Midline Venous Catheter vs Peripherally Inserted Central Catheter for Intravenous Therapy
Bibliographic record
Abstract
Importance: Peripherally inserted central catheters (PICCs) are frequently used for peripheral intravenous therapy (IVT) that could be administered through a peripheral midline venous catheter (MVC). Objective: To assess the noninferiority of MVCs compared with PICCs as a reliable vascular access for peripheral IVT and blood draws for IVT that does not require a central VC. Design, Setting, and Participants: This randomized clinical trial was conducted in a single tertiary care center from September 2018 to March 2022. Participants were all consecutive adult patients who were referred for PICC and eligible for MVC. Patients likely to require a central VC (those in the critical care unit, those with kidney failure, or those requiring a multilumen VC) were excluded. Analyses were based on the evaluable population. Interventions: Participants were randomized 1:1 to either MVC or PICC. For the MVC group, a 20-cm-long, 4F (French), single-lumen MVC without a valve was used without fluoroscopic assistance. For the PICC group, a 4F, single-lumen PICC without a valve was positioned under fluoroscopy at the cavoatrial junction. Main Outcomes and Measures: The primary outcome was the percentage of patients without VC-related adverse events or dysfunctions requiring medical intervention during follow-up. A noninferiority test was performed to compare the proportion of adverse events or dysfunctions between the MVC and PICC groups. A noninferiority margin was set at 10% and a 5% 1-sided significance level. Results: Of the 6821 patients referred to the tertiary care center for PICC insertion, 294 (180 males [61.2%]; median [IQR] age, 56.3 [38.2-66.7] years) were randomized to receive MVCs (n = 146) or PICCs (n = 148); 135 and 137 participants, respectively, were included in data analysis after exclusion of those who did not complete follow-up. Ninety of 135 patients (66.7%) in the MVC group and 128 of 137 (93.4%) in the PICC group were without VC-related adverse event or dysfunction. The noninferiority of MVC could not be demonstrated (P > .99 for noninferiority). Conclusions and Relevance: In this randomized clinical trial, MVCs were associated with a significantly higher percentage of patients with VC-related adverse events or dysfunctions and could not be demonstrated as a noninferior alternative to PICCs. Trial Registration: ClinicalTrials.gov Identifier: NCT03502980.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".