Benefits and Harms of Citrate Locking Solutions for Hemodialysis Catheters: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Citrate has theoretical advantages over heparin for locking hemodialysis central venous catheters (CVCs), but the comparative effectiveness of these agents is not clear. OBJECTIVES: 1) To compare the benefits and harms of citrate versus heparin locking solutions among patients undergoing hemodialysis through CVCs; 2) to appraise methodological quality of the supporting evidence. DATA SOURCES: CENTRAL, MEDLINE, EMBASE, CINAHL, ISI Web of Science, and nephrology conference abstracts. STUDY ELIGIBILITY PARTICIPANTS AND INTERVENTIONS: We included randomized, parallel arm clinical trials that enrolled adult patients (>18 years) receiving chronic hemodialysis through CVCs using a citrate locking solution. We excluded studies in which citrate was combined with other agents, such as antibiotics. APPRAISAL AND SYNTHESIS METHODS: We used the GRADE approach to systematic reviews and quality appraisal. Two reviewers performed data extraction independently and in duplicate. We pooled count data using generic inverse variance with random-effects models, and used fixed-effect models when only two studies were available for pooling. Subgroups included low (≤5%) vs. higher (≥30%) citrate. RESULTS: We screened 600 citations. Forty-one proceeded to full-text screen; 5 met inclusion criteria. Studies included between 19 and 291 participants (Median N = 61) followed for a total of 174.6 catheter-years; 2 were multi-centred trials. Three studies assessed all-cause mortality; the pooled relative risk for death was 0.71 (95% CI = 0.42-1.24; p = 0.21; I(2) = 0%). The rate ratio for bacteremic episodes was 0.54 (95% CI = 0.23-1.29; p = 0.16; I(2) = 65%) while the rate ratio for bleeding was 0.48 (95% CI = 0.3-0.75; p = 0.001;I I(2) = 5%). Rates of catheter exchange/replacement, all-cause hospitalization and in-situ thrombolysis were not significantly different between groups in any of the pooled analyses. Risk of bias within pooled studies was low. LIMITATIONS: Outcome definitions varied across studies. Imprecision due to small sample sizes and low event rates reduce our overall confidence in the pooled effect estimates. IMPLICATIONS: Benefits and harms of citrate vs. heparin locking solutions remain unclear; larger studies and standardization of outcome measurement and reporting are warranted. TRIAL REGISTRATION: Protocol Registration Number: CRD42013004781.
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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 | 0.023 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".