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Another #sensitivity / #specificity thread.
People are mixing up analytical sens/spec with clinical sens/spec. And translate "clinical" sens/spec in a lab-setting to real-world.
This has implications for the discussions we have about the accuracy of a test.
A #dta 🧵
People are mixing up analytical sens/spec with clinical sens/spec. And translate "clinical" sens/spec in a lab-setting to real-world.
This has implications for the discussions we have about the accuracy of a test.
A #dta 🧵
Analytical sensitivity is how much (or how little) of a certain compound can be measured.
E.g. in blood, what is the lowest glucose concentration or lowest concentration of antibodies to be detected?
Analytical specificity is about the absence of cross-reactivity.
E.g. Does my/
E.g. in blood, what is the lowest glucose concentration or lowest concentration of antibodies to be detected?
Analytical specificity is about the absence of cross-reactivity.
E.g. Does my/
Influenza - antigen test remain negative in samples with other viruses?
This does translate, but is not similar to diagnostic accuracy, as assessed in a lab.
If I have 100 samples of which I am certain that they contain virus particles, how many of those test positive?
And/
This does translate, but is not similar to diagnostic accuracy, as assessed in a lab.
If I have 100 samples of which I am certain that they contain virus particles, how many of those test positive?
And/
1/n: On the occasion of current discussions on testing strategies in #COVID19 let's make a short tweetorial on medical decision making (a branch of biomedical cybernetics, which is underestimated but has enormous impact). #cybernetics #biocybernetics #DecisionTheory
2/n: #Sensitivity, also known as "true positive rate" (TPR) is the fraction of the number of diseased subjects with positive test divided by all diseased patients. Since in both numerator and denominator are pure counts it is independent of the prevalence of the disease: 
3/n: Likewise, the true-negative rate (TNR), the ratio of true negatives to the sum of false positives and true negatives, is independent of the prevalence:
Our ELISA validation Breakdown for #SARSCoV2, in short, we validated six (6) ELISAs: spike & RBD IgG, IgM and IgA (check out @cispt2’s summary too!) (1/9) medrxiv.org/content/10.110…
Great ELISA starts with great protein: @domespo @FredNatLab generated two spike and two RBD constructs from different plasmids, and we found that @NIAIDNews VRC spike ectodomain and @SchmidtLabHMS @ragoninstitute RBD were the ideal antigens. (2/9)
Evaluating sensitivity & specificity of spike + RBD double positive, focusing on specificity, showed 0/100 negative controls came back “#seropositive” (Spike+RBD+) for IgG/IgM/IgA. We have since shown on robot w 0/300 for IgG (100% specificity @ 95% CI 98.78% to 100%) (3/9)
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%).
