Search DrRajHealth

Saturday, May 23, 2020

Annual Physicals Need To Go

For those who have had tele-health care in lieu of usual face to face in person care during this pandemic, what’s your take on the quality of care with telemedicine—equivalent, lesser, or preferable to in-person care? https://ift.tt/1VMjaZw
from Rajesh Harrykissoon, MD

Saturday, May 16, 2020

FDA Cautions About Accuracy Of Widely Used Abbott Coronavirus Test

COVID-19 Testing, testing, testing. Is it worth it? We've been asking this question on the healthcare frontlines since day one of this pandemic. More specifically, is a negative diagnostic test for COVID-19 a true negative or a false negative? A false negative is analogous to an enemy combatant successfully getting past your security checkpoint because you didn't identify them as such and now they are on your base and will destroy your troops from within. So, what frontline health care is really interested is a test with a near 100% true negative result. This true negative result is called the "specificity" of the test. This is in contradistinction to the sensitivity of the test (previously discussed in an earlier post). The reason why a highly sensitive test is not the most essential but a highly specific test is is because when a disease has a high prevalence in the community, the expectation is that many, if not most, are infected whether we have a test that says so or not. So, the high population prevalence of the disease is a highly sensitive "pre-test" already. An analogy would be weather forcasting. If you wish to know if it's raining in your neighborhood and you look outside and rain is falling from the sky, why do you need a further test to tell you it's raining? The prevalence of rain is 100% so, any test that tells you it's not raining, including the meteorologist on TV saying it's not raining, would not change your assessment and it would be considered a "false negative." Now, if you looked outside and it was not raining but there were dark, heavy storm clouds and the smell of water in the air, you might have a "pre-test" probability of 80% that it's going to rain. If the meteorologist concurs that it will rain today, that might move your pre-test expectation of rain closer to 100% (this is called the positive predictive value (PPV) of a test because the positive results of that test further further strengthened your pre-test expectations). But, if the meteorologist says, it's overcast with a low chance of rain, your pre-test expectation of rain may drop lower than 80%--perhaps the rain clouds will blow on over and deliver rain elsewhere, but not to you (this is called the negative predictive value (NPV) of a test because the test did not support your pre-test expectations). If the meteorologist offers no insight and shrugs her shoulder and says, "maybe it will rain, maybe not." Then that does not change your own pre-test expectations. You're still no better off than looking out the window and sticking with your assumption. So, when we're in a pandemic, why are we so concerned with a diagnostic test to tell us the disease is here? Afterall, isn't that what a pandemic is--the disease is everywhere? If you've left your backyard, you're at risk for getting it. Plus, what is the utility of a single, one-time test anyway? Once negative, is not always negative. Let's say you go and get tested today and the test is negative for the virus, but while walking out the testing center, an incoming person sneezes in your face, what's the value of that test you just got? It may have been instantly invalidated moments after you took it. And, what about the next day and the day after that and the week after that as you go about your life in the community--shopping, driving, neighborhood walks, interacting with other family and friends who are doing likewise? Are you going to get tested on a daily or weekly basis? Is that practical for each individual in society to get serial testing? Do we have sufficient testing supplies for that and sufficient laboratory capacity to run all those tests? It's more pragmatic to test those who are symptomatic and those undergoing high risk medical procedures where the risk of infecting others in the procedure room is high. Otherwise, for the rest of the community, continue droplet precautions--mask, hand hygiene, maintain social distance. There are reasons for diagnostic testing community-wide such as to define the case fatility rate as well as the infectivity vs virulence of the virus. More to come. https://ift.tt/1VMjaZw
from Rajesh Harrykissoon, MD

Thursday, May 14, 2020

Texas Workforce Commission pays $20 million in benefits to self-employed Texans, freelancers

Self-employed and Freelancers in Texas get $20 million in Pandemic Unemployment Assistance So, what does unemployment have to do with health and wellness? Almost everything, actually. People who do not have health care coverage have worse disease states and shorter life spans. By and large healthcare in America for able-bodied adults is employer-sponsored. It's a job-lock system. The mechanism to provide health care to the able-bodied outside of employment is severely restricted. Texas Medicaid rules strictly limit which adults can get health coverage, and most adults who can work are ineligible. Only those who get federal supplemental security income disability benefits can get Medicaid. Medicaid is for low-income adults, kids, people with disabilities and pregnant women. If you are an adult without children, you can't quailfy for medicaid in Texas, no matter how little you earn. Most Texas adults with serious and chronic illnesses do not qualify for Medicaid. Medicare is customarily for people age 65 and older. Although, you can qualify if you're under 65 and have a certain disability or a chronic illness such as End-Stage Renal Disease (ESRD) or Amyotrophic Lateral Sclerosis (ALS). The ACA offered states the optional expansion of Medicaid to those at 138% of the federal poverty income level; however, Texas does not participate in this expansion. Subsidies for private insurance in the Marketplace (www.healthcare.gov) are only available to people above the poverty level. Moreover, the Marketplace insurance products may not be well accepted by healthcare facilities. You may pay your monthly premiums, but this does not guarantee access to care. Coverage does not mean access. Essential workers commonly fall into such gaps. Public service workers, truckers, packers, stockers, food service workers, cashiers, self-employeds, freelancers, etc are afloat without a life vest. We need to move beyond a job-lock system of healthcare in America. Your healthcare should be portable. For security of self and your family, you should have access to affordable healthcare insurance, have healthcare insurance which is actually accepted where you live, and be able to take your preferred healthcare product with you job or not. Finally, your health care insurance should be accepted throughout the US. Just because you cross a state line does not void/restrict that coverage. Afterall, are we full Americans only if we get ill in Texas? Or, are we Americans deserving of full healthcare in whichever state we may succumb to illness? https://ift.tt/1VMjaZw
from Rajesh Harrykissoon, MD

Tuesday, May 12, 2020

How Coronavirus Spreads through the Air: What We Know So Far

How Coronavirus Spreads About 100 years ago we suspected that infection may spread when coughing and sneezing. Petri dishes were placed in rooms of persons coughing and sneezing in order to isolate potential pathogens. This was the origin of “droplets“ as a means of infection transmission. Literally, particles large enough to drop out of the air into bowls called Petri dishes. But, this was an insufficient explanation for all cases. We noticed that sometimes people got sick with the same illness when they were not in close proximity with the little person at the same time. So, we considered the prospect of “airborne“ transmission. This was evaluated in the early days of tuberculosis by placing guinea pigs into the air ducts of tuberculosis sanitariums. The guinea pigs were not in the same room as the patient, thus, were not exposed to the heavy droplets; but, they did share the same airflow from those rooms. Many of the guinea pigs came down with tuberculosis infection; thus, the concept of airborne transmission was solidified. Since those early days, we have sought to characterize respiratory infection transmissions as EITHER droplets or airborne. However, a cough and a sneeze is an aerosol which is a combination of BOTH droplets and aerosols. This complicated matters. Overall, although both droplet and airborne mechanisms may be at hand, we tend to designate the mechanism according to the major clinical pattern of transmission. https://ift.tt/1VMjaZw
from Rajesh Harrykissoon, MD

Saturday, May 9, 2020

12 Cognitive Biases Explained - How to Think Better and More Logically Removing Bias

Why I didn't believe we would succumb to a Pandemic I have to admit, I like many others didn't believe the COVID pandemic would hit the US with such a powerful blow and knock us off our feet and down to the canvas for a 10-count. I wanted to believe it would be flu-like and just pass on after a bit of a nuisance. Why was I susceptible to such fanciful thinking when, in the healthcare community, we've had warnings for years now that a pandemic was likely to occur? It goes back to innate biases and influences. I was really fighting my own brain and how it's wired to receive or not receive negative information. The mind is full of psychological biases that can lead us dismiss, minimize or overlook serious warnings. Here are a few of my biases: -Normalcy bias: normalcy bias prevents us from seeing just how bad things are getting until we are overwhelmed by the problem. We don't want to believe the occurrence is significant enough to disrupt our lives and routines. -Optimism bias: which is the tendency to think that even if a disaster is happening all around me, I myself won't be affected, so I don't need to take precautions. -Social proof: even as the pandemic is gathering momentum, if everyone else is acting like they're not worried, we don't get worried. We don't start wearing masks. We don't start avoiding crowds. -Authority and Credibility bias: barring our own ability to assess the situation, we look to those who we have placed in positions of authority with access to situational awareness and who are entrusted to act and advocate for our good. If they don't seem concerned, we are not concerned. -Recency bias or near-miss bias: our most recent experiences weigh heaviest in our assessment of risk. We have had near misses with SARS, MERS, H1N1, Ebola, Zika and measles all of which were anticipated to devastate our society, but never manifested as such. So, in effect, it's like the boy who cried wolf. We stopped paying attention to the warnings. These are some of my biases which came to bear in the current pandemic situation. You may have others. By the way, even knowing my biases I am still susceptible them. I don't wish to believe a second devastating wave of COVID-19 may occur for all the same biases. But, my saving grace, is the recency bias. If a second wave does occur, I'm likely to overcome my other biases and spring into action more quickly. https://ift.tt/1VMjaZw
from Rajesh Harrykissoon, MD

Saturday, May 2, 2020

Pandemic-onomics: Lessons From The Spanish Flu

The economic effects of social distancing measures on American cities during the 1918 Spanish Flu pandemic. Put in your earbuds--very interesting and eye-opening 9-minute listen. https://ift.tt/1VMjaZw
from Rajesh Harrykissoon, MD

Thursday, April 30, 2020

Antiviral Drug Remdesivir Shows Promise For Treating Coronavirus In NIH Study

How many do we have to treat with remdesivir to save one life? Remdesivir (an anti-viral drug developed for Ebola treatment) demonstrated a 3% reduction in mortality rates (preliminary data, pending peer review, pending reproduction, pending publication from the NIH). That means in order to save one life with this drug we need to treat 33 patients. Or, to phrase it differently, for every 33 patients we treat with remdesivir, 32 will die and 1 will live. This is called the number needed to treat (NNT). The ideal NNT is 1, where everyone improves with treatment and no one improves with control. A higher NNT indicates that treatment is less effective. As a general rule of thumb, an NNT of 5 or under for treating a symptomatic condition is usually considered to be acceptable and in some cases even NNTs below 10. The NNT for remdesivir is 33. In the sickest of the sick, COVID-19 induces sepsis (an overwhelming infection and systemic failure of the body) with the damage largely due to the body's own immune response rather than to the virus itself. We know that with sepsis of other infectious causes, it's not what we do, it's when we do it. For instance, if we administer sepsis therapies within the initial 6 hours of the patient presenting to the ER, the NNT is 6 (we save one life out of every six). If we do the exact same management outside of that 6-hour window, we save no more lives and mortality remains at 20-30%. It's not what we do, it's when we do it. Take oseltamivir, an antiviral used to treat influenza infection. It's only; it's only effective if taken within the first 48 hours of symptom onset. Outside of that window, it's not effective and you just have to let the flu run its course. Likewise, it may be a timing issue with COVID-19 sepsis. We have to act sooner rather than later. From the New York City patient cohort of 5,700 COVID-infected patients, we know that the mortality rate for those age 65 and over who are intubated on mechanical ventilation, the mortality rate is 97% (JAMA 2020). Since death is a virtual certainty if you are in this patient demographic, perhaps we should offer antiviral therapy sooner in their presentation. https://ift.tt/1VMjaZw
from Rajesh Harrykissoon, MD