Bleeding Risk of Central Venous Catheterization in Adults: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Central venous catheter (CVC) insertion is a cornerstone procedure in hospitalized and critically ill adults. However, many patients requiring CVCs have coagulopathy, thrombocytopenia, liver disease, or hematologic malignancies, raising concerns about bleeding risk. The true incidence of hemorrhagic complications and the value of preventive measures in these populations remain uncertain. The objective of this study is to systematically evaluate the incidence of bleeding related to CVC placement in adults at increased hemorrhagic risk and to assess the effectiveness of periprocedural preventive strategies. PubMed, Embase, Cochrane Library, and Web of Science were searched from January 2000 to March 2025. Randomized trials and observational studies involving adults with elevated bleeding risk undergoing CVC placement were included. Data extraction and risk of bias assessment (RoB 2 and Newcastle–Ottawa Scale) were performed independently by two reviewers. Certainty of evidence was rated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation), and random-effects meta-analyses were conducted when appropriate. Forty-one studies encompassing 7,603 patients and 8,796 CVC insertions were analyzed. Major bleeding occurred in 0.57% of procedures and minor bleeding in 8.1%. The pooled incidence of any bleeding across 22 studies was 6.8% (95% confidence interval, 3.7–10.7%). Bleeding was more frequent among patients with hematologic malignancies, severe thrombocytopenia, or critical illness. Ultrasound guidance markedly reduced complications compared with landmark technique. Platelet transfusion was effective only below 30 × 109/L, whereas fresh-frozen plasma showed no clear benefit. CVC placement in adults with coagulopathy or thrombocytopenia is generally safe. Ultrasound guidance, restrictive transfusion thresholds, and thromboelastography-guided assessment enhance procedural safety and reduce unnecessary transfusions.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".