of consecutive patients diagnosed with spastic paraplegia at Miyagi Children's Hospital from 2016 to 2020 identified six patients with heterozygous KIF1A variants. To understand the long-term changes in clinical symptoms, we examined these patients in terms of their characteristics, clinical symptoms, results of electrophysiological and neuroimaging studies, and genetic testing. The median follow-up period was 30 years (4-44 years). This long-term observational study showed that early developmental delay and equinus gait, or unsteady gait, are the first signs of disease onset, appearing with the commencement of independent walking. In addition, later age-related progression was observed in spastic paraplegia, and the appearance of axonal neuropathy and reduced visual acuity were characteristic features of the late disease phenotype. Brain imaging showed age-related progression of cerebellar atrophy and the appearance of hyperintensity of optic radiation on T2WI and FLAIR imaging. Long-term follow-up revealed a pattern of steady progression and a variety of clinical symptoms, including spastic paraplegia, peripheral neuropathy, reduced visual acuity, and some degree of cerebellar ataxia. Clinical variability between patients was observed to some extent, and therefore, further studies are required to determine the phenotype-genotype correlation.