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Primary Care Corner: Hyperuricemia and cardiometabolic disease

12 Jun, 17 | by gmodest

​A recent study suggested that hyperuricemia itself predicts the development of several cardiac risk factors, including hypertension and hyperlipidemia (see doi: 10.1161/HYPERTENSIONAHA.116.08998.)


— 5899 Japanese subjects were enrolled who at baseline did not have overweight/obesity (BMI>25), hypertension (>140/90 after resting quietly for 5 min), diabetes (meds or A1c>6.4), and dyslipidemia (LDL >140, HDL <40, and/or TG >150), as well as any history of gout or hyperuricemia on medications, or chronic kidney disease with the eGFR <60. [ie, a pretty normal cohort medically]

— 282 men and 133 women had  hyperuricemia defined as serum uric acid (SUA) > 7 mg/dL in men or >6 mg/dL in women

— Mean age 47, 1864 men, there was small but statistically significant differences between those with hyperuricemia versus normal SUA at baseline (e.g. in men, BMI 22.4 vs 21.8, blood pressure 116/73 vs 114/72, eGFR 87 vs 82, albumin 4.5 vs 4.4, with similarly small differences in women) though there was a more convincing difference in drinking habits at 72% vs 62%).

— SUA on average was 7.65 in hyperuricemic men vs 5.59 in those with SUA <7; 6.44 in hyperuricemic women vs​ 4.20 in those with SUA < 6

— patients had an initial exam in 2004, and a follow-up exam in 2009


— hyperuricemia was associated with an increased cumulative incidence of (all OR’s expressed as per SUA increase of 1 mg/dL):

— hypertension, 14.9% vs 6.1% (p<0.001), odds ratio (OR) of 1.5 [ie, the OR is much higher in those with much higher SUA levels]

— dyslipidemia, 23.1% vs 15.5% (p<0.001), OR of 1.3

— chronic kidney disease, 19.0% vs 10.7% (p<0.001), OR of 1.3

— overweight/obesity, 8.9% vs 3.0% (p<0.001),  OR of 1.5

— diabetes, 1.7% vs 0.9% (p<0.001), OR 1.5

–in the above, there were some differences between men and women: there was no increase in diabetes in men (though in women was 2.3% vs 0.5%, with p=0.011); and in women no increase in dyslipidemia (though in men 5.2% vs 19.2%, p=0.020) or overweight/obesity (trend in women with p=0.08, but in men was 11.0% vs 4.9%, p<0.001)

— multivariate analysis:

–model 1 (controlling for age, sex, and smoking/drinking), all looking at OR and p value per SUA increase of 1gm/dL:

–hypertension increased with OR of 1.4, p<0.001

–dyslipidemia increased with OR of 1.3, p<0.001

–CKD increased with OR of 1.3, p<0.001

–model 2 (controlling also for eGFR), all looking at OR and p value per SUA increase of 1gm/dL:

–hypertension increased with OR of 1.5, p<0.001

–diabetes increased with OR of 1.5, p=0.004

–dyslipidemia increased with OR of 1.3, p<0.001

–CKD increased with OR of 0.9, p=0.006 [ie, lower odds ratio]

–overweight/obesity increased with OR of 1.4, p<0.001

–model 3 (also controlling for BMI), all looking at OR and p value per SUA increase of 1gm/dL:

–hypertension increased with OR of 1.4, p<0.001

–diabetes increased with OR of 1.4, p=0.01

–dyslipidemia increased with OR of 1.2, p<0.001

–CKD increased with OR of 0.9,  p=0.004

–overweight/obesity increased with OR of 1.1,  p nonsignificant


— this study is particularly interesting because it isolates any of the cardiometabolic issues ​from hyperuricemia, which have historically been conflated with them, by choosing people who had hyperuricemia initially but none of these issues at baseline and following them 5 years later. It has been quite unclear what the directionality is (or if it exists): does hyperuricemia in fact lead to these medical problems, or do these issues lead to hyperuricemia through its effects on insulin resistance (leading to the various components of the metabolic syndrome), and renal vasoconstriction and reduced GFR (leading to decreased renal uric acid excretion). Or are both hyperuricemia and cardiometabolic risk factors both related to a third entity, perhaps insulin resistance. Animal studies have supported the role of uric acid as causal in these conditions. This study would have been stronger if they had intermediate exams, not just at the beginning and 5 years later, but still would not answer the issue of causality definitively.

— one big issue with multivariate adjustment (as a general issue), which really comes to the fore in this study, is that it really depends on the variables being independent. For example, controlling for eGFR even within the <60 range and finding no significant relationship between SUA and developing CKD does not necessarily mean that there really is no relationship. Perhaps a mild reduction of eGFR within the normal range is leading to reduced excretion of SUA (and higher blood levels) from this mild decrease in GFR itself (so controlling for eGFR may create the perhaps erroneous impression that SUA is unrelated). Or, controlling for BMI within the normal range may similarly not show that SUA elevation is not predictive of subsequent overweight/obesity, since mild increases of BMI may be associated with some increased insulin resistance leading to higher BMI in the future. So, I would not attach much significance to models 2 or 3 above.


so, this study complements and adds to the previously noted association between hyperuricemia and cardiovascular disease (see blogs noted below). However, one can still not definitively show causation, because the hyperuricemia could be an innocent bystander associated with the real cause.

— But, based on these studies, it seems reasonable to me to check SUA levels for 2 reasons (and I have been doing so pretty regularly):

— there are important lifestyle risk factors for increased SUA levels, especially fructose intake. I have been successful in a few cases of working with patients to decrease their consumption of sodas and other products with high fructose corn syrup, often finding pretty dramatic decreases in SUA levels (eg from the 8.5 range to the 7 range). And decreasing alcohol consumption

— In addition, I also think it would be reasonable to be even more aggressive in primary prevention of cardiac disease in those patients who have high SUA levels, both in terms of discussing the importance of healthy lifestyles and also having a lower threshold for starting meds. And the meds chosen might be different: eg, using losartan (but not other ARBs) or amlodipine/nifedipine for hypertension, since these lower SUA levels: see below.

a Danish study suggested that treating hyperuricemia in those with allopurinol led to fewer cardiovascular events

— another study provides an interesting evolutionary perspective on hyperuricemia, as well as a Taiwanese study finding a dramatic decrease in cardiovascular events by treating hyperuricemia

–here is my very brief blog on antihypertensives and uric acid from 2012, predating the bmj website:

— large study of general practices in UK, looking at 25K pts with gout. I had seen some older studies finding that losartan (but NOT other arb’s or ace-I’s) lower uric acid levels.  In this large UK database, they found a 19% dec risk of clinical gout with losartan (compared to other hypertensive pts), 13% with ccbs (21% dec with amlodipine, 13% with nifed, and 14% with dilt), with inc gout risk with diuretics, b-blockers, ace-I’s, other arb’s besides losartan.  They note in their discussion some studies (which I looked at and are pretty small…) find that ccbs (esp nifed and amlod) and losartan are uricosuric and decrease serum uric acid levels.  See doi:10.1136/bmj.d8190 ).  there have been some recent reports that high fructose corn syrup is perhaps the largest (or close to it) dietary component which increases uric acid.

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  ). 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

Reporting and appraising research: a cautionary tale

3 Oct, 16 | by Kelly Horwood, BMJ

Substituting various fats for carbohydrates or saturated fat: an uncertain recipe missing quantitative context and a cautionary example of reporting and appraising research

Guest Blog Post
Author: Martin Mayer, MS, PA-C
Institution: Department of Physician Assistant Studies, East Carolina University

Broadly speaking, science is a way of thinking that involves asking answerable questions about phenomena and then systematically and impartially pursuing means to reduce uncertainty about the answer as much as possible. During the pursuit, findings must always be appropriately contextualized to avoid inaccurate, disproportionate, or otherwise mistaken interpretations, as such mistaken interpretations run contrary to the raison d’être of scientific inquiry. Unfortunately, confusion about and mistaken or overreaching interpretations of research abound.

A recently-published article investigating various patterns of fat intake on total and cause-specific mortality1 speaks to the above and will add tangibility to the above considerations; it therefore serves as an instructive example to be considered in some detail, but the concepts considered herein are certainly more broadly applicable.


Nutritional studies are often plagued by methodologic shortcomings that preclude strong knowledge statements and contribute to implausible results.2,3 Perhaps most bothersome is the lack of methodologic rigor required to start making causal inferences about dietary patterns or interventions, and better designs do seem feasible with proper design and sufficient infrastructural support (including, importantly, funding).2,3

There have been reproachful whispers of “methodolatry” with respect to appraisal of research, and some champion observational data as reflecting “real-world” data; nevertheless, well-designed, well-executed randomized controlled trials (RCTs) are undoubtedly the most reliable method to assess interventional effects or cause-and-effect relationships. Due to inherent methodological limitations, observational data are typically unable or less able to provide such insight, though Hill’s classic criteria offer foundational considerations for the degree to which observational data can begin to facilitate or permit causal inferences.4,5 For instance, there will never be an RCT of smoking and lung cancer, but observational data make this causal link abundantly clear; however, such instances of observational data clearly demonstrating a causal relationship are decidedly uncommon.

Still, good observational data do have value, and to the extent people blindly view the RCT as a sacred cow of epistemology (e.g., not applying the same degree of critical appraisal to RCTs as one would observational studies, failing to consider a given RCT within the broader context of what is known about the topic at hand [greatly simplified, this latter concept forms the basis for the Bayesian notion of priors]), the reproachful whispers of “methodolatry” have considerable credence, elevating them to appropriate admonitions.


Wang and colleagues recently published an investigation of intake of specific types of fat and possible associations with total and cause-specific mortality; specifically, they investigated quintiles of intake for specific types of fat and isocaloric substitution of specific types of fat for either carbohydrates or saturated fat at certain levels of energy intake.1 Theirs is among the most recent of many similar studies investigating dietary patterns and patient-relevant outcomes.6-10

Wang and colleagues’ data come from two large and well-known prospective cohort studies: the Nurses’ Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). Follow-up for both cohorts via biennial postal questionnaires exceeds 90% of potential person-time. Wang and colleagues excluded those who did not report information on fat intake, those who reported what they considered to be implausible energy intakes (men, <800 or >4,200 kcal/day; women, <600 or >3,500 kcal/d), and those with a history of diabetes, cardiovascular disease, or cancer. The final sample for analysis had 83,349 women and 42,884 men and amounted to 3,439,954 person-years of follow-up. Dietary intake was assessed with a semiquantitative food frequency questionnaire (SFFQ); the SFFQ asks how often, on average, the respondent consumed a specified portion of food during the preceding year. For all but one survey used Wang and colleagues’ analysis, this was done for 116 to 150 foods. Wang and colleagues also collected detailed information on the type of fat or oil used when preparing food as well as the brand or type of margarines used. A total of nine SFFQ assessments from the NHS and seven SFFQ assessments from the HPFS were included in their analysis.


The large sample and long and fairly complete follow-up are obvious strengths of Wang and colleagues’ study, but sample size and follow-up duration and completeness are not themselves sufficient qualities to establish the reliability or meaningfulness of research; indeed, their study still suffers from typical and important weaknesses inherent to cohort data and questionnaire-based nutritional studies. For instance, the observational design with use of SFFQs in populations that offer only questionable generalizability (e.g., exclusively health care professionals with noteworthy exclusion criteria) leaves much to be desired, and to the extent one might be inclined to point to the frequency with which food surveys or similar methods of dietary assessment are used in nutritional research, this ultimately does nothing to lessen the marked uncertainties and methodological weaknesses inherent in such a strategy. Prevalence is not and never will be a per se indicator of rigor or acceptability, and to argue otherwise is tantamount to argumentum ad populum (argument from popularity). While Wang and colleagues acknowledge weaknesses in their study to a certain extent in their discussion, they still make overly-assertive statements (e.g., “Our analyses provide strong evidence that using PUFAs [polyunsaturated fatty acids] and/or MUFAs [monounsaturated fatty acids] as the replacement nutrients for SFAs [saturated fatty acids] can confer substantial health benefits”1(p1142)) even though they later state “causality cannot be established” 1(p1143) by their study.

Although Wang and colleagues make efforts to provide evidential context for their findings via their discussion of related literature, another prominent weakness of their article is failure to provide appropriate quantitative context for their findings even if one theoretically accepts their findings as being likely reflective of an underlying truth (which must in reality be decided only after careful critical appraisal). This becomes even more problematic due to their repeated statements of “substantial” findings, sometimes also erroneously using causal phrasing (e.g., “can confer substantial health benefits”1(p1143)). Unfortunately, they only report associated relative metrics, which precludes a straightforward quantitative evaluation of their findings and even lends to an exaggerated sense of the findings.


It is imperative to seek satisfactory appreciation of the quantitative implications of research findings, perhaps particularly when the research does not readily lend itself to such. When it is possible to construct or otherwise establish a reasonable quantitative framework, one can then use this framework as a thought experiment of sorts to help gauge the potential meaning of given findings under the (potentially strong) assumption that the research actually reflects an underlying truth. One can then subjectively levy any weaknesses in the methodology against this “best-case-scenario” framework in an attempt to form a judicious appreciation for the research findings.

Using the total number of deaths and person-years of follow-up in the individual cohorts and pooled dataset, one can derive baseline estimates for rate of death (supplemental file). With these baseline estimates, one can use the hazard ratios from the rightmost column of Tables 2 and 3 in Wang and colleagues’ study to estimate the associated risk of death with isocaloric substitution of a particular fat for total carbohydrates at a particular percentage of energy intake (supplemental file).11 One can use Figure 2 in Wang and colleagues’ study to do the same for substitution of a particular non-saturated fat for saturated fat (supplemental file). Finally, one can then derive absolute risk differences between baseline risk estimates and the dietary-substitution-adjusted risk estimates (supplemental file).

It is not clear why Wang and colleagues did not provide such estimates, and further data or analysis from the authors’ dataset might allow for better or additional estimates than those outlined above and in the supplemental file; in the absence of such, however, it remains important to consider what the reported data might mean on an individual level, and the above approach is certainly reasonable.


Wang and colleagues’ study ultimately leaves much to be desired, one should remember they conducted their study in an attempt to help clarify existing uncertainty surrounding this topic, and other research echoes the sentiment of uncertainty.7 So, although sometimes a reflexively-offered sentiment, further – and better – research does seem indicated. Additionally, relative metrics are most useful when appropriately applied to corresponding baseline absolute risks, but relative metrics in isolation are considerably less informative and can contribute to distorted appraisal of research findings. This can be readily appreciated via the supplemental file or by simply considering, for instance, the absolute versus relative difference between 0.5% and 0.25% (0.25% versus 50%, respectively). Relative metrics might also convey important information when pursuing a population-level appreciation of research findings. While this is certainly not irrelevant, clinicians and patients ultimately care most about applying research on an individual level. The additional quantification of Wang and colleagues’ data shows how this can be estimated (at least in the setting of hazard ratios) when estimates of absolute differences are not provided. With specific regard to Wang and colleagues’ study, the estimation of absolute risk differences suggests much less “substantial” findings than what Wang and colleagues’ article suggests even if one thought their findings were valid, and then when one considers the notable weaknesses in Wang and colleagues’ study, the absolute risk differences seem even less “substantial”.

The considerations herein, although important, are but a whisper amidst a roaring literature pertaining to the execution, translation, and application of medical research. Nevertheless, this writing hopefully makes clear the importance of researchers maintaining the utmost care when reporting research, always providing balanced and objective qualitative and quantitative context for their findings; similarly, readers must maintain an exquisitely judicious approach to the appraisal, synthesis, translation, and application of research.


  1. Wang DD, Li Y, Chiuve SE, et al. Association of specific dietary fats with total and cause-specific mortality. JAMA Intern Med. 2016;176(8):1134-1145. doi:10.1001/jamainternmed.2016.2417. Epub 2016 Jul 5.
  2. Nissen SE. U.S. dietary guidelines: An evidence-free zone. Ann Intern Med. 2016 Apr 19;164(8):558-559. doi: 10.7326/M16-0035. Epub 2016 Jan 19.
  3. Ioannidis JP. Implausible results in human nutrition research. BMJ. 2013 Nov 14;347:f6698. doi: 10.1136/bmj.f6698.
  4. Hill AB. The environment and disease: association or causation? Proc R Soc Med. 1965;58(5):295-300. PMCID: PMC1898525.
  5. Lucas RM, McMichael AJ. Association or causation: evaluating links between “environment and disease”. Bull World Health Organ. 2005 Oct; 83(10):792-795. PMID: 16283057. PMCID: PMC2626424.
  6. Chowdhury R, Warnakula S, Kunutsor S, et al. Association of dietary, circulating, and supplement fatty acids with coronary risk: a systematic review and meta-analysis. Ann Intern Med. 2014;160(6):398-406. doi: 10.7326/M13-1788.
  7. de Souza RJ, Mente A, Maroleanu A, et al. Intake of saturated and trans unsaturated fatty acids and risk of all cause mortality, cardiovascular disease, and type 2 diabetes: systematic review and meta-analysis of observational studies. BMJ. 2015;351:h3978. doi: 10.1136/bmj.h3978.
  8. Farvid MS, Ding M, Pan A, et al. Dietary linoleic acid and risk of coronary heart disease: a systematic review and meta-analysis of prospective cohort studies. Circulation. 2014;130(18):1568-1578. Epub 2014 Aug 26. doi: 10.1161/CIRCULATIONAHA.114.010236.
  9. Jakobsen MU, O’Reilly EJ, Heitmann BL, et al. Major types of dietary fat and risk of coronary heart disease: a pooled analysis of 11 cohort studies. Am J Clin Nutr. 2009;89(5):1425-1432. doi: 10.3945/ajcn.2008.27124.
  10. Mozaffarian D, Micha R, Wallace S. Effects on coronary heart disease of increasing polyunsaturated fat in place of saturated fat: a systematic review and meta-analysis of randomized controlled trials. PLoS Med. 2010;7(3):e1000252. doi: 10.1371/journal.pmed.1000252.
  11. Altman DG, Andersen PK. Calculating the number needed to treat for trials where the outcome is time to an event. BMJ. 1999 Dec 4;319(7223):1492-1495. PMID: 10582940. PMCID: PMC1117211.

Primary Care Corner with Geoffrey Modest MD: Empaglifozin, the good and the bad

21 Dec, 15 | by EBM

By Dr. Geoffrey Modest

A recent study looked at the SGLT2 inhibitor (sodium-glucose cotransporter 2) empagliflozin and cardiovascular outcomes/mortality in patients with type 2 diabetes (see N Engl J Med 2015;373:2117​). The SGLTs are involved in active renal transport of glucose in the kidneys, and SGLT2 is the most important one (reabsorbs 90% of the glucose filtered by the glomeruli) and seems to be pretty kidney-specific (SGLT1 is less important in active glucose transport, getting the remaining 10%, and is more widely expressed and therefore more likely to have broader physiologic effects and adverse effects if blocked). The context of this study is that there are a slew of studies showing markedly increased cardiovascular (CV) mortality in patients with type 2 diabetes, this relationship seems to be dose-related, and the increase extends to those with pre-diabetes/glucose intolerance. Other studies have shown that empagliflozin is associated with weight loss, reductions in blood pressure, increases in both LDL and HDL, and decreases in arterial stiffness/vascular resistance, visceral adiposity, albuminuria, and plasma urate levels (all of these might contribute to CV disease).

Details of the current study:

  • 7020 patients (mean age 62, 72% white/22% asian/18% latino, BMI 30.7, A1c 8.08%, 74% on metformin/49% insulin with mean dose 52 units/43% sulfonylurea/11% DPP-4 inhibitor/4% TZD, 95% hypertensive, 80% on lipid-lowering therapy. 83% on aspirin), all with established cardiovascular disease, all with A1C=7-9 and not on meds for >12 weeks or A1C=7-10% and on stable diabetes meds for >12 weeks). Subjects were randomized to empagliflozin 10mg, 25mg, or placebo daily, followed 3.1 years
  • Excluded: BMI >45, eGFR <30,  fasting glucose >240, ALT >3x upper limit of normal


  • 4% prematurely stopped the study drug (similar to placebo)
  • Weight decreased with med from 86 to 84 kg, waist circumference from 105 to 103 cm, SBP from 135 to 132 mmHg, DBP from 76 to 75 mmHg, LDL increased from 88 to 90 mg/dL and HDL from 44 to 46 mg/dL, uric acid decreased from 6 to 5.7 mg/dL
  • In the group on placebo, 31.5% had changes in their other diabetic meds, esp. sulfonylureas (increased 3.8% in those on empagliflozin and 7.0% on placebo), insulin (11.5% vs 5.8%), TZD (not sure which used, but increased 2.9% vs 1.2%), DPP-4 increased (8.3 vs 5.6%)
  • A1c was about 0.5% lower in those on empagliflozin, though there were changes as noted in other diabetic meds given
  • ​Primary outcome (composite of death from CV causes, nonfatal MI or nonfatal stroke) in 490 of 4687 (10.5%) of those in the pooled empagliflozin groups, vs 282 of 2333 patients on placebo (12.1%), so HR 0.86 (0.74-0.99; p=0.04)
  • No difference in rates of MI or stroke, but a lower death rate from CV causes (3.7% vs 5.9%, relative risk reduction RRR of 38%), hospitalization for heart failure (2.7% vs 4.1%, RRR of 35%), and death from any cause (5.7% vs 8.3%, RRR of 32%)
  • No difference in secondary outcome (primary outcome plus hospitalization for unstable angina)
  • Adverse events: increase in genital infections (5% in men vs 1.5% on placebo, 10% in women vs 2.6% on placebo). Rest nonsignificant.

So, a few issues (many of which were buried in the supplemental materials, which seems to be happening a lot in the past few years and my guess is that relatively few readers delve into these details, in part because it is a hassle, in part because it requires full, and expensive, access to the journals, and also is on the internet only. BUT it is often hard to really interpret the studies without seeing them…)

  • Of the very significant difference in CV deaths (5.9% in placebo and 3.7% with empagliflozin), the largest single category was “other cardiovascular death” (2.4% vs 1.6%) which “includes fatal cases that were not assessable due to a lack of information and were presumed to be cardiovascular deaths as per conventional definition”. And much smaller numbers of other CV events (acute MI in 0.5 vs 0.3%, worsening in heart failure in 0.8 vs 0.2%, stroke in 0.5 vs 0.3%). these increases in “presumed” events really undercuts the significance of the cardiac effect, especially in light of the very small numbers of events in these very high risk patients over >3 years of follow-up
  • The beneficial effects of the empagliflozin were within 3-6 months overall, a very rapid change. This makes the change in A1C from increased excretion of glucose in the urine an unlikely candidate for the CV benefit, and perhaps a quick change in arterial stiffness is more likely, or a decrease in arrhythmias for unclear reasons (sudden death was the most common single cardiac death event, with 1.6% in those on placebo vs 1.3% in those on empagliflozin). But one might imagine an even more profound cardiovascular benefit by having more of the patients on statins (only 76% of this really high risk population were on statins!!!)
  • Unclear what thiazolidinedione was used. Rosiglitazone??? (Which has more CV events). Subgroup analysis did find a nonsignificant trend to increased CV death in those on TZDs overall, though the interpretation really depends on which is being prescribed (pioglitazone may actually decrease cardiovasc events, see next point)
  • I think the study was not really accurately framed. their comment that evidence of lowering blood sugar “reduces the rate of cardiovascular events and death has not been convincingly shown” in fact does have some reasonable support for a few agents:
    • Metformin in UKPDS: there was a 16% reduction in cardiovascular complications — combined fatal or nonfatal MI and sudden death with metformin (p=0.052), was borderline significant. In a further analysis, patients allocated to metformin, compared with the conventional group (including insulin and sulfonylurea), had risk reductions of 42% for diabetes-related death (p=0·017), and 36% for all-cause mortality (p=0·011) (seeLancet 1998; 352: 854)
    • A large VA study compared monotherapy with sulfonylureas and metformin, finding a 21% increased hazard ratio for CV events or deaths in those on sulfonylureas vs those on metformin (see Ann Intern Med. 2012;157:601-610.)
    • Pioglitazone: in the PROACTIVE study, the main secondary endpoint was the composite of all-cause mortality, non-fatal myocardial infarction, and stroke. 301 patients in the pioglitazone group and 358 in the placebo group reached this endpoint (0·84, p=0·027) (see Lancet 2005; 366: 1279)
  • Not to surprise you too much, but the cost of this drug is actually a lot: $5000/year with very low absolute benefit
  • And, within days of release of this article, the FDA released a warning for SGLT2 inhibitors (see, noting the risks for ketoacidosis and serious urinary tract infections. Updating their May 2015 warning, the FDA noted that 73 cases of diabetic ketoacidosis and 19 cases of urosepsis and pyelonephritis that started as UTIs have now been reported in patients taking these drugs, with some needing ICU treatment and dialysis (and this undoubtedly does not include all cases). So, be aware of these issues and stop the med/treat promptly​. They are now requiring postmarketing safety studies for 5 years.  But, as noted in prior blog , <20% of required postmarketing studies for medical devices were done within 3 years of the FDA requiring them, and no fines have been issued for noncompliance with the FDA mandates.  Also, as a point of reference regarding the DKA issue: noted the increase in ketoacidosis with SGLT2 inhibitors, with 1/2 the cases without any typical DKA triggering factors (e.g. infection), events happened in some with only very mildly elevated blood sugars (including <200 mg/dL), and ketoacidosis ranged  from 1-175 days after starting the med.

So, what is one to do??? As many of you may be aware, I am pretty hesitant to jump on the bandwagon of new drugs, especially when we have drugs that work pretty well. There are a lot of questions above about this study, ranging from what additional drugs were used in the placebo group (more sulfonylureas, which don’t seem to have much CV benefit and may even have some harm; and ??rosiglitazone — unclear if this was used). Also the likely mechanism of action was not by lowering the A1c, given the rapidity of decreasing cardiovascular events, so is this the best drug to achieve the benefit? Should more people be on statins? And SGLT2 drugs are not necessarily benign (hence the FDA warning).​

Primary Care Corner with Geoffrey Modest MD: Medication in Elderly with Comorbidities

21 Oct, 15 | by EBM

By Dr. Geoffrey Modest

BMJ printed a new population-based cohort study looking at guideline-recommended drugs and deaths in older adults with multiple chronic conditions (see BMJ 2015;351:h498). These guidelines were typically based on randomized control studies with younger people and a single chronic condition.


  • 8578 older adults (mean age 77 with 36% >80yo, 59% women, 87% white), having multiple chronic conditions: hypertension (HTN)  92%, hyperlipidemia (HL) 77% , diabetes (DM) 40% , coronary artery disease (CAD) 39%, depression (DEP) 26%, heart failure (HF) 20%, atrial fibrillation (AF) 19%, chronic kidney disease (CKD) 12%, and thromboembolic disease 6%.
  • Data were from Medicare Current Beneficiary Survey cohort, a nationally representative sample of Americans >65yo, followed through 2011
  • The 9 study drugs: RAS blockers (ACE-I or ARBs) were used in 54%, statins in 53%, thiazides 47%, b-blockers 47%, calcium channel blockers (not differentiated by class) in 33%, SSRIs/SNRIs 21%, warfarin 14% , metformin 14%, clopidogrel 13%. 54% took at least 3 of the 9 study drugs. Mean total number of drugs (including nonstudy drugs) was 10. They also tracked changes in meds over the study period
  • Median follow-up of 24 months. 15% (1287) people died during follow-up.


  • Mortality over the 24 months: 27% in those with AF, 19% with CAD, 17% with DM, 33% with HF, 11% with HL, 15% with HTN
  • For the specific drugs (all of below were statistically significant), the HR for mortality was:
    • ​b-blockers: adjusted HR of 0.59 for AF, 0.70 for CAD,  0.68 for HF, and 0.48 for combo of AF/CAD/HL/HTN, 0.59 for HF/CAD/HL/HTN [note: an HR of 0.59 means a 41% decrease in mortality]
    • Statins:  HR 0.75 for CAD, 0.75 for DM, 0.68 for HL, and 0.65 for combo DM/CAD/HL/HTN, 0.68 for HF/CAD/HL/HTN, 0.70 for DEP/CAD/HL/HTN
    • Calc channel blockers: HR 0.78 for AF, 0.85 for HTN, and 0.69 for DM/CAD/HL/HTN, 0.71 for AF/CAD/HL/HTN and 0.72 for HF/CAD/HL/HTN
    • Thiazides: no significant benefits for HTN or any of the combo comorbidities
    • RAS blockers: 0.72 for HF, 0.80 for HTN, 0.82 for CAD, and 0.73 for AF/CAD/HL/HTN, 0.77 for HF/CAD/HL/HTN
    • Clopidogrel: no significant benefit for AF or CAD, or any of the combos (aspirin use could not be tracked in this database)
    • SSRI/SNRI: no significant benefit for DEP or any of the combos
    • Metformin: no significant benefit for DM or any of the combos
    • Warfarin: 0.69 for AF, 0.44 for thromboembolic dz, but no benefit for any of the combos​

So, this study, I think, is important for several reasons:

  • It largely reinforces what we are already doing, treating older patients with comorbidities based on the usual randomized controlled trials which typically limited the age range to younger patients and those usually limited to a single disease (e.g., excluding those with renal failure, etc.). And, of course, as people get older, they regularly and routinely develop multiple comorbid conditions
  • The study shows that in patients with multiple common comorbidities, the usual medications do improve mortality, even in a pretty short-term 2-year study. And the association between drug use and mortality was pretty similar across patterns of coexisting comorbidities, suggesting that similar benefits were evident despite the presence of comorbidities. This last finding supports the utility of randomized control trials limited to a single disease and then being applied more generally, at least in the above diseases/medications.​​
  • Although there is empirical evidence that observational studies usually have similar results to controlled intervention studies (see Cochrane Database Syst Rev 2014;4:MR000034), one has to remain somewhat skeptical that there could be unexpected biases. This study was quite good in that it incorporated certain social comorbidities (e.g. functional level, amount of time in the hospital, and living in a nursing facility), but still is open to the potential for other potential biases
  • For example, it is pretty clear that many of the cardiac meds do well. The hardest one for me to accept is that metformin does not have clear benefit, though on each analysis, there was a clear non-significant trend to benefit. My guess is that there is a strong selection bias here: those who are sicker do not get metformin. My bet is that they have a little (or lot) of renal dysfunction, or heart failure, etc., which scare the providers away from using metformin, leaving only the healthier elderly on it (and with a lower likelihood of showing mortality benefit in the healthier subgroup over a short 2-year study).  [Though, there are strong arguments that metformin is still a safe drug in many of these cases, esp. at a lower dose: See]
  • There have been increasing studies showing that, for example, anticoagulation for the very common condition of atrial fibrillation seems to be safer in the elderly than we thought in the old days, and I do have several patients into their late 80’s/early 90’s doing very well on them. And we know that the benefits of statins are typically evident within 6 months of starting them (based on studies of mostly younger people but some elderly) – i.e., these drugs seem to work well and are pretty well tolerated in the elderly.
  • So, bottom line, this study provides some pretty strong scientific rationale for continuing to treat elderly patients with their common multiple medical conditions with the same meds we have been using based on studies of younger people with single diseases. ​But, it is also important to bear in mind that this study only looked at mortality, which is not the only important end-point….

Primary Care Corner with Geoffrey Modest MD: NSAIDs post-MI???

5 Mar, 15 | by EBM

By: Dr. Geoffrey Modest

A retrospective Danish study evaluated patients post-MI to see if taking NSAIDs influenced subsequent mortality, using their nationwide administrative registries. In Denmark, NSAIDs require prescriptions, except for the lowest dose ibuprofen. (see JAMA. 2015;313(8):805-814)​. Guidelines in Denmark advise that all patients with MI have dual antithrombotic therapy (aspirin and clopidogrel) for up to 12 months, then single agent thereafter, and discourage the use of NSAIDs. Details:

–61,971 patients (mean age 67.7, 63% men) were analyzed during a median followup of 3.5 years. 2% were not on antithrombotics, 19.7% on only one agent, 64.9% on aspirin plus clopidogrel, and 5% either on oral anticoagulant (OAC) alone or with one other agent, and 8.5% on triple therapy (aspirin, clopidogrel, and OAC). also 78.1% on b-blockers, 49.8% ACE-I/ARB, 75.1% statins, 24.3% PPIs

–34% filled at least 1 NSAID prescription: 23.1% ibuprofen, 9.9% diclofenac, 1.7% naproxen, 2% coxibs

–total number of deaths in the followup period was 18,105 (29.2%).  a total of 5288 (799 fatal) bleeding events occurred (8.5%) as well as 18,568 cardiovascular events (30.0%)

–crude incidence rates were (as events per 100 person-years):

–bleeding: 4.2 for those taking NSAIDs and 2.2 if not. Risk even higher when NSAIDs were added to double or triple antihrombotic regimens

–cardiovascular events: 11.2 for those taking NSAIDs and 8.3 if not​.

–multivariate analysis: adjusting for age; gender; comorbidities of peripheral or cerebral vascular disease, renal failure, COPD, previous bleeding; or concommitant med therapy (b-blockers, statins, ACE-I/ARB, glucose lowering drugs, diuretics, PPIs)

–increased bleeding with NSAIDs, HR=2.02 (1.81-2.26) –, ie twice the risk

​–increased cardiovascular risk, HR=1.40 (1.30-1.49)  — ie, 40% increase

–these increases were evident with NSAID use, independent of antithrombotic treatment, types of NSAIDs or duration of use
–for overall bleeding risk, highest for celecoxib (crude rate 9.1/100 person-yrs), then diclofenac (6.1), rofecoxib (4.6). Naproxen (3.3) and ibuprofen (3.1) were better than average. And no NSAI was 2.2

–for overall cardiovascular risk, highest for celecoxib (crude rate 25.9/100 person-yrs), then diclofenac (12.0), ibuprofen (10.0), and naproxen (7.4). And no NSAID was 8.3.

A few comments:

–Part of the issue may be that taking NSAIDs may decrease the antiplatelet efficacy of aspirin. For example, a study found that taking aspirin prior to NSAIDs did not block the cyclooxygenase-1 activity of aspirin (as measured by serum thromboxane B levels), BUT taking a single dose of ibuprofen 2 hours before aspirin did block the inhibition of thromboxane B and inhibition of platelet aggregation by aspirin. This was not found with acetaminophen or diclofenac (see N Engl J Med. 2001;345:1809).

–Several studies have looked at the different NSAIDs and cardiovascular outcomes, generally finding that naproxen is the safest. A recent network meta-analysis (see BMJ.2011;342:c7086) of 31 trials and >115,000 patient-years of followup found that ibuprofen had the highest risk of stroke, followed by diclofenac (which has somewhat better GI tolerability and is used a lot in Europe, has mixed anti-COX1 and anti-COX-2 effects, though it has stronger anti-COX-2 than most other nonselective NSAIDs, similar to celecoxib). Diclofenac is also associated with high risk of cardiovascular death. and, their conclusion: “Naproxen seemed least harmful”.

So, this study adds to several other observational studies finding adverse cardiovascular effects by the use of NSAIDs (with the possible exception of naproxen). But, as well as the known GI adverse effects, NSAIDs in general are associated with increases in blood pressure, heart failure, atrial fibrillation (in a couple of studies), stroke, MI, and cardiovascular death (these outcomes are noted both in patients with and without known cardiovascular disease). I personally think NSAIDs are way overused, especially in the elderly, and should be used sparingly, at the lowest dose and shortest duration possible, and that we should consider using acetaminophen, topical preparations or local injections when possible to treat pain. and, if NSAIDs are necessary, I think the data are pretty consistently better for naproxen.

Primary Care Corner with Geoffrey Modest MD: Dabagratan, again

30 Jan, 15 | by EBM

By: Dr. Geoffrey Modest 

There have been a slew of articles recently promoting dabigatran and the direct acting thrombin inhibitors, and a remarkable number of articles in the on-line throw-away journals (delete-away??), like MedPage, interviewing leading researchers (many on the pharma dole) extolling the virtues of these medications. Recent articles include:

1. A meta-analysis noting that dabigatran, rivaroxaban, apixaban and edoxaban are non-inferior to vitamin K antagonists in stroke prevention for patients with atrial fibrillation, assessed the endpoints of all-cause and vascular mortality along with safety issues (see DOI:10.1111/jth.12651).

–71,683 patients with nonvalvular atrial fibrillation (from 4 RCTs , with follow-up of 1.8-2.8 years) found significant declines in all-cause mortality by 11% with NNT=132 (p<0.0001) and vascular mortality by 12%, NNT =189 (p<0.0001)​, with a striking decrease in mortality from bleeding (RR 0.54, p<0.0001, esp. intracranial bleeding with RR 0.42, p<0.00001)

2. A meta-analysis were done of the efficacy and treatment of acute venous thromboembolism — VTE (see doi:10.1001/jama.2014.10538). they assessed 8 strategies, though this was a “network meta-analysis”, mathematically combining different studies, since there were no direct comparisons of them. Strategies included: unfractionated heparin (UFH), low-molecular weight heparin (LMWH) in combo with vitamin K antagonists (VKA), LMWH with dabigatran or edoxaban, rivaroxaban, apixaban, and LMWH alone.

–45 studies with 45K patients, 22 comparing UFH-VKA with LMWH-VKA. only 6 studies looked at the new agents (2 with rivaroxaban, 2 with dabigatran, one each with edoxaban and apixaban), median follow-up of 3 months.
–Compared with LMWH-VKA, UFH-VKA associated with increased risk of recurrent VTE (HR 1.42), with proportion of patients with recurrent VTE over the 3 months: UFH-VKA 1.84%, LMWH-VKA 1.30%. so, no statistically signif diff for efficacy in any of these strategies, except UFH-VKA (which did badly)
–Risk of major bleeding event: rivaroxaban with 0.49%, apixaban 0.28%, LMWH-VKA 0.89%, with apixaban being the only one with statistically significant decrease in bleeding

BUT, a study released by JAMA Internal Medicine assessed retrospectively the Medicare pharmacy and medical claims for 1302 people on dabigatran used in atrial fibrillation vs. 8102 on warfarin (see doi:10.1001/jamainternmed.2014.5398). This was a real-world post-marketing study, assessing major and minor bleeding events (major= intracranial hemorrhage, hemoperitoneum, hosp visits/admits for hematuria, GI or other hemorrhage).

–Dabigatran associated with higher risk of bleeding than warfarin– 32.7% vs. 26.5%, with HR 1.30 (CI 1.20-1.41) for any bleeding event, major bleeding 9.0% vs. 5.9%, with HR 1.58. GI bleeding​ 17.4% vs. 10.0%, with HR 1.58 (CI 1.36-1.83), though risk of intracranial bleeding lower with dabigatran, 0.6% vs. 1.8%, with HR 0.32 (CI 0.20-0.50)​
–The risk of major bleeding with dabigatran was especially high in certain subgroups: African Americans had more bleeding with dabigratan with HR 2.12, and patients with chronic kidney disease had an increase with HR 2.07. the increased rate of intracranial bleeds was only higher in warfarin in white patients older than 75 (no diff in those

So, what does this all mean? I posted several blogs on dabigatran, some showing drug company malfeasance in promoting it, both withholding data and their own sense that levels should be monitored (the big push for this drug was that you didn’t need to do INRs, so it was easy for patients and providers). Also an article on increase in MI and ACS. and one on post marketing surveillance and increased bleeding with dabigatran. the current article on the Medicare population confirms (at least to me) the importance of post-marketing surveillance. All-too-often, there are serious adverse effects of meds (eg COX-2 inhibitors such as vioxx….) that are not found on initial studies, either legitimately through the gaps of statistical analysis or drug company malfeasance (or both). Some may be due to study design or to the cloistered setting of the academic medical center and selection biases. In any event, post-marketing analysis provides larger numbers of real-world patients on the med. As noted below, one of the big issues with direct thrombin inhibitor bleeding, unlike warfarin, is that there is no antidote/ability to reverse the effect.

Primary Care Corner with Geoffrey Modest MD: Heart failure microbiome

28 Jan, 15 | by EBM

By: Dr. Geoffrey Modest

So, another microbiome blog (I can’t help myself). In a 5-year observational study of 720 patients with heart failure followed at the Cleveland Clinic, elevated levels of TMAO (trimethylamine-N-oxide) were associated with long-term mortality, independent of traditional risk factors and BNP or renal function (see Per prior conceptions, the role of the gut in heart failure was basically that splanchnic circulatory congestion led to changes in gut permeability and in intestinal barrier integrity leading to entry into the circulation of lipopolysaccharides from gram negative bacteria, activating cytokines and creating systemic inflammation. The current study basically found that the plasma TMAO levels were increased in those with CHF. TMAO is derived from foods containing carnitine (eg red meats) or lecithin (eg from eggs). (See the blog from 2013 at the end, which found that consumption of red meat actually led to changes in intestinal bacteria that, in the presence of red meat or carnitine, led to TMAO production). Other studies have found that increased TMAO levels is associated with coronary artery disease and poor prognosis, perhaps related to TMAO effects on cholesterol transport, macrophage activity, ?other mechanisms. (And, by the way, it is possible that the association between renal dysfunction and CAD is at least partly mediated by TMAO levels, since TMAO is renally-excreted). And other studies have found relations between the gut microbiome and obesity, type 2 diabetes, and chronic inflammation.

In the current study (sponsored by NIH):

–702 patients (mean age 67, 59% male, 41% with diabetes, 78% hypertension, 64% ischemic cardiomyopathy, BMI 28.4, with baseline meds: ACE-I/ARB 70%, b-blockers 70%, loop diuretics 59%, statins 61%, aspirin 64%; and baseline BNP 300, hsCRP 3.5) undergoing elective non-urgent caths, and followed 5 years
–Median TMAO level was 5.0 mM in this group, but 3.5 mM in a healthy cohort (their healthy cohort was 300 people without known heart disease from a health-screening program)
–Those with higher TMAO levels tended to be sicker: history of diabetes, renal insufficiency, lower HDL levels; and also to have higher BNP levels and diuretic use and lower use of b-blockers.
–BUT, there was a strong, graded association between TMAO levels and mortality, even after adjustment for traditional cardiac risk factors, with mathematical modeling showing that adding TMAO levels significantly improved the cardiac risk classification over the standard cardiac risk calculator (eg Framingham).
–TMAO levels were also significantly associated with mortality, controlling for BNP and eGFR
–Subgroup analysis showed no difference in outcome for those with ischemic or nonischemic heart failure
–Overall, 1.8-fold increase in mortality in patients with fasting TMAO levels >8.5m​M, controlling for all of these cardiac and renal risk factors

One interesting feature of this study is that there was no difference in the mortality associated with TMAO in those with ischemic vs. non-ischemic cardiomyopathies, suggesting that the pro-atherosclerotic mechanisms of TMAO really may only explain part of its toxicity in heart failure. Or that there are multifactorial changes with a disease such as heart failure, leading to diverse microbiome changes, with the production of TMAO plus other changes in other bacteria/toxins, etc.

So, not that I am going to run out and measure the TMAO levels on all of my patients with heart failure, but this study adds to other ones highlighting the significant role of the gut microbiome in health and disease. And the microbiome is very susceptible to changes in diet (as in blog below), use of antibiotics, even other meds. For example, there was a study of metformin (see dm metformin microbiome GUT 2014 in dropbox, or, the 7th most prescribed medicine and the first choice for diabetics (in part because of its cardio protection!!). This study was in mice, and found that those on metformin improved their glycemic profile, but significantly changed the gut microbiome to increase the bacterium Akkermansia. In another experiment, just increasing this bacterium (in the absence of metformin) also enhanced glucose tolerance and decreased adipose tissue inflammation, suggesting that an additional mechanism of action for metformin may be through its effect on the microbiome.

Bottom line: a healthy diet (esp. one high in fruits and vegetables — eg Mediterranean diet), exercise, and a generally healthy lifestyle are really important to preserving health, and deviations clearly affect the microbiome, which might be part of the cause of many of the common diseases in our society. What this really means is that our often simplistic/reductionist models (eg that the Mediterranean diet improves lipids, decreases inflammation, decreases oxidative stress, etc. etc.) sometimes leads us to miss the big picture: the better the quality of diet for example has profound effects on the overall, coordinated functioning of our complex bodies in ways we do not fully understand, and that medications which individually improve lipids, decrease inflammation, decrease oxidative stress etc. really do not fully compensate for lack of a good diet. medications are often necessary (and I certainly prescribe my fair share) but they also often have unanticipated changes in the body (eg effects of antibiotics on the gut microbiome). The key is for society to coherently and unambiguously promote these healthy lifestyle components and not rely on medications to compensate for the adverse effects of smoking, sedentary lifestyle, poor diet, job/social stress, etc.

Blog from 2013:

Article in NY times (see here) seems that presumptive coronary heart disease culprit of carnitine (in red meat, same Latin route at “carnivore”) may be only partially correct. Published in Nature Medicine. Turns out to (maybe) be more complex:

–In regular meat eaters, eating a sirloin leads to an increase in TMAO (trimethylamine-N-oxide), which in lab studies leads to accumulation of cholesterol in macrophages and also seems to decrease the ability to excrete excess cholesterol (for excruciating detail, see the paper itself), with some previous data that blood TMAO is assoc with CAD, both in humans and mice
–In vegans who had a similar meal of sirloin (presumably with a significant bribe), no increase in TMAO.
–Larger group of vegetarians given carnitine pill, also no increase in TMAO.
–So, speculation is that it was intestinal bacteria responsible (precursor TMA known to be produced by intestinal bacteria), and that the intestinal flora are different in vegetarians than meat-eaters — mouse studies show that increasing L-carnitine leads to changes in intestinal bacteria. beef has highest level of carnitine. Lesser amounts in fish, chicken, and dairy. Also in high-energy drinks for body-builders
–Meat-eaters pretreated with antibiotics to sterilize the colon did no have TMAO in their blood
–Further analysis of 2600 pts., controlling for traditional risk factors, found that TMAO and not carnitine was assoc with CAD

So, bottom line, might be good idea to pre-treat cows with even more antibiotics….

Primary Care Corner with Geoffrey Modest MD: CPR articles

26 Jan, 15 | by EBM

By: Dr. Geoffrey Modest

So, I happened to peruse the last few issues of the journal Resuscitation on my coffee table and found a couple of interesting articles about CPR… in any event, here are the articles.

1. A Swedish study looked at 222 patients who underwent unsuccessful CPR and had autopsies done (see​). of these 83 had manual CPR and 139 had mechanical with a LUCAS device (a Swedish mechanical device for doing chest compression, which in some studies achieved better circulation than manual compression). Results:

–75.9% of those in manual CPR and 91.4% with mechanical had CPR-related injuries
–54.2% with manual and 58.3% had sternal factures
–64.6% with manual and 78.8% with mechanical had at least one rib fracture (signif difference at p=0.02), with median numbers of ribs fractured at 7 in the manual and 6 in the mechanical groups.
–None of these injuries were considered to be cause of death
–Subgroups: all 46 patients with signs of osteoporosis had rib fractures, 82.6% with sternal fractures; and (perhaps related) older people tended to have more traumatic injury.
–(but this is a select group of nonsurvivors)

2. Another Resuscitation journal article looked at in-hospital cardiac arrest survivors to assess their memories in a prospective multi-center study (see Results:

–330 survivors of 2060 cardiac arrests (16%), of whom 140 were deemed fit to interview (not clear why so few?? The listed reasons were that they died after discharge, were not deemed suitable by their MD, or did not respond to the invitation to be included. But there is a likely significant selection bias in the 140 included)
–46% had memories with 7 cognitive themes: fear; seeing animals/plants; bright light; violence/persecution, e.g. being dragged through deep water; deja-vu; family being present or talking with them; recalling events post resuscitation, eg a tooth coming out after removing the endotrach tube.
–9% had “near-death experiences”
–2% recalled seeing/hearing actual events related to the resuscitation

So, what does this all mean?? I think CPR is a challenging conversation with patients, part of the issue being that the popular culture depicts it deceptively as typically successful and with really good outcomes. For example, a study done assessing the survival in reality-like medical TV shows from 1994-1995 (ER, Chicago Hope, Rescue 911) found that 75% survived CPR and 2/3 were discharged with full brain function (thanks, Jenny Siegel). It probably makes sense that patients have a more appropriate, medically grounded understanding. And the real outcome data are actually pretty bad. Out-of-hospital survival rates are in the 1-6% range (a 2012 study of adults found that only 2% of adults who collapse on the street and got CPR achieve a full recovery), perhaps in the 5-10% when done by EMS types. In-hospital, it is 15% or so of patients who survive to discharge (and many of these patients are not exactly restored to their former health…). These studies above highlight another component of the issue. A very high percentage develop rib fractures and other traumatic injuries (one concern about the poor survival rate in hospitals is that studies have found that trained health care providers pretty consistently do not do CPR correctly, though perhaps the higher rib fracture rate with the mechanical device attests not only to its improved achieved circulation but also to its actually really compressing the chest…..). And there are clearly documented psych effects (PTSD) along with some pretty miserable memories or associations. A study done in 1983 (which perhaps dates me a tad) looked at factors influencing survival post in-hospital cardiac arrest (e.g., terrible if have underlying diagnosis of pneumonia, sepsis, poor urine output/high BUN, prior fitness, or if resuscitation taking >30 minutes). But of significant interest to me was that of the 41 survivors (14% of those getting CPR and surviving to discharge), 100% reported a functional status decrease and 42% stated that they would NOT choose to be resuscitated in the future (up to 47% when asked 6 months later), see (cpr bedell nejm 1983 in dropbox, or N Engl J Med 1983; 309: 569-76). So, the patient may well be bringing to the discussion of CPR very unrealistic expectations, reinforced by the ambient culture. In order to get a real sense of what the patient wants, seems to me that we as clinicians should outline several of the issues above: the survival likelihood overall is not great (though of course some can be expected to do better than others: my guess is that the stats are better for the reasonably healthy 32 year old who arrests on the table getting electrophysiological studies), that there is a really high incidence of rib/sternal fractures with chest compressions (esp. if older, osteoporotic), and that patients rarely come back to their prior state (with cognitive, psychiatric and medical issues). Then the patient can choose more knowledgeably.

Primary Care Corner with Geoffrey Modest MD: Obesity and left ventricular mass in kids

25 Jan, 15 | by EBM

By: Dr. Geoffrey Modest
A long-term analysis of the Bogalusa Heart Study (in Bogalusa, LA) in kids has confirmed a longitudinal relationship between obesity and hypertension in the development of left ventricular remodeling/hypertrophy, with obesity being the most significant driver (see . There are a slew of studies finding that obesity and hypertension are associated with LVH (left ventricular hypertrophy). Prior pediatric epidemiologic studies from several different countries have pretty consistently found that there is an association between cardiovascular risk factors in kids and increased left ventricular mass, and that early risk factors predict adult LVH as well as LV geometry. This analysis looked at the long-term burden and trends of cardiovascular risk factors in kids and the development of LVH and LV geometry. The Bogalusa Heart Study is a biracial community-based study (65% white, 35% black) assessing the natural history of cardiovascular disease in kids, starting in 1973. There have been 9 cross-sectional surveys done in kids aged 4-18, then 10 more in 19-52 year olds who were analyzed initially as kids. in the current study, 1061 adults aged 24-46 who had been examined at least 4 times for BMI and BP starting in childhood were assessed for the total and incremental AUC (area under the curve) of BMI and BP and their relationship with different LV geometric shapes (normal, concentric remodeling or CR, eccentric hypertrophy or EH, and concentric hypertrophy or CH), with a mean follow-up of 28 years (see discussion below for significance of these terms).


–Baseline: for kids, the only significant racial difference was that DBP (diastolic blood pressure) was higher in black males.
— For adults at the end of the study, there were BMI differences (BMI higher in black vs. white, mostly because of being much higher in black women); blood pressures higher in black than white, male than female.
–LV mass: higher in black than white for both sexes, and higher in males than females. LV geometry: black patients had higher EH than whites.
–Higher BMI and both systolic and diastolic blood pressures in childhood and adulthood were associated with higher LV mass and LVH (adjusted for race, sex, and age) as well as with EH and CH but not with CR.
–This association was also with AUC and incremental AUC. for AUC, both SBP and BMI were associated with increased risk of both EH (41% and 73% increase, respectively) and CH (123% and 140% increase). for incremental AUC, both SBP and BMI were associated with increased risk of both EH (28% and 93% increase, respectively) and CH (104% and 99% increase)​.
–BMI had a consistently and significantly greater effect than did the BP measurements.​

So, the adverse effects of​ BMI and blood pressure begin in childhood, as evidenced in their increased LV mass. The AUC calculation was reflects the group averages of the sum of the heights of the risk factor multiplied by the time the risk factor was high, over sequential measurements, thereby reflecting the total cumulative burden of this risk factor. The incremental AUC was the individual’s variation from his or her own baseline, and therefore represented the trend of the risk factor over time for the individual patient. The AUC and incremental AUC were both strongly related to the adverse effect on LV mass and geometry, with most studies finding that CH, or concentric hypertrophy, is more strongly related to cardiac events, though EH, or eccentric hypertrophy, is also associated with risk. Since both of the AUC measurements were related to ventricular hypertrophy, this suggests that people who have less time with the risk factors or a lesser trend to an increase (eg, they lose weight, or lower their blood pressure), have less LV mass increases — though remember that this is still just an observational, not intervention study. But other studies do suggest that decreasing blood pressure can lead to relatively rapid changes in LV mass (eg, a metaanalysis found that of the five categories of antihypertensives studied, specifically b-blockers, diuretics, calcium channel blockers, ACE-I’s and ARBs, that b-blockers were unequivocally the worst and it seemed that ARBs were the best, with ACE-I pretty close behind in decreasing LV mass — see doi: 10.1161/HYPERTENSIONAHA.109.136655​) and other studies have found that decreasing LV mass decreases cardiac events (eg the LIFE study found that cardiac events were decreased by lowering EKG-LVH by either losartan or atenolol, but that losartan overall was much better than atenolol in decreasing LVH — see Lancet 2002; 359: 995–1003). Small studies of patients with bariatric surgery have found decreasing LV mass within months of surgery. So, bottom line, putting all of this together is: cardiac risk factors in kids tend to track into adulthood, the intensity and trend of the risk factor correlates with the effect on LV mass including concentric hypertrophy which is a pretty strong predictor of clinical events, that changes in these risk factors in kids does have an effect on adult LVH, that obesity is more of a risk factor than hypertension (at least for LVH), and (likely) if we as clinicians can help kids lose weight, this will have a positive effect on their risk of heart disease/strokes as an adult (and the earlier they lose weight, the better).

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