What You Need to Know About Chronic Disease and Coronavirus
A physician explains the finer details

Photo: AndreyPopov/Getty Images

By Bo Stapler, MD
June 2,2020 [Your life, sourced by science. A new Medium.com publication about health and wellness]

What You Need to Know About Chronic Disease and Coronavirus

By now you’ve heard that all sorts of chronic medical problems can increase a person’s risk for complications, and even death, from Covid-19, the disease caused by the coronavirus. The CDC reports that those suffering from chronic lung disease, moderate to severe asthma, diabetes, heart disease, liver disease, end-stage kidney disease on dialysis, and class 3 obesity are at increased risk — as are people with immune deficiencies or on immunosuppressive medications. In addition, race, gender, and socioeconomic status affect a person’s risk. As the list continues to grow, it’s a wonder there’s anyone left who’s not at increased risk of complications from Covid-19.

In a recent article, David Spiegelhalter, chair of the Winton Centre for Risk and Evidence Communication, insightfully noted, “As Covid-19 changes from being seen as a societal threat to a problem in risk management, it is essential that we get a handle on the magnitudes of the risk we face, and try to work out ways to communicate these appropriately.”

Communicating appropriately about the magnitude of Covid-19 risk to people living with chronic disease is the primary goal of this article. So, let’s get started.

Evaluating risk

We already know that age increases the risk of poor outcomes from Covid-19. There is little argument that those over age 65 must take special precautions to avoid exposure to the virus. But what about people under 65 who suffer from chronic disease? One report indicates that more than 40 million adults in the United States under age 65 fit into this high-risk category because of chronic medical conditions.

Thus far, people with chronic medical conditions have largely been given a binary, one-size-fits-all notice that they are at increased risk, but what does that mean from a practical standpoint? How should individuals living with chronic disease behave differently?

The answer is unique to each person and requires looking at risk in a quantitative, rather than simply a qualitative manner. Viewing risk qualitatively answers the question of who is at risk, but now that more data on the coronavirus is available, we can also begin to assess risk quantitatively and answer the question of how much.

Perhaps you have diabetes and high blood pressure and want to know if you should go back to work as an elementary school teacher this fall. Perhaps you are one of the 70 million Americans who are considered obese (defined as a body mass index above 30). Maybe you have a family member with a kidney transplant or a friend with HIV. As prevalent as chronic disease is and as widespread as Covid-19 has become, chances are this topic has entered your sphere of influence and you could use some answers.

Fresh data

Until recently, little was known about how much chronic disease increases the risk of complications from Covid-19. OpenSAFELY, a new study from the University of Oxford, offers some preliminary answers. This study is unique because it analyzes the risk of death due to Covid-19 in a large population comprising both infected and uninfected individuals.

Using a sophisticated method of data acquisition that maintains patient confidentiality, OpenSAFELY reviewed electronic health records of 17 million adults in England. With this information, the authors calculated the risk associated with various chronic medical conditions, age, ethnicity, and gender, as displayed below:

Source: OpenSAFELY

How do we interpret these findings? The chart above is on a logarithmic scale. Healthy females ages 50 to 59 were assigned a baseline hazard ratio (HR) of one. The HR is analogous to degree of risk. HRs for each risk factor were adjusted for all the other factors to avoid confounding.

With a couple notable exceptions that we’ll cover in a moment, each factor adds some amount of risk. Interestingly, the only items that contribute more than a threefold risk of death are hematologic malignancy (that is, a blood cancer) and organ transplantation. This makes sense because patients with both of these conditions are often receiving treatment with medications that suppress the immune system — making the body particularly susceptible to the coronavirus.

Age is king

It is important to note that, as is the case with other Covid-19 studies, age is far and away the greatest influencer of risk. In fact, the risk for patients ages 18 to 39 is so low that the dot representing this group is literally off the chart. Their HR of 0.07 means this cohort of young patients assumes just 7% of the risk of death from Covid-19, as does the baseline group ages 50 to 59. Conversely, the chance of a patient over age 80 dying from the coronavirus is more than 1,200% that of the baseline group.

The authors’ choice to designate the 50 to 59 age group as their baseline risk is important because the infection fatality rate (IFR, or the risk of dying from Covid-19 among people who are infected) of patients ages 50 to 59 is 0.2% to 0.4%, which is notably about twice the IFR of influenza.

Thus far, people with chronic medical conditions have largely been given a binary, one-size-fits-all notice that they are at increased risk, but what does that mean from a practical standpoint?

Two cases

Based on the information in this study, we observe that a 38-year-old white female never-smoker with a BMI of 37, uncontrolled diabetes, and uncontrolled asthma would have a relative risk of 0.32 for death from Covid-19. This was calculated with the following HRs: 0.07 (age) x 1.56 (class 2 obesity) x 1.25 (asthma with recent oral steroid use) x 2.36 (uncontrolled diabetes) = 0.32, which is equivalent to that of a healthy 40-to-50-year-old of the same ethnicity, gender, and smoking status.

Coincidentally, the IFR of Covid-19 for a healthy 40-to-50-year-old is about the same as the IFR for influenza among all patients with the flu. So, in effect, the woman in this example would be at a similar risk of death from the coronavirus as the general population is from influenza.

Let’s look at the example of a 61-year-old black male who is a former smoker with stage 3 chronic kidney disease but otherwise healthy. His relative risk compared to baseline is 15.3, which is equivalent to that of a white female over the age of 80.

Healthy people over age 80 have an IFR of 10% to 25% for Covid-19 — about 100 times the IFR of influenza in the general population. At such a high level of risk, it would be prudent for this man and any of his close contacts to scrupulously exercise precautions avoiding exposure to SARS-CoV-2 until an effective treatment, proven vaccine, or natural herd immunity arrives.

Unexpected findings

You may be wondering why high blood pressure (hypertension) did not pose an increased risk in this study. This is because hypertension is playing the role of a confounder. What does this mean? You have probably seen studies showing that over 50% of patients who died of Covid-19 had hypertension. While this association is true, it does not necessarily mean that hypertension caused these patients to die of Covid-19 or that it even increased their risk of dying. Patients with hypertension are often older and frequently suffer from other comorbidities, such as heart disease, diabetes, and kidney disease. Because the authors of this study were able to isolate each chronic medical condition and analyze their risk separately, we see it is the other conditions associated with hypertension that confer the increased risk, not the hypertension itself.

A similar pattern that others have recognized occurred with smoking. While the data may appear to say that current smoking imparts no additional risk for death, this is because chronic respiratory disease was considered a separate comorbidity. Due to the strong causal relationship between smoking and chronic lung disease, continuing to smoke remains a risky choice.

Clarifications and limitations

For simplicity’s sake, in the examples above I did not take into account what the authors call “deprivation,” which is akin to socioeconomic status. The study did show a modest but noteworthy effect of deprivation, which is worth both recognizing and investigating further.

As we draw lessons from this study, it is essential to review its weaknesses as well. Even though 17 million patients were included, the study drew from a small geographic area. The related deaths counted were only those that occurred in the hospital setting. Only adults were included. When considering how this study applies to the United States, it should be noted that the ethnic minorities of this British population are dissimilar to those in the United States, where African Americans, Hispanics, and Native Americans form a larger representation.

Another limitation is that OpenSAFELY is in preprint, meaning it has yet to pass through peer review. Even though OpenSAFELY cannot calculate an exact risk for everyone, it does provide a framework for the magnitude of risk facing individuals with chronic disease. It certainly has the potential to beneficially influence our approach to the pandemic.