MétaCan
Menu
Back to cohort
Record W4282938686 · doi:10.1186/s13098-022-00843-8

The 2021–2022 position of Brazilian Diabetes Society on diabetic kidney disease (DKD) management: an evidence-based guideline to clinical practice. Screening and treatment of hyperglycemia, arterial hypertension, and dyslipidemia in the patient with DKD

2022· article· en· W4282938686 on OpenAlexfundno aff
João Roberto de Sá, Érika Bevilaqua Rangel, Luís Henrique Santos Canani, Andréa Carla Bauer, Gustavo Monteiro Escott, Themis Zelmanovitz, Marcello Casaccia Bertoluci, Sandra Pinho Silveiro

Bibliographic record

VenueDiabetology & Metabolic Syndrome · 2022
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsnot available
FundersNovo NordiskSanofiServierAmgenLondon Health Sciences CentreEli Lilly and Company
KeywordsMedicineGuidelineObservational studyRandomized controlled trialIntensive care medicineDiabetes mellitusMEDLINEClinical trialKidney diseaseDiseaseSystematic reviewDyslipidemiaFamily medicineInternal medicinePathologyEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Diabetic kidney disease is the leading cause of end-stage renal disease and is associated with increased morbidity and mortality. This review is an authorized literal translation of part of the Brazilian Diabetes Society (SBD) Guidelines 2021-2022. This evidence-based guideline provides guidance on the correct management of Diabetic Kidney Disease (DKD) in clinical practice. METHODS: The methodology was published elsewhere in previous SBD guidelines and was approved by the internal institutional Steering Committee for publication. Briefly, the Brazilian Diabetes Society indicated 14 experts to constitute the Central Committee, designed to regulate methodology, review the manuscripts, and make judgments on degrees of recommendations and levels of evidence. SBD Renal Disease Department drafted the manuscript selecting key clinical questions to make a narrative review using MEDLINE via PubMed, with the best evidence available including high-quality clinical trials, metanalysis, and large observational studies related to DKD diagnosis and treatment, by using the MeSH terms [diabetes], [type 2 diabetes], [type 1 diabetes] and [chronic kidney disease]. RESULTS: < 40%). B. Data from metanalysis, including large observational studies, a single randomized clinical trial, or a pre-specified subgroup analysis. C: Data from small or non-randomized studies, exploratory analyses, or consensus of expert opinion. The degree of recommendation was obtained based on a poll sent to the panelists, using the following criteria: Grade I: when more than 90% of agreement; Grade IIa 75-89% of agreement; IIb 50-74% of agreement, and III, when most of the panelist recommends against a defined treatment. CONCLUSIONS: To prevent or at least postpone the advanced stages of DKD with the associated cardiovascular complications, intensive glycemic and blood pressure control are required, as well as the use of renin-angiotensin-aldosterone system blocker agents such as ARB, ACEI, and MRA. Recently, SGLT2 inhibitors and GLP1 receptor agonists have been added to the therapeutic arsenal, with well-proven benefits regarding kidney protection and patients' survival.

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)0.059
metaresearch head score (Gemma)0.111
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.111
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0160.012
Science and technology studies0.0020.002
Scholarly communication0.0070.004
Open science0.0070.005
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0060.006

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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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".

Quick stats

Citations13
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueDiabetology & Metabolic SyndromeSame topicChronic Kidney Disease and DiabetesFrench-language works237,207