5G and Me: And the Golden Hour

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What is the “Golden Hour”?

The Golden Hour is within the first hours of the Stroke or acute CHF or MI. Every minute that the blood flow is not restored in the brain (where it is lost), nearly two million additional nerve cells die. Therefore, it becomes imperative for the patients with stroke to get to necessarily equipped care locations.

In this blog we will discuss how 5G technology has a profound effect on the golden hour and how this technology can save lives.

Who does Stroke and CHF effect?

We just celebrated a grim annual event — the World Stroke Day on 29th October. Combined, Stroke, CHF (Congestive Heart Failure) and Myocardial Infarctions (MI) are the leading causes of death and disability in the world.

A “Stroke” happens when the blood supply to a part of the brain is cut off — without blood, these brain cells get damaged and perish. Its severity depends on which part of the brain is affected and can affect a person’s mobility, speech, and the ability to think and feel.

Congestive Heart Failure and Myocardial Infarction are chronic conditions where the heart operates less efficiently than normal. The circulatory system cannot carry oxygen and other nutrients to the body, causing the heart to stretch or stiffen, causing the kidneys to retain more fluid and salts.

Globally, 1 in 4 people over the age of 25 are at risk for stroke during their lifetime In the US, the incidence of and deaths from Heart Disease has increased within the past 10 years (especially in rural areas). It is the No. 1 killer in the US (and almost all other countries in the world):

The Current Problem:

Since most care is moving away from the hospital and to the home (or remote clinic), Point-of-Care Imaging (PoCI) will become one of the most important diagnostic areas of the future.

Even though Head CT (computed tomography) is the standard method to determine stroke and identifies a wide range of abnormalities, ultrasound is slowly becoming the go-to modality for remote imaging, especially for carotid atherosclerosis, especially using Transcranial Color-Doppler imaging (TCDI). Color Doppler imaging is also advantageous for CHF and MI assessment at the point of care.

Current ambulance platforms are modern marvels with some of the latest instrumentation on-board. However, from a data perspective, they do not utilize the knowledge and imaging available at their hub locations (usually the hospital). Most current techniques for remote ultrasound (tele-sonography) use asynchronous transmission which have incurred significant transmission delays.

Reliability has been a central theme as variable levels of image degradation have been reported, which resulted in reduced sensitivity and specificity. Outcomes including image quality and transmission reliability suggest it may be problematic to transmit real time images from an ambulance. In situations like this, every minute matters so it has to be both accurate and in real time.

The Solution 5G Brings:

The connected ambulance 5G network slicing concepts were demonstrated at the Mobile World Congress (MWC) in Barcelona, Spain in Feb 2019 by Dell EMC Cork Centre of Excellence (CoE).

Network slicing is a type of virtual networking architecture similar to software-defined networking (SDN) and network functions virtualization (NFV) whose goal is software-based network automation. This technology allows the creation of multiple virtual networks on a shared physical infrastructure.

There are many algorithms that measure and score Stroke and CHF: Emergency Heart Failure Mortality Risk Grade (EHFMRG), the NIH Stroke Scale (NIHSS), Cincinnati Prehospital Stroke Scale (CPSS), Los Angeles Pre-hospital Stroke Scale (LAPSS) and Face, Arm, Speech Time Test (FAST), etc.

The goal for the future of connected care in emergencies would be to identify the conditions for Stroke, CHF & MI; measure and score at site, predictively collect Electronic Medical Record (EMR) metadata in conjunction with specific image studies via DICOM (Digital Imaging and Communications in Medicine) and combine this with the metadata from disease-specific epidemiological studies for that geographic region — all within the “golden hour”. This combinatorial analysis at the “point of care” is the future and can prevent disability and death at scale — especially since not all the ambulance visits are emergencies.

Dell Technologies is leading the path on the journey to 5G and partnering with Telcos as their build their networks. We are committed to bringing this technology to the market because we believe in the life-saving capabilities of 5G.

  BIBLIOGRAPHY:

  • The Global Burden of Disease 2016 Lifetime Risk of Stroke Collaborators, “Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990-2016″, NEJM (Dec 2018),https://www.nejm.org/doi/full/10.1056/NEJMoa1804492
  • The US Centers for Disease Control (CDC). “Heart Disease and Stroke Maps”, https://www.cdc.gov/dhdsp/maps/quick-maps/index.htm (Last viewed 31Oct2019)
  • Marsh-Feiley G, Eadie L, Wilson P (2018), “Telesonography in emergency medicine: A systematic review.”, PLoS ONE 13(5): e0194840, https://doi.org/10.1371/journal.pone.0194840
  • Bøtker et al., “The role of point of care ultrasound in prehospital critical care: a systematic review.”, Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, (2018) 26:51, https://doi.org/10.1186/s13049-018-0518-x
  • Ketelaars et al. “ABCDE of prehospital ultrasonography: a narrative review.”, Critical Ultrasound J (2018) 10:17, https://doi.org/10.1186/s13089-018-0099-y
  • Saxena et al., “Imaging modalities to diagnose carotid artery stenosis: progress and prospect.”, BioMed Eng OnLine, (2019) 18:66, https://doi.org/10.1186/s12938-019-0685-7
  • Herzberg et al., “Prehospital stroke diagnostics based on neurological examination and transcranial ultrasound.”, Critical Ultrasound Journal 2014, 6:3, http://www.criticalultrasoundjournal.com/content/6/1/3
  • Marsh-Feiley G, et al., “Paramedic and physician perspectives on the potential use of remotely supported prehospital ultrasound.”, Rural and Remote Health 2018; 18: 4574. https://doi.org/10.22605/RRH4574
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