Unique ID issued by UMIN | UMIN000032194 |
---|---|
Receipt number | R000035471 |
Scientific Title | Identification of Predictive Phenotypes for Development of Asthma in 1-Year-Old Children with Recurrent Wheeze (Phenotyping of wheezing infants; P-WIN study) |
Date of disclosure of the study information | 2018/04/12 |
Last modified on | 2021/10/13 10:13:49 |
Identification of Predictive Phenotypes for Development of Asthma
in 1-Year-Old Children with Recurrent Wheeze
(Phenotyping of wheezing infants; P-WIN study)
P-WIN study
Identification of Predictive Phenotypes for Development of Asthma
in 1-Year-Old Children with Recurrent Wheeze
(Phenotyping of wheezing infants; P-WIN study)
P-WIN study
Japan | Asia(except Japan) |
infantile wheeze
Clinical immunology | Pediatrics |
Others
NO
To investigate outcome of 1-year-old children with recurrent wheeze
Others
To clarify the (short-term) prognosis of recurrent wheeze in children aged 1 year by prospectively following the outcomes under various treatment in real world settings and to establish a new classification of wheezing phenotypes based on the common medical practice in Japan.
Remission of wheezing symptoms 2 years after enrollment
Physical exam, family history, environment (e.g., pets, passive smoking), infection, allergen sensitization, rhinitis symptoms, and phenotypic classification of wheezing according to drug used
Biomarkers by phenotypic class (e.g., serum EDN, periostin, SCCA2)
Observational
12 | months-old | <= |
24 | months-old | > |
Male and Female
1) At least one episode of wheeze before more than 1 month prior to enrollment
2) Apparent expiratory wheeze persisting for more than 24 h at enrollment
1) Wheezing due to underlying disease other than asthma (e.g., congenital tracheal stenosis, tracheomalacia, heart diseases)
2) History of respiratory diseases requiring mechanical ventilation during the perinatal period
3) Immunocompromised children
250
1st name | Mizuho |
Middle name | |
Last name | Nagao |
Mie National Hospital
Department of Clinical Research
514-0125
357 Osato-kubota, Tsu, Mie 514-0125, Japan
059-232-2531
nagao.mizuho.yt@mail.hosp.go.jp
1st name | Shinobu |
Middle name | |
Last name | Tanimura |
Mie National Hospital
Department of Clinical Research
514-0125
357 Osato-kubota, Tsu, Mie 514-0125, Japan
059-232-2531
mieclinicalresearch@gmail.com
National Hospital Organizationie, Mie National Hospital
National Hospital Organization, Japan
Japanese Governmental office
Japan
National Hospital Organization Headquarters Clinical Research Central Ethics Review Committee
2-5-21 Higashigaoka, Meguroku, Tokyo
03-5712-5050
700-kenkyu@mail.hosp.go.jp
NO
国立病院機構三重病院(三重県)、国立病院機構仙台医療センター (宮城県)、国立病院機構下志津病院(千葉県)、国立病院機構横浜医療センター(神奈川県)、国立病院機構神奈川病院(神奈川県)、国立病院機構相模原病院(神奈川県)、国立病院機構栃木医療センター(栃木県)、国立病院機構名古屋医療センター(愛知県)、国立病院機構長良医療センター(岐阜県)、国立病院機構南岡山医療センター(岡山県)、国立病院機構福山医療センター(広島県)、国立病院機構高知病院(高知県)、国立病院機構熊本医療センター(熊本県)、国立病院機構福岡病院(福岡県)、国立病院機構福岡東医療センター(福岡県)、群馬県立小児医療センター(群馬県)、岩見沢こども・産科婦人科クリニック(北海道)、 まつだ小児科クリニック (三重県)、熱田小児科クリニックアレルギークリニック(三重県)、あおぞら小児科(鹿児島県)、大阪はびきの医療センター(大阪府)、福岡市立こども病院(福岡県)、昭和大学病院(東京都)、杢保小児科医院(香川県)、井手小児科(福岡県)、Manna&Babyこどもクリニック(福岡県)、井上四郎小児科(福岡県)、寺本こどもクリニック(岐阜県)、東京女子医科大学 東医療センター(東京都)
2018 | Year | 04 | Month | 12 | Day |
Unpublished
No longer recruiting
2018 | Year | 01 | Month | 23 | Day |
2018 | Year | 01 | Month | 22 | Day |
2018 | Year | 04 | Month | 12 | Day |
2023 | Year | 01 | Month | 31 | Day |
2023 | Year | 02 | Month | 28 | Day |
2023 | Year | 03 | Month | 31 | Day |
2023 | Year | 06 | Month | 30 | Day |
1) Analysis of the primary variables:
The proportion of patients with remission of wheezing symptoms after 2 years of enrollment will be calculated.
2) Analysis of the secondary variables:
Hierarchical cluster analysis using information at entry and 2 years
after enrollment, treatment administered and wheezing symptoms during the study period. Appropriate number clusters will be identified through construction of a dendrogram.
For each selected cluster, descriptive statistics of demographics of the subjects will be performed. The variables will be compared between clusters using analysis of variance, chi-square test or Kruskal-Wallis test. Descriptive statistics of biomarkers in each cluster will be calculated. Values of biomarkers will be compared between clusters using analysis of variance, chi-square test, or Kruskal-Wallis test.
2018 | Year | 04 | Month | 11 | Day |
2021 | Year | 10 | Month | 13 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000035471