When using the prevalence to calculate PPV and NPV, we need to take into account the fact that the patient in question may have symptoms, so the prevalence of the disease among a patient with those symptoms is definitely higher than the prevalence in the population. People seem confused about that. The PPV and NPV depends on how typical the patient presentation is. It will be different in a typical patient, and atypical patient, and a contact of a positive patient, than it is in a member of the population without symptoms.
Doyou know why 4 states, NY and NJ the Governors actually sent COVID19 patients to nursing homes? Why would anyone send COVID19 patients to nursing homes when there were plenty of beds - like in NY that ship in the harbor over 1000 beds that was rarely used?? And in NJ they had tents set up and was plenty of room? Would appreciate your expert comments.
They did that too in my country - UK. It's as if they want the elderly to died. Maybe they want their pensions, tax credit etc...... It all doesn't make sense otherwise
That's horrific!!!!! I am an Australian RN that works casual nights in aged care. In one facility I was the only qualified nurse (ie. other than unskilled carers) for 214 residents. I refused to go back to that facility, but I regularly am the only nurse on duty for 100 residents. I was horrified that in Australia, when an aged care facility had Covid-19 +ve residents, there was no increase in either nurses or carers, resulting in cross contamination +++, but to actually think of sending Covid-19 patients into aged care is bordering criminal!
I have been sent home from nursing home/post hospital rehab after 10 days (Medicare/Medicaid) with pneumonia, and has taken me 18 mos (with constant dr appts, and overnight hospitalizatons) because of underlying copd and chf, to get well. Now the same thing has happened to a 92 yr old relative who suffered a broken hip. Discharged with numerous issues, and most likely will have to go back to a va place, with many covid cases.
Question: On the CDC website it shows the daily to date fatalities COVID19 but then when one goes to their other "category" page, entitled COVID19 Provisional Deaths by Week - CDC breaks into categories: pneumonia, influenza and COVID19. They explain there is a 7 day delay as the totals for one day, they take these figures and break out into groups. My question: I have been plotting these statistics since March, and the general count is like this: whatever the total that day reported, take 20K to 25K from that to get to the actual total COVID19 as in their COVID1`9 Category on the Provisional Death COVID19 by Week page??? How I interpret the 100K today fatalities, actual would be more 75 - 80K/ Just confused on these numbers. Hope future video you can explain these differences. Thank you
Dr. Langelier - would love his comment on Israel now in human trials for DNA type of vaccine - neutralize the protein spike on COVID19 - compared to traditional RNA vaccine.
73% Patients latin - any relationship of low levels Vit D??? Excellent you prone your patients - unlike what many hospitals in NYC did not leading to more lung damage
Hi I'm lost on the slide that appears at 1 hour 18 minutes and 11 seconds. can anyone explain this better to me? Or is there a link to the source location?
It means that you don't have antibodies right after the infection. Antibodies can take 20 days or more to develop and it's unclear whether they provide immunity to covid and for how long.
Hi, The slide you ask about appears to be a modified excerpt from Figure 1B (middle row) in a manuscript released online but not (yet) peer-reviewed: www.medrxiv.org/content/10.1101/2020.04.25.20074856v2.full.pdf+html My take is that this particular slide in Chaz's presentation addresses the question: Once infected with SARS-CoV-2 and experiencing symptom onset, how long does it take to detect antibodies (that is, for a serologic test to "turn" positive? The take home message from this slide (and study): most symptomatic infections have detectable levels of IgG antibody when tested at time points greater than 3 weeks post onset of symptoms (to know exactly how many days you'll need to look at the paper online but it would be incorrect to state "by 3 weeks" since that is not what is presented in this slide). There is some (expected) performance variability noted among manufacturers' kits. ------- Background The slide presents results of anti-SARS-CoV-2 IgG antibody testing. This test is performed on blood and is intended to detect past - not current - infection with SARS-CoV-2. (It is not a test for present infection: for virus in saliva or nasal swab specimens, for example. Rather, it's a test for immune response proteins that indicate prior infection with the virus.) It takes time for your body to recognize viral infection and to respond by producing antibodies and further, to produce these proteins in sufficient levels to be detected in blood using a test kit. The important question Chaz tries to address here is: just how long (measured in days following initial onset of symptoms)? Data Presented in the Slide To orient yourself to the slide, first review the labels: left to right across the top of the first three frames. Those reflect time (measured in days) since first onset of reported symptom, grouped into 5-day frames (1-5 days post onset of symptoms, 6-10 days post, .... >20 days post). The pattern to first examine is across FRAMES (not the dots within each). You'll see that in general, among ten manufacturer tests examined, there is a pattern of increasingly positive results over time so that >20 days (at some point greater than 3 weeks post symptoms onset), the vast majority (82-100%) of patient specimens tested have detectable levels of IgG antibodies - regardless which of the 10 manufacturer test kits are used. Prior to 3 weeks, antibodies are not routinely detected (they are not yet formed or in levels still too low to detect): when tested just 1-5 days post onset of symptoms, only about 1 in 4 patients have detectable IgG antibodies; when tested 6-10 days post symptoms, only about 1 in 2 patients have detectable IgG antibodies, regardless the manufacturer kit used. And again, (at some point) more than 3 weeks post onset of symptoms, most patients tested have detectable levels of IgG antibodies, regardless the specific manufacturer test kit used. The second thing you now may wish to examine in the slide is variability in performance among manufacturers' kits. To examine this, look within a given frame to compare the 10 different kits to see which have higher percentages testing positive by a specific time frame (before 6 days, before 11 days, some time greater than 3 weeks post symptom onset). The dots provide specific percentages of patient specimens that are positive for IgG antibodies for each of ten kits studied. There is no intrinsic interest in patterns left to right within frames since the dots aren't arranged other than alphabetically by manufacturer's name. The vertical bars above and below each dot present 95% confidence intervals around point estimates. Finally, the fourth frame in this slide presents completely different but complementary data.The fourth frame shows results when testing a wholly different group of people: folks NOT infected with SARS-CoV-2. So the label across the top is no longer time since symptom onset but rather "Pre-COVID-19". It's very important to note in this fourth frame that the vertical axis label differs. It is no longer "Sensitivity (%)" but rather "Specificity (%)"; the scale is changed too, from a range 0-100% to 70-100%. This change of label means that - unlike the first three frames presented in this slide that showed percentage of tested specimens that are positive, this frame presents the percentage of (uninfected patient) specimens that are NEGATIVE. And what you'd like to see of course, is that for each of the ten manufacturer kits studied, 100% of specimens from these uninfected patients do indeed test negative. That's not the case; some false positives are expected and observed (the reasons for false positive antibody tests will undoubtedly be the subject of ongoing additional study). Caveats This is an area of very active, ongoing research. Updates in the coming weeks and months are warranted, of course. These findings need to be confirmed by multiple studies in different patient populations (especially the very relevant and large percentage of infected people who don't present in clinics with symptoms). Nothing in this slide addresses whether these antibodies are neutralizing antibodies that effectively control infection (perhaps the online paper says all of these patients tested ultimately died). Nothing in this slide addresses whether these IgG antibodies detected confer immunity and protect from subsequent SARS-CoV-2 reinfection. Nothing in this slide addresses whether patients with these antibodies remain infectious to others or for how long. Nothing in this slide suggests how long such antibodies persist and at what level. Fine Print Chaz's slide incorporates some changes to the original Figure 2B in the online manuscript. These changes most likely are intended to improve clarity of a necessarily fast-paced presentation to a broad audience. Have one look at the original Figure 2B and you'll readily appreciate his effort! (1) The label on the vertical axis has in the first three frames in this slide was changed from the original Figure 1B middle row: from "Positive (%)" IgG to "Sensitivity (%)". This reflects expert opinion and improves clarity. (2) You may have noted the time frame omission in the slide presented here. Not represented: 11-20 days (only shown are 0-5 days, 6-10 days, ?, ?, >20 days); Chaz chose to delete two original frames from Figure 2B middle row, (those corresponding to 11-15 and 16-20 days). Again, I presume he did this to simplify and improve clarity. Hopes this helps and that I've not made too many typos or errors!
See here: www.medrxiv.org/content/10.1101/2020.04.25.20074856v2 , Figure 1 B in the end pages . Alex Marson also covers it here: th-cam.com/video/n3mtPC6V408/w-d-xo.html . The chart shows performance of a number of antibody assay tests identified by manufacturer's name. The three plots to the left show sensitivity averages across time windows in days after patient-reported symptom onset. (All samples were confirmed to be SARS-CoV-2 positive via RT-PCR.) This is a sensitivity metric -- it tells how well each test detects antibodies for someone who is known to have been infected. The plot to the right shows percentage negative test result for samples taken from before SARS-CoV-2 started spreading. It is a specificity metric. The right side gives an indication of false negatives. The left side gives an indication of false positives.
It seems like someone needs to make you aware that many older people aren't being bad if they aren't staying home. Social security only pays a loto f us $750 a month, what are you thinking. We go to work!
At the initial stage of corona virous sign while taking nutritious food eat two Murunga seeds after food every time and drink a cup of water for about 20 days.It may help you . RABINDRA
I hear so much about asymptomatic but I have yet to see a single person who has had their vital signs monitored (meaning carefully measured), at least daily, from BEFORE infection through to the diagnosis. I've been looking for almost three months and not a single data point. If anyone knows of a case, please comment to me. Thanks.
Thank you all for your work in elder care. You're highly appreciated.
When using the prevalence to calculate PPV and NPV, we need to take into account the fact that the patient in question may have symptoms, so the prevalence of the disease among a patient with those symptoms is definitely higher than the prevalence in the population. People seem confused about that. The PPV and NPV depends on how typical the patient presentation is. It will be different in a typical patient, and atypical patient, and a contact of a positive patient, than it is in a member of the population without symptoms.
In France it is the kids responsibility to take care of their parents by law. SO your point is well taken.
Doyou know why 4 states, NY and NJ the Governors actually sent COVID19 patients to nursing homes? Why would anyone send COVID19 patients to nursing homes when there were plenty of beds - like in NY that ship in the harbor over 1000 beds that was rarely used?? And in NJ they had tents set up and was plenty of room? Would appreciate your expert comments.
They did that too in my country - UK. It's as if they want the elderly to died. Maybe they want their pensions, tax credit etc...... It all doesn't make sense otherwise
That's horrific!!!!! I am an Australian RN that works casual nights in aged care. In one facility I was the only qualified nurse (ie. other than unskilled carers) for 214 residents. I refused to go back to that facility, but I regularly am the only nurse on duty for 100 residents. I was horrified that in Australia, when an aged care facility had Covid-19 +ve residents, there was no increase in either nurses or carers, resulting in cross contamination +++, but to actually think of sending Covid-19 patients into aged care is bordering criminal!
I have been sent home from nursing home/post hospital rehab after 10 days (Medicare/Medicaid) with pneumonia, and has taken me 18 mos (with constant dr appts, and overnight hospitalizatons) because of underlying copd and chf, to get well. Now the same thing has happened to a 92 yr old relative who suffered a broken hip. Discharged with numerous issues, and most likely will have to go back to a va place, with many covid cases.
Question: On the CDC website it shows the daily to date fatalities COVID19 but then when one goes to their other "category" page, entitled COVID19 Provisional Deaths by Week - CDC breaks into categories: pneumonia, influenza and COVID19. They explain there is a 7 day delay as the totals for one day, they take these figures and break out into groups. My question: I have been plotting these statistics since March, and the general count is like this: whatever the total that day reported, take 20K to 25K from that to get to the actual total COVID19 as in their COVID1`9 Category on the Provisional Death COVID19 by Week page??? How I interpret the 100K today fatalities, actual would be more 75 - 80K/ Just confused on these numbers. Hope future video you can explain these differences. Thank you
Thank you. Following your work with interest from the UK.
Dr. Langelier - would love his comment on Israel now in human trials for DNA type of vaccine - neutralize the protein spike on COVID19 - compared to traditional RNA vaccine.
Medically patented 💰 use of 10130701. Bill Gates bribe 💉🐑💰. 🙄⚕️Non consent to be murdered
Brillant idea - IV poles outside room
Must use an awful lot of extension tubing:)
73% Patients latin - any relationship of low levels Vit D??? Excellent you prone your patients - unlike what many hospitals in NYC did not leading to more lung damage
And in general those who have the money to afford the best care really don't want to pay for that care for those who can't afford it.
Thankyou good info
Hi I'm lost on the slide that appears at 1 hour 18 minutes and 11 seconds. can anyone explain this better to me? Or is there a link to the source location?
It means that you don't have antibodies right after the infection. Antibodies can take 20 days or more to develop and it's unclear whether they provide immunity to covid and for how long.
Try this:
www.medrxiv.org/content/10.1101/2020.04.25.20074856v1.full.pdf
Hi,
The slide you ask about appears to be a modified excerpt from Figure 1B (middle row) in a manuscript released online but not (yet) peer-reviewed:
www.medrxiv.org/content/10.1101/2020.04.25.20074856v2.full.pdf+html
My take is that this particular slide in Chaz's presentation addresses the question: Once infected with SARS-CoV-2 and experiencing symptom onset, how long does it take to detect antibodies (that is, for a serologic test to "turn" positive?
The take home message from this slide (and study): most symptomatic infections have detectable levels of IgG antibody when tested at time points greater than 3 weeks post onset of symptoms (to know exactly how many days you'll need to look at the paper online but it would be incorrect to state "by 3 weeks" since that is not what is presented in this slide). There is some (expected) performance variability noted among manufacturers' kits.
-------
Background
The slide presents results of anti-SARS-CoV-2 IgG antibody testing. This test is performed on blood and is intended to detect past - not current - infection with SARS-CoV-2. (It is not a test for present infection: for virus in saliva or nasal swab specimens, for example. Rather, it's a test for immune response proteins that indicate prior infection with the virus.)
It takes time for your body to recognize viral infection and to respond by producing antibodies and further, to produce these proteins in sufficient levels to be detected in blood using a test kit. The important question Chaz tries to address here is: just how long (measured in days following initial onset of symptoms)?
Data Presented in the Slide
To orient yourself to the slide, first review the labels: left to right across the top of the first three frames. Those reflect time (measured in days) since first onset of reported symptom, grouped into 5-day frames (1-5 days post onset of symptoms, 6-10 days post, .... >20 days post). The pattern to first examine is across FRAMES (not the dots within each). You'll see that in general, among ten manufacturer tests examined, there is a pattern of increasingly positive results over time so that >20 days (at some point greater than 3 weeks post symptoms onset), the vast majority (82-100%) of patient specimens tested have detectable levels of IgG antibodies - regardless which of the 10 manufacturer test kits are used.
Prior to 3 weeks, antibodies are not routinely detected (they are not yet formed or in levels still too low to detect): when tested just 1-5 days post onset of symptoms, only about 1 in 4 patients have detectable IgG antibodies; when tested 6-10 days post symptoms, only about 1 in 2 patients have detectable IgG antibodies, regardless the manufacturer kit used. And again, (at some point) more than 3 weeks post onset of symptoms, most patients tested have detectable levels of IgG antibodies, regardless the specific manufacturer test kit used.
The second thing you now may wish to examine in the slide is variability in performance among manufacturers' kits. To examine this, look within a given frame to compare the 10 different kits to see which have higher percentages testing positive by a specific time frame (before 6 days, before 11 days, some time greater than 3 weeks post symptom onset). The dots provide specific percentages of patient specimens that are positive for IgG antibodies for each of ten kits studied. There is no intrinsic interest in patterns left to right within frames since the dots aren't arranged other than alphabetically by manufacturer's name. The vertical bars above and below each dot present 95% confidence intervals around point estimates.
Finally, the fourth frame in this slide presents completely different but complementary data.The fourth frame shows results when testing a wholly different group of people: folks NOT infected with SARS-CoV-2. So the label across the top is no longer time since symptom onset but rather "Pre-COVID-19". It's very important to note in this fourth frame that the vertical axis label differs. It is no longer "Sensitivity (%)" but rather "Specificity (%)"; the scale is changed too, from a range 0-100% to 70-100%. This change of label means that - unlike the first three frames presented in this slide that showed percentage of tested specimens that are positive, this frame presents the percentage of (uninfected patient) specimens that are NEGATIVE. And what you'd like to see of course, is that for each of the ten manufacturer kits studied, 100% of specimens from these uninfected patients do indeed test negative. That's not the case; some false positives are expected and observed (the reasons for false positive antibody tests will undoubtedly be the subject of ongoing additional study).
Caveats
This is an area of very active, ongoing research. Updates in the coming weeks and months are warranted, of course. These findings need to be confirmed by multiple studies in different patient populations (especially the very relevant and large percentage of infected people who don't present in clinics with symptoms). Nothing in this slide addresses whether these antibodies are neutralizing antibodies that effectively control infection (perhaps the online paper says all of these patients tested ultimately died). Nothing in this slide addresses whether these IgG antibodies detected confer immunity and protect from subsequent SARS-CoV-2 reinfection. Nothing in this slide addresses whether patients with these antibodies remain infectious to others or for how long. Nothing in this slide suggests how long such antibodies persist and at what level.
Fine Print
Chaz's slide incorporates some changes to the original Figure 2B in the online manuscript. These changes most likely are intended to improve clarity of a necessarily fast-paced presentation to a broad audience. Have one look at the original Figure 2B and you'll readily appreciate his effort!
(1) The label on the vertical axis has in the first three frames in this slide was changed from the original Figure 1B middle row: from "Positive (%)" IgG to "Sensitivity (%)". This reflects expert opinion and improves clarity.
(2) You may have noted the time frame omission in the slide presented here. Not represented: 11-20 days (only shown are 0-5 days, 6-10 days, ?, ?, >20 days); Chaz chose to delete two original frames from Figure 2B middle row, (those corresponding to 11-15 and 16-20 days). Again, I presume he did this to simplify and improve clarity.
Hopes this helps and that I've not made too many typos or errors!
See here: www.medrxiv.org/content/10.1101/2020.04.25.20074856v2 , Figure 1 B in the end pages . Alex Marson also covers it here: th-cam.com/video/n3mtPC6V408/w-d-xo.html . The chart shows performance of a number of antibody assay tests identified by manufacturer's name. The three plots to the left show sensitivity averages across time windows in days after patient-reported symptom onset. (All samples were confirmed to be SARS-CoV-2 positive via RT-PCR.) This is a sensitivity metric -- it tells how well each test detects antibodies for someone who is known to have been infected. The plot to the right shows percentage negative test result for samples taken from before SARS-CoV-2 started spreading. It is a specificity metric. The right side gives an indication of false negatives. The left side gives an indication of false positives.
If anyone reading this, has symptoms, please write to me.
It seems like someone needs to make you aware that many older people aren't being bad if they aren't staying home. Social security only pays a loto f us $750 a month, what are you thinking. We go to work!
At the initial stage of corona virous sign while taking nutritious food eat two Murunga seeds after food every time and drink a cup of water for about 20 days.It may help you . RABINDRA
Portugal
I hear so much about asymptomatic but I have yet to see a single person who has had their vital signs monitored (meaning carefully measured), at least daily, from BEFORE infection through to the diagnosis. I've been looking for almost three months and not a single data point. If anyone knows of a case, please comment to me. Thanks.
The four frail test pathomorphologically phone because ex-wife coincidentally pause save a wakeful command. giant, imminent brass