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Record W2078888839 · doi:10.1159/000341723

Acid-Base and Electrolyte Abnormalities during Renal Support for Acute Kidney Injury: Recognition and Management

2012· review· en· W2078888839 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBlood Purification · 2012
Typereview
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersFonds de Recherche du Québec - Santé
KeywordsHyperkalemiaHyperphosphatemiaHypokalemiaAcute kidney injuryMedicineDialysisMetabolic acidosisIntensive care medicineHypophosphatemiaAcidosisRenal replacement therapyPeritoneal dialysisAlkalosisAcid–base imbalanceKidney diseaseInternal medicine

Abstract

fetched live from OpenAlex

Acute kidney injury (AKI) is associated with electrolyte and acid-base disturbances such as hyperkalemia, metabolic acidosis, hypocalcemia and hyperphosphatemia. The initiation of dialysis in AKI can efficiently treat these complications. The choice of dialysis modality can be made based on their operational characteristics to tailor the therapy according to the clinical scenario. Each dialysis modality can also trigger significant electrolyte and acid-base disorders, such as hypokalemia, hypophosphatemia and metabolic alkalosis, which may direct changes in fluid delivery and composition. Continuous techniques may be particularly useful in these situations as they allow more time for correction and to maintain balance. This review provides an overview of the electrolyte and acid-base disturbances occurring in AKI and after the initiation of dialysis and discusses therapeutic options in this setting.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.042
GPT teacher head0.307
Teacher spread0.265 · 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