[JAPANESE TRANSLATION AND LINGUISTIC VALIDATION OF THE RECAP OF ATOPIC ECZEMA (RECAP)].

BACKGROUND: The Recap of atopic eczema (RECAP), a new core outcome of the atopic dermatitis trial, was translated into Japanese and linguistically validated. METHODS: Translation into Japanese was accomplished according to the ISPOR (International Society for Pharmacoeconomics and Outcome Research) guidelines and the basic guidelines for scale translation. The translation process included two forward translations, reconciliation with native English speakers, third-party back translation, cognitive debriefing, review and harmonization by the original authors. Twenty-seven atopic dermatitis and pediatric specialists from 21 centers in Japan participated in the translation process. Cognitive debriefing was conducted through face-to-face interviews using a think-aloud method with the interview guide including questions about comprehensibility, relevance, comprehensiveness, recall period and suggested improvements, based on the COSMIN methodology. RESULTS: No linguistic or cultural problems were encountered in the translation into Japanese. Cognitive debriefings were conducted with 10 adult patients and 10 parents of pediatric patients. Some minor modifications were made following discussion and approval by the research team and the original authors. The Japanese version of RECAP was considered to be understandable, comprehensive and relevant for adult patients and families of pediatric patients. CONCLUSION: The Japanese version of the RECAP, which has been validated as linguistically equivalent to the original version, is now available. Further evaluation of the measurement properties is needed in the future.

Food-dependent exercise-induced anaphylaxis in Japanese elementary school children.

BACKGROUND: In 2012, we clarified that the prevalence of food-dependent exercise-induced anaphylaxis (FDEIA) was 0.018% in junior-high students in Yokohama, Japan. Furthermore, although different from FDEIA, one student who had completed oral immunotherapy developed anaphylaxis during exercise after eating causative food. There have been few large-scale epidemiological studies of FDEIA, however, in elementary school children, therefore we conducted an epidemiological study in elementary school children in Yokohama to clarify the frequency and characteristic of FDEIA. METHODS: We sent a questionnaire regarding the occurrence of FDEIA to all 348 public elementary school nurses in Yokohama. We also compared the results with those for junior-high school that we previously reported. We excluded those children with a past history of immediate food allergy who had achieved desensitization status after oral immunotherapy, from FDEIA, and instead defined them as having desensitization status and exercise-induced anaphylaxis (DEIA). RESULTS: Of 348 school nurses, 317 responded (91.1%). Overall, eight of 170 146 children were diagnosed with FDEIA, which was significantly lower than the prevalence in junior-high school students (0.0047% vs 0.018%, P = 0.0009). The causative foods were wheat (n = 4), and soy, fruit, crustaceans, and squid (n = 1 each). Four children had DEIA and the causative foods were wheat and milk (n = 2 each). Multiple episodes occurred in five children with FDEIA and in three children with DEIA. CONCLUSIONS: FDEIA was far less common in elementary school than in junior-high school, and wheat was the major causative food. The new appearance of DEIA was notable. Decreasing episode recurrence remains an issue that needs to be resolved.

Wheeze Recognition Algorithm for Remote Medical Care Device in Children: Validation Study.

BACKGROUND: Since 2020, peoples' lifestyles have been largely changed due to the COVID-19 pandemic worldwide. In the medical field, although many patients prefer remote medical care, this prevents the physician from examining the patient directly; thus, it is important for patients to accurately convey their condition to the physician. Accordingly, remote medical care should be implemented and adaptable home medical devices are required. However, only a few highly accurate home medical devices are available for automatic wheeze detection as an exacerbation sign. OBJECTIVE: We developed a new handy home medical device with an automatic wheeze recognition algorithm, which is available for clinical use in noisy environments such as a pediatric consultation room or at home. Moreover, the examination time is only 30 seconds, since young children cannot endure a long examination time without crying or moving. The aim of this study was to validate the developed automatic wheeze recognition algorithm as a clinical medical device in children at different institutions. METHODS: A total of 374 children aged 4-107 months in pediatric consultation rooms of 10 institutions were enrolled in this study. All participants aged ≥6 years were diagnosed with bronchial asthma and patients ≤5 years had reported at least three episodes of wheezes. Wheezes were detected by auscultation with a stethoscope and recorded for 30 seconds using the wheeze recognition algorithm device (HWZ-1000T) developed based on wheeze characteristics following the Computerized Respiratory Sound Analysis guideline, where the dominant frequency and duration of a wheeze were >100 Hz and >100 ms, respectively. Files containing recorded lung sounds were assessed by each specialist physician and divided into two groups: 177 designated as "wheeze" files and 197 as "no-wheeze" files. Wheeze recognitions were compared between specialist physicians who recorded lung sounds and those recorded using the wheeze recognition algorithm. We calculated the sensitivity, specificity, positive predictive value, and negative predictive value for all recorded sound files, and evaluated the influence of age and sex on the wheeze detection sensitivity. RESULTS: Detection of wheezes was not influenced by age and sex. In all files, wheezes were differentiated from noise using the wheeze recognition algorithm. The sensitivity, specificity, positive predictive value, and negative predictive value of the wheeze recognition algorithm were 96.6%, 98.5%, 98.3%, and 97.0%, respectively. Wheezes were automatically detected, and heartbeat sounds, voices, and crying were automatically identified as no-wheeze sounds by the wheeze recognition algorithm. CONCLUSIONS: The wheeze recognition algorithm was verified to identify wheezing with high accuracy; therefore, it might be useful in the practical implementation of asthma management at home. Only a few home medical devices are available for automatic wheeze detection. The wheeze recognition algorithm was verified to identify wheezing with high accuracy and will be useful for wheezing management at home and in remote medical care.

Measurement of Exhaled Nitric Oxide in Children: A Comparison Between NObreath® and NIOX VERO® Analyzers.

PURPOSE: Few studies have compared fractional exhaled nitric oxide (FeNO) measurement by NIOX VERO® (NOV) and other devices in children. Moreover, there is no agreement between differences in FeNO values obtained using different devices in adults. Here, we compared FeNO values obtained using NOV and NObreath® (NOB) systems to derive a correction equation for children. METHODS: Eighty-eight participants (age 7-15 years) who were diagnosed with atopic bronchial asthma and visited Sagamihara National Hospital as outpatients between January and April of 2017 were included. We measured FeNO values obtained using NOB and NOV, and analyzed them using Wilcoxon tests and Altman-Bland plots. RESULTS: The median age of the participants was 11.5 years, and the scored Asthma Control Test (ACT) or Childhood ACT (C-ACT) was 25 (interquartile range, 24-25) or 26 (24-27). NOB and NOV values were significantly different (31 [14-52] versus 36 [20-59] ppb; P = 0.020) and strongly correlated (r = 0.92). An equation to convert NOB values into NOV values was derived using linear regression as follows: log NOV = 0.7329 × log NOB + 0.4704; NOB for 20, 40, 58, 80 and 100 ppb corresponded to NOV for 27, 44, 59, 73 and 86 ppb. Thus, NOB < 58 ppb suggested NOB < NOV, whereas NOB > 58 ppb suggested NOB > NOV. CONCLUSIONS: NOB and NOV values were strongly correlated. Participants whose FeNO values were relatively low represented NOB < NOV, whereas those whose FeNO values were relatively high represented NOB > NOV.