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Record W1564601355 · doi:10.1159/000381241

Increasing Water Intake in Chronic Kidney Disease: Why? Safe? Possible?

2015· article· en· W1564601355 on OpenAlexaff
William F. Clark, Jessica M. Sontrop, Louise Moist, S.-H. Huang

Bibliographic record

VenueAnnals of Nutrition and Metabolism · 2015
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineUrine osmolalityKidney diseaseUrineFluid intakeAdverse effectVasopressinRandomized controlled trialUrine specific gravityWater intakeInternal medicineUrinary systemKidneyPhysiology

Abstract

fetched live from OpenAlex

Increased water intake may slow the progression of chronic kidney disease by lowering vasopressin levels. Prior to initiating a large randomized controlled trial on the effect of increased water intake on renal decline, we conducted a six-week pilot study to examine the safety and feasibility of asking adults with chronic kidney disease to increase their water intake. We randomly assigned 29 patients to either a hydration or a control group. The hydration group was asked to increase water intake by 1 to 1.5 l/day relative to their weight, gender, and 24 h urine osmolality, in addition to usual consumed beverages; the control group was asked to continue with usual fluid intake. After six weeks, the change in urine volume was significantly different between groups (0.9 l/day; p = 0.002) with no change in serum sodium and no serious adverse effects. Similarly, preliminary results of our large clinical trial of the same intervention (489 patients enrolled to date) demonstrated a significant separation between groups on 24 h urine volume (at 12 months the mean difference between groups was 1.2 l/day; p < 0.001) with no serious adverse effects. Serum sodium has remained stable in both groups over follow-up. To our knowledge, this trial is currently the largest of its kind to date; the significant separation between groups with respect to urine volume indicates that we will have scientifically reliable data on the effect of increased fluid intake on renal decline. The analysis of primary and secondary outcomes will be conducted at the conclusion of follow-up in July 2016.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.313
Teacher spread0.271 · 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 designNot applicable
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

Citations8
Published2015
Admission routes1
Has abstractyes

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