National survey of abnormal uterine bleeding according to the FIGO classification in Japan
National survey of abnormal uterine bleeding according to the FIGO classification in Japan
复制标题
日本根据FIGO分类进行的全国异常子宫出血调查
DOI:
10.1111/jog.15464
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发表时间:
2022
影响因子:
1.6
通讯作者:
Iwase Akira
中科院分区:
文献类型:
--
作者:
Kitahara Yoshikazu;Hiraike Osamu;Ishikawa Hiroshi;Kugu Koji;Takai Yasushi;Yoshino Osamu;Ono Masanori;Maekawa Ryo;Ota Ikuko;Iwase Akira
AimTo investigate the status of abnormal uterine bleeding (AUB) in Japan using the International Federation of Gynecology and Obstetrics (FIGO) classification (AUB system 1 and 2; PALM‐COEIN) and to clarify the relationship between AUB symptoms and the diseases causing AUB.MethodsIn a nationwide study, we enrolled first‐time patients who visited target facilities during two consecutive weeks from December 1, 2019 to January 31, 2020. The FIGO classification was used to investigate patients with symptoms and causative diseases of AUB. Based on the proportion of patients in the nationwide study, 373 cases were included in the detailed survey. Survey items included symptoms of AUB according to AUB system 1, examination details, and causative diseases according to the PALM‐COEIN classification.ResultsWithin the study period, we encountered 61 740 first‐time patients, of which 8081 (13.1%) were diagnosed with AUB. Among them, 39.9% had abnormal menstrual cycles and 56.9% had abnormal menstrual bleeding. In the survey, PALM had the highest percentage of AUB‐L and COEIN had the highest percentage of AUB‐O. Correspondence analysis showed that COEIN was strongly associated with abnormal menstrual cycles and PALM with abnormal menstrual bleeding.ConclusionWe conducted the first nationwide survey of AUB in Japan. The FIGO classification was a useful tool for the diagnosis of AUB, with a strong correlation between symptoms of AUB by AUB system 1 and the causative disease of AUB by PALM‐COEIN. Conversely, a high percentage of AUB‐N and AUB‐E suggests that AUB system 1 and PALM‐COEIN are ambiguous as diagnostic tools.
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影响因子:
3.7
作者:
Mutakha GS;Mwaliko E;Kirwa P
通讯作者:
Kirwa P
影响因子:
1.6
作者:
P. Ni;Mei Wu;H. Guan;Yuqi Yuan;Lu;Feixue Zhang;Xiuliang Wei;Ya Li
通讯作者:
Ya Li
影响因子:
1.1
作者:
Kanika Singh;C. Agarwal;M. Pujani;Sujata Raychaudhuri;Nimisha Sharma;Varsha Chauhan;R. Chawla;Rashmi Ahuja;Mita Singh
通讯作者:
Mita Singh
影响因子:
2.1
作者:
Hadigheh Kazemijaliseh;F. Ramezani Tehrani;S. Behboudi;D. Khalili;F. Hosseinpanah;F. Azizi
通讯作者:
F. Azizi
影响因子:
3.8
作者:
Munro, Malcolm G.;Critchley, Hilary O. D.;Fraser, Ian S.
通讯作者:
Fraser, Ian S.