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Record W4382810445 · doi:10.7759/cureus.41252

Cardiorenal Syndrome: A Literature Review

2023· review· en· W4382810445 on OpenAlexaff
Abimbola O Ajibowo, Okelue E Okobi, Erhieyovbe Emore, Elizabeth Soladoye, Cherechi G Sike, Victor A Odoma, Ibrahim O Bakare, Olasunkanmi A Kolawole, Adebola Afolayan, Emeka Okobi, Chinyereadaeze Chukwu

Bibliographic record

VenueCureus · 2023
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
Fundersnot available
KeywordsCardiorenal syndromeMedicineHemodynamicsIntensive care medicineIntervention (counseling)Heart failureCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Cardiorenal syndrome (CRS) is a condition characterized by the intricate two-way relationship between the heart and kidneys, which can lead to acute or chronic dysfunction in these organs. The interplay between cardiorenal connectors and both hemodynamic and non-hemodynamic factors is crucial to understanding this syndrome. The clinical importance of these interactions is evident in the changes observed in hemodynamic factors, neurohormonal markers, and inflammatory processes. Identifying and understanding biomarkers associated with CRS is valuable for early detection and enabling intervention before significant organ dysfunction occurs. This comprehensive review focuses on the clinical significance of biomarkers in the diagnosis, prognosis, and management of CRS. Finally, it highlights the necessity for further advancements in managing this condition.

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)0.001
metaresearch head score (Gemma)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.073
GPT teacher head0.384
Teacher spread0.311 · 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
GenreReview

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

Citations30
Published2023
Admission routes1
Has abstractyes

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