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Evaluating the Efficacy and Safety of 48-Week Low-Dose Dienogest Administration in Patients With Dysmenorrhea Caused by Endometriosis: Protocol for a Randomized, Open-Label, Parallel-Group Trial

Kyoko Kikuno, Ryuta Asada, Takuma Ishihara, Yoshimasa Bomoto, Saki Murase, Yoko Ueda, Tomomi Shiga, Yoh Hayasaki, Tatsuro Furui, Satoko Matsuzaki, Masahiko Takemura, Kazutoshi Matsunami, Makoto Kubo, Naoki Ito, Masanori Isobe, Ken-ichirou Morishige

JMIR Res Protoc 2025;14:e66246

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Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study

Fujibayashi et al [7] used Hb A1c values, FPG levels, and 2-hour PG to predict instances of high future risk of developing diabetes. Complete data, including 1-hour and 2-hour PG and IRI values obtained by OGTT, may improve the prediction accuracy for diabetes risk. Previously, logistic regression (LR) analyses were used as initial screening tests [5,8-10].

Katsutoshi Maeta, Yu Nishiyama, Kazutoshi Fujibayashi, Toshiaki Gunji, Noriko Sasabe, Kimiko Iijima, Toshio Naito