Best evidences summary on oral hydration therapy for the prevention of contrast-induced nephropathy in patients after percutaneous coronary intervention
Bibliographic record
Abstract
ObjectiveTo retrieve and summarize the best evidences of oral hydration therapy for the prevention of contrast⁃induced nephropathy in patients after percutaneous coronary intervention（PCI），so as to provide reference for clinical practice.MethodsTo search the PubMed，Web of Science、Ovid、Cochrane Library、JBI Evidence-Based Health Care Center Library，Guidelines International Network（GIN），National Institute for Health and Clinical Excellence（NICE），National Guideline Clearinghouse（NGC），Registered Nurses' Association of Ontario（RNAO），the Scottish Intercollegiate Guidelines Network（SIGN），Kidney Disease：Improving Global Outcomes（KDIGO），and China Biology Medicine disc（CBMdisc）.All evidence on oral hydration therapy for the prevention of contrast⁃induced nephropathy in patients after percutaneous coronary intervention，including guidelines，expert consensus，evidence summaries，systematic evaluations，and original researches closely related to evidence，were collected.The qualities of included literatures were evaluated by 4 researchers.Then，evidences were extracted from the literatures that met the quality standards.ResultsA total of 15 literatures were included in this study，including 3 guidelines，4 systematic evaluations，4 randomized controlled trials，3 quasi-experiment studies and 1 expert consensus.Finally，12 pieces of best evidences were defined.ConclusionsThe formed best evidences on oral hydration therapy for the prevention of contrast⁃induced nephropathy in patients after percutaneous coronary intervention in this study，which could provide evidence-based reference for clinical practice.It was suggested that we should evaluate clinical environments of the medical institutions，factors that promote and hinder the medical personnel to apply evidences，and the patient's willingness and state of illness when using evidence in clinics.Further，to make a targeted evidence selection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.017 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".