Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Importance: Umbilical venous catheterization (UVC) is a common procedure for critically ill newborn infants. The insertion depth was estimated before the procedure using various formulae.
Objective: To compare the accuracy of five published formulae based on birth weight (BW).
Methods: This is a secondary retrospective analysis using data collected in a previous study, in which the actual final insertion depth of UVC was recorded. Predicted insertion depths were calculated by five published formulae based on BW. Then the actual depth and predicted depth were compared. Accurate position was defined as predicted depth being within ± 10% of actual depth. The accuracy rate calculated as "(accurately positioned UVCs/ all UVCs) × 100%" and the ratio of difference calculated as "(|predicted depth - actual depth|/ actual depth)" were compared among five formulae.
Results: Totally 1298 were enrolled, with gestational age 29.8 ± 2.3 weeks and BW 1215 ± 273 g. The accuracy rates were: Tambasco formula (67.2%), Shukla formula (65.0%), JSS formula (64.4%), BW formula (48.9%), and revised Shukla formula (26.9%). Tambasco formula had the highest accuracy rate in newborns with BW ≥ 1000 g. JSS formula had the highest accuracy rate in newborns with BW<1000 g.
Interpretation: It is suggested to use the Tambasco formula for estimating the UVC insertion depth for newborns, especially for those with BW ≥ 1000 g, and to apply the JSS formula for newborns with BW < 1000 g. There is no universal formula for achieving 100% accurate positioning.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664533 | PMC |
| http://dx.doi.org/10.1002/ped4.12451 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Performance of vision language models for optic disc swelling identification on fundus photographs.
Front Digit Health
August 2025
Department of Ophthalmology, Stanford University, Palo Alto, CA, United States.
Introduction: Vision language models (VLMs) combine image analysis capabilities with large language models (LLMs). Because of their multimodal capabilities, VLMs offer a clinical advantage over image classification models for the diagnosis of optic disc swelling by allowing a consideration of clinical context. In this study, we compare the performance of non-specialty-trained VLMs with different prompts in the classification of optic disc swelling on fundus photographs.
View Article and Find Full Text PDFA hybrid 1DCNN-GRU deep learning framework for classifying caprine granulosa cell fertility potential using single-cell transcriptomics.
Vet World
July 2025
Department of Veterinary Science, Faculty of Veterinary Medicine, Rajamangala University of Technology Tawan-OK, Chonburi, Thailand.
Background And Aim: Granulosa cells (GCs) are crucial mediators of follicular development and oocyte competence in goats, with their gene expression profiles serving as potential biomarkers of fertility. However, the lack of a standardized, quantifiable method to assess GC quality using transcriptomic data has limited the translation of such findings into reproductive applications. This study aimed to develop a hybrid deep learning model integrating one-dimensional convolutional neural networks (1DCNNs) and gated recurrent units (GRUs) to classify GCs as fertility-supporting (FS) or non-fertility-supporting (NFS) using single-cell RNA sequencing (scRNA-seq) data.
View Article and Find Full Text PDFOptimizing dose rate to minimize delivery time in proton pencil beam dose-driven continuous scanning.
Med Phys
September 2025
Department of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, Florida, USA.
Background: Dose-driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness.
Purpose: This study introduces a Break Spot-Guided (BSG) method, combined with two acceleration strategies-dose rate skipping and bounding-to optimize beam intensity while minimizing beam delivery time (BDT).
Prediction of in-hospital mortality in patients with acute myocardial infarction following primary percutaneous coronary intervention: A machine learning approach.
Heart Lung
September 2025
Department of Nursing, College of Medicine, National Cheng Kung University, No. 1, University Road, East District, Tainan City 70101, Taiwan. Electronic address:
Background: In-hospital mortality in patients with acute myocardial infarction (AMI) following primary percutaneous coronary intervention (pPCI) remains a significant concern. Developing a predictive model of in-hospital mortality is crucial for identifying high-risk patients, guiding clinical decisions, and preventing in-hospital mortality. Machine learning (ML) may analyze patterns in large datasets and provide accurate predictions of in-hospital mortality in AMI patients following pPCI.
View Article and Find Full Text PDFFeasibility of HyperSight CBCT for adaptive radiation therapy: A phantom benchmark study of dose calculation accuracy and delivery verification on the Halcyon.
J Appl Clin Med Phys
September 2025
Department of Radiation Oncology, University of Utah, Salt Lake City, Utah, USA.
Purpose: The development of on-board cone-beam computed tomography (CBCT) has led to improved target localization and evaluation of patient anatomical change throughout the course of radiation therapy. HyperSight, a newly developed on-board CBCT platform by Varian, has been shown to improve image quality and HU fidelity relative to conventional CBCT. The purpose of this study is to benchmark the dose calculation accuracy of Varian's HyperSight cone-beam computed tomography (CBCT) on the Halcyon platform relative to fan-beam CT-based dose calculations and to perform end-to-end testing of HyperSight CBCT-only based treatment planning.
View Article and Find Full Text PDF