OBJECTIVE: This study aimed to determine the effects of telemedicine on asthma control and the quality of life in adults.
METHODS: An electronic search was performed from the inception to March 2018 on the following databases: Cochrane CENTRAL, CINAHL, ClinicalTrials.gov, EMBASE, PubMed, and Scopus. Randomized controlled trials that assessed the effects of telemedicine in adults with asthma were included in this analysis, and the outcomes of interest were levels of asthma control and quality of life. Random-effects model meta-analyses were performed.
RESULTS: A total of 22 studies (10,281 participants) were included. Each of 11 studies investigated the effects of single-telemedicine and combined-telemedicine (combinations of telemedicine approaches), and the meta-analyses showed that combined tele-case management could significantly improve asthma control compared with usual care (standardized mean difference [SMD] = 0.78; 95% confidence interval [CI]: 0.56, 1.01). Combined tele-case management and tele-consultation (SMD = 0.52 [95% CI: 0.13, 0.91]) and combined tele-consultation (SMD = 0.28 [95% CI: 0.13, 0.44]) also significantly improved asthma outcomes, but to a lesser degree. In addition, combined tele-case management (SMD = 0.59 [95% CI: 0.31, 0.88]) was the most effective telemedicine for improving quality of life, followed by combined tele-case management and tele-consultation (SMD = 0.31 [95% CI: 0.03, 0.59]), tele-case management (SMD = 0.30 [95% CI: 0.05, 0.55]), and combined tele-consultation (SMD = 0.27 [95% CI: 0.11, 0.43]), respectively.
CONCLUSIONS: Combined-telemedicine involving tele-case management or tele-consultation appear to be effective telemedicine interventions to improve asthma control and quality of life in adults. Our findings are expected to provide health care professionals with current evidence of the effects of telemedicine on asthma control and patients' quality of life.
METHODS: This cross-sectional study in a tertiary hospital in Kuala Lumpur, Malaysia involved parents of children with asthma. Parents of children without asthma were the control group. Eleven validated video clips showing wheeze, stridor, transmitted noises, snoring or normal breathing were shown to the parents. Parents were asked, in English or Malay, "What do you call the sound this child is making?" and "Where do you think the sound is coming from?"
RESULTS: Two hundred parents participated in this study: 100 had children with asthma while 100 did not. Most (71.5 %) answered in Malay. Only 38.5 % of parents correctly labelled wheeze. Parents were significantly better at locating than labelling wheeze (OR 2.4, 95 % CI 1.64-3.73). Parents with asthmatic children were not better at labelling wheeze than those without asthma (OR1.04, 95 % CI 0.59-1.84). Answering in English (OR 3.4, 95 % CI 1.69-7.14) and having older children with asthma (OR 9.09, 95 % CI 3.13-26.32) were associated with correct labelling of wheeze. Other sounds were mislabelled as wheeze by 16.5 % of respondents.
CONCLUSION: Parental labelling of wheeze was inaccurate especially in the Malay language. Parents were better at identifying the origin of wheeze rather than labelling it. Physicians should be wary about parental reporting of wheeze as it may be inaccurate.
METHOD: Segmented and validated wheeze sounds were obtained from auscultation recordings of the trachea and lower lung base of 55 asthmatic patients during tidal breathing manoeuvres. The segments were multi-labelled into 9 groups based on the auscultation location and/or breath phases. Bandwidths were selected based on the physiology, and a corresponding SI feature was computed for each segment. Univariate and multivariate statistical analyses were then performed to investigate the discriminatory behaviour of the features with respect to the severity levels in the various groups. The asthmatic severity levels in the groups were then classified using the ensemble (ENS), support vector machine (SVM) and k-nearest neighbour (KNN) methods.
RESULTS AND CONCLUSION: All statistical comparisons exhibited a significant difference (p asthma severity levels. In addition, the classification performances of the inspiratory and expiratory related groups were comparable, suggesting that the samples from these locations are equally informative.
METHODS: We developed mouse models representing three different phenotypes of allergic airway inflammation-eosinophilic, mixed, and neutrophilic asthma via different methods of house dust mite sensitization and challenge. Transcriptomic analysis of the lungs, followed by the RT-PCR, western blot, and confocal microscopy, was performed. Primary human bronchial epithelial cells cultured in air-liquid interface were used to study the mechanisms revealed in the in vivo models.
RESULTS: By whole-genome transcriptome profiling of the lung, we found that airway tight junction (TJ), mucin, and inflammasome-related genes are differentially expressed in these distinct phenotypes. Further analysis of proteins from these families revealed that Zo-1 and Cldn18 were downregulated in all phenotypes, while increased Cldn4 expression was characteristic for neutrophilic airway inflammation. Mucins Clca1 (Gob5) and Muc5ac were upregulated in eosinophilic and even more in neutrophilic phenotype. Increased expression of inflammasome-related molecules such as Nlrp3, Nlrc4, Casp-1, and IL-1β was characteristic for neutrophilic asthma. In addition, we showed that inflammasome/Th17/neutrophilic axis cytokine-IL-1β-may transiently impair epithelial barrier function, while IL-1β and IL-17 increase mucin expressions in primary human bronchial epithelial cells.
CONCLUSION: Our findings suggest that differential expression of TJ, mucin, and inflammasome-related molecules in distinct inflammatory phenotypes of asthma may be linked to pathophysiology and might reflect the differences observed in the clinic.