抄録
Background: Prognosis of nephrotic syndrome has been evaluated based on pathological diagnosis, whereas its clinical course is monitored using objective items and the treatment strategy is largely the same. We examined whether the entire natural history of nephrotic syndrome could be evaluated using objective common clinical items. Methods: Machine learning clustering was performed on 205 cases from the Japan Nephrotic Syndrome Cohort Study, whose clinical parameters, serum creatinine, serum albumin, dipstick hematuria, and proteinuria were traceable after kidney biopsy at 5 measured points up to 2 years. The clinical patterns of time-series data were learned using long short-term memory (LSTM)-encoder–decoder architecture, an unsupervised machine learning classifier. Clinical clusters were defined as Gaussian mixture distributions in a two-dimensional scatter plot based on the highest log-likelihood. Results: Time-series data of nephrotic syndrome were classified into four clusters. Patients in the fourth cluster showed the increase in serum creatinine in the later part of the follow-up period. Patients in both the third and fourth clusters were initially high in both hematuria and proteinuria, whereas a lack of decline in the urinary protein level preceded the worsening of kidney function in fourth cluster. The original diseases of fourth cluster included all the disease studied in this cohort. Conclusions: Four kinds of clinical courses were identified in nephrotic syndrome. This classified clinical course may help objectively grasp the actual condition or treatment resistance of individual patients with nephrotic syndrome.
本文言語 | 英語 |
---|---|
ページ(範囲) | 1170-1179 |
ページ数 | 10 |
ジャーナル | Clinical and Experimental Nephrology |
巻 | 26 |
号 | 12 |
DOI | |
出版ステータス | 出版済み - 12-2022 |
All Science Journal Classification (ASJC) codes
- 生理学
- 腎臓病学
- 生理学(医学)
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In: Clinical and Experimental Nephrology, Vol. 26, No. 12, 12.2022, p. 1170-1179.
研究成果: ジャーナルへの寄稿 › 学術論文 › 査読
TY - JOUR
T1 - Deep learning analysis of clinical course of primary nephrotic syndrome
T2 - Japan Nephrotic Syndrome Cohort Study (JNSCS)
AU - Kimura, Tomonori
AU - Yamamoto, Ryohei
AU - Yoshino, Mitsuaki
AU - Sakate, Ryuichi
AU - Imai, Enyu
AU - Maruyama, Shoichi
AU - Yokoyama, Hitoshi
AU - Sugiyama, Hitoshi
AU - Nitta, Kosaku
AU - Tsukamoto, Tatsuo
AU - Uchida, Shunya
AU - Takeda, Asami
AU - Sato, Toshinobu
AU - Wada, Takashi
AU - Hayashi, Hiroki
AU - Akai, Yasuhiro
AU - Fukunaga, Megumu
AU - Tsuruya, Kazuhiko
AU - Masutani, Kosuke
AU - Konta, Tsuneo
AU - Shoji, Tatsuya
AU - Hiramatsu, Takeyuki
AU - Goto, Shunsuke
AU - Tamai, Hirofumi
AU - Nishio, Saori
AU - Nagai, Kojiro
AU - Yamagata, Kunihiro
AU - Yasuda, Hideo
AU - Ichida, Shizunori
AU - Naruse, Tomohiko
AU - Nishino, Tomoya
AU - Sobajima, Hiroshi
AU - Akahori, Toshiyuki
AU - Ito, Takafumi
AU - Terada, Yoshio
AU - Katafuchi, Ritsuko
AU - Fujimoto, Shouichi
AU - Okada, Hirokazu
AU - Mimura, Tetsushi
AU - Suzuki, Satoshi
AU - Saka, Yosuke
AU - Sofue, Tadashi
AU - Kitagawa, Kiyoki
AU - Fujita, Yoshiro
AU - Mizutani, Makoto
AU - Kashihara, Naoki
AU - Sato, Hiroshi
AU - Narita, Ichiei
AU - Isaka, Yoshitaka
N1 - Funding Information: JNSCS was supported by a Grant-in-Aid for Intractable Renal Diseases Research, Research on Rare and Intractable Diseases, Health and Labour Sciences Research Grants for the Ministry of Health, Labor, and Welfare of Japan (#2031693). Funding Information: JNSCS has been supported by a large number of investigators in 56 participating facilities; Hokkaido University Hospital, Sapporo, Hokkaido (Saori Nishio, Yasunobu Ishikawa, Daigo Nakazawa, and Tasuku Nakagaki); JCHO Sendai Hospital, Sendai, Miyagi (Toshinobu Sato, Mitsuhiro Sato, and Satoru Sanada); Tohoku University Hospital, Sendai, Miyagi (Hiroshi Sato, Mariko Miyazaki, Takashi Nakamichi, Tae Yamamoto, Kaori Narumi, and Gen Yamada); Yamagata University Hospital, Yamagata, Yamagata (Tsuneo Konta, and Kazunobu Ichikawa); Fukushima Medical University Hospital, Fukushima, Fukushima (Junichiro James Kazama, Tsuyoshi Watanabe, Koichi Asahi, Yuki Kusano, and Kimio Watanabe); University of Tsukuba Hospital, Tsukuba, Ibaraki (Kunihiro Yamagata, Joichi Usui, Shuzo Kaneko, and Tetsuya Kawamura); Gunma University Hospital, Maebashi, Gunma (Keiju Hiromura, Akito Maeshima, Yoriaki Kaneko, Hidekazu Ikeuchi, Toru Sakairi, and Masao Nakasatomi); Saitama Medical Center, Saitama Medical University, Kawagoe, Saitama (Hajime Hasegawa, Takatsugu Iwashita, Taisuke Shimizu, Koichi Kanozawa, Tomonari Ogawa, Kaori Takayanagi, and Tetsuya Mitarai); Department of Nephrology, Saitama Medical University, Irumagun, Saitama (Hirokazu Okada, Tsutomu Inoue, Hiromichi Suzuki, and Kouji Tomori); Tokyo Women’s Medical University, Shinjuku-ku, Tokyo (Kosaku Nitta, Takahito Moriyama, Akemi Ino, and Masayo Sato); Teikyo University School of Medicine, Itabashi-ku, Tokyo (Shunya Uchida, Hideaki Nakajima, Hitoshi Homma, Nichito Nagura, Yoshifuru Tamura, Shigeru Shibata, and Yoshihide Fujigaki); Juntendo Faculty of Medicine, Bunkyo-ku, Tokyo (Yusuke Suzuki, Yukihiko Takeda, Isao Osawa, and Teruo Hidaka); St. Marianna University, Kawasaki, Kanagawa (Daisuke Ichikawa, Yugo Shibagaki, Sayuri Shirai, Tsutomu Sakurada, Tomo Suzuki, and Mikako Hisamichi); Niigata University Medical and Dental Hospital, Niigata, Niigata (Ichiei Narita, Naohumi Imai, Yumi Ito, Shin Goto, Yoshikatsu Kaneko, and Rhohei Kaseda); Kanazawa Medical University, Uchinada, Ishikawa (Hitoshi Yokoyama, Keiji Fujimoto, and Norifumi Hayashi); Kanazawa University Hospital, Kanazawa, Ishikawa (Takashi Wada, Miho Shimizu, Kengo Furuichi, Norihiko Sakai, Yasunori Iwata, Tadashi Toyama, and Shinji Kitajima); National Hospital Organization Kanazawa Medical Center, Kanazawa, Ishikawa (Kiyoki Kitagawa); Ogaki Municipal Hospital, Ogaki, Gifu (Hiroshi Sobajima, Norimi Ohashi, So Oshitani, and Kiyohito Kawashima); Gifu Prefectural Tajimi Hospital, Tajimi, Gifu (Tetsushi Mimura); Hamamatsu University Hospital, Hamamatsu, Shizuoka (Hideo Yasuda, Akira Hishida, and Yoshihide Fujigaki); Shizuoka General Hospital, Shizuoka, Shizuoka (Satoshi Tanaka, and Noriko Mori); Chutoen General Medical Center, Kakegawa, Shizuoka (Toshiyuki Akahori, and Yutaka Fujita); Nagoya University Graduate School of Medicine, Nagoya, Aichi (Shoichi Maruyama, Naotake Tsuboi, Tomoki Kosugi, Takuji Ishimoto, Takayuki Katsuno, Noritoshi Kato, and Waichi Sato); Japanese Red Cross Nagoya Daini Hospital, Nagoya, Aichi (Asami Takeda, Kunio Morozumi, Yasuhiro Ohtsuka, Hibiki Shinjo, and Akihito Tanaka); Fujita Health University School of Medicine, Toyoake, Aichi (Hiroki Hayashi, Yukio Yuzawa, Midori Hasegawa, Daijo Inaguma, Shigehisa Koide, and Kazuo Takahashi); Konan Kosei Hospital, Konan, Aichi (Takeyuki Hiramatsu, Shinji Furuta, and Hideaki Ishikawa); Anjo Kosei Hospital, Anjo, Aichi (Hirofumi Tamai, and Takatoshi Morinaga); Ichinomiya Municipal Hospital, Ichinomiya, Aichi (Arimasa Shirasaki, Toshiki Kimura, and Mina Kato); Japanese Red Cross Nagoya Daiichi Hospital, Nagoya, Aichi (Shizunori Ichida, and Nobuhide Endo); Kasugai Municipal Hospital, Kasugai, Aichi (Tomohiko Naruse, Yuzo Watanabe, and Yosuke Saka); Kainan Hospital, Yatomi, Aichi (Satashi Suzuki, Michiko Yamazaki, and Rieko Morita); Masuko Memorial Hospital, Nagoya, Aichi (Kunio Morozumi, Kunio Morozumi, Kaoru Yasuda, Chika Kondo, Takahiro Morohiro, Rho Sato, and Yuichi Shirasawa); Chubu Rosai Hospital, Nagoya, Aichi (Yoshiro Fujita, Hideaki Shimizu, and Tatsuhito Tomino); Handa City Hospital, Handa, Aichi (Makoto Mizutani); Yokkaichi Municipal Hospital, Yokkaichi, Mie (Yosuke Saka, Hiroshi Nagaya, and Makoto Yamaguchi); Kitano Hospital, Osaka, Osaka (Tatsuo Tsukamoto, Eri Muso, Hiroyuki Suzuki, Tomomi Endo, and Hiroko Kakita); Toyonaka Municipal Hospital, Toyonaka, Osaka (Megumu Fukunaga); Osaka General Medical Center, Osaka, Osaka (Tatsuya Shoji, and Terumasa Hayashi); Osaka City University Hospital, Osaka, Osaka (Eiji Ishimura, Akihiro Tsuda, Shinya Nakatani, Ikue Kobayashi, Mitsuru Ichii, Akinobu Ochi, and Yoshiteru Ohno); Osaka University Hospital, Suita, Osaka (Yoshitaka Isaka, Enyu Imai, Yasuyuki Nagasawa, Hirotsugu Iwatani, Ryohei Yamamoto, and Tomoko Namba); Kobe University Hospital, Kobe, Hyogo (Shunsuke Goto MD, and Shinichi Nishi); Nara Medical University Hospital, Kashihara, Nara (Yasuhiro Akai, Ken-ichi Samejima, Masaru Matsui, Miho Tagawa, Kaori Tanabe, and Hideo Tsushima); Wakayama Medical University Hospital, Wakayama, Wakayama (Takashi Shigematsu MD, Masaki Ohya, Shigeo Negi, and Toru Mima); Shimane University Hospital, Izumo, Shimane (Takafumi Ito); Okayama University Hospital, Okayama, Okayama (Hitoshi Sugiyama, Keiko Tanaka, Toshio Yamanari, Masashi Kitagawa, Akifumi Onishi, and Koki Mise); Kawasaki Medical School, Kurashiki, Okayama (Naoki Kashihara, Tamaki Sasaki, Sohachi Fujimoto, and Hajime Nagasu); Graduate School of Medicine, The University of Tokushima,Tokushima,Tokushima (Kojiro Nagai, and Toshio Doi); Kagawa University, Miki-cho, Takamatsu, Japan (Tadashi Sofue, Hideyasu Kiyomoto, Kumiko Moriwaki, Taiga Hara, Yoko Nishijima, Yoshio Kushida, and Tetsuo Minamino); Kochi Medical School, Kochi University, Nankoku, Kochi (Yoshio Terada, Taro Horino, Yoshinori Taniguchi, Kosuke Inoue, Yoshiko Shimamura, and Tatsuki Matsumoto); Kyushu University Hospital, Fukuoka, Fukuoka (Kazuhiko Tsuruya, Hisako Yoshida, Naoki Haruyama, Shunsuke Yamada, Akihiro Tsuchimoto, and Yuta Matsukuma); Fukuoka University Hospital, Fukuoka, Fukuoka (Kosuke Masutani, Yasuhiro Abe, Aki Hamauchi, Tetsuhiko Yasuno, and Kenji Ito); Kurume University Hospital, Kurume, Fukuoka (Kei Fukami, Junko Yano, Chika Yoshida, Yuka Kurokawa, and Nao Nakamura); National Hospital Organization Fukuokahigashi Medical Center, Koga, Fukuoka (Ritsuko Katafuchi, Hiroshi Nagae, Shumei Matsueda, and Kazuto Abe); Nagasaki University Hospital, Nagasaki, Nagasaki (Tomoya Nishino, Tadashi Uramatsu, and Yoko Obata); Miyazaki University Hospital, Miyazaki, Miyazaki (Shouichi Fujimoto, Yuji Sato, Masao Kikuchi, Ryuzo Nishizono, Takashi Iwakiri, and Hiroyuki Komatsu). Publisher Copyright: © 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Background: Prognosis of nephrotic syndrome has been evaluated based on pathological diagnosis, whereas its clinical course is monitored using objective items and the treatment strategy is largely the same. We examined whether the entire natural history of nephrotic syndrome could be evaluated using objective common clinical items. Methods: Machine learning clustering was performed on 205 cases from the Japan Nephrotic Syndrome Cohort Study, whose clinical parameters, serum creatinine, serum albumin, dipstick hematuria, and proteinuria were traceable after kidney biopsy at 5 measured points up to 2 years. The clinical patterns of time-series data were learned using long short-term memory (LSTM)-encoder–decoder architecture, an unsupervised machine learning classifier. Clinical clusters were defined as Gaussian mixture distributions in a two-dimensional scatter plot based on the highest log-likelihood. Results: Time-series data of nephrotic syndrome were classified into four clusters. Patients in the fourth cluster showed the increase in serum creatinine in the later part of the follow-up period. Patients in both the third and fourth clusters were initially high in both hematuria and proteinuria, whereas a lack of decline in the urinary protein level preceded the worsening of kidney function in fourth cluster. The original diseases of fourth cluster included all the disease studied in this cohort. Conclusions: Four kinds of clinical courses were identified in nephrotic syndrome. This classified clinical course may help objectively grasp the actual condition or treatment resistance of individual patients with nephrotic syndrome.
AB - Background: Prognosis of nephrotic syndrome has been evaluated based on pathological diagnosis, whereas its clinical course is monitored using objective items and the treatment strategy is largely the same. We examined whether the entire natural history of nephrotic syndrome could be evaluated using objective common clinical items. Methods: Machine learning clustering was performed on 205 cases from the Japan Nephrotic Syndrome Cohort Study, whose clinical parameters, serum creatinine, serum albumin, dipstick hematuria, and proteinuria were traceable after kidney biopsy at 5 measured points up to 2 years. The clinical patterns of time-series data were learned using long short-term memory (LSTM)-encoder–decoder architecture, an unsupervised machine learning classifier. Clinical clusters were defined as Gaussian mixture distributions in a two-dimensional scatter plot based on the highest log-likelihood. Results: Time-series data of nephrotic syndrome were classified into four clusters. Patients in the fourth cluster showed the increase in serum creatinine in the later part of the follow-up period. Patients in both the third and fourth clusters were initially high in both hematuria and proteinuria, whereas a lack of decline in the urinary protein level preceded the worsening of kidney function in fourth cluster. The original diseases of fourth cluster included all the disease studied in this cohort. Conclusions: Four kinds of clinical courses were identified in nephrotic syndrome. This classified clinical course may help objectively grasp the actual condition or treatment resistance of individual patients with nephrotic syndrome.
UR - http://www.scopus.com/inward/record.url?scp=85135870087&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135870087&partnerID=8YFLogxK
U2 - 10.1007/s10157-022-02256-3
DO - 10.1007/s10157-022-02256-3
M3 - Article
C2 - 35962244
AN - SCOPUS:85135870087
SN - 1342-1751
VL - 26
SP - 1170
EP - 1179
JO - Clinical and Experimental Nephrology
JF - Clinical and Experimental Nephrology
IS - 12
ER -