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Record W2040516523 · doi:10.1093/ndt/gfu158

DIALYSIS. EPIDEMIOLOGY, OUTCOME RESEARCH, HEALTH SERVICES 1

2014· article· en· W2040516523 on OpenAlexaff
Tatsuyoshi Ikenoue, K. Koike, S. Fukuma, Soshiro Ogata, Yoshiharu Tsubakihara, Kunitoshi Iseki, S. Fukuhara, Rakesh Malhotra, Aileen Grassmann, R. Pecoits-Filho, C. Marelli, B. Canaud, Edwina A. Brown, O. Iiyasere, Lina Johansson, Joanna Smee, Les Huson, H. Kim, Sang Won Lee, Jung‐Hwa Ryu, S.-J. Kim, Donna Kang, Kelly Baekyung Choi, D.-R. Ryu, Adrián Guinsburg, P. Kotanko, Russell Brock, M. Wang, Angelo Karaboyas, R. A. Fissell, Takeshi Hasegawa, S. V. Jassal, David L. Mapes, Hal Morgenstern, Hugh C. Rayner, Bruce Robinson, F. Tentori, Connie M. Rhee, Hamid Moradi, Steven M. Brunelli, Tracy Nakata, Danh V. Nguyen, Csaba P. Kövesdy, Gregory A. Brent, Kamyar Kalantar‐Zadeh, Anouk TN van Diepen, Tialda Hoekstra, Joris I. Rotmans, Mark de Boer, Saskia le Cessie, M. Suttorp, Dirk G. Struijk, E. W. Boeschoten, R. T. Krediet, Friedo W. Dekker, Sheridan Johnson, Gus Khursigara, James H. Yen, J. Wang, Nancy Silliman, Camille L. Bedrosian, Murat Arıcı, Usman Farooqui, Catrin Treharne, F. X. Liu, Til Leimbach, J Kron, Jutta Czerny, Birgit Urbach, Sabine Aign, S Kron, Elliott Brown, Osasuyi Iyasere, I. Masakane, Celine Foote, Rachael L. Morton, M Jardine, Martin Gallagher, M. Brown, Kirsten Howard, Alan Cass, Josipa Radić, Dragan Klarić, Marijana Gulin, Milena Ilić, V. Kovacic, Valentina Vukman, V. Rozankovic, Nardi Silić, M. Primorac, J. Meter, T. Cornelis, Karthik Tennankore, Éric Goffin, Virpi Rauta, Eero Honkanen, Akin Özyilmaz, Subhajit Mitra, Frank M. van der Sande, Jeroen P. Kooman, Christopher T. Chan, Anirudh Rao, David Pitcher, Richard Phelps, Bruce F. Culleton, Claudia Torino, Graziella D’Arrigo, M. Postorino, G. Tripepi, A. Testa, F. Mallamaci, Carmine Zoccali, Takasuke Asakawa, Terumasa Hayashi, Yoshiyuki Tanaka, Nobuhiko Joki, Masaki Iwasaki, S Kubo, Ai Matsukane, Yoko Takahashi, Yoshihiko Imamura, Koichi Hirahata, Ken Sakai, Hiroki Hase, E. Dehelean, Dan Munteanu, Marta Gemene, Gabriel Mircescu, Bård Waldum, T. Leivestad, Anna Varberg Reisæter, Ingrid Os, Yutaka Satō, Shota Fujimoto, T. Toida, Hideto Nakagawa, Alexandra Tasmoc, Ionuţ Nistor, Mihaela Dora Donciu, Luminița Voroneanu, Carmen Volovăţ, Adrian Covic, Yasunori Takahashi, Michal Vostrý, Daniel Rajdl, Jaromír Eiselt, L. Malanova, Giorgina Barbara Piccoli, G. Cabiddu, Gabriella Guzzo, Giuseppe Daidone, S. Maxia, S. Ghiotto, I. Ciniglio, V. Postorino, Valentina Loi, M. Nichelatti, R. Attini, Alessandra Coscia, A. Pani, H.-Y. Chen, Yen‐Ling Chiu, Shih‐Ping Hsu, Mei‐Fen Pai, Ju‐Yeh Yang, Hao Wu, Yi Peng, Li Liu, Li Zuo, Yang Luo, S. Abbas, C. Cartagena, César Flores-Gama, C. Williams, M. Carter, F. Zhu, N. W. Levin, Stephan Thijssen, Julia Tsobaneli, Theoharis Tsobanelis, Peter Kurz, Norbert Hensel, Konrad Obermann, V. Schwenger, І. Shifris, І. Dudar, Rudenko Av, V. Krot, K. Tsuchida, Jun Minakuchi, Tatsuya Tomo, Shinichi Kawashima, Philipe Gomes Vieira, Angélica Martins de Souza Gonçalves, Nuno Guimarães Rosa, Luís Resende, José Durães, Anne Kayline Soares Teixeira, G. G. Silva, José Alencastro de Araújo, Hannah Currie, Jyoti Baharani, Ebad Ur Rahman, M. A. Sulaiman, M. Darabi Mahboob, Fahad Hawas, Naveed Aslam, G. Shoel, Amy Kang, Z. Yu, Marjorie Wai Yin Foo, K. Griva, Cristiana David, Ileana Peride, D. Radulescu, Andrei Niculae, Ionel Alexandru Checheriţă, A. Ciocalteu, Ki Sung Ahn, Gurpawan Kang, I. H. Lee, Je‐Hwan Lee, Yuwen Ji, Jungmin Woo, Leszek Domański, Tomasz Prystacki, Krzysztof Safranow, Violetta Dziedziejko, Kazimierz Ciechanowski, Jana Holmar, Ivo Fridolin, F. Uhlin, Merike Luman, Anders Fernström, Alessia Palermo, Paola Cusimano, G Locascio, Shigeru Otsubo, K. Tsuchiya, T. Akiba, Kosaku Nitta, Yong Wang, N. Wang

Bibliographic record

VenueNephrology Dialysis Transplantation · 2014
Typearticle
Languageen
FieldMedicine
TopicMedical Case Reports and Studies
Canadian institutionsQueen's UniversityUniversity Health Network
Fundersnot available
KeywordsMedicineEpidemiologyDialysisIntensive care medicineOutcome (game theory)MEDLINEFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

Introduction and Aims: Although some guidelines recommend salt restriction, few studies have examined the association between salt restriction and clinical outcomes in hemodialysis (HD) patients.Methods: We conducted a retrospective cohort study of 88,115 adult patients enrolled in the Japanese Society for Dialysis Therapy (JSDT) registry (2008) who had received HD for at least two years and were considered anuric.The primary outcome measure was all-cause mortality at one year, and the secondary outcome was cardiovascular (CV) mortality.Estimated salt intake was the main predictor, and was calculated from interdialytic weight gain and pre-and postdialysis serum sodium levels according to the validated method of Kimura and Ramdeen.Nonlinear logistic regression was used to determine the association of salt intake with mortality, adjusting for age, gender, body mass index, vintage of HD, dialysis time, Kt/V, protein catabolic rate normalized to body weight, comorbid conditions, type of vascular access, serum potassium, phosphate, calcium, CRP level, and endotoxin level in dialysate.Cubic splines were plotted and the reference was median salt intake.Salt consumption was categorized by intake levels of 2 g per day and the association with mortality examined.Results: Median [25th-75th percentile] salt intake at baseline was 6.4 [4.6-8.3]g per day.At one year, all-cause mortality occurred in 1,845 (2.1%) patients, including cardiovascular mortality in 821 (0.9%).We observed an association between low salt intake and clinical outcomes (all-cause and CV mortality) (Fig. 1).We observed the highest all-cause mortality in the low salt group (<6g/day) (Fig. 2), and no association between all-cause mortality and high salt intake.Further, we observed similar associations between salt intake and CV mortality.Conclusions: Low salt intake is associated with all-cause and CV mortality.These findings do not support current clinical guidelines, which recommend restricting salt intake to less than 6g per day.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.013
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0230.003

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 head0.090
GPT teacher head0.409
Teacher spread0.319 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2014
Admission routes1
Has abstractyes

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