MétaCan
Menu
Back to cohort
Record W1915200030 · doi:10.5539/gjhs.v8n5p120

Acute Kidney Injury Recognition and Management: A Review of the Literature and Current Evidence

2015· review· en· W1915200030 on OpenAlexvenueno aff
Syed Raza Shah, Sameer Tunio, Mohammad Hussham Arshad, Zorays Moazzam, Komal Noorani, Anushe Mohsin Feroze, Maham Shafquat, Huma Syed Hussain, Syed Ali Hyder Jeoffrey

Bibliographic record

VenueGlobal Journal of Health Science · 2015
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcute kidney injuryNephrotoxicitySepsisRenal functionIntensive care medicineRifleKidney diseaseAcute tubular necrosisKidneyMortality rateDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Acute renal failure is defined as a rapid decrease in the glomerular filtration rate, occurring over a period of hours to days and by the inability of the kidney to regulate fluid and electrolyte homeostasis appropriately. AKI is a catastrophic, life-threatening event in critically ill patients. AKI can be divided into pre-renal injury, intrinsic kidney disease (including vascular insults) and obstructive uropathies. The prognosis of AKI is highly dependent on the underlying cause of the injury. Children who have AKI as a component of multisystem failure have a much higher mortality rate than children with intrinsic renal disease. Treatment of AKI is subjected to risk stratification and ongoing damage control measures, such as patients with sepsis, exposure to nephrotoxic agents, ischemia, bloody diarrhea, or volume loss, could be helped by optimizing the fluid administrations, antibiotics possessing least nephrotoxic potential, blood transfusion where hemoglobin is dangerously low, limiting the use of nephrotoxic agents including radio contrast use, while maximize the nutrition. Acute kidney injury remains a complex disorder with an apparent differentiation in pathology between septic and nonseptic forms of the disease. Although more studies are still required, progress in this area has been steady over the last decade with purposeful international collaboration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.759
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.162
GPT teacher head0.503
Teacher spread0.342 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations24
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicAcute Kidney Injury ResearchFrench-language works237,207