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Record W2618204419 · doi:10.3923/ajdd.2017.54.62

A Review on Epidemiology and Etiology of Renal Stone

2017· review· en· W2618204419 on OpenAlexaboutno aff
Atul Sohgaura, Papiya Bigoniya

Bibliographic record

VenueAmerican Journal of Drug Discovery and Development · 2017
Typereview
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsEtiologyMedicineKidney stonesPathophysiologyEpidemiologyNephronDiabetes mellitusKidney diseaseKidneyRenal colicDiseaseInternal medicineType 2 diabetesObesityIntensive care medicineBioinformaticsEndocrinologyPathologyBiology

Abstract

fetched live from OpenAlex

Renal calculi are crystalline structures of calcium oxalate with associated risk factors like dehydration, high fat diet, animal protein, high salt intake and obesity.Crystals form in the distal tubule, nephron loop and/or collecting tubule have symptoms of severe pain and renal colic.Nephrolithiasis is a global problem affecting all geographical regions.This study compiles the epidemiology of renal calculi focusing on prevalence, occurrence and re-occurrence rate in global perspective.Literature of nephrolithiasis prevalence has been reviewed for Europe, Canada, American, East Asia, Gulf region, Japan, China and different parts of India.Etiology of nephrolithiasis was reviewed in detail for types, factors, symptoms, promoters and inhibitors.Renal calculi induction and progression mechanism was discussed with pathophysiology involved.Water and Food are directly related to occurrence of renal calculi, as a major concern correlation has been discussed.Depending on the type of renal stone, food which are to be avoided and preventive actions were discussed.Concise information was provided on the different experimental models of nephrolithiasis induction in animals.Understanding the pathophysiology of this disorder is necessary for the development of new therapeutic options and treatment.Nephrolithiasis is associated with chronic kidney dysfunction, bone loss and fractures, increased risk of coronary artery disease, hypertension, type 2 diabetes mellitus etc. and understanding the pathophysiology is necessary to develop highly effective drugs.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.092
GPT teacher head0.409
Teacher spread0.317 · 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 designSystematic review
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

Citations99
Published2017
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Drug Discovery and DevelopmentSame topicKidney Stones and Urolithiasis TreatmentsFrench-language works237,207