Warren symposium follows legacy of geneticist giant

If we want to understand how the brain creates memories, and how genetic disorders distort the brain’s machinery, then the fragile X gene is an ideal place to start. That’s why the Stephen T. Warren Memorial Symposium, taking place November 28-29 at Emory, will be a significant event for those interested in neuroscience and genetics. Stephen T. Warren, 1953-2021 Warren, the founding chair of Emory’s Department of Human Genetics, led an international team that discovered Read more

Mutations in V-ATPase proton pump implicated in epilepsy syndrome

Why and how disrupting V-ATPase function leads to epilepsy, researchers are just starting to figure Read more

Tracing the start of COVID-19 in GA

At a time when COVID-19 appears to be receding in much of Georgia, it’s worth revisiting the start of the pandemic in early 2020. Emory virologist Anne Piantadosi and colleagues have a paper in Viral Evolution on the earliest SARS-CoV-2 genetic sequences detected in Georgia. Analyzing relationships between those virus sequences and samples from other states and countries can give us an idea about where the first COVID-19 infections in Georgia came from. We can draw Read more
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Shamim Nemati

Predict the future of critical care in #STATMadness

Emory is participating in STAT Madness, a “March Madness” style bracket competition featuring biomedical research advances instead of basketball teams. Universities or research institutes nominate their champions, research papers that were published the previous year. It’s like “Battle of the Bands.” Whoever gets the loudest — or most numerous — cheers wins.

Please check out all 64 entries, follow the 2019 STAT Madness bracket and vote here:
https://www.statnews.com/feature/stat-madness/bracket/

Emory’s entry for 2019:
It’s like the “precogs” who predict crime in the movie Minority Report, but for sepsis, the deadly response to infection. Shamim Nemati and colleagues have been exploring ways to analyze vital signs in ICU patients and predict sepsis, hours before clinical staff might otherwise notice.

As landmark clinical studies have documented, every hour of delay in giving someone with sepsis antibiotics increases their risk of mortality. So detecting sepsis as early as possible could save thousands of lives. Many hospitals have developed “sniffer” systems that monitor patients for sepsis, but this algorithm tries to spot problems way before they become apparent.

As published in 2018 in Critical Care Medicine, the algorithm can predict sepsis onset—with some false alarms—four, eight, even 12 hours ahead of time. No algorithm is going to be perfect, but it was better than any other previous sepsis predictor. The technology is headed for additional testing and evaluation at several medical centers, as part of a project supported by the federal Biomedical Advanced Research and Development Authority (BARDA).

You can fill out a whole bracket or you can just vote for Emory. The contest will last several rounds. The first round began on Monday, March 4, and lasts until the end of the week. Before 10 am Eastern time Monday morning, there were already more than 5,000 brackets entered!

If Emory advances, then people will be able to continue voting for us starting on Friday. Emory’s first opponent is a regional rival, Vanderbilt University School of Medicine. We are on the upper left side of the bracket.

STAT News is a Boston-based news organization covering biomedical research, pharma and biotech. If you feel like it, please share on social media using the hashtag #statmadness.

Posted on March 4, 2019 by Quinn Eastman in Uncategorized Leave a comment

Life-saving predictions from the ICU

It’s similar to the “precogs” who predict crime in the movie Minority Report, but for sepsis, the deadly response to infection. That’s how Tim Buchman, director of the Emory Critical Care Center, described an emerging effort to detect and ward off sepsis in ICU patients hours before it starts to make their vital signs go haywire.

As landmark clinical studies have documented, every hour of delay in giving someone with sepsis antibiotics increases their risk of mortality. So detecting sepsis as early as possible could save lives. Many hospitals have developed “sniffer” systems that monitor patients for sepsis risk. See our 2016 feature in Emory Medicine for more details.

What Shamim Nemati and his colleagues, including bioinformatics chair Gari Clifford, have been exploring is more sophisticated. A vastly simplified way to summarize it is: if someone has a disorderly heart rate and blood pressure, those changes can be an early indicator of sepsis.* It requires continuous monitoring – not just once an hour. But in the ICU, this can be done. The algorithm uses 65 indicators, such as respiration, temperature, and oxygen levels — not only heart rate and blood pressure. See below.

Example patient graph. Green = SOFA score. Purple = Artificial Intelligence Sepsis Expert (AISE) score. Red = official definition of sepsis. Blue = antibiotics. Black + red = cultures.    Around 4 pm on December 20, roughly 8 hr prior to any change in the SOFA score, the AISE score starts to increase. The top contributing factors were slight changes in heart rate, respiration, and temperature, given that the patient had surgery in the past 12hr with a contaminated wound and was on a mechanical ventilator. Close to midnight on December 21, other factors show abnormal changes. Five hours later, the patient met the Sepsis-3 definition of sepsis.

As recently published in the journal Critical Care Medicine, Nemati’s algorithm can predict sepsis onset – with some false alarms – 4, 8 even 12 hours ahead of time. No predictor is going to be perfect, Nemati says. The paper lays out specificity, sensitivity and accuracy under various timelines. They get to an AUROC (area under receiving operating characteristic) performance of 0.83 to 0.85, which this explainer web site rates as good (B), and is better than any other previous sepsis predictor. Read more

Posted on January 11, 2018 by Quinn Eastman in Heart, Immunology Leave a comment