Evidence map›Paper›PMID 36117541›Full record

ArticleHardwareX2022

CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring.

Qing Arn Ng, Christopher Yew Shuen Ang, Yeong Shiong Chiew, Xin Wang, Chee Pin Tan, Mohd Basri Mat Nor, Nor Salwa Damanhuri, J Geoffrey Chase

Open access · goldAbstract read
In one paragraph

Article in HardwareX, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
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

2 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
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 at 4 institutions in 2 countries.

Qing Arn NgSchool of Engineering, Monash University Malaysia, Subang Jaya, Selangor 47500, Malaysia.
Christopher Yew Shuen AngSchool of Engineering, Monash University Malaysia, Subang Jaya, Selangor 47500, Malaysia.
Yeong Shiong ChiewSchool of Engineering, Monash University Malaysia, Subang Jaya, Selangor 47500, Malaysia.
Xin WangSchool of Engineering, Monash University Malaysia, Subang Jaya, Selangor 47500, Malaysia.
Chee Pin TanSchool of Engineering, Monash University Malaysia, Subang Jaya, Selangor 47500, Malaysia.
Mohd Basri Mat NorKulliyah of Medicine, International Islamic University Malaysia, Kuantan, Pahang 25200, Malaysia.
Nor Salwa DamanhuriFaculty of Electrical Engineering, Universiti Teknologi MARA, Cawangan Pulau Pinang, 13500, Permatang Pauh, Pulau Pinang, Malaysia.
J Geoffrey ChaseCenter of Bioengineering, University of Canterbury, Christchurch 8041, New Zealand.
Monash University Malaysia · MYHospital Pulau Pinang · MYInternational Islamic University Malaysia · MYUniversity of Canterbury · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mechanical ventilation (MV) provides respiratory support for critically ill patients in the intensive care unit (ICU). Waveform data output by the ventilator provides valuable physiological and diagnostic information. However, existing systems do not provide full access to this information nor allow for real-time, non-invasive data collection. Therefore, large amounts of data are lost and analysis is limited to short samples of breathing cycles. This study presents a data acquisition device for acquiring and monitoring patient ventilation waveform data. Acquired data can be exported to other systems, allowing users to further analyse data and develop further clinically useful parameters. These parameters, together with other ventilatory information, can help personalise and guide MV treatment. The device is designed to be easily replicable, low-cost, and scalable according to the number of patient beds. Validation was carried out by assessing system performance and stability over prolonged periods of 7 days of continuous use. The device provides a platform for future integration of machine-learning or model-based modules, potentially allowing real-time, proactive, patient-specific MV guidance and decision support to improve the quality and productivity of care and outcomes.

Indexed as

Data acquisition deviceMechanical ventilationVentilator waveform data

Identifiers

PMID36117541
PMCPMC9474567
OpenAlexW4294796097

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.