What influences interruption of continuous renal replacement therapy in intensive care unit patients: A review with meta‐analysis on outcome variables
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that 8%-10% of ICU patients receive renal replacement therapy. However, there is a high rate of unplanned CRRT interruption, ranging between 17% and 74%. Studies on unplanned interruption of CRRT mainly focused on the retrospective investigation of related risk factors and conclusions have been diverse. AIM: This article aims to clarify the main influencing factors related to unplanned interruption of continuous renal replacement therapy (CRRT) in adult patients in intensive care units (ICUs). STUDY DESIGN: A literature review and meta-analysis were undertaken. Following the application of the Newcastle-Ottawa Scale (NOS), a total of 15 articles were included in a total of 2132 patients who underwent 3690 CRRT procedures and 2181 unplanned interruption times. The methodological guideline of a scoping review was applied for the evidence synthesis while applying the meta-analysis quantitative methodological guideline to identify and clarify main influencing factors related to unplanned interruption of CRRT. The reporting Prisma Protocol was followed. RESULTS: Longer filter life and prothrombin activation time, higher red blood cell count, greater transmembrane pressure, faster blood flow rate, intermittent saline irrigation, lower creatinine level, low prothrombin activity and pre-dilution are factors identified to potentially affect unplanned CRRT in ICU patients. CONCLUSIONS: Available evidence suggests four clinical challenges associated with unplanned CRRT interruption, namely: (a) effects of red blood cell count, filter life, cross-mode pressure, blood flow velocity, prothrombin activity and activated partial thrombin time on unplanned interruption; (b) influence of dilution mode on unplanned interruption; (c) influence of intermittent saline irrigation on unplanned interruption; (d) influence of Scr level on unplanned interruption. RELEVANCE TO CLINICAL PRACTICE: The potential to increase the ability to better manage unplanned CRRT in ICUs has been identified in this article and constitutes a relevant potential health care management contribution that can be implemented by nurses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".