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Restrição proteica na DRC: uma estratégia obsoleta na era moderna

2025· article· pt· W4407353316 on OpenAlexaff
Abdullah Bawazir, Joel Michels Topf, Swapnil Hiremath

Bibliographic record

VenueBrazilian Journal of Nephrology · 2025
Typearticle
Languagept
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineInternal medicine

Abstract

fetched live from OpenAlex

Resumo Tradicionalmente, o manejo da doença renal crônica (DRC) tem enfatizado a restrição dietética de proteínas para retardar a progressão da doença e atrasar a doença renal em estágio terminal (DRET). No entanto, evidências de estudos clínicos questionam a suposta eficácia dessa abordagem e também destacam potenciais riscos, como desnutrição e redução da qualidade de vida. Esta revisão discute os fundamentos para a restrição proteica na DRC, apresenta críticas às evidências existentes e defende um cuidado personalizado que priorize a adequação nutricional e uma farmacoterapia eficaz. Avanços importantes no tratamento da DRC, incluindo inibidores da ECA, inibidores de SGLT2 e agonistas do receptor de GLP-1, são discutidos com o objetivo de propor uma estratégia abrangente que otimize os desfechos dos pacientes.

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)0.006
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.008
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.283
Teacher spread0.269 · 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
GenreEmpirical

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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Citations1
Published2025
Admission routes1
Has abstractyes

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Same venueBrazilian Journal of NephrologySame topicDialysis and Renal Disease ManagementFrench-language works237,207