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Record W3198645672 · doi:10.1002/ams2.659

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J‐SSCG 2020)

2021· article· en· W3198645672 on OpenAlex
Moritoki Egi, Hiroshi Ogura, Tomoaki Yatabe, Kazuaki Atagi, Shigeaki Inoue, Toshiaki Iba, Yasuyuki Kakihana, Tatsuya Kawasaki, Shigeki Kushimoto, Yasuhiro Kuroda, Joji Kotani, Nobuaki Shime, Takumi Taniguchi, Ryosuke Tsuruta, Kent Doi, Matsuyuki Doi, Taka‐aki Nakada, Masaki Nakane, Seitaro Fujishima, Naoto Hosokawa, Yoshiki Masuda, Asako Matsushima, Naoyuki Matsuda, Kazuma Yamakawa, Yoshitaka Hara, Masaaki Sakuraya, Shinichiro Ohshimo, Yoshitaka Aoki, Mai Inada, Yutaka Umemura, Yusuke Kawai, Yutaka Kondo, Hiroki Saito, Shunsuke Taito, Chikashi Takeda, Takero Terayama, Hideo Tohira, Hideki Hashimoto, Kei Hayashida, Toru Hifumi, Tomoya Hirose, Tatsuma Fukuda, Tomoko Fujii, Shinya Miura, Hideto Yasuda, Toshikazu Abe, Kohkichi Andoh, Yuki Iida, Tadashi Ishihara, Kentaro Ide, Kenta Ito, Yusuke Ito, Yu Inata, Akemi Utsunomiya, Takeshi Unoki, Koji Endo, Akira Ouchi, Masayuki Ozaki, Satoshi Ono, Morihiro Katsura, Atsushi Kawaguchi, Yusuke Kawamura, Daisuke Kudo, Kenji Kubo, Kiyoyasu Kurahashi, Hideaki Sakuramoto, Akira Shimoyama, Takeshi Suzuki, Shusuke Sekine, Motohiro Sekino, Nozomi Takahashi, Sei Takahashi, Hiroshi Takahashi, Takashi Tagami, Goro Tajima, Hiroomi Tatsumi, Masanori Tani, Asuka Tsuchiya, Yusuke Tsutsumi, Takaki Naito, Masaharu Nagae, Ichiro Nagasawa, Kensuke Nakamura, Tetsuro Nishimura, Shin Nunomiya, Yasuhiro Norisue, Satoru Hashimoto, Daisuke Hasegawa, Junji Hatakeyama, Naoki Hara, Naoki Higashibeppu, Nana Furushima, Hirotaka Furusono, Yujiro Matsuishi, Tasuku Matsuyama, Yusuke Minematsu, Ryoichi Miyashita, Yuji Miyatake, Megumi Moriyasu, Toru Yamada, Hiroyuki Yamada, Ryo Yamamoto, Takeshi Yoshida, Yuhei Yoshida, Jumpei Yoshimura, Ryuichi Yotsumoto, Hiroshi Yonekura, Takeshi Wada, Eizo Watanabe, Makoto Aoki, Hideki Asai, Takakuni Abe, Yutaka Igarashi, Naoya Iguchi, Masami Ishikawa, Go Ishimaru, Shutaro Isokawa, Ryuta Itakura, Hisashi Imahase, Haruki Imura, Takashi Irinoda, Kenji Uehara, Noritaka Ushio, Takeshi Umegaki, Yuko Egawa, Yuki Enomoto, Kohei Ota, Yoshifumi Ohchi, Takanori Ohno, Hiroyuki Ohbe, Kazuyuki Oka, Nobunaga Okada, Yohei Okada, Hiromu Okano, Jun Okamoto, Hiroshi Okuda, Takayuki Ogura, Yu Onodera, Yuhta Oyama, Motoshi Kainuma, Eisuke Kako, Masahiro Kashiura, Hiromi Kato, Akihiro Kanaya, Tadashi Kaneko, Keita Kanehata, Kenichi Kano, Hiroyuki Kawano, Kazuya Kikutani, Hitoshi Kikuchi, Takahiro Kido, Sho Kimura, Hiroyuki Koami, Daisuke Kobashi, Iwao Saiki, Masahito Sakai, Ayaka Sakamoto, Tetsuya Sato, Yasuhiro Shiga, Manabu Shimoto, Shinya Shimoyama, Tomohisa Shoko, Yoh Sugawara, Atsunori Sugita, Satoshi Suzuki, Yuji Suzuki, Tomohiro Suhara, Kenji Sonota, Shuhei Takauji, Kohei Takashima, Sho Takahashi, Yoko Takahashi, Jun Takeshita, Yuuki Tanaka, Akihito Tampo, Taichiro Tsunoyama, Kenichi Tetsuhara, Kentaro Tokunaga, Yoshihiro Tomioka, Kentaro Tomita, Naoki Tominaga, Mitsunobu Toyosaki, Yukitoshi Toyoda, Hiromichi Naito, Isao Nagata, Tadashi Nagato, Yoshimi Nakamura, Yuki Nakamori, Isao Nahara, Hiromu Naraba, Chihiro Narita, Norihiro Nishioka, Tomoya Nishimura, Kei Nishiyama, Tomohisa Nomura, Taiki Haga, Yoshihiro Hagiwara, Katsuhiko Hashimoto, Takeshi Hatachi, Toshiaki Hamasaki, Takuya Hayashi, Minoru Hayashi, Atsuki Hayamizu, Go Haraguchi, Yohei Hirano, Ryo Fujii, Motoki Fujita, Naoyuki Fujimura, Hiraku Funakoshi, Masahito Horiguchi, Jun Maki, Naohisa Masunaga, Yosuke Matsumura, Takuya Mayumi, Keisuke Minami, Yuya Miyazaki, Kazuyuki Miyamoto, Teppei Murata, Machi Yanai, Takao Yano, Kohei Yamada, Naoki Yamada, Tomonori Yamamoto, Shodai Yoshihiro, Hiroshi Tanaka, Osamu Nishida

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcute Medicine & Surgery · 2021
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsSeptic shockGuidelineMedicineSepsisMultidisciplinary approachIntensive careIntensive care medicineClinical PracticeFamily medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020), a Japanese-specific set of clinical practice guidelines for sepsis and septic shock created as revised from J-SSCG 2016 jointly by the Japanese Society of Intensive Care Medicine and the Japanese Association for Acute Medicine, was first released in September 2020 and published in February 2021. An English-language version of these guidelines was created based on the contents of the original Japanese-language version. The purpose of this guideline is to assist medical staff in making appropriate decisions to improve the prognosis of patients undergoing treatment for sepsis and septic shock. We aimed to provide high-quality guidelines that are easy to use and understand for specialists, general clinicians, and multidisciplinary medical professionals. J-SSCG 2016 took up new subjects that were not present in SSCG 2016 (e.g., ICU-acquired weakness [ICU-AW], post-intensive care syndrome [PICS], and body temperature management). The J-SSCG 2020 covered a total of 22 areas with four additional new areas (patient- and family-centered care, sepsis treatment system, neuro-intensive treatment, and stress ulcers). A total of 118 important clinical issues (clinical questions, CQs) were extracted regardless of the presence or absence of evidence. These CQs also include those that have been given particular focus within Japan. This is a large-scale guideline covering multiple fields; thus, in addition to the 25 committee members, we had the participation and support of a total of 226 members who are professionals (physicians, nurses, physiotherapists, clinical engineers, and pharmacists) and medical workers with a history of sepsis or critical illness. The GRADE method was adopted for making recommendations, and the modified Delphi method was used to determine recommendations by voting from all committee members. As a result, 79 GRADE-based recommendations, 5 Good Practice Statements (GPS), 18 expert consensuses, 27 answers to background questions (BQs), and summaries of definitions and diagnosis of sepsis were created as responses to 118 CQs. We also incorporated visual information for each CQ according to the time course of treatment, and we will also distribute this as an app. The J-SSCG 2020 is expected to be widely used as a useful bedside guideline in the field of sepsis treatment both in Japan and overseas involving multiple disciplines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.471
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.188
GPT teacher head0.473
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it