ArticleCureus2025
The Development and Evaluation of a Low-Cost, High-Fidelity Ultrasound-Guided Abdominal Paracentesis Simulator.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction Paracentesis is a vital procedure for diagnosing and managing ascites, yet hands-on training opportunities are limited due to issues related to patient availability and procedural risks. Simulation-based training helps develop skills and confidence, but high-fidelity commercial models remain expensive and scarce. To address this gap, we created a novel, low-cost, high-fidelity ultrasound-guided abdominal paracentesis (USGAP) simulation model. Designed for affordability and realism, this model aims to improve trainee confidence and integrate ultrasound guidance to enhance procedural safety and precision. Methods A 3-litre saline bag was modified to simulate the abdominal cavity, incorporating aqueous dietary fibre antifreeze mix gel for liver tissue, fluid-filled sausage casing for the bowel, and dyed water for ascitic fluid. The model was sealed and coated with latex for self-sealing properties, with a total cost of £25. Assessment took place over two sessions (January-February 2025) involving 19 participants (senior house officers (SHOs), registrars, and consultants). Pre- and post-training questionnaires assessed training opportunities, confidence, and model effectiveness using a five-point Likert scale. Data was analysed using IBM SPSS Statistics (IBM Corp., Armonk, NY) (Wilcoxon signed-rank test, p<0.05). Ethics approval was not required as this study was registered as a quality improvement project. Consent was obtained, and all responses were anonymised. Results Pre-training data revealed significant gaps in USGAP training, with only 31.6% of participants reporting adequate exposure (median Likert 2/5). However, all participants (100%) recognised the importance of high-quality simulation. Following model use, confidence in performing USGAP significantly improved from 47.3% to 78.9% (p = 0.005). The model received unanimous positive feedback (100%) with participants praising its affordability, realism, and procedural accuracy. Conclusions This study demonstrated that a cost-effective, high-fidelity USGAP model significantly enhances trainees' confidence while providing a sustainable and accessible alternative to expensive commercial models. The realistic anatomical structures, ultrasound capability, and self-sealing properties make it a valuable training tool. While the sample size was limited, the findings strongly support broader implementation into medical training. Future research should assess long-term skill retention and multi-centre adoption.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.