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Archive for January, 2017

Primary Care Corner with Geoffrey Modest MD: 30-day hospital readmission rates, ?? an appropriate QI marker

30 Jan, 17 | by EBM

By Dr. Geoffrey Modest

A recent NIH study looked at the effect of the Medicare Hospital Readmissions Reduction Program (HRRP) on 30-day readmission rates after hospitalizations for acute myocardial infarction, congestive heart failure, or pneumonia, and in particular looking at whether the previously lowest performing hospitals improved more than the higher performing ones after the introduction of HRRP  (see doi:10.7326/M16-0185).

Details:

  • 15,170,008 Medicare patients discharged alive from US acute care hospitals between 2000 and 2013.
  • Mean age 79.5, 54% female, 85% white/10% black/4.7% other race, 19% admitted with acute MI/45% CHF/36% pneumonia, 52% discharged to home/18% to home with care/23% to nursing home, average length of stay 6 days, 25% rural hospitals/65% private nonprofit/9% major teaching hospitals, overall observed readmission rate 23%.
  • HRRP penalties for 30-day readmission rates were: 0% for the highest performing hospitals, 0-0.5% for average performing hospitals, 0.5-0.99% for low performing hospitals, and >1% for the lowest performing ones.
  • Of 2868 hospitals serving 1,109,530 Medicare discharges annually, 30.1% were highest performers, 44.0% were average performers, 16.8% were low performers, and 9.0% were lowest performers

Results:

  • Overall risk-standardized readmissions increased by an estimated 0.5 per 10,000 discharges per year prior to the passage of HRRP, then decreased by 76.6 per 10,000 discharges per year after passage.
    • For acute MI, risk-standardized readmissions decreased by 23.7 per 10,000 discharges per year before passage, then by 99.3 per 10,000 discharges per year after passage
    • For CHF, risk-standardized readmissions increased by 5.1 per 10,000 discharges per year before the passage and then decreased by 84.7 per 10,000 after.
    • For pneumonia, risk-standardized admissions increased by 3.1 per 10,000 discharges per year before passage and then decreased by 48.2 per 10,000 after.
  • After controlling for pre-HRRP trends, readmissions per 10,000 discharges that were averted and attributable to the law were:
    • 6 for the highest performing hospitals
    • 8 for the average performers
    • 4 for the low performers
    • 1 for the lowest performers

Commentary:

  • It does seem that after passage of the law, there was a pretty dramatic decrease in the 30-day readmission rate among all hospitals, but especially among those that had been the lowest performers.
  • It should be pointed out that the data overall on the utility of financial incentives in changing the “quality of care” metrics is pretty mixed. This study found that the lowest performing hospitals were able to change the most; however, other studies of financial incentives have not shown this to be true, often attributed to the fact that these hospitals had insufficient infrastructure to implement change. Also, this does raise the ideological concern that using financial incentives to make change in fact reinforces the conception and actuality in the US that health care is just a business and not a fundamental human right that should be managed as in most other industrialized (and may less resource-rich) countries: an essential governmental social program such as education.
  • However, and the reason I bring up the study, is that it really brings up to me some concerns about quality goals, especially when looking at surrogate markers.
    • For A1c: as mentioned in several blogs, using a target A1c goal is fraught with potential downsides
      • For patients who have really erratic blood sugars (often because of lack of dietary consistency), just increasing meds to lower the A1c (and get “credit” for better care) may well lead to significantly poorer real-world outcomes from hypoglycemia (e., over treating patients at times when their blood sugars are already low).
      • Some of the meds that decrease A1c may actually increase clinical morbidity (rosiglitazone increasing cardiac disease, —  see the many blogs on other new but concerning meds at: http://blogs.bmj.com/ebm/category/diabetes/ )
      • And those who use A1c as a metric do not include actual clinical outcomes as part of their assessment.
    • In terms of hospital 30-day readmission rates, there certainly should be a mechanism to make sure that hospitals don’t just discharge and readmit patients as a means to increase their earnings (e., getting paid for 2 admissions instead of 1), but there is also a real down-side to focusing on decreasing the readmission rate:
      • Hospitals are dangerous places to be because:
        • They are crawling with resistant bacteria
        • There is a tendency/imperative to do lots of testing for things that we in outpatient medicine might just observe and workup later as needed (this is due to several issues: specialists are often involved in the hospitalized patient’s care, and studies have shown that specialists order more tests than generalists; and, even if there is a lowish probability of a problem, it does in some ways make sense to get more tests in hospitalized patients to see what is going on, since putting off the tests might prolong the hospitalization. But the net result of more testing is the likelihood of more adverse events (either because of the test itself, or because of the downstream further testing/procedures for false positive findings)
        • And those who use hospital readmission rates as a metric do not include actual clinical outcomes as part of their assessment.​ interestingly, when there have been doctors’ strikes and dramatic decreases in hospital admissions, as in 1976 in California as well as others, there has been an attendant lower mortality (and, that is a clinical outcome…..)
      • So, I think it makes sense to avoid unnecessary hospitalizations, and, I would think, to keep the length-of-stay as short as possible
      • My practice until 2 years ago (when our health center was still doing in-patient rounding) was to discharge patients as soon as I felt they were stable (often during my rounding early the morning after their admission) when I felt they had a roughly 80% chance of doing well at home, but with aggressive outpatient follow-up (home visits, or seeing them in clinic the next day, ). And my experience was that it was really uncommon for patients to be readmitted. But with the incentives being strongly to avoid readmissions, I am afraid that might translate into longer in-hospital observation and lengths-of stay (at least it was clear that I discharged patients much sooner than the house staff would have, in large part because I could assure timely and appropriate outpatient follow-up). The point here is that we should be developing coherent integrated systems of care that would allow decreased hospitalizations overall, and lower lengths-of-stay if possible when hospitalizations happen. and, not simply using a single marker of “quality” for the complex and often highly individual decisions on how long to keep a patient in the hospital (for example, the same patient who is homeless or does not have adequate home supports may need to stay in the hospital longer appropriately.)
      • ​And, the other side of the issue: if a patient is really sick with end-stage heart failure, , they are likely to be readmitted within 30 days perhaps no matter what happens (though, of course, we should do as aggressive outpatient management as we can). And their being home as much as possible may have important value to them: being with family, in a friendly and supportive environment, etc., even if they are aware they might be back in the hospital soon

So, the real issue is how does one blend the need for some quality control issues (better care for diabetics or decreasing hospitalizations, in the above examples) but avoid using a blunt instrument (a1c levels, 30-day readmissions) which may well decrease real quality care????  This is certainly not easy to do by large-scale data-mining, looking just at numbers (a1c’s) or billing (readmission rates), but I think really requires looking at individual patients to see what an appropriate a1c might be for them, or whether they were really discharged too early and needed readmission because of poor clinical judgment. If you send me their emails, I can add them to the list

Primary Care Corner with Geoffrey Modest MD: Early Activity After Concussion?

26 Jan, 17 | by EBM

By Dr. Geoffrey Modest

A large Canadian study looked at outcomes in kids according to whether there was strict rest versus different levels of physical activity in the week after a concussion (see doi:10.1001/jama.2016.17396​ ).

Details at initial exam:

  • 2413 participants aged 5 to 18 with acute concussion completed the questionnaires in the emergency room, at day 7, and at day 28 post-injury. The researchers assessed persistent postconcussive symptoms (PPCS, defined as at least 3 new or worsening individual symptoms vs preconcussion status) to see how that varied according to the amount of physical activity begun within 7 days of the ED visit.
  • Mean age 11.8 years, 39% female, arrived at ED a median of 8.7 hours after injury, 24% lost consciousness (11% >3 minutes), 2% had seizure, 8% had prior concussions lasting more than a week.
  • 49% appeared dazed and confused, 41% answered questions slowly, 14% repeated the questions, 21% were forgetful.
  • Parental report of headache in 87%, nausea in 59%, balance problem in 44%, dizziness in 70%, drowsiness 73%, increased sleeping 35%, sensitivity to light or noise 37%, irritability 27%, sadness 40%, seemed mentally foggy 40%, increased fatigue 75%, poor concentration 37%, acts more emotional 40%

Results:

  • 1677 (69.5%) participated in early physical activity, 736 (30.5%) had no physical activity:
    • Light aerobic exercise (e.g. walking, swimming, or stationary cycling) in 795 (32.9%)
    • Sport-specific exercise (e.g. running drills in soccer or skating drills in ice hockey) in 214 (8.9%)
    • Noncontact drills (e.g. complex passing drills) in 143 (5.9%)
    • Full contact practice (e.g. normal training activities) in 106 (4.4%)
    • Full competition (e.g. normal game play) in 419 (17.4%)
  • PPCS at 28 days occurred in 733 people (30.4%)
  • The incidence of PPCS at 7:
    • Those who engaged in early physical activity: 523 (31.3%) were symptom-free and 803 (48%) had at least three persistent or worsening postconcussive symptoms.
    • Those not engaging in physical activity: 584 (79.5%) had at least three persistent or worsening postconcussive symptoms
  • The incidence of PPCS at 28 days, by propensity score matching:
    • Early physical activity: 28.7% versus 40.1% for no physical activity
    • Among those symptomatic at day 7, the incidence of PPCS:
      • Light aerobic activity: absolute risk benefit of 6.5% over no activity
      • Moderate activity: absolute risk benefit 14.3% over no activity
      • Full contact activity: absolute risk benefit 16.8% over no activity

Commentary:

  • Pediatric concussion guidelines uniformly recommend an initial period of cognitive as well as physical rest after a concussion. These recommendations include modification of school attendance and mental activities as well as avoidance of any physical activity until postconcussive symptoms have returned to baseline, and then a gradual resumption of activities. However, there is no actual evidence to support these recommendations: they reflect a concern for preventing harm.
  • It is, however, very clear from the literature, that re-injury and recurrent concussions are deleterious.
  • This study, though quite large, is an observational study. They did propensity score matching as a means to mathematically control for differences between the different groups of activity level, in an attempt to decrease the inherent bias in an observational study (by mathematically adjusting the groups for likely relevant variables). It was notable that of the 20 items that they asked parents initially (e.g. headache, balance problem, drowsiness, etc., as noted above), there really was not much difference between the groups that performed physical activity and those that did not. However, this study still does not rise to the same evidence quality as a randomized controlled trial (i.e., mathematically modeling is just not the same…). A further caveat is that they did not look at cognitive rest, and it is conceivable that those who did not do any physical activity had much more cognitive activity, and it was the cognitive activity actually caused an increase in PPCS (not so likely, but possible). Also, the cutpoint of beginning exercise within the first 7 days of injury is arbitrary. It would be useful to see data on when exercise was started, perhaps over the first 3 weeks post-concussion and stratified by the initial concussion scores, to see what was the optimal timing or degree of exercise postconcussion
  • It was also impressive that there was an apparent dose-response curve: those that did more activity seemed to benefit the most
  • There really are an array of reasons that might support the conclusions of the study: for some children having to avoid all activity creates significant dysphoria (being the parent of two kids who had concussions, I can attest that not participating in sports created a lot of unhappiness) which can account for some of the psychological symptoms such as fatigue, poor concentration, irritability, etc. As a contrary issue, it is quite clear in the literature that physical activity is important for skeletal health, cardiorespiratory fitness, improvement in symptoms of depression, anxiety, self-esteem, cognitive performance, and academic achievement. In addition, exercise may well lead to improved cerebral blood flow and promote neuro-plasticity,
  • The study is very important in challenging a long-held, though not rigorously demonstrated, view about dealing with injury, in this case concussion. Similarly, for a long time, we were all advised to limit any activity at all for patients with low back pain, for a minimum of two weeks. That also seemed prudent at the time, but turned out to be the antithesis of what we should have been doing. And in these cases, I think this conception that rest is the right prescription really undercuts the power of exercise in preserving and restoring health.

So, based on the study as well as some others, it seems to make sense to have a gradual resumption of physical activity as soon as tolerated after an acute concussion, but avoiding activities that might risk re-injury, given how much better kids did who resumed exercise within a week after a concussion. However, it certainly makes sense to have a real randomized controlled trial to assess the optimal degree of physical activity and its timing after concussion, as well as specific characteristics of the concussion which might dictate different exercise programs. And, also to look at the effect of cognitive rest (which, i think, may be nearly impossible in our technological era, given the intense cognitive stimulation of smartphones, electronic devices, etc.)

For prior blogs: http://blogs.bmj.com/ebm/2015/02/03/primary-care-corner-with-geoffrey-modest-md-concussion-a-less-aggressive-approach/ for another study suggesting more rapid introduction of physical activity; or http://blogs.bmj.com/ebm/2014/09/09/primary-care-corner-with-geoffrey-modest-md-need-for-safe-sustainable-sports/​ for a study looking at the time-course of postconcussive symptoms in kids seen in the Boston children’s hospital ED

Primary Care Corner with Geoffrey Modest MD: Thumb Sucking and Immunity

25 Jan, 17 | by EBM

By Dr. Geoffrey Modest

Another microbiome article (I realize this is the third in a series of two, but can’t help myself). This one looked at the “hygiene hypothesis”, which is basically that kids exposed to more microbes early in life have fewer allergies or asthma. This article looked at thumb-sucking, nail-biting and atopic sensitization, also finding that the more the fingers went into the mouth, the fewer had atopic sensitization (see DOI: 10.1542/peds.2016-0443).

Details:

  • The Dunedin Multidisciplinary Heath and Development Study, a population-based birth cohort study of 1037 people (52% male) born in Dunedin (the second largest city in the South Island of New Zealand with 120,000 inhabitants), with follow-up at ages 3,5,7,9,11,13,15,18,21,26,32, and 38
  • At age 5,7,9,11 the parents were asked about the kid’s thumb-sucking and nail-biting, along with an estimate of frequency
  • Skin-prick testing was done at age 13 on 724 of the 1031 kids (70%), including testing for house dust mites, grass, cat, dog, horse, aspergillus, penicillium, and a few others; a positive test was a wheal >2mm larger than the negative saline control
  • Detailed respiratory reviews were done since age 9
  • The researchers controlled for potential confounders of sex and parental history for asthma or hayfever; breastfeeding; exposure to cat or dog in childhood (a prior analysis of this cohort showed that this exposure led to lower risk of atopic sensitization); parental smoking history, household crowding (total number of kids divided by number of rooms), socioeconomic status

Results:

  • Overall 31% of children were frequent thumb-suckers or nail-biters at age >1yo
    • Nail-biting or thumb-sucking were each found in 20% of girls and 17% of boys
  • Incidence of atopy:
    • ​Atopic sensitization in 38% of girls/52% of boys age 13; 58% of girls/61% of boys at age 32
    • ​Asthma in 10% of girls/16% of boys age 13; 18% of girls/18% of boys at age 32
    • ​Hayfever in 28% of girls/32% of boys age 13; 42% of girls/37% of boys at age 32
  • For atopic sensitization, as compared to those without thumb-sucking or nail-biting:
    • At age 13:
      • There was an adjusted 36% lower likelihood of atopic sensitization: OR 0.64 (0.45-0.90) for either thumb-sucking or nail-biting
      • A 36% lower likelihood if only thumb-sucking, OR 0.64 (0.42-0.97)
      • A 30% lower likelihood if only nail-biting, OR 0.70 (0.47-1.10), nonsignificant
    • At age 32:
      • There was a 38% adjusted lower likelihood of atopic sensitization: OR 0.62 (0.45-0.86) for either thumb-sucking or nail-biting
      • A 31% lower likelihood if only thumb-sucking, OR 0.69 (0.47-1.00), borderline significant
      • A 29% lower likelihood if only nail-biting, OR 0.71 (0.49-1.02), nonsignificant
    • The only significant difference for specific allergens was for house dust mites in those aged 32, though all of the others had trends that were almost significant
  • For asthma or hayfever:
    • None were significantly associated, at either ages 13 or 32
  • A dose-response curve (doing both thumb-sucking and nail-biting vs either one of them) was only evident at age 13

Commentary:

  • This study further supports the “hygiene hypothesis”, though it was notable that the dramatic difference in atopy was only in the objective measurement of sensitization (but, one might argue that these clinical manifestations of atopy are what really matters….). Why not with asthma or hayfever?
  • Is it just that these were by report and therefore less “reliable” than the objective measure of atopic sensitization?
  • Asthma, also, is more complicated, given that atopy is only part of the issue playing into it
  • Or, my guess, is that they were looking at kids who were already too old (there were no data on thumb-sucking and nail-biting during the preschool years), that immune tolerance largely develops earlier in life, and other studies showing a relationship between “hygiene” and atopic conditions (e.g. hayfever or asthma) included much younger children (see blogs listed below)
  • The study does support the results of a prior study finding that in kids using pacifiers, there seemed to be fewer allergies later in life when the mothers sucked the pacifiers to clean them
  • The proposed mechanism here is that exposure to bacteria and other microorganisms early changes the gut microbiome (and, see blog below about the respiratory microbiome); and the microbiome can change the function of helper T cell (TH) subsets, increasing the helper T cell type 1 (TH-1, which produce interferon-g, IL-2, TNF-b and leads to cell-mediated immunity) and decreasing helper T cell type 2 (TH-2, which produces a slew of interleukins which lead to strong antibody responses), with these changes promoting the development of immune tolerance to allergen exposures.
  • But overall this study does support the concept that early exposure to some microbes leads to more immune tolerance. And thumb-sucking or nail-biting certainly increases exposure to a diverse variety of microbes.

See http://blogs.bmj.com/ebm/2016/09/19/primary-care-corner-with-geoffrey-modest-md-microbiome-and-type-1-diabetes-etc/​ which includes an article on the microbiome and type 1 diabetes, and two more on the “hygiene hypothesis”: one on the increased incidence of autoimmune disease in kids in those born in North Karelia Finland (more automated, advanced technologically) vs the Russian side (same gene pool but more natural environment/exposures); and the other being the recent NEJM article finding the same type of difference for asthma in the Hutterites (industrialized farming) vs the Amish (traditional farming)​

See http://blogs.bmj.com/ebm/2015/11/09/primary-care-corner-with-geoffrey-modest-md-gi-microbiome-in-little-kids-and-development-of-asthma/ which is a Canadian longitudinal study finding that early infancy microbiome changes increase the risk of childhood asthma; or http://blogs.bmj.com/ebm/2014/08/13/primary-care-corner-with-geoffrey-modest-md-asthma-and-early-exposure-to-allergens/ which looks at 4 US cities and similarly finding that early allergen exposure leads to more asthma

There was a blog I sent out 8/27/2014 (which did not make it into the BMJ blogs) which looked at the lung microbiome, showing that diet leads to changes in the TH1 and TH2 cells in the lung itself (i.e., there is more than one microbiome, not just the gut one). For the article, see doi:10.1038/nm.3444. With regards to asthma: there is evidence of increased prevalence of chlamydia and mycoplasma with asthma exacerbations. Also, the respiratory microbiome is different in asthmatic vs nonasthmatic patients, even in asymptomatic asthmatic patients, with abundance of Proteobacteria. There is also some evidence that airway hyperresponsiveness tracks with bacterial diversity and composition (esp. increase in Proteobacteria).

Primary Care Corner with Geoffrey Modest MD: pregnancy and congenital heart disease management

25 Jan, 17 | by EBM

By Dr. Geoffrey Modest

There was a new guideline from the American Heart Association on the management of congenital heart disease in pregnancy (see http://circ.ahajournals.org/content/early/2017/01/12/CIR.0000000000000458?sid=3d46cd93-3125-4db0-8f6c-a1002093e09d  ). Given that this is not a common primary care issue, I will broadly review their approach and defer to the article itself for the specifics

In (very) brief, this article has sections on:

  • Physiology of pregnancy and its effects on the heart/lungs (e.g. increased blood volume, increased cardiac output, decreased oncotic pressure, increased heart rate, increased B-type natriuretic peptide, vascular tree remodeling to accommodate the increased blood volume, increased pulmonary tidal volume/minute ventilation)
  • Preconception counseling/diagnostic evaluation
  • Estimating maternal and fetal risk, including some risk stratification calculators
  • Medications in pregnancy (with detailed chart on cardiac meds, pregnancy risk category, teratogenic risk, lactation suggestions, etc.
  • Fetal screening
  • Approach to obstetric care
  • Therapy for cardiac problems (arrhythmias, heart block, mechanical valves/anticoagulation, heart failure, cyanosis)
  • Interventional therapies (transcatheter interventions, cardiovascular surgery, cardioversion, ablation, implantable defibrillators/pacemakers)
  • Specific cardiac conditions (pulmonary hypertension, aortic stenosis/LV outlet tract obstruction, transposition of great arteries, etc.)

It seems to be a good reference to keep on hand for those of us doing prenatal care, or general medical care of women with congenital heart disease who are thinking of becoming pregnant

Primary Care Corner with Geoffrey Modest MD: Asthma “misdiagnosis”

24 Jan, 17 | by EBM

By Dr. Geoffrey Modest

A recent Canadian study evaluated patients with physician-diagnosed asthma to see if they could be tapered off medications, and whether subsequent testing confirmed the diagnosis of asthma (see  Aaron SD. JAMA.2017;317(3):269)​.

Details:

  • 701 patients who had physician-diagnosed asthma within the last five years were enrolled in a prospective multicenter study in 10 Canadian cities from 2012 to 2016. 613 people completed the study
  • Mean age 51, 67% women, 90% white, BMI 30, 70% college-educated, 29% current smokers, mean age of asthma diagnosis was 45, spirometry or serial peak flow testing was done in the community in 56%, 18% had an urgent visit to healthcare facility for asthma in the past year, 90% using current asthma medications (49% using asthma controlling medications daily, 44% inhaled corticosteroids with or without long-acting beta-agonists, 7% leukotriene antagonists only), FEV1 pre-bronchodilator was 88% of predicted, 21% had a post bronchodilator improvement of >12%, 86% had dyspnea and 82% wheezing in the past 12 months, comorbidities included depression in 32%, history of GERD in 30%, vocal cord dysfunction 2%, diabetes in 6%, hypertension 20%
  • All patients had spirometry done before and after bronchodilators. They used a cutpoint of FEV1 improving by at least 12% after bronchodilator administration as characteristic of current asthma. Those who did not have this level of improvement were then given a methacholine challenge at week 1. Individuals with a decrease in FEV1 of 20% or more on <=8 mg/ mL of methacholine were considered to have airway hyper-responsiveness characteristic of current asthma. The methacholine challenge was repeated at 4-5 and week 7-8. Those who did not have asthma by these tests were seen by a pulmonologist, had workup to consider other diagnoses. They had their asthma medications tapered over 6 weeks and kept a symptom diary and record of daily peak flow rates, though they could use PRN beta-agonists. These people then had another methacholine challenge at 6 and 12 months later.

Results:

  • -62% were confirmed to have current asthma, by having: >12% improvement after albuterol on spirometry (in 23%), bronchial hyperresponsiveness on methacholine testing on either their 2nd, 3rd, or 4th study visit (in 75%), or by worsening asthma symptoms during medication tapering (2%).
  • Current asthma was ruled out in 203 of 613 people (33.1%).
  • 12 people (2.0%) were found to have serious cardiorespiratory conditions that had been misdiagnosed as asthma
  • Of those patients with no evidence of airflow obstruction, bronchial hyperreactivity, or worsening of asthma symptoms after having all medications withdrawn, 13% were still felt to have asthma by the study pulmonologists. [not sure what this means]
  • After 12 months of follow-up, 22 people in whom current asthma had been ruled out by the initial spirometry and 3 initial methacholine challenges had a positive bronchial challenge test at either 6 or 12 months, of whom 16 were asymptomatic and did not have respiratory symptoms, and 6 needed asthma medications. 181 people (29.5%) continued to have no clinical laboratory evidence of asthma.
  • Of note, these patients were less likely to have had airflow limitation documented at the time of the initial diagnosis (43.8% versus 55.6% of those with confirmed asthma, an absolute difference of 11.8%) [they make a big point of this: how the lack of confirmation of asthma was related to lack of firm diagnosis initially]
  • Of the 273 people who were using asthma controlling medications daily at study entry, 71 (26%) had current asthma ruled out. After 12 months, 68 of the 71 remain free of current asthma
  • Therefore, of adults with physician-diagnosed asthma, in this study 33.1% did not have a current diagnosis of asthma

Commentary:

  • Although guidelines suggest testing expiratory airflow to confirm the diagnosis of asthma, less than half of patients with this diagnosis in the community have this testing done, similar to the findings in the above study. The issue here is that asthma can be difficult to diagnose, has different clinical presentations, and some of these clinical presentations are from non-asthma conditions.
  • This article does not mean that these 33.1% of patients did not have asthma at the time they were diagnosed, just that they did not have it after 5 years. My guess is that some of them may have had asthma which resolved spontaneously over time (for which there are little data, though some retrospective data suggests it is less often in adults than kids). Or perhaps they had wheezing with a URI (some viruses cause asthma symptoms more than others), and perhaps even several times. Or they had asthma associated with allergic triggers that they subsequently avoided. Hard to know. But undoubtedly some did not have asthma and were misdiagnosed. Though it is important to emphasize that asthma can be a very intermittent disease: in this study 22 patients who had asthma “ruled out” subsequently had a positive methacholine challenge 6-12 months later. And it is notable that this pretty large group of randomly chosen asthmatics at the time of this study had pretty mild asthma (though 90% had been using asthma meds and 18% went to an urgent care setting for asthma, the mean FEV1 pre-bronchodilator was normal at 88% of predicted).
  • I would make an argument that a significant subset of patients with perhaps milder forms of asthma do not need formal spirometry testing. I certainly agree that there are some cases where the diagnosis is uncertain, and spirometry testing is appropriate. But there are some patients who have episodic wheezing episodes, who have predictable allergic or viral triggers, who respond to beta-agonists, and have a remarkably high likelihood of having easily treated clinical asthma (i.e. they walk like a duck, quack like a duck, and probably are ducks). Although more of the patients who continued to have asthma did have objective testing done (55.6% versus 43.8%), this is pretty close to a 50-50 mix. I’m not sure what the added value is to having the formal testing done in every case. Also, I even wonder if the 2% of patients who had serious cardiorespiratory conditions in this study, who had been “misdiagnosed as asthma”, years previously may well that asthma: one third of them had ischemic heart disease, and I am not sure that their diagnosis of asthma several years before was necessarily related to the ischemic heart disease 5 years later
  • One of the important findings in this study was that 33.1% of individuals with asthma were able to taper off their medications safely within 5 years of the diagnosis, including some who had prior spirometry confirming the asthma diagnosis. This reinforces the importance of trying to step down therapy when patients are asymptomatic on regular meds, perhaps at the 3 month interval suggested by the Global Initiative for Asthma guidelines. One thing to keep in mind (perhaps related to the 3 month number) is that after an asthma attack, there is bronchial hyperresponsiveness for around 3 months later (i.e., increased bronchoconstriction at much lower doses of precipitant than usual for that patient)

So, bottom line points:

  • We should be sure of the diagnosis, since asthma symptoms can be mimicked by other problems (cardiac, other pulmonary, upper airways…). My sense, which is also stated in this article, is that periodic peak flows or a very convincing clinical presentation is reasonable for many patients to make the diagnosis (i.e., low peak flow which reliably improves with beta-agonists). Though that we should have a low threshold to confirm asthma by formal spirometry with pre- and post-bronchodilator measurements. The Global Initiative for Asthma guidelines (see ginasthma.org ) does accept variability of peak flow measurements (using the same peak flow meter) as an acceptable alternative to spirometry
  • As with some other conditions (e.g. GERD), it makes sense to try to step down therapy in a slow but methodical manner in those on daily meds who are asymptomatic for at least 3 months. This study suggests that many may not need further meds (especially if no spirometry done, but even with documented prior asthma). I would add that it is important to understand the asthma precipitants for each individual and tailor therapy to them (e.g., if seasonal, perhaps meds only that season; if someone has intermittent but very severe asthma attacks, consider giving them oral steroids to keep at home to take at the onset of their symptoms, using meds with exercise or exposure to allergens, etc.). As a primary care physician, I am well aware of the many needs of patients, and the strong tendency to simply refill meds when a patient has a stable condition (as with GERD) in order to move on to deal with other problems for the patient. This trial is a reminder that we should periodically try to taper asthma meds to the minimally effective ones for that patient.
  • And these really are the most important findings (be clinically convinced the patient has asthma, and periodically try to taper the meds), not the hype that clinicians are frequently misdiagnosing asthma — which I think this study did NOT show. Only that 5 years later many patients did not need meds…..

 

Primary Care Corner with Geoffrey Modest MD: Microbiome 2

24 Jan, 17 | by EBM

By Dr. Geoffrey Modest

This is the second of two blogs on the microbiome, inspired by a recent review that highlighted several other health-related data besides the non-caloric artificial sweeteners (see Lynch SV. N Engl J Med 2016;375:2369).

Details:

  • ​The microbiome is huge, with 9.9 million microbial genes represented, as found from studying 1200 people in the US, China, and Europe. And it has >1000 species of microbes
  • Although the microbiome was previously felt to develop after birth, bacteria are found in the placentas of healthy mothers, in the amniotic fluid of preterm infants, and in meconium. And, the mode of infant delivery does influence postnatal microbial exposure: intravaginal delivery does seem to confer an infant microbiome taxonomically similar to the maternal gut and vaginally microbiota. Also the infant microbiome does become more similar to the adult one with the cessation of breast-feeding, and over the years bacterial diversity and functional capacity expand. The microbiome becomes less diverse in elderly, which could reflect coexisting conditions and age-related declines in immunocompetence.
  • Things that affect the microbiome include sex, age, diet, exposure to antimicrobial agents, changes in stool consistency, PPIs and other meds, travel, malnutrition, exercise (the effect of exercise on the microbiome is pretty clear in mice, not so clear in humans, since it is hard to sort out the effect of exercise vs different diets in those who exercise more). Also, host genetic features, host immune response, xenobiotics (including antibiotics), other drugs, infections, diurnal rhythms (see below), and environmental microbial exposures.
  • Clostridium difficile infections
    • This is probably the most advanced and practicable microbiome application. See http://blogs.bmj.com/ebm/category/clostridium-difficile/ for many studies and analyses. However about 90% of patients affected with severe, recurrent antibiotic-resistant C. difficile infections respond to fecal microbial transplants
  • Effects on immunity:
    • There are data that the infant microbiota at one month of age is significantly related to allergy in two-year-old children and to asthma in four-year-old children. Several of the products of the higher risk microbiota are associated with subclinical inflammation, which precedes childhood disease. Also other studies have found that children born by cesarean section, who do have differences in their microbiota, are more likely to develop type I diabetes, celiac disease, asthma, hospitalizations for gastroenteritis, and allergic rhinitis.
  • Obesity/metabolic syndrome/insulin resistance/diabetes
    • There are several studies finding that there are significant differences in the microbiome between obese and lean human subjects, with a decrease in Bacteroidetes and an increase in Firmicutes species in obese individuals. Studies have shown that taking microbiome samples from pairs of identical human twins, one lean and one obese, and placing them into genetically identical baby mice, have found that the mice with the microbiota from the obese twin develops more weight gain and more body fat, along with a less diverse microbiome, than those from the lean twin. Also, interestingly, women in their third trimester of pregnancy have an altered microbiome, which, when transplanted into mice, leads to more obesity, and that pro-obesity microbiome is more efficient in extracting energy from food [one common clinical issue with overweight/obese patients is that they may often eat much less than others but still do not lose weight, which has been shown in several studies, and attributed to their being more efficient in metabolizing foods. But perhaps this is mediated through the microbiome???]
    • Some proteins elaborated by E. coli stimulate glucagon-like peptide-1 (GLP-1) secretion, which could augment glycemic control in diabetics, where this hormone is less active than in nondiabetics. In addition, E. coli can elaborate peptide YY (produced in the ileum in response to feeding), which can activate anoxeretic pathways in the brain, mediating satiety.
  • Atherosclerosis/cerebral artery occlusion
    • There are pretty convincing studies that eating red meat leads to changes in the gut microbiota, which leads to increase production of trimethylamine-N-oxide (TMAO), which is a very strong risk factor for human atherosclerotic disease. And feeding meat to vegetarians does not increase TMAO until there are these microbiota changes from recurrent red meat diets. See blogs listed below for more details. Also, experimental data on mice show that cerebral arterial occlusion leads to 60% less damage in those with microbiota which are sensitive to antibiotics; mice given probiotics have less impairment after spinal cord injury.
  • Cancer
    • In mice, specific gut bacteria (most clearly shown for Bifidobacterium) enhance the efficacy of cancer immunotherapy, delaying melanoma growth. Human data has shown that certain microbiota species (B. Thetaiotaomicron or B. fragilis) can improve the effects of anti-tumor therapy targeting cytotoxic T-lymphocytes-associated antigen 4.
  • Autism
    • There are even some suggestive data that the microbiome may play a role in autism spectrum disorders. MIA mice, a maternal immune activation mouse model, exhibits autistic-like behavior, gut microbiome dysbiosis, increased gut mucosal permeability, and an increase in 4-ethylphenylsulfate (4EPS, a metabolite of gut bacteria). Injection of 4EPS into healthy, normal mice results in anxiety. And, feeding the MIA strain of mice a strain of Bacteroides fragilis normalized these adverse gut changes and decreased behavioral abnormalities, associated with decreasing circulating 4EPS levels. There are other neuropsych issues potentially related to the microbiome: gut bacteria can produce several neurotransmitters (eg norepinephrine, serotonin, dopamine, GABA, acetylcholine), and can change emotional behavior of mice (which seems to be related to central GABA receptor expression).
  • Other diseases with suggestive data of a linkage to microbiome dysbiosis include inflammatory bowel disease, kwashiorkor, juvenile rheumatoid arthritis, and multiple sclerosis. Also, in mice, stress leads to altered microbiota (less Bacteroides and more Clostridia), and in humans undergoing bariatric surgery, there are huge differences in the microbiome by either the Roux-en-Y gastric bypass or vertical banded gastroplasty, and this microbiome transplanted into germ-free mice leads to reduced fat deposition, suggesting that these microbiome changes themselves might play a direct role in decreasing adiposity (see Tremaroli V. Cell Metabolism2015; 22:228)​. And perhaps the changes in the microbiome, through the gut-brain relationship is part of the reason for the documented improvement in memory noted after bariatric surgery.
  • Diurnal rhythms (see Thaiss CA. Cell. 2014; 159: 514): the gut microbiota has diurnal variations that reflect feeding rhythms; humans with jet lag have dysbiosis; this jet lag leads to microbiome changes promoting glucose intolerance and obesity and are transferable to germ-free mice.

Commentary:

  • We should approach these studies on the microbiome with caution: some of the most impressive studies were done in animals in highly controlled conditions, and predictions in humans based on the studies is always fraught. For example, in general the use of probiotics in human adults has not shown as dramatic a response as found in rodents. (Although an interesting study of human neonatal probiotic supplementation in the first month of life was associated with a 60% reduction in the risk of pancreatic islet cell autoimmunity, a precursor to type 1 diabetes, before school-age). In addition, a stool sample may not be an adequate proxy for the microbial content of the entire GI tract. And, most of these studies have focused primarily on bacterial species in the microbiota, not taking into account the many other types of microorganisms found or their complex interactions.
  • One concern I have in general is our tendency towards reductionism. The microbiome appears to be a quite complex organ, composed of many different varieties of organisms which undoubtedly interact with each other in complex ways, and which are influenced by many known and undoubtedly unknown external cues (diet, antibiotic use, etc., etc.). So, for example, simply attempting to manipulate that microbiome through the introduction of one species or another of probiotics (i.e., our usual medical fix) may not deal with the complexity of this situation.
  • There have been a slew of other blogs on the microbiome over the years. See http://blogs.bmj.com/ebm/category/microbiome/ . One particularly interesting finding in one of the blogs was that one of metformin’s major action might be in its effects on the microbiome (see http://blogs.bmj.com/ebm/2015/01/28/primary-care-corner-with-geoffrey-modest-md-heart-failure-microbiome/, which also reviews some of the TMAO data.
  • So, although I am pretty convinced of the importance of a healthy microbiome, it does seem to me that the major initiative should be around lifestyle changes overall: a healthy diet (and specifically one which is predominantly vegetarian), adequate exercise, perhaps adequate sleep (would be great to have more data on the effect of sleep patterns overall on the microbiome and if changing those patterns changes the microbiome), and minimizing exposure to unnecessary antibiotics (both in humans and in animals that make it into our food chain).

Primary Care Corner with Geoffrey Modest MD: Artificial Sweeteners Microbiome1

23 Jan, 17 | by EBM

By Dr. Geoffrey Modest

As mentioned in prior blogs, I think that the microbiome represents a very important mediator between the external environment and health/disease. A few recent articles supplement and strengthen this understanding. The first in a series of two is a study reinforcing the potentially deleterious effects of non-caloric sweeteners on the microbiome and health outcomes. The second (to be sent tomorrow) is a broader description of our understanding of the microbiome overall and its potential relationship to health.

​Non-caloric artificial sweeteners (NAS) were developed from the biological perspective that these potent sweeteners (more than 100 times sweeter than sucrose) are non-caloric and  are excreted unchanged; they should therefore be an important sugar alternative to help people lose weight and control glucose intolerance. Although a study done in the 1980s, prior to DNA sequencing capabilities, did show that saccharin could alter the rat microbiome, it is only relatively recently that we understand the fuller effects of NAS on both the microbiota as well as clinical outcomes. Many of the clearest studies were done on animals, since it is easier to control the environment completely and isolate the effects attributable to NAS. A recent study looked further into the relationship between NAS, the microbiome, and the clinical effects (see Suez J. Gut Microbes 2015; 6(2), 149). This is an update of a prior article in Nature (see prior blog: http://blogs.bmj.com/ebm/2014/12/04/primary-care-corner-with-geoffrey-modest-md-artificial-sweeteners-microbiome-and-glucose-intolerance-in-mice-and-men-and-women/​ )

Background:

  • The human weight control studies here are a bit mixed. However it should be noted that most of the comparisons were between individuals consuming NAS to those consuming caloric sweeteners, with very few comparing NAS consumption to avoiding all sweeteners.
  • Several studies have shown NAS leads to weight gain in rats (including saccharin, sucralose, aspartame and Stevia), and are associated with increased adiposity
  • NAS can also induce hyperinsulinemia, impaired insulin tolerance, impaired glucose homeostasis, and worsened atherosclerosis in genetically susceptible mice
  • It should be noted that there are some genetically-altered mice where there are some discordant defects: some with decreasing glucose and insulin levels but increasing adiposity, and in some cases hyperinsulinemia

Details of the current study:

  • Mice drinking water supplemented with high doses of commercial saccharin, sucralose, or aspartame, after 11 weeks had marked glucose intolerance, as compared to controls drinking water, sucrose, or glucose.
  • Further studies of saccharin showed that mice on different baseline diets (e.g. high-fat or other) and at different doses of saccharin had increased glucose intolerance
  • The glucose intolerance induced by NAS was ameliorated by prior dosing with antibiotics (ciprofloxacin and metronidazole, in an attempt to sterilize the gut)
  • There were specific changes in the microbiome associated with NAS, including enrichment of Bacteroides and some Clostridiales and decreases in Lactobacilli and some other members of Clostridiales, several of the microbiota changes previously associated with type II diabetes in humans
  • Fecal microbiomes from mice consuming either water or commercial saccharin were then transplanted into germ-free mice, finding that those germ-free mice receiving the saccharin-associated microbiome developed glucose intolerance
  • In 381 nondiabetic humans, NAS consumption was associated with increases in BMI, blood pressure, hemoglobin A1c, and fasting glucose levels. Also there were changes in microbial taxa in the microbiome: more Actinobacteria, Enterobacteriales, and certain Clostridiales.
  • A preliminary small-scale human study found that supplementing the regular diet with higher doses of saccharin led to elevated glycemic responses in four of the seven volunteers, those 4 had microbiome alterations. And when these microbiomes were transplanted into germ-free mice, these mice also developed the same abnormal glycemic responses. Of note, in two of these 4 volunteers, their microbiome changes reverted to normal within 2 to 8 weeks.

Commentary:

  • NAS is consumed by approximately 32% of adult Americans.
  • The microbiome can be rapidly altered by diet, as noted in diets rich in fat (for example, see http://blogs.bmj.com/ebm/2015/01/28/primary-care-corner-with-geoffrey-modest-md-heart-failure-microbiome/)
  • There are a remarkable number of largely unregulated food additives in the current food supply, many added for purely commercial ends, such as preservatives to extend the shelf life of some foods. I believe this NAS data challenges the concept that even those ingredients that are not absorbed and internalized could conceivably adversely affect the human microbiome. The main point here is not that all additives or chemicals are necessarily bad, but that we should be very circumspect about assuming that they are probably benign based on our often incomplete models (i.e. It did make intuitive sense at the time that a non-absorbed sweetener would lead to less obesity and diabetes; but as our understanding and models have expanded/become more complex, our “intuitive” sense has changed). But, I think all of this reinforces what Michael Pollan (author or many books, including The Omnivore’s Dilemma) has suggested: it really does make sense to eat natural foods, especially ones which our bodies have evolutionarily adapted to, and avoid foods with ingredients that your grandmother would not know.

In my practice, I have focused on trying to get patients to decrease their consumption of sodas, and with some reasonable success. I think this is often the low-hanging fruit (though less healthy than other fruits), and at least most of my patients say they have dramatically decreased or eliminated sodas by either substituting water (best) or water slightly flavored by fruit juice. For regular sodas, the attempt is to decrease the consumption of high-fructose corn syrup (a bad actor with multiple bad effects, including increasing uric acid levels), was well as “diet” sodas (commenting on the fact that they really are not benign, non-sugar alternatives, as above). I think my patients have been able to change this soda habit by our regularly and repeatedly targeting this issue (with motivational interviewing) over the past several years, especially with my patients who are overweight, glucose intolerant/diabetic or hyperuricemic.

Primary Care Corner with Geoffrey Modest MD: Physical activity and decreased recurrent strokes

19 Jan, 17 | by EBM

By Dr. Geoffrey Modest

The SAMMPRIS trial (Stenting and Aggressive Medical Management for Preventing Recurrent Stroke in Intracranial Stenosis) compared aggressive medical management of patients with intracranial stenosis and a non-disabling stroke/TIA, versus stenting plus aggressive medical management, finding that aggressive medical management was superior (see  doi 10.1212/WNL.0000000000003534​).​ In a prespecified analysis, they looked at the relationship between risk factor control during follow-up and outcomes in the aggressive medical arm.

Details:

  • 227 patients were analyzed, with risk factors recorded at baseline, 30 days, 4 months, and then every 4 months for up to 32 months.
  • Aggressive medical therapy included aspirin 325 mg per day along with clopidogrel 75 mg daily for the first 90 days, as well as treating the systolic blood pressure and LDL cholesterol to target (see below). Secondary risk factors included the non-HDL cholesterol, hemoglobin A1c in diabetics, smoking, weight management, and physical activity. Coaching on healthy lifestyle behaviors was done at regularly scheduled times throughout the follow-up
  • Target for risk factors:
    • Cholesterol: LDL <70 mg/dl (47% in target over the course of the study)
    • Blood pressure: systolic blood pressure < 140, or <130 if diabetic (53% in target)
    • Hemoglobin A1c < 7% if diabetic (42% in target)
    • Smoking cessation (65% target)
    • Weight management (if initial BMI 25-27, target <25;  initial BMI >27, target 10% weight loss; 19% in target)
    • Physical activity, assessed using the 8 point Physician-based Assessment and Counseling for Exercise (PACE) questionnaire (target score 4-8; 44% in target), where:
      • PACE 3= trying to do vigorous or moderate exercise but not exercising regularly
      • PACE 4= moderate exercise (brisk walking or slow cycling for at least 10 minutes at a time) <5 times per week or vigorous exercise (jogging or fast cycling for at least 20 minutes at a time) <3 times a week
      • PACE 6= at least 30 minutes of moderate exercise a day for at least 5 days a week for the past 6 months or more

Results:

  • At 3 years, the likelihood of the endpoint of a recurrent stroke, MI, or vascular disease in multivariate analysis, controlling for the above risk factors:
    • Higher PACE score decreased the likelihood by 40% [OR 0.6 (0.4 0.8)], with a dose effect for exercise (i.e., more exercise, more benefit)
    • Blood pressure, cholesterol, as target variables (i.e., dichotomized to above and below target) were nonsignificant. smoking, BMI, and hemoglobin A1c were also not significant
    • For recurrent ischemic stroke as the only endpoint at 3 years:
      • PACE had a highly significant odds ratio of 6.7 (2.5- 18.1)
      • LDL overall was not statistically significant as a dichotomized variable, though there was a significant odds ratio of 1.1 (1.0- 1.3) looking at it as a continuous variable, for each increase of 10 mg/dL)
      • Systolic blood pressure was similarly nonsignificant though had a significant odds ratio 1.2 (1.0- 1.6) as a continuous variable, for each increase of 10 mmHg
      • Hemoglobin A1c for diabetic patients had an odds ratio of 2.3 (1.0-5.0)
      • Smoking, BMI remained nonsignificant

Commentary:

  • Patients with intracranial atherosclerotic stenosis are at particularly high risk of recurrent stroke. Other trials had found that poorly controlled blood pressure and elevated cholesterol are important risk factors for this. The above SAMMPRIS trial was an NIH-funded trial for intensive risk factor management, evaluating patients within 30 days of a TIA or non-disabling stroke caused by a 70-99% stenosis of a major intracranial artery. And the primary outcomes were stroke, MI or vascular death within 30 days after enrollment, as well as ischemic stroke in the territory of the qualifying artery beyond 30 days
  • Although the study did show that controlling blood pressure and cholesterol were important for reducing vascular events, the independent effect of physical activity was considerably stronger for the prevention of recurrent vascular events, and especially for recurrent ischemic stroke. Other studies had shown that exercise decreased mortality among stroke patients and decreased the incidence of incident stroke among healthy people.
  • Although the above trial was an observational trial, and there is certainly a potential bias from post-stroke depression, they did note that the percentage of patients involved in physical activity increased from 32% at 30 days to 56% at the 4-month follow-up visit, perhaps reflecting the focus on lifestyle modification by the researchers. This increase in exercise would make less likely but not eliminate the potential depression bias.
  • One side concern in post-stroke patients is how rapidly to lower blood pressure. This study did suggest that in those enrolled within 30 days of a TIA or nondisabling stroke, they did better with more intensive blood pressure control (33.8% had blood pressure at the target at baseline, increasing to 47.6% at 30 days). As in another study, they did not find that diabetes, weight, or smoking cessation were significantly related to recurrent vascular events, though part of this may be due to lack of power to detect a significant effect.
  • The likely mechanisms for the positive effect of exercise include augmented arterial blood to the brain (including collaterals), improvement in other risk factors (HDL, insulin resistance, blood pressure), and decreased arterial stiffness.

So, this post hoc analysis (but of a prespecified endpoint) demonstrated the remarkable predictive power of exercise for fewer recurrent vascular events; and this relationship was increasingly evident as the amount of exercise increased. Unfortunately, they did not look at dietary interventions as part of their lifestyle modification. But, to me, bottom line is that we should be aggressively encouraging patients to increase their exercise as much as possible if they have intracranial-arterial stenosis causing a TIA or nondisabling stroke, as well as prescribing the usual culprits to control blood pressure, lipids, and give an antiplatelet drug.

Primary Care Corner with Geoffrey Modest MD: Cardiovascular Fitness — a new vital sign?

19 Jan, 17 | by EBM

By Dr. Geoffrey Modest

A recent scientific statement from the American Heart Association stresses the importance of assessing cardiorespiratory fitness (CRF) as part of the risk assessment for cardiovascular disease (see DOI: 10.1161/CIR.0000000000000461)​.

Details:

  • Studies since the 1950s have consistently found that CRF is a strong and independent marker of cardiovascular risk as well as all-cause mortality, adjusting for age and the other standard risk factors. This is been found in healthy men and women, those with known or suspected cardiovascular disease, and those with the co-morbidities of obesity, type 2 diabetes, hypertension, and hyperlipidemia. In many studies CRF is a more powerful predictor of mortality risk than traditional cardiovascular risk factors. It has even been shown to be a more powerful risk predictor than ST-segment depression, cardiovascular symptoms, or hemodynamic responses.
  • The survival benefit in 13 studies showed that each 1-MET (metabolic equivalent) higher CRF, a small increment, was associated with a marked 10-25% improvement in survival. And, one study found that men who improved from unfit to fit between two successive examinations had a reduction in mortality risk of 44% relative to those who remained unfit in both exams (i.e., those with higher CRF have dramatic clinical benefit)
  • As a quick guide to METs:
    • Light activity (<3 METs): includes walking 2.5 mph (2.9 METs)
    • Moderate activity (3-6 METS): includes walking 3.0 mph (3.3 METs), walking 3.4 mph (3.6 METs), stationary biking (light effort) 5.5 METs
    • Vigorous activity (>6 METs):  jogging (7.0 METs), calisthenics/pushups/situps (8.0 METs), rope jumping (10.0 METs)
  • Of note, even though the most dramatic differences in all-cause and cardiovascular mortality were found comparing the most fit to the least fit subjects (70% and 56% respectively), the greatest increase in mortality benefit was in comparing the least fit group to the next least fit category
  • A recommendation in the paper is that CRF should become an accepted “vital sign”, and should be part of the standard clinical encounter
  • CRF also is associated with heart failure exacerbations and mortality, with one study finding that for every 6% increase in CRF over three months there was a 4% lower risk of cardiovascular mortality or hospitalization, and an 8% decrease risk of cardiovascular mortality or heart failure hospitalization (for example, see http://blogs.bmj.com/ebm/2016/11/09/primary-care-corner-with-geoffrey-modest-md-vigorous-exercise-helps-those-with-heart-failure/ which shows the benefit of vigorous exercise in patients with heart failure and reduced ejection fraction), timing of cardiac transplantation, preoperative surgical risk prediction (including studies of abdominal aortic aneurysm repair, liver transplant, lung cancer resection, upper GI surgery, intra-abdominal surgery, bariatric surgery, coronary artery bypass grafting). And interventions seem to help: in patients waiting for CABG surgery, those randomized into an exercise training group had superior outcomes to the control group, with a reduced rate of perioperative complications and shorter hospital stays. And observational studies have also shown that men with higher CRF had 68% lower stroke mortality, controlling for standard risk factors.
  • There were a few studies showing that those with a higher level of CRF had a reduced risk of developing dementia or Alzheimer’s, one study showing a 36% lower risk of developing dementia in those with the highest quartile of CRF. Higher levels of CRF are also associated with lower measures of anxiety or depression symptoms
  • Many studies have shown decreased risk of development of prediabetes, metabolic syndrome, and type 2 diabetes in those with higher CRF, again with the biggest difference in those going from lower CRF to the moderate range.
  • Lower levels of CRF at a younger age are also associated with a higher risk of disability at an older age. For example one study of obese adults with type 2 diabetes found that after four years, improvement of CRF decrease the likelihood of developing disability
  • Added value of CRF to the traditional risk calculators:
    • Several analyses have looked at various ways of incorporating the additional value of CRF. In one 30-year study of patients with stage II hypertension, the 30 year risk of cardiovascular mortality was 18.4% in those with low CRF versus 10.1 present in those with high CRF (i.e., a huge difference)
    • Overall, adding CRF to the traditional risk stratification led to actual CVD and all-cause mortality outcomes being correctly reclassified through the risk predictor as being decreased 23.3% and 20.6% respectively through correctly reclassifying patients as higher risk, and 55.8% and 46.0% respectively for correctly reclassifying patients as lower risk. The overall changes reflected a 30.5% and 24.5% correct reclassification for all-cause mortality, with larger changes in correctly reclassifying patients as lower risk because of CRF. [e., those at apparently high risk by a traditional risk calculator, in reality have significantly lower risk if they are more fit; there are changes apparent in the other direction as well, but less emphatically so]. Also as a point of comparison, when looking at the nontraditional risk factors, such as coronary artery calcium scores  (which seems to be the best of the lot), the level of correct reclassification from the traditional risk calculators is much lower
  • So, how does one measure CRF?
    • The most accurate and standardized quantification of CRF is through CPX (cardiopulmonary exercise testing), a combination of conventional exercise testing with ventilatory expired gas analysis
    • A step below that is to look at achieved treadmill speed/grade and duration, making sure the patient does not hold the hand rails
    • Another approach is to look at submaximal exercise testing or the 6-minute walk test to assess distance walked (walking <350 meters is associated with high risk).
    • And the easiest overall/least time-consuming/cheapest/easiest to implement is to do nonexercise prediction calculations. These are not standardized at this point, and each study seems to have somewhat different calculators. Perhaps the best is to use the one by Nes BM. Med Sci Sports Exerc 2011; 43: 2024, which incorporated an assessment of patient reported physical activity, age, waist circumference, and resting heart rate, and this is one of the studies which included a lot of people (n= 2067 men and 2193 women) and looked at actual clinical outcomes, finding that 90.2% of women and 92.5% of men in the lowest two quartiles of fitness were correctly classified. Their questions for physical activity included: frequency of exercise (never, <1x/wk, 1x/wk, 2-3x/wk, >3x/wk), intensity (“no sweat/heavy breathing, “heavy breath and sweat”, “push myself to exhaustion”), and duration (<15 in, 15-30 min, 30-60 min, >60 min).
    • Overall exercise recommendations:
      • Type: exercise should involve major muscle groups (legs, arms, trunk) that is continuous and rhythmic (e.g. brisk walking, jogging, cycling, swimming, rowing)
      • Intensity: moderate and/or vigorous intensity relative to the persons capacity
      • Frequency: at least five days per week of moderate or three days per week of vigorous intensity exercise
      • Time: 30 to 60 minutes per day (150 minutes per week) of moderate and 20 to 60 minutes per day (75 minutes per week) of vigorous exercise. Of note between 10 and 20 minutes can be beneficial in previously inactive people
      • Amount: a target of 500 to 1000 MET-min/wk
      • Pattern: one continuous session per day or multiple sessions per day of greater than 10 minutes each. Less than 10 minutes may work in deconditioned individuals.

Commentary:

  • Incorporating CRF reflects a more individualized physiologic approach (assessing the constellation of how well the heart, lung, circulation, and oxygen extraction by muscles works). It is clear from epidemiologic data that on a community basis, as well as individual basis, the traditional risk factors of smoking, hypertension, hyperlipidemia, and diabetes confer an increased risk of cardiovascular disease. However, CRF is a truly specific individual physiologic risk factor, reflecting how these risk factors and more play out in the individual’s body. For example, hypertension itself confers different levels of individual risk dependent on CRF.
  • One note of caution: there is no uniformity in clinical practice as to which of the traditional risk calculators is the best: the Am Heart Association/Am College of Cardiology just published an updated tool, including a spreadsheet calculator (see org/10.1161/CIR.0000000000000467 for the article, and http://circ.ahajournals.org/highwire/filestream/234917/field_highwire_adjunct_files/0/Appendix_Users_Guide_Spreadsheet.xlsfor the spreadsheet to calculate risk. BUT, this tool also needs to be validated in different populations prior to being accepted (also, see http://blogs.bmj.com/ebm/2015/08/05/primary-care-corner-with-geoffrey-modest-md-comparison-of-the-2013-accaha-lipid-guidelines-to-atpiii/ for a critique of the 2013 ACC/AHA lipid guidelines.)
  • Interestingly, several studies suggest that CRF is a more potent predictor of cardiovascular disease than any of the individual risk factors we have incorporated into our predictive models
  • Why is CRF so important? There are several explanations: improved traditional cardiovascular risk profiles (though most of the studies did control for the major ones we know), changes in autonomic tone that may reduce arrhythmogenic risk, fewer thrombotic events (exercise decreases fibrinogen levels, for example), improved endothelial function, lower levels of visceral adiposity/improved insulin sensitivity, lower levels of inflammation, as well as perhaps improved mental health and sense of well-being. And, there might be important positive changes in the gut microbiome with exercise, which is clear in animal models, less clear in humans where those who exercise tend to eat differently from those who do not, so hard to control well).
  • I should add a couple of caveats here: it is important not to confound fitness with doing lots of exercise; a significant component of fitness (on the order of 30+%) is genetic and not related to regular exercise. And most of the studies above are observational, not intervention studies (i.e., only a few actually randomized patients to exercise programs vs none and looked at long-term outcomes. Though the one on pre-surgery exercise programs was pretty impressive. And, the overall data on the benefits of exercise overall are quite robust)
  • For ballpark figures, those with a CRF level less than 5 METs have a particularly high risk of mortality, whereas those with CRF levels of greater than 8 to 10 METS seem to have much more protection. And, more than half the reduction in all-cause mortality occurs between those who are least fit (e.g. CRF less than 5 METs) and those in the next least fit group (e.g. CRF 5-7METS); i.e., benefits for cardiorespiratory fitness are particularly strong in those people in the least fit as compared to the next higher category (i.e., one does not need to be an Olympic athlete to achieve the benefits)

So, the key points here are:

  • Cardiorespiratory fitness is an independent in additive risk assessor for total and cardiovascular mortality
  • Improving CRF dramatically decreases cardiovascular and all-cause mortality
  • This clinical improvement is especially profound in those who are the least fit, finding a greater than 50% risk reduction by moving one step up to the next least fit group. An increase in CRF of only one MET is associated with the 10 to 20% decrease in mortality rate
  • There is a reasonable argument based on studies that have been done to propose that a simple, non-exercise based calculator should be added as a vital sign. This could easily be measured by nonclinical staff and would provide clinicians important information to help encourage patient-specific exercise programs. This should to be evaluated more completely in different populations to assess its generalizability. However, even without those studies, given the documented benefits of exercise and the dramatic relationship in the above studies of CRF as a risk predictor, I personally will ask patients about CRF more and further reinforce the importance of exercise as part of a healthy lifestyle.

For other blogs on exercise, see http://blogs.bmj.com/ebm/category/exercise/

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