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Record W2050682522 · doi:10.1159/000362455

Pre-Procedure Desmopressin Acetate to Reduce Bleeding in Renal Failure: Does It Really Work?

2014· article· en· W2050682522 on OpenAlexaff
Seetha Radhakrishnan, Rahul Chanchlani, Bairbre Connolly, Valérie S. Langlois

Bibliographic record

VenueNephron Clinical Practice · 2014
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineDesmopressinNephrologyUrologyInternal medicineIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

<b><i>Background:</i></b> Desmopressin (DDAVP) is often used prior to procedures to minimize bleeding in patients with renal failure; however, there is little evidence to support this practice. The objectives of this study were to evaluate the practice of administration of DDAVP prior to procedures within our division and to determine the number of bleeding episodes for patients who received DDAVP compared to those who did not. <b><i>Methods:</i></b> Hospital records of patients who underwent renal biopsy or central line placement between April 2006 and March 2008 were reviewed. Patients with glomerular filtration rate (GFR) <60 ml/min/1.73 m<sup>2</sup> were identified and subcategorized into three groups: group A GFR <15 ml/min/1.73 m<sup>2</sup>, group B GFR 15-29 ml/min/1.73 m<sup>2</sup>, and group C GFR 30-60 ml/min/1.73 m<sup>2</sup>. The number of bleeding events was noted in each group. <b><i>Results:</i></b> No significant difference was found in the number of bleeding events between those who received and did not receive DDAVP overall and in each GFR group. A possible trend towards the benefit with treatment in group A was observed. <b><i>Conclusion:</i></b> There was no significant reduction in bleeding for those who received DDAVP which questions the validity of this practice. Patients with GFR <15 ml/min/1.73 m<sup>2</sup> may possibly derive benefit.

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)0.001
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.454
Teacher spread0.386 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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