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In This Week’s Podcast
For the week ending December 9, 2022, John Mandrola, MD comments on the following news and features stories.
Nudges and Statin Prescribing
JAMA Cardiology has published an interesting cluster randomized trial that evaluated the efficacy of nudging doctors and patients to prescribe statins.
First, a bit on nudges. Harvard Law professor Cass Sunstein has made nudges as a policy instrument famous. The grand idea is that a nudge is a liberty-preserving approach that steers people in particular, beneficial directions. For instance, having an opt-in to a job-savings program checked as a default. That way you don't have to opt in, you are already in, and saving money.
Yet not everyone is convinced. Behavior economists have pointed out downsides.- For example, nudges to encourage low-calorie milk consumption may have the undesired effect of increasing both low and high-calorie milk consumption. So, I am not sure about the concept—in general.
Sinath Adusumalli and colleagues at the University of Pennsylvania had this idea: Statins reduce cardiac events but most people who qualify by 10-year risk aren't on them. One reason is inertia — both doctor and patient inertia.
The electronic health record (EHR) allows for e-prompts. Doctors like ratings. So, the investigators designed an active prompt in EPIC telling doctors they should prescribe a statin for a patient with a greater than 10% risk. Then they showed the doctor a scorecard on how they stacked up with their peers. The authors also gave patient nudges by text message; however, only one-third consented to getting a text from the health system.
What I love about their idea is that they didn't just institute this good-intentioned policy, say like the Hospital Readmission Reduction Program (HRRP). They studied it in cluster randomized fashion in 28 primary care practices with 158 clinicians and more than 4100 patients. The control group was standard care.
This, my friends, is the way to do policy. Don't just foist it on already over-burdened patients and doctors. Study it.
Well, the nudge worked — sort of.
In the main adjusted analyses relative to usual care, the clinician nudge significantly increased statin prescribing alone (5.5 percentage points; P = .01) and when combined with the patient nudge (7.2 percentage points; P = .001).
The patient nudge alone did not significantly increase statin prescribing relative to usual care.
The maximum absolute statin prescribing was only 15% in the clinician plus patient nudge group.
The authors describe 4 take-homes:
The dual nudge had the biggest effect size.
The clinician-only nudge also worked albeit with a smaller effect size.
The fact that the active nudge had clinician input may have helped its utility. They say this is because adoption was better than previous studies had shown.
Finally, patient-only nudges were not effective.
Comments. Again, kudos to the authors for having the humility to study their good intentioned policy.
My view of statins has changed; I am convinced that the reduction is real, and cumulative. I see our role as advisors.
Tell people the numbers.
Use clear communication; let them decide.
There is no way that statin prescribing should be a quality measure. We should not browbeat patients into good health.
Some will want to do everything to reduce cardiac risk and will feel that the disutility of taking a pill every day is worth the 25% relative risk reduction.
If you like quality measures — I don't — but if you do, measure quality by asking patients how they decided to take a statin. Positive points would be that my doctor showed me my 10-year risk and I found the risk reduction convincing. Negative points would be that my doctor said I had to take it because my cholesterol was high.
Final comment: studies of policies like this are a good start. Statin prescribing is a surrogate endpoint. What you want to know is whether this policy leads to better outcomes. It's not a guarantee, right? Nudges can have un-intended negative outcomes that may negate the positive of more statin prescriptions.
For instance, what if the time spent distracting clinicians with yet another yellow box in EPIC, and another dashboard, detracts from time that could be spent discussing things like exercising every day that you eat, or not eating veggie straws in front of the TV.
Nearly all policies ought to ultimately be studied for health outcomes. Lest you end up with something like HRRP that might actually increase mortality.
AI, Chest X-Ray, and CV risk
The headline says, "Single Chest X-Ray Could Predict 10-Year CVD Risk." This was the lede: "A single chest x-ray could predict a patient's 10-year risk of dying from a heart attack or stroke, say researchers who presented the results of their deep-learning model at the Radiological Society of North America 2022 Annual Meeting."
The researchers used nearly 150,000 chest x-rays from the PLCO screening randomized controlled trial (RCT) of prostate, lung, colorectal, and ovarian cancer.
They trained a deep-learning model and compared its ability to predict risk to the standard ACC/AHA Pooled Cohort Risk Equations (PCE) using clinical features. You know, the one that calculates 10-year risk in about 45 seconds at the bedside.
The results were that it was nearly the same.
In a subgroup of patients eligible to receive statins, the performance of the machine learning algorithm of chest x-rays had a c-stat of 0.64 vs 0.65 with the PCE.
Comments. Gerd Gigerenzer is a German psychologist who is famous for his work in the heuristics of decision making. You should be familiar with his work, especially the famous experiment where doctors failed basic specificity and sensitivity questions regarding mammography. I am oversimplifying, but one of his concepts is that when there is uncertainty, fast and frugal algorithms are just as good if not better than complicated ones.
This is a classic case. Every single model that purports to predict cardiovascular (CV) risk must pass muster against the fast and frugal atherosclerotic CV disease risk-predictor using basic clinical data. For instance, the famous gene risk score studies are no better than clinical data.
And here, a super fancy artificial intelligence (AI) model using a chest x-ray is no better. Use the clinical data and the equation. By the way, this is the best argument for CHADSVASC, yet I think CHADSVASC is ripe for being overturned.
The second reason to mention this is to always be on the alert for AI hype. While I am a huge proponent of AI, and I am sure it will improve care in some areas, CV risk prediction is likely not one.
The BOX Trial
To become a cardiologist in Denmark, you must first earn a PhD. This was one of the many stunning revelations I learned during my visit to Roskilde in the Spring. This is the likely reason so many great trials come from Denmark. Cynics would say it's because they force young people to do research, but I think it's more likely that the policy has inculcated a positive scientific culture.
One of the more impressive but least noticed trials from American Heart Association 2022 meeting was the BOX trial of multiple interventions in survivors of out of hospital cardiac arrest.
BOX had a 2x2 factorial design to study the use of two different blood pressure (BP) targets — mean arterial blood pressure of 63 or 77 mmHg, and two different arterial oxygen concentrations — restrictive (68 to 75 mm Hg) or liberal 98 to 105 mm Hg).
Within that trial was yet another subordinate trial of duration of fever prevention – either 36 or 72 hours.
All these questions remained a matter of debate before the trial. When there is equipoise, the answer is not eminence or what is most plausible, the answer is randomization.
About 800 survivors of cardiac arrest were randomly assigned at multiple big hospitals in Denmark.
The New England Journal of Medicine (NEJM) published all three papers.
In the Oxygen study, first author Henrik Schmidt, there were no significant differences in the primary outcome of death or disability. The hazard ratio (HR) was 0.95 with a confidence interval (CI) ranging from 0.75-1.21). This finding was very similar to the HOT-ICU trial, another DANISH-led RCT that found no difference in outcomes with a restrictive oxygen strategy.
Less oxygen is not different. Critical care docs are probably not surprised but it is a bit counter-intuitive.
In the BP part of the BOX trial, first author Jesper Kjaergaard, there were no differences in the primary outcome of death or disability with either mean arterial pressure (MAP) target of 63 vs 77 mmHg; HR 1.08 (0.84-1.37). Observational data suggest that the MAP that should be used to secure flow to the postanoxic brain is at least 75 mmHg, whereas guidelines suggest that the MAP should be maintained above 65 mmHg.
In this trial, the extra effort it takes to keep MAP up, say with pressors, does not lead to better outcomes.
In the Duration of Device-based Fever Prevention part of the study, first author, Christian Hassager, there was no difference in the primary outcome of death or disability in the 36 vs 72-hour group. The HR was 0.99.
Recall that this podcast has also covered the TTM trials, which found that basic fever prevention strategies were similar to lower temps. That was for the early hours to one day. This trial studied the use of fever prevention with a cooling device and found doing it for a shorter time was as good.
Comments. I don't work in the intensive care unit much. You may not either. But these trials are worth studying because they show a method of thinking that is incredibly valuable. The question of oxygen and BP targets and duration of fever prevention were each debated before the trials. Where there was once "eminence," there is no evidence. This is our path forward in so many areas of medicine.
In my critical appraisal lectures, I start by saying that not everything in medicine can be studied in RCTs, and not everything needs to be studied in an RCT. For example, kindness, listening, empathy, and compassion need not be subjected to randomization, but a heck of a lot more of what we do, ought to be tested in RCTs.
Perhaps it is the culture of science in Denmark that pushes these groups to have frameworks in which to study important questions. Whatever it is, it is a model to which more systems should strive.
Something else that strikes me: in each of these trials, less was as good as more. Lower oxygen and BP targets and shorter duration of fever prevention all performed equally well to the targets requiring more intervention. Perhaps there is a pattern there as well too.
Of course, there are times when more care is obviously better, but when in doubt, I wonder if the Bayesian priors ought to favor the "less intense" strategy.
Congratulations to the Danish group involved in BOX. And to my friends who have the opportunity to visit the Danish health system, I would take it. It was such an eye-opening experience.
In the last few weeks, a German group of pathologists report in the journal Clinical Research in Cardiology: "Standardized autopsies were performed on 25 persons who had died unexpectedly and within 20 days after SARS-CoV-2 vaccination. In four patients who received an mRNA vaccination, we identified acute (epi-)myocarditis without detection of another significant disease or health constellation that may have caused an unexpected death."
In JAMA-Pediatrics, a meta-analysis of 23 observational studies and 854 patients with SARS-CoV-2 vaccine-associated myocarditis reports that the incidence was greater after dose 2. The mean age of patients was 16 years, and men were 10 times more likely to be affected than women.
92% of these young people with this condition were hospitalized;
23% required ICU admission;
Mean hospital stay was 2.8 days;
15% had left ventricular (LV) dysfunction
The authors called these largely favorable early outcomes in adolescents and young adults.
The Journal of the American College of Cardiology (JACC) has published an observational study comparing the outcomes of patients who had viral myocarditis in the 20 years before the pandemic to those who had vaccine-induced myocarditis. If I were giving awards for the most dubious non-randomized comparisons ever published, this paper would be competitive.
Exercise as Medicine
I work in Kentucky. We are one of the least healthy states with some of the highest rates of obesity and obesity-related diseases. Most of my patients are either sedentary or severely under-exercised.
Let me tell you about an observational study using the UK Biobank, which is sort of a longitudinal prospective data source that follows mostly healthy volunteers over time. One nice thing is that the volunteers had accelerometers that objectively measured physical activity (PA).
Matthew Ahmadi and colleagues studied the association of very short periods (a few minutes) of vigorous exercise (VPA) and mortality.
The follow-up was about 6 years.
They found a dose-response curve for no VPA, 0-10 minutes of VPA, 10-30 minutes of VPA, 30-60 minutes of VPA, and greater than 60 minutes of VPA. These were per week.
The 'optimal dose' (nadir of the curve) was 53 minutes/week. That's 7.5 minutes per day.
The 'minimal' volume dose (50% of the optimal dose) was roughly 15 (14.3, 16.3) minutes/week for all-cause [HR: 0.82 (0.75, 0.89)].
These findings suggest reduced health risks may be attainable through relatively modest amounts of VPA accrued in short bouts across the week.
You know the deal: Studies like this overflow with limitations. The big deal here is the possibility of reverse causation. Meaning, it wasn't the exercise that caused better survival. It was the fact that healthy people who survive longer are more likely to do VPA.
The UK data bank is also known for healthy people's bias so these may not be representative of people with challenging social and economic conditions.Nonetheless, I am trying this experiment of explaining to people the benefits of even short periods of consistent PA. I'm calling 10-15 minutes/ day of exercise a heart pill. Take it every day. Be consistent. Some patients have already come back with good results. The key is that you aren't prescribing a personal trainer or a gym membership or a half-marathon training program, You are simply saying do something physical and sustained for even a short period, but do it every day.
December in the Hospital
I wonder if your hospital is like ours. In the United States, December is always stressful, because people have met their insurance deductibles and want to get surgeries or procedures before the new year. That, combined with the respiratory virus season, and this year has been tough — not with COVID, the pneumonias of 2020 and 2021 are thankfully almost totally gone — but gosh we have a lot of older and vulnerable people with all manner of respiratory viruses. Then they get atrial fibrillation and venous thromboembolism and oodles of other medical complications.
The positive side of this stress is that you feel extremely useful. Even subspecialists like electrophysiologists feel useful. As I've said before, Medicine is most pure when we are helping people who are asking for our help. At its core, we all picked meaningful and important jobs. This time of year highlights that choice.
I thank you for listening.
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Any views expressed above are the author's own and do not necessarily reflect the views of WebMD or Medscape.
Cite this: Dec 9, 2022 This Week in Cardiology Podcast - Medscape - Dec 09, 2022.