Using a tablet screening app could prove to be an effective method to aid in the effort to reduce the incidence of avoidable blindness in populations at high-risk for glaucoma with limited access to health care, according to a study released today at AAO 2014, the 118th annual meeting of the American Academy of Ophthalmology. In this study, researchers from the University of Iowa, the University of Maryland, Johns Hopkins University, the University of Michigan and the Tilganga Eye Institute in Nepal used a free peripheral vision assessment app to screen approximately 200 patients in Nepal for glaucoma using an iPad. The results show promise for screening populations that have limited or no access to traditional eye care and certain ethnic groups that have a high risk of developing the disease.
Glaucoma is the second leading cause of blindness worldwide, affecting more than 60.5 million people. The disease can be effectively treated; however, it generally does not present symptoms in its early stages, resulting in many patients being unaware that they suffer from the condition until it progresses to later stages. Early diagnosis can easily be achieved through a routine examination from an ophthalmologist or an optometrist.
In order to determine if a screening test using mobile technology could be effectively administered to communities outside of a traditional clinical setting, the research team used the Visual Fields Easy app, which simulates a visual field test on an iPad (1st Generation), to screen more than 400 eyes for glaucoma.
Approximately half of the eyes screened were healthy

In the first year after the Accreditation Council for Graduate Medical Education (ACGME) reduced the number of continuous hours that residents can work, there was no change in the rate of death or readmission among hospitalized Medicare patients, according to a new study. The study was led by researchers at the Perelman School of Medicine at the University of Pennsylvania and The Children

Imagine this scenario: You’ve been feeling persistently blue lately, so you pull out your phone. Instead of asking Siri to tell you a joke, though, you open an app that records you simply talking about your day. A few hours later, your therapist sends you a message asking if you’d like to meet.

A program like this one that analyses your speech and uses it to gain information about your mental health could soon be feasible, thanks in part to research from the University of Maryland showing that certain vocal features change as patients’ feelings of depression worsen.

The research is part of an interdisciplinary initiative at the University of Maryland to engineer patient-focused mental health monitoring systems. Rather than relying solely on patients’ self-reports, these systems could monitor both physical and psychological symptoms of mental illness on a regular basis and provide both patients and their mental health providers with feedback about their status.

To conduct a quantitative experiment on the vocal characteristics of depression acoustician Carol Espy-Wilson and her colleagues repurposed a dataset collected from a 2007 study from an unaffiliated lab also investigating the relationship between depression and speech patterns. The earlier study assessed patients’ depression levels each week using the Hamilton Depression Scale (a standard clinical evaluation tool to measure the severity of depression) and then recorded them speaking freely about their day.

The University of Maryland researchers used data from six patients who, over the six-week course of the previous study, had registered as depressed some weeks and not depressed other weeks. They compared these patients’ Hamilton scores with their speech patterns each week, and found a correlation between depression and certain acoustic properties.

When patients’ feelings of depression were worst, their speech tended to be breathier and slower. The team also found increases in jitter and shimmer, two measures of acoustic disturbance that measure the frequency and amplitude variation of the sound, respectively. Speech high in jitter and shimmer tends to sound hoarse or rough.

The researchers plan to repeat the study in a larger population, this time comparing speech patterns in individuals with no history of mental illness to those with depression to create an acoustic profile of depression-typical speech. A phone app could use this information to analyse patients’ speech, identify acoustic signatures of depression and provide feedback and support.

Espy-Wilson hopes the interactive technology will appeal to teens and young adults, a particularly vulnerable group for mental health problems. ‘Their emotions are all over the place during this time, and that’s when they’re really at risk for depression. We have to reach out and figure out a way to help kids in that stage,’ she said. EurekAlert

Imaging tests like mammograms or CT scans can detect tumours, but figuring out whether a growth is or isn

A new study from Massachusetts General Hospital (MGH) investigators has found, for the first time, evidence of neuroinflammation in key regions of the brains of patients with chronic pain.  By showing that levels of an inflammation-linked protein are elevated in regions known to be involved in the transmission of pain, the study paves the way for the exploration of potential new treatment strategies and identifies a possible way around one of the most frustrating limitations in the study and treatment of chronic pain