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Record W2801700634 · doi:10.1186/s13643-018-0701-1

Drug discontinuation before contrast procedures and the effect on acute kidney injury and other clinical outcomes: a systematic review protocol

2018· review· en· W2801700634 on OpenAlexafffundabout
Swapnil Hiremath, Jeanne Françoise Kayibanda, Benjamin J.W. Chow, Dean Fergusson, Greg Knoll, Wael Shabana, Brianna Lahey, Olivia McBride, Alexandra Davis, Ayub Akbari

Bibliographic record

VenueSystematic Reviews · 2018
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineDiscontinuationAcute kidney injuryObservational studyMEDLINEIntensive care medicineCochrane LibraryAdverse effectRandomized controlled trialMetforminClinical trialInternal medicineKidney disease

Abstract

fetched live from OpenAlex

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is defined as worsening of renal function after the administration of iodinated contrast material. In patients with cardiovascular disease, kidney disease, and/or diabetes, renin-angiotensin system blockers, non-steroidal anti-inflammatory drugs, diuretics, and metformin can increase the risk of CI-AKI when undergoing contrast imaging. Despite CI-AKI being the leading iatrogenic cause of acute kidney injury, there is a lack of sufficient scientific evidence supporting which drugs should be stopped, when they should be stopped, and when they should be resumed. The purpose of this systematic review is to assess (1) the effect of withholding medication before contrast procedures on the risk of CI-AKI and other clinical outcomes and (2) the incidence of adverse events occurring after withholding these drugs prior to contrast procedures. This protocol has been registered with PROSPERO, https://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42016033178 . METHODS: An information specialist will assist in searching MEDLINE, Embase, and the Cochrane Library databases to identify randomized controlled trials, observational studies, case reports, and case series. Relevant abstracts from professional society meetings and web-based registries of clinical trials will also be included. Studies included will compare patients aged ≥ 18 years instructed to continue taking the drugs of interest and those advised to stop taking them before undergoing contrast procedures. If these drugs are not withheld prior to contrast procedures, the studies must compare patients who are administered these drugs and those who are not before undergoing contrast procedures. Two reviewers will independently screen the titles and abstracts of the studies obtained from the search using pre-defined inclusion criteria and will then extract data from the full texts of selected studies. The quality of the studies will be assessed by two independent reviewers using the Cochrane Risk of Bias 2.0 tool for randomized trials and the Newcastle-Ottawa Scale for observational studies. DISCUSSION: This systematic review will provide a synthesis of current evidence on the discontinuation of drugs prior to contrast procedures and its effect on CI-AKI and other clinical outcomes. These findings will provide clinicians with guidelines and serve as a strong research base for future studies in this field. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016033178.

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)0.038
metaresearch head score (Gemma)0.047
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: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.068
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.047
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0200.015
Bibliometrics0.0120.012
Science and technology studies0.0040.004
Scholarly communication0.0060.008
Open science0.0050.005
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0680.007

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 head0.060
GPT teacher head0.476
Teacher spread0.416 · 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
GenreProtocol

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

Citations9
Published2018
Admission routes3
Has abstractyes

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