Key performance indicators for acute intermittent kidney replacement therapy in critically ill patients: a protocol for a systematic review
Bibliographic record
Abstract
INTRODUCTION: There have been previous initiatives to identify key performance indicators (KPIs) for continuous kidney replacement therapy. However, no formal reviews of the evidence for KPIs of intermittent kidney replacement therapy (IKRT) have been conducted. This systematic review will appraise the evidence for KPIs of IKRT in critically ill patients and is part of the DIALYZING WISELY (NCT05186636) programme which aims to improve the performance of acute renal replacement therapy in intensive care units by aligning local practices with evidence-based best practices. METHODS AND ANALYSIS: Ovid MEDLINE, Ovid Embase, CINAHL and Cochrane Library will be searched for studies involving KPIs for IKRT. Grey literature will also be searched and include technical reports, practice guidelines and conference proceedings as well as websites of relevant organisations. We will search the Agency of Healthcare Research and National Quality Measures Clearinghouse for IKRT-related KPIs. Studies will be included if they contain KPIs, occur in critically ill patients and are associated with IKRT. We will evaluate the risk of bias using the modified Cochrane tool and certainty of evidence using the Grading of Recommendations, Assessment, Development and Evaluations methodology. The analysis will be primarily descriptive. Each KPI will be evaluated for importance, scientific acceptability, usability and feasibility using the four criteria proposed by the United States Strategic Framework Board for a National Quality Measurement and Reporting System. Finally, KPIs will be appraised for potential operational characteristics, potential to be integrated into electronic medical records, adoptability by stakeholders and affordability, if applicable. ETHICS AND DISSEMINATION: Ethics approval is not required as primary data will not be collected. Findings of this review will be disseminated through peer-related publication. PROSPERO REGISTRATION NUMBER: CRD42022074444.
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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 | 0.089 | 0.116 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.017 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.063 | 0.009 |
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".