Evidence map›Paper›PMID 40951844›Full record

ArticleFrontiers in medical technology2025

State machine design for an automated peritoneal dialysis machine.

Wafa A Baroudi, Fatimah B Alnahdi, Raghad S Aljohani, Maryam A Alzuabi, Nora K Alsaqoub, Ibrahim A Aljamaan, Naif A Alrubai, Sajid Ali

Abstract read
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In one paragraph

Article in Frontiers in medical technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Wafa A BaroudiBiomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Fatimah B AlnahdiBiomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Raghad S AljohaniBiomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Maryam A AlzuabiBiomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Nora K AlsaqoubBiomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Ibrahim A AljamaanBiomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Naif A AlrubaiDepartment of Mechanical and Energy Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Sajid AliDepartment of Mechanical and Energy Engineering, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

According to the National Library of Medicine (NLM), chronic kidney disease (CKD) affects more than 10% of the world's population, and peritoneal dialysis (PD) is one of the promising treatments. Despite the advantages of the current PD machine over alternative treatments, it has certain limitations, such as high consumable costs, lengthy daily sessions, and a lack of portability. This work aims to implement a finite state machine design to modify the process of an automated, economical PD system. The proposed optimized process includes a flush system stage, where tubes are rinsed before and after each session to avoid contamination. This design is intended for use by only one patient to prevent contamination. Furthermore, a turbidity sensor is added to measure the efficiency of the dialysis process and reduce the current dialysis time, which can reach eight hours. The finite state machine design is developed using LabVIEW software, featuring a user-friendly interface that allows users to track the process's progress.

Indexed as

automated peritoneal dialysis (APD)biomechanicschronic kidney disease (CKD)dialysis solutionshemodialysisperistaltic pumpstate machine design

Identifiers

PMID40951844
PMCPMC12426040

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Registered trials

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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.