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Record W2345713390 · doi:10.14740/cr465w

The Association of Calcium-Phosphorus Product With the Severity of Cardiac Valves Failure in Patients Under Chronic Hemodialysis

2016· article· en· W2345713390 on OpenAlexvenueno aff
Simindokht Moshar, Seyedehsara Bayesh, Maryam Mohsenikia, Reza Najibpour

Bibliographic record

VenueCardiology Research · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineHemodialysisCalciumPhosphorusChronic renal failureMetallurgyMaterials science

Abstract

fetched live from OpenAlex

BACKGROUND: Recent studies have mainly focused on the roles of serum calcium and phosphorus product in the development of valvular heart failure. We determined the association of calcium-phosphorus product with the severity of heart valve failure in patients under chronic hemodialysis (being under hemodialysis for 6 months or more) in Boo-Ali Hospital in 2012 and 2013. METHODS: It was a cross-sectional, descriptive, comparative study. Thirty-three patients undergoing chronic hemodialysis were recruited to the study. All the patients were hospitalized at Boo-Ali Hospital. The study was done in a 2 years long time frame and the association of calcium-phosphorus product and severity of heart valve failure was evaluated among them. RESULTS: The results demonstrated that there was no significant association between age, gender, renal failure cause and hemodialysis duration (P > 0.05). Our results showed a negative correlation between the severity of cardiac valves failure and CA × P level. It was not a meaningful correlation though (P > 0.05). CONCLUSIONS: Based on the obtained results, it is concluded that there is not any association between calcium-phosphorus product and the severity of heart valve failure in patients under chronic hemodialysis.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.348
Teacher spread0.327 · 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 designObservational
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

Citations14
Published2016
Admission routes1
Has abstractyes

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