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Record W3062404038 · doi:10.1093/pch/pxaa068.035

36 Contrast Enhanced Radiography for Peripherally Inserted Central Venous Catheter Tip localization- Is it really needed for all infants?

2020· article· en· W3062404038 on OpenAlexaff
Mary Jim Jose, Amuchou Soraisham

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicinePeripherally inserted central catheterRadiographyModality (human–computer interaction)CatheterContrast (vision)RadiologyMedical physicsComputer scienceComputer vision

Abstract

fetched live from OpenAlex

Abstract Background Contrast enhanced radiography (CER) is considered one of the best available methods for localizing the tip of a peripherally inserted central venous catheters (PICC) in neonates, which was the standard practice at our NICU. It was observed that multiple catheter readjustments and radio-graphs were required due to contrast jet appearing radio-graphically as a distal extension of the catheter creating a false impression of deep location of the PICC tip. This raised the question of whether we need to use contrast routinely for all infants or can we selectively use contrast when needed. Objectives The intention of this quality improvement project was to adopt the use of plain radiography (PR) as the first modality for PICC tip localization and use CER only if localization was unsuccessful in the first instance. The objective was to examine the effect of this change of clinical practice on the: a) number of radio-graphs taken for PICC insertions b) the frequency of intravenous contrast use in PICC insertion. Design/Methods This was a QI initiative conducted over a 7 month period. After educating all care providers who insert PICC, we changed our practice to use plain radiography as first modality for PICC tip visualization starting June 1, 2019. CER was only used if catheter tip was not visualized on plain radiography. We collected the information on infants who had PICC inserted in the NICU before and after the implementation of the initiative for a given period. Outcome measures were a) proportion of infants with PICC tip visualized on first plain radiography (b) proportion of infants who received CER (c) Number of X-rays per line insertion. We compared the data regarding the above outcomes between the two time periods. Results Of the 113 PICC inserted, 39 PICCs were inserted during routine CER period, and 74 PICCs were inserted during PR period. The mean gestational age (26 ± 2.8 vs 27± 3.5), birth weight (878 ± 406g vs 1024g ± 559g, site of insertion - upper limb PICC (74% vs 69%) were comparable between the two groups. Catheter was visualized on first plain radiography in 56/74 (75%) in the PR period. Overall, the CER was performed in 30/74 (40%), of which 18 were for non-visualization of tip on first plain radio-graph and 11 for non-visualization after subsequent manipulation. There was no difference in the median (IQR) number of radio-graphs between CER period and PR period [2 (2-3) vs 2 (1-3), p =NS] with similar proportion of infants requiring 2 or less X-rays (71% vs 67%). Conclusion The use of plain radiography as the initial imaging modality is a safe alternative, without increasing radiation exposure and it minimizes the use of intravenous contrast in neonates undergoing PICC insertions. In spite of being superior for tip visualization, CER does not reduce the number of X-rays taken for the same purpose.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.031
GPT teacher head0.324
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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