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CompletedNCT03362346Updated Jun 6, 2018

Signal Analysis for Neurocritical Patients

An observational study in Brain Injuries, Acute, sponsored by Far Eastern Memorial Hospital. Completed at 1 site in Taiwan. Open to participants aged 20 Years and older. Per ClinicalTrials.gov, last updated 2018-06-06.

Sponsored by Far Eastern Memorial Hospital · Observational

Study type
Observational
Model
Cohort
Time perspective
Retrospective
Enrollment
156
Ages
20 Years and older
Sex
All
01

Study summary

The project uses big data analysis techniques such as wavelet transform and deep learning to analyze physiological signals from neurocritical patients and build a model to evaluate intracranial condition and to predict neurological outcome. By identification of correlations among these parameters and their trends, we may achieve early detection of anomalies and enhance the ability in judgement of current neurological condition and prediction of prognosis. By continuous input of the past and contemporary data in the ICU, the model will be modified repeatedly and its accuracy improves as the model grows. The model can be used to recognize abnormalities earlier and provide a warning system. Clinicians taking care of neurocritical patients can adjust their treatment policy and evaluate the outcome according to such system.

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Conditions studied

  • Brain Injuries, Acute

Browse trials for

Keywords

  • Wavelet transform
  • Deep learning
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Who can participate

Ages eligible
20 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Neurocritical patients admitted to intensive care unit (ICU), including but not limited to traumatic brain injury, hemorrhagic stroke, ischemic stroke, brain infection, brain tumor and acute hydrocephalus.

Inclusion criteria

  • Age equal to or older than 20 years
  • Neurocritical patients admitted to intensive care unit (ICU), including but not limited to traumatic brain injury, hemorrhagic stroke, ischemic stroke, brain infection, brain tumor and acute hydrocephalus.
  • Patients who have undergone cranial surgery and had intracranial pressure monitor inserted or external ventricular drainage. The central monitor of ICU is able to collect the data continuously

Exclusion criteria

Exclusion Criteria:

  • Age younger than 20 years.
  • Continuous monitoring of intracranial pressure is not feasible.
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Study design

Observational model
Cohort
Time perspective
Retrospective
Enrollment
156 participants (actual)
Patient registry
No

Groups and cohorts

  • Neurocritical patients

    Patients with brain injury from trauma, ischemic stroke, hemorrhage stroke (intracerebral hemorrhage, subarachnoid hemorrhage), brain tumor with increased intracranial pressure, brain infection, hydrocephalus, among others.

    Device: intracranial pressure monitoring

Interventions

  • Deviceintracranial pressure monitoring

    The patients may have either intracranial pressure (ICP) monitor insertion or external ventricular drainage that can be used as ICP monitor.

    Also known as: physiological monitoring

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What researchers measure

Primary outcomes

  1. Neurological status

    Glasgow coma scale/Mortality

    Time frame: Discharge out of the intensive care unit, averaged 2 weeks

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Study locations

1 site
  • Far Eastern Memorial Hospital
    New Taipei City, 200, Taiwan
07

References and documents

Publications

  • Diederik P. Kingma and Jimmy Lei Ba. Adam: A method for stochastic optimization. Conference paper at ICLR 2015.
  • Michael Unser and Akram Aldroubi. (1996 Apr) A review of wavelets in biomedical applications. Proceedings of the IEEE 84(4): 626-638.
  • LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015 May 28;521(7553):436-44. doi: 10.1038/nature14539. PubMed 26017442 ↗
  • Christopher Torrence and Gilbert P. Compo. (1998 Jan) A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 79(1):61-78.
  • Theis, Fabian & Meyer-Base, Anke. (2010). Biomedical Signal Analysis - Contemporary Methods and Applications. Biomedical Signal Analysis: Contemporary Methods and Applications.
  • Min S, Lee B, Yoon S. Deep learning in bioinformatics. Brief Bioinform. 2017 Sep 1;18(5):851-869. doi: 10.1093/bib/bbw068. PubMed 27473064 ↗
  • Yi Mao, Wenlin Chen, Yixin Chen, Chenyang Lu, Marin Kollef, and Thomas Bailey. (2012) An integrated data mining approach to real-time clinical monitoring and deterioration warning. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining Pages 1140-1148. doi>10.1145/2339530.2339709

Individual participant data

Plan to share: No

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Registry details

Key details

Study ID
NCT03362346
Lead sponsor
Far Eastern Memorial Hospital
Responsible party
Yi-Hsin Tsai (Chief of Neurointensive Care Unit, Far Eastern Memorial Hospital) — Principal investigator
First posted
Dec 5, 2017
Start date
Dec 18, 2017
Primary completion
May 24, 2018
Completion
May 31, 2018
Last update
Jun 6, 2018

Study contacts

Yi-Hsin Tsai, M.D.
principal investigator · Far Eastern Memorial Hospital

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Jun 2018. You cannot join it, but the record below documents what was studied.

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