Complications of Central Venous Catheters in Neonates: A Comprehensive Level III Neonatal Intensive Care Unit Analysis
Bibliographic record
Abstract
Background: To evaluate the use of central venous catheters (CVC), the incidence of related complications, to identify risk factors for these complications and their impact in a level III Neonatal Intensive Care Unit (NICU). Methods:A retrospective cohort study at Centro Hospitalar Universitário de São João, Portugal, included neonates who underwent CVC placement from January 1, 2021, to December 31, 2022.Patient's demographics, CVC's characteristics, complications, and outcomes were collected.Statistical methods were used to assess CVC utilization rates, complication rates, associated risk factors and consequences.Results: Out of 677 admissions, 288 neonates met the study criteria.A total of 463 CVCs were placed, resulting in a utilization ratio of 59.3%.CVCs' complications occurred in 24.3% of neonates, corresponding to a complication rate of 22.9 per 1000 catheter days.Mechanical complications were the most common, followed by infectious and thrombotic events.Risk factors significantly associated with complications included inborn status and the cumulative number of CVCs.PICCs, in particular, had higher complication rates: infectious complications increased significantly after 14 days of placement, while mechanical complications were most prevalent within the first 4 days.CVC-related complications significantly impacted hospital length of stay and mortality.Conclusions: Strategies to minimize CVC's complications should focus on reducing the number of CVCs per patient, and improving insertion and maintenance techniques.PICCs, while beneficial, were associated with a higher risk of complications, suggesting a need for careful consideration of their use.Further research is required to refine guidelines for CVC management and enhance neonatal outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".