Smartphone App Bests Clinical Assessment of Blood Flow

MedicalResearch.com Interview with:

Benjamin Hibbert MD PhD FRCPCz Interventional Cardiologist Clinician Scientist and Assistant Professor CAPITAL Research Group Vascular Biology and Experimental Medicine Laboratory University of Ottawa Heart Institute

Dr. Benjamin Hibbert

Benjamin Hibbert MD PhD FRCPCz
Interventional Cardiologist
Clinician Scientist and Assistant Professor
CAPITAL Research Group
Vascular Biology and Experimental Medicine Laboratory
University of Ottawa Heart Institute

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: When we designed the study in 2014 we were routinely using the modified allen’s test (MAT) to screen patients for transradial access for coronary angiography and PCI. We all had iPhones and we started using the HeartRate monitoring application as a photoplethysmograph. Quite quickly we found that using the application was simple, worked well and because we always had our iPhone with us we tended to use it more often. That being said – we wanted to test it in a scientifically rigorous method and thus we elected to perform an RCT to evaluate it’s diagnostic accuracy.

smart app measures blood flowThe current study is the first to use the photoplethysmographic capabilities of smartphones to assess blood flow – in this case in the hand to assess for blockages in arteries before accessing them for a procedure. The hand is supplied by two arteries – the radial artery and the ulnar artery. In many cases in medicine we use the radial artery, whether it be placing a catheter to monitor blood pressure, as a method of getting to the heart for angioplasty and in coronary artery bypass grafting it is removed and used as a bypass to restore blood flow to the heart. In many instances doctors assess the patency of the ulnar artery to decided if they are going to use the radial artery for a procedure – the concept being that if the ulnar is compromised and we use the radial then the hand can develop complications from not enough blood flow. To determine if a patient is eligible doctors would use a bedside physical exam test called the modified Allen’s test in which they occlude both arteries to cause the hand to turn white. They then release pressure on the ulnar letting blood only pass through this vessel to see if the hand turns pink. However, there is a lot of variability in what doctors consider to be abnormal and determining if the test is positive can depend on numerous factors including skin tone, the amount of pressure applied and the size of the vessels. Continue reading

Neural Prosthetic Improved Short Term Memory Coding and Recall

MedicalResearch.com Interview with:

Robert E. Hampson, PhD Professor, Physiology & Pharmacology School of Medicine Wake Forest

Dr. Hampson

Robert E. Hampson, PhD
Professor, Physiology & Pharmacology
School of Medicine
Wake Forest

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: There are many diseases and injuries that affect human memory, and many types of memory deficits, from inability to recall stored memories to the inability to make new memories.  We focused on problems with making new memories, and identifying the brain activity associated with those memories.  We found that we could identify when the brain formed “codes” for new memory, and when those codes were incorrect or faulty.  By identifying what both “strong” and “weak” naturally occurring codes should be, we influence the process to strengthen the weak codes, resulting in better memory.

Continue reading

Single-Dose LipiFlow® Treatment Relieves Dry Eye Symptoms

MedicalResearch.com Interview with:

Dr. Caroline A. Blackie, OD PhD FAAO Medical Director, Dry Eye Johnson & Johnson Vision

Dr. Caroline Blackie

Dr. Caroline A. Blackie, OD PhD FAAO
Medical Director, Dry Eye
Johnson & Johnson Vision

MedicalResearch.com: What is the background for these studies? Would you briefly explain the problem of dry eye, how common it is and why it is difficult to treat? 

Response: Dry eye disease is a condition where the eyelids and/or the tear film are unable to protect the ocular surface from the negative effects of desiccating stress. If left untreated, a vicious cycle ensues resulting in a broad spectrum of sequelae, including ocular discomfort and compromised vision. The result is partial or pervasive reduced quality of life for the individual along with a significant economic burden on our society. Conversely, when the ocular surface is healthy, patients feel better, see better and live better.

Meibomian gland health is essential for ocular surface health. Meibomian glands secrete the oils necessary to protect the ocular surface from the negative effects of desiccating stress. Predictably, meibomian gland dysfunction (MGD) is a leading cause of dry eye disease. MGD is almost always the result of thickened and stagnated gland secretions. These stagnated secretions obstruct and/or limit the flow of functional oil into the tear film. MGD is the most common form of dry eye disease and is also known as evaporative dry eye. While management of dry eye in general can be complex, the management of MGD affords a relatively straightforward approach, which is to improve meibomian gland function by treating obstruction.

Dry eye disease is pretty common – more than 340 million people suffer from it globally. Short-term management of dry eye involves improving signs and symptoms of the condition, including the use of tear supplementation and reducing ocular surface inflammation.

Long-term dry eye management requires that the cause (or causes) of the condition is also diagnosed and treated. That cause is often MGD, and MGD can be successfully managed with LipiFlow®.  Continue reading

Machine Learning Enhances Ability To Predict Survival From Brain Tumors

MedicalResearch.com Interview with:

Lee Cooper, Ph.D. Assistant Professor of Biomedical Informatics Assistant Professor of Biomedical Engineering Emory University School of Medicine - Georgia Institute of Technology

Dr. Cooper

Lee Cooper, Ph.D.
Assistant Professor of Biomedical Informatics
Assistant Professor of Biomedical Engineering
Emory University School of Medicine – Georgia Institute of Technology

MedicalResearch.com: What is the background for this study? What are the main findings? 

Response: Gliomas are a form of brain tumor that are often ultimately fatal, but patients diagnosed with glioma may survive as few as 6 months to 10 or more years. Prognosis is an important determinant in selecting treatment, that can range from simply monitoring the disease to surgical removal followed by radiation treatment and chemotherapy. Recent genomic studies have significantly improved our ability to predict how rapidly a patient’s disease will progress, however a significant part of this determination still relies on the visual microscopic evaluation of the tissues by a neuropathologist. The neuropathologist assigns a grade that is used to further refine the prognosis determined by genomic testing.

We developed a predictive algorithm to perform accurate and repeatable microscopic evaluation of glioma brain tumors. This algorithm learns the relationships between visual patterns presented in the brain tumor tissue removed from a patient brain and the duration of that patient’s survival beyond diagnosis. The algorithm was demonstrated to accurately predict survival, and when combining images of histology with genomics into a single predictive framework, the algorithm was slightly more accurate than models based on the predictions of human pathologists. We were also able to identify that the algorithm learns to recognize some of the same tissue features used by pathologists in evaluating brain tumors, and to appreciate their prognostic relevance. Continue reading

AI Trained Computer Program Can Monitor Health Forums To Detect Adverse Drug Reactions

MedicalResearch.com Interview with:

Kavita Sarin, M.D., Ph.D.

Dr. Sarin

Kavita Sarin, M.D., Ph.D.
Assistant Professor of Dermatology
Stanford University Medical Center

MedicalResearch.com: What is the background for this study? What are the main findings? 

Response: Drug reactions occur in the majority of patients undergoing cancer therapies. Half of serious drug reactions are detected after market approval which can result in painful complications and interruption in therapy. Post-market drug surveillance platforms such as FDA monitoring rely on medical publications and physician reporting and take time to identify trends. We sought to determine if we could identify trends in patient discussions in internet health forums to more rapidly identify chemotherapeutic drug reactions. We chose skin reactions as a proof-of-principle because patients can more easily describe what they see on their skin.

Julia Ransohoff, a medical student, and Azadeh Nikfarham, an informatics postdoctoral fellow trained a computer to recognize when a patient undergoing anti-cancer treatment with PD-1 antagonists or EGFR-inhibitors described a drug reaction in their internet forum posts.

Continue reading

Social Media Does Not Displace Face-to-Face Communication With Family and Friends

MedicalResearch.com Interview with:

Jeffrey A. Hall, Ph.D. Associate Professor The University of Kansas

Dr. Hall

Jeffrey A. Hall, Ph.D.
Associate Professor
The University of Kansas
Relationships and Technology Lab

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: The idea that new forms of media displace our face-to-face relationships with close friends and family is an old idea.  Two decades ago, when the internet experienced a period of rapid growth, the most recent form of the social displacement hypothesis emerged. Studies from that time ended up finding little to no evidence of displacement by the internet.

The main findings of this study focus on displacement by social media.  The first study was conducted with a longitudinal, nationally representative sample of Americans from 2009-2011.  This study found that during a period of rapid social media adoption, there was little to no association between adopting and using social media and direct social contact over the three years of the study.  Furthermore, using more social media did not result in lowered well-being.

The second study in this paper looked at data from 2015, and found that using social media in a day had little bearing on who people communicated with and how they communicated. That is, passive social media use did not seem to displaced face-to-face communication with close friends and family.  Continue reading

Decision Aids Can Help Heart Failure Patients Determine If They Want an LVAD

MedicalResearch.com Interview with:

A left ventricular assist device (LVAD) pumping blood from the left ventricle to the aorta, connected to an externally worn control unit and battery pack. Wikipedia image

A left ventricular assist device (LVAD) pumping blood from the left ventricle to the aorta, connected to an externally worn control unit and battery pack.
Wikipedia image

Larry A. Allen, MD, MHS
Associate Professor, Medicine
Associate Head for Clinical Affairs, Cardiology
Medical Director, Advanced Heart Failure
Aurora, CO 80045

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Deciding whether or not to get a left ventricular assist device (LVAD) is one of the most challenging medical decisions created by modern medicine.

LVADs improve overall survival but also come with serious risks and lifestyle changes. Particularly for older patients with multiple medical problems, this is a complex choice.

Our research group at the University of Colorado spent years systematically developing unbiased pamphlet and video decision aids for patients and caregivers. We also developed a clinician-directed decision support training for LVAD program staff. The DECIDE-LVAD trial studied the implementation and effectiveness of this decision support intervention with patients and their caregivers in 6 hospitals in the U.S. When compared to previously used education materials, the decision aids appeared to improve patients’ decision quality and lowered the total number of patients getting LVADs.

Continue reading

Machines Can Be Taught Natural Language Processing To Read Radiology Reports

MedicalResearch.com Interview with:

Eric Karl Oermann, MD Instructor Department of Neurosurgery Mount Sinai Health System New York, New York 10029 

Dr. Oermann

Eric Karl Oermann, MD
Instructor
Department of Neurosurgery
Mount Sinai Health System
New York, New York 10029 

MedicalResearch.com: What is the background for this study? What are the main findings? 

Response: Supervised machine learning requires data consisting of features and labels. In order to do machine learning with medical imaging, we need ways of obtaining labels, and one promising means of doing so is by utilizing natural language processing (NLP) to extract labels from physician’s descriptions of the images (typically contained in reports).

Our main finding was that (1) the language employed in Radiology reports is simpler than normal day-to-day language, and (2) that we can build NLP models that obtain excellent results at extracting labels when compared to manually extracted labels from physicians.  Continue reading

Arm Cycling Can Improve Walking After Stroke

MedicalResearch.com Interview with

Paul Zehr PhD Professor & Director Centre for Biomedical Research, Rehabilitation Neuroscience Laboratory, McKinnon Division of Medical Sciences Exercise Science, Physical & Health Education International Collaboration on Repair Discoveries (ICORD)| Affiliate, Division of Neurology, Department of Medicine, UBC

Dr. Zehr

E. Paul Zehr PhD
Professor & Director
Centre for Biomedical Research,
Rehabilitation Neuroscience Laboratory, McKinnon
Division of Medical Sciences
Exercise Science, Physical & Health Education
International Collaboration on Repair Discoveries (ICORD)|
Affiliate, Division of Neurology, Department of Medicine, UBC

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: For many years we explored the role of the spinal cord in regulating rhythmic arm and leg movements like we do during walking, running and swimming.  Although we humans tend to move and locomote around on our two legs as bipeds, we are basically quadrupeds in terms of how our nervous system controls our limbs during walking. We have an extensive network of brain and spinal cord connections that help coordinate our limbs while we move. A lot of our work showed that using the arms rhythmically, like during arm cycling, strongly affected the activity of the spinal cord controlling leg muscles. Getting the spinal cord for leg muscles more coordinated and activated is a major goal of rehabilitation  of walking after neurotrauma so we wanted to see if training the arms could help with this. This is particularly important because a lot of the time, the arms are not engaged at all in rehabilitation training for the legs.

We found that after only 5 weeks of arm cycling (3 x 30 minutes each week), neural excitability, strength, and leg function were increased along with enhanced clinical tests of balance and walking ability.

Continue reading

‘Liver-on-a-Chip’ Technology Can Accurately Mimic Hepatitis B Infection

MedicalResearch.com Interview with:

Primary hepatocytes grown in 3D microfluidic “liver-on-a-chip” platform following infection with hepatitis B virus. Credit: Marcus Dorner/Imperial College London

Primary hepatocytes grown in 3D microfluidic “liver-on-a-chip” platform following infection with hepatitis B virus. Credit: Marcus Dorner/Imperial College London

Marcus Dorner, PhD
Non-Clinical Senior Lecturer in Immunology
Wellcome Trust Investigator
Imperial College London
Department of Medicine, Section of Virology
School of Medicine
London United Kingdom 

MedicalResearch.com: What is the background for this study? What are the main findings?

Response:  Hepatitis B virus (HBV) infection globally affects over 250 million people and is currently not curable. This infection can lead to liver cirrhosis and liver cancer and is among the leading causes for liver transplantation. Unfortunately, HBV is among the most difficult viruses to study in the laboratory, since model systems are not very good at recapitulating what happens in infected humans.

We have just described the first model to effectively change this. Using an artificial “Liver-on-a-Chip”, we have developed a tool, which can potentially revolutionise how we study viral infections by merging the study of viruses with tissue engineering. This model is over 10,000-fold more susceptible to HBV infection and accurately mimics, what happens in an infected patient. This can now be utilised to develop novel and potentially curative therapies, which would benefit millions of people currently living with chronic HBV infection.  Continue reading