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Record W4413442294 · doi:10.7759/cureus.90276

Estimating Umbilical Venous Catheter Insertion Depth in Newborns Using Weight or Body Measurements: A Multicenter Randomized Clinical Trial

2025· article· en· W4413442294 on OpenAlexaff
Fawzy K Abdelhamid, Abdulrahman Al Matery, B. Mahmoud, Tagwa B Eltayeb, Mohammed Almasoud, Emad Ahmad Alhulaimi, Mohammed Al‐Qahtani, Mohammed Y Al‐Hindi

Bibliographic record

VenueCureus · 2025
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsHealth Sciences Centre
FundersKing Fahad Medical CityNorthwestern University
KeywordsMedicineMulticenter studyRandomized controlled trialCatheterMulticenter trialBody weightSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Introduction The current methods for estimating umbilical venous catheter (UVC) insertion depth, including the umbilical to nipple (Gupta) and the birth weight-based (modified Shukla) formula, have varying accuracy rates. Objectives To compare the accuracy of UVC insertion length using the birth weight-based formula versus the surface measurement formula in determining the optimal UVC tip position. Methods A multicenter randomized clinical trial was conducted across three centers, including level III neonatal intensive care units (NICUs) in the Second Cluster in Riyadh (Al-Yamama Hospital and King Fahad Medical City), as well as King Salman Armed Forces Hospital in Tabuk City, Northwestern Region, Saudi Arabia. Neonates requiring UVC insertion during their NICU admission were randomly assigned to one of two formulas: (1) the umbilicus to nipple distance in centimeters minus 1 (UN - 1) or (2) the modified Shukla weight-based formula in centimeters (3×birth weight in kg+9, divided by 2) to estimate the pre-insertion UVC depth and to determine the UVC tip position anteroposterior and lateral thoracoabdominal radiographs were taken and reviewed by a neonatologist, who was blinded to the group assignments. Data analysis was conducted using appropriate statistical methods, ensuring adherence to ethical standards. Results A total of 158 infants were analyzed, with 88 in the Gupta group and 70 in the modified Shukla group. The majority of UVC insertions (n=156, 98.7%) were performed for intravenous fluids, total parenteral nutrition (TPN), and antibiotics, while only two cases (n=2, 1.3%) involved blood exchange transfusion. The demographic and clinical data of the two groups were comparable. The Gupta method demonstrated a significantly higher rate of correct catheter placements (n=55, 62.5%) compared to the modified Shukla method (n=32, 45.7%; p=0.02). The Gupta method was particularly effective in the SGA group, with 70.0% (n=21) correct placements, compared to 42.9% (n=9) in the modified Shukla group (p=0.04). No significant differences in catheter advancement rates or fix-on measurements were observed between the two methods (p=0.59 and p=0.45, respectively). The modified Shukla group had a significantly abnormal catheter low tip position (n=23, 32.9%) compared to the Gupta group (n=13, 14.8%; p=0.02). Conclusions The Gupta method provides more accurate UVC placement, especially in SGA neonates, compared to the modified Shukla method. Both methods showed similar catheter advancement success and insertion depth, suggesting that the Gupta method may be a more reliable approach for UVC insertion in neonates. Further studies with larger sample sizes and advanced imaging techniques are needed to confirm these findings and assess long-term outcomes.

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)0.011
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.177
GPT teacher head0.477
Teacher spread0.300 · 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 designRandomized trial
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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