I'm a family physician. A 86 year old care home resident with moderate dementia I care for had a major fall leading to a severely swollen arm. She was admitted over 3 days as some debate as to whether fracture or not- eventually decided not. During admission she was found to be in Atrial Fibrillation so discharged on NOAC. The HASBLED score gives her only one point ie >65. No account taken of advanced frailty and numerous falls including the cause of the current admission.
To me as a old fashioned doc of 30 yrs clearly looked wrong- felt obliged to speak to her son but we agreed NOAC to be stopped as tiny benefit potential and clearly significant risk.
An error on my part and I forgot to update the care home and they continued NOAC- 3 days later
developmed intractable nose bleeding and had to attend Accident and Emergency. The hospitals action .... must continue NOAC but have 14 days of tranexamic acid....
Any clinicians on here please tell me if I'm wrong but I struggle to think of this as anything other the crass, unthinking tick box medicine.
For ELAN, I see no major practical difference in composite poor outcomes: 29 out of 1000 vs. 41 out of 1000. That means 1930 out of 2000 (96.5%) had good outcomes with either treatment arm. What could matter, however, is if the incidence of death was overwhelming in either treatment arm.
Here is the very simple Bayesian analysis. Let x be the true fraction of patients who will have a primary (bad) outcome under a given protocol. N patients are given that protocol, P have the primary outcome, N-P do not. Assuming a uniform prior for x (that is, we have no idea what x is going in), the "posterior" probability that x has a particular value is p(x) = C x^P (1-x)^(N-P), where C = (N+1)!/(P!(N-P)!). This is what we now know about what x is likely to be (for a specific protocol), given the data that we now have.
Here are the plots of p(x) vs x for N=1000, P=29 (blue) or P=41 (orange):
Now we could quantify the differences between the two curves in various fancy ways, but just look at them. Again, the x axis is the true fraction of patients who will have a bad outcome. Do you want to be given the blue protocol or the orange protocol? Is there really any question in your mind?
Your comparison of medical studies to running races, with statistics as the judge, is an apt metaphor that underscores the complexities of interpreting study results. I am looking forward to your upcoming discussions on evidence-based medicine. Your work is a valuable contribution to the ongoing dialogue on improving patient care and outcomes. Thank you for your dedication to sharing these important insights with the wider community. Please keep up the excellent work.
I've always been frustrated at the way most medical research is analyzed and reported - only relative risk reductions, not absolute risk reductions. Also annoying is the failure to talk about selection bias in clinical trials (e.g., disqualifying those who had AE's in Phase 1 and/or 2 from inclusion in Phase 3, causing misleading conclusions about the rate of AE's). So your articles on this are refreshing. However, I was surprised to see them from you, Dr. M., because I always thought you were a big statin fan (maybe from your Medscape articles, or I just assumed it), including for primary prevention where the ARR is only 1-2% over 5 years, less than the incidence of AE's. So I went back to some of your old articles on your blog, and discovered your position is much more nuanced. Now I see that you recognize the benefit varies based on one's absolute risk to begin with. I would like to see you write more about this in the future with statins. For example, is a CAC score a better indicator of absolute risk than calculators that rely heavily on lipid profiles? Does this vary by age? Also, if one starts taking a statin, this tends to increase the CAC score because it turns the soft plaque to calcified plaque, supposedly making it less dangerous, although this is controversial. What are your thoughts on that, and how useful is a CAC score once one starts on a statin? Since cholesterol is not a very good predictor, especially in seniors, and if the CAC score's usefulness is nullified by statins, how should one assess risk in seniors on statins? Most doctors just want to get that cholesterol down really low, but is that useful, especially in seniors? So many questions! :) Thanks!
I am a physician and I'm just getting my feet wet in clinical research. Your aubstack has allowed me to have more confidence questioning some research papers I read. Thank you for your work. It keeps me inspired.
The results described for the THAPCA trial seems backwards: The survival rate for therapeutic hypothermia is specified as 8% less (12% vs. 20% standard care), yet the article implies that there was a massive benefit from the intervention. Please explain or correct.
Not buying it until I can see the entire studies. None of these drugs can beat the positive effects of high potency cayenne solutions which are extremely cheap to use and with no risk of side effects.
I'm a family physician. A 86 year old care home resident with moderate dementia I care for had a major fall leading to a severely swollen arm. She was admitted over 3 days as some debate as to whether fracture or not- eventually decided not. During admission she was found to be in Atrial Fibrillation so discharged on NOAC. The HASBLED score gives her only one point ie >65. No account taken of advanced frailty and numerous falls including the cause of the current admission.
To me as a old fashioned doc of 30 yrs clearly looked wrong- felt obliged to speak to her son but we agreed NOAC to be stopped as tiny benefit potential and clearly significant risk.
An error on my part and I forgot to update the care home and they continued NOAC- 3 days later
developmed intractable nose bleeding and had to attend Accident and Emergency. The hospitals action .... must continue NOAC but have 14 days of tranexamic acid....
Any clinicians on here please tell me if I'm wrong but I struggle to think of this as anything other the crass, unthinking tick box medicine.
For ELAN, I see no major practical difference in composite poor outcomes: 29 out of 1000 vs. 41 out of 1000. That means 1930 out of 2000 (96.5%) had good outcomes with either treatment arm. What could matter, however, is if the incidence of death was overwhelming in either treatment arm.
thanks for this; we look forward to the next installment
Here is the very simple Bayesian analysis. Let x be the true fraction of patients who will have a primary (bad) outcome under a given protocol. N patients are given that protocol, P have the primary outcome, N-P do not. Assuming a uniform prior for x (that is, we have no idea what x is going in), the "posterior" probability that x has a particular value is p(x) = C x^P (1-x)^(N-P), where C = (N+1)!/(P!(N-P)!). This is what we now know about what x is likely to be (for a specific protocol), given the data that we now have.
Here are the plots of p(x) vs x for N=1000, P=29 (blue) or P=41 (orange):
https://i.postimg.cc/bNzMJt9G/rates.jpg
Now we could quantify the differences between the two curves in various fancy ways, but just look at them. Again, the x axis is the true fraction of patients who will have a bad outcome. Do you want to be given the blue protocol or the orange protocol? Is there really any question in your mind?
Views in the millions! Congratulations
Bayesian methodology would fix all this. Frequentism is a dreadful ideology.
Your comparison of medical studies to running races, with statistics as the judge, is an apt metaphor that underscores the complexities of interpreting study results. I am looking forward to your upcoming discussions on evidence-based medicine. Your work is a valuable contribution to the ongoing dialogue on improving patient care and outcomes. Thank you for your dedication to sharing these important insights with the wider community. Please keep up the excellent work.
I've always been frustrated at the way most medical research is analyzed and reported - only relative risk reductions, not absolute risk reductions. Also annoying is the failure to talk about selection bias in clinical trials (e.g., disqualifying those who had AE's in Phase 1 and/or 2 from inclusion in Phase 3, causing misleading conclusions about the rate of AE's). So your articles on this are refreshing. However, I was surprised to see them from you, Dr. M., because I always thought you were a big statin fan (maybe from your Medscape articles, or I just assumed it), including for primary prevention where the ARR is only 1-2% over 5 years, less than the incidence of AE's. So I went back to some of your old articles on your blog, and discovered your position is much more nuanced. Now I see that you recognize the benefit varies based on one's absolute risk to begin with. I would like to see you write more about this in the future with statins. For example, is a CAC score a better indicator of absolute risk than calculators that rely heavily on lipid profiles? Does this vary by age? Also, if one starts taking a statin, this tends to increase the CAC score because it turns the soft plaque to calcified plaque, supposedly making it less dangerous, although this is controversial. What are your thoughts on that, and how useful is a CAC score once one starts on a statin? Since cholesterol is not a very good predictor, especially in seniors, and if the CAC score's usefulness is nullified by statins, how should one assess risk in seniors on statins? Most doctors just want to get that cholesterol down really low, but is that useful, especially in seniors? So many questions! :) Thanks!
I am a physician and I'm just getting my feet wet in clinical research. Your aubstack has allowed me to have more confidence questioning some research papers I read. Thank you for your work. It keeps me inspired.
The results described for the THAPCA trial seems backwards: The survival rate for therapeutic hypothermia is specified as 8% less (12% vs. 20% standard care), yet the article implies that there was a massive benefit from the intervention. Please explain or correct.
I'd appreciate a reference/link to NEJM article referenced. Thanks.
so what about when individual drugs are evaluated when they are normally given in conjunction with others? Or using unusual dosages?
I get confused when there are conflicting results due to strange choices that don't mirror what is usually prescribed.
It's almost like there is an attempt to prop up propaganda...
Not buying it until I can see the entire studies. None of these drugs can beat the positive effects of high potency cayenne solutions which are extremely cheap to use and with no risk of side effects.
Looking forward to next week: "Therefore, no statistical hypotheses as to superiority, inferiority, or noninferiority were tested."
Looking forward to next week discussion. Check whether you flipped the 12 and 20…. Should be 20 in low temp and 12
In not cooled
Sensible Medicine…
we can only hope.
Thank you.