Discover and read the best of Twitter Threads about #Diagnostics

Most recents (5)

Daily Bookmarks to GAVNet 5/18/2020-2

Interpreting Diagnostic Tests for SARS-CoV-2 | JAMA | JAMA Network

jamanetwork.com/journals/jama/…
#testing #coronavirus #diagnostics
Tools for Culture Design: Toward a Science of Social Change?

slideshare.net/joebrewer31/to…
#tools #culture #design
Why this crisis is a turning point in history

newstatesman.com/international/…
#TurningPoint #History #crisis
Read 8 tweets
21 WAYS TO SPIN RESULTS FROM A COVID DIAGNOSTIC TEST ACCURACY (morning thoughts whilst walking the dog - please add others I've missed). I'm putting this out to help us critique the "number theatre" being thrown at us.
#diagnostics #COVID19 @deb_cohen @MHRAgovuk @drhelmac
1/22
#1 Use a small sample size (and never report how big it isn’t). Use phrases like"we detected all cases" the test is "100% accurate" without mentioning it is only from 29 samples.
2/22
#2 Talk about the total sample size when interpreting results about sensitivity (especially if you have tested 5000 blood donors to estimate specificity and only 29 to estimate sensitivity)
3/22
Read 23 tweets
Thoughts on upcoming #COVID19 #serology tests:
This is actually quite a challenge! (#Diagnostics often involve a lot of complexities). There is a lot of pressure to roll these tests out, but they need to perform well, or we do more harm than good. #MicroRounds (A thread)
WHY we need these soon:
1. Contact tracing.
2. Can be used to test if a vaccine is working during a clinical trial (70 of them ongoing right now, I believe)
3. Inform public policy makers about rate of asymptomatic cases + previous infections/exposures =informed decision making
How is developing a #PCR different than developing a #serology test?
1. #PCR tests detect viral RNA/DNA (in this case RNA) and can be pretty straight-forward in terms of development
2. #Serology relies on knowing about the #SARSCoV2 structure and how the human body responds.
Read 13 tweets
Closing the loop on #Diagnostics #Tweetorial with example #AppleWatch #AFib #Screening. From a company website: "Atrial fibrillation is a silent killer. The heart arrhythmia causes more life-threatening strokes than any other chronic condition, and will affect 1 in 4 of us."
"But the sad fact is that atrial fibrillation often goes unnoticed: It is estimated that 40% of those who experience the heart condition are completely unaware of it."
Using #AppleWatch technology and #DeepLearning #AI #ML, a device algorithm can reportedly detect atrial fibrillation with high accuracy (c-statistic 93%).
Read 44 tweets
#Tweetorial on #Diagnostics and #Screening interpretation.
An otherwise healthy 40 year old woman comes to you after reading on the internet about a terrible disease that one in a thousand women get, and a highly accurate test that can save her life.
The test is over 99% accurate in people with the disease. For those without disease, the test is only wrong 5% of the time.

You order this test and it comes back positive. The woman anxiously asks you, do I have the disease? What is the chance this woman has the disease?
Assuming they weren't immediately fooled by the "test is only wrong 5 % of the time," most I've asked correctly recognize the stats provided are Sensitivity = 99% and Specificity = 95%, and that the objective is to determine the Positive Predictive Value.
Read 21 tweets

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