Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
10.1161/CIRCULATIONAHA.116.025629 Weight Loss and Heart Failure: A Nationwide Study of Gastric Bypass Surgery Versus Intensive Lifestyle Treatment Running Title: Sundström et al.; Weight Loss and Heart Failure Johan Sundström, MD, PhD1; Gustaf Bruze, PhD2; Johan Ottosson, MD, PhD3; Claude Marcus, MD, PhD4; Ingmar Näslund, MD, PhD3; Martin Neovius, PhD2 Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 1 Department of Medical Sciences, Uppsala University, and Uppsala Clinical Research Center Epidemio iolo logy lo gy Unit, Uni nit, t, (UCR), Uppsala, Sweden; 2Department of Medicine, Solna, Clinical Epidemiology Karolinska Institutet, Stockholm, Sweden; 3Department of Surgery, Faculty of Me M Medicine dicine and Health, Örebro University, Örebro, Sweden; 4Department of Clinical Science, Intervention and Te ech hno n lo ogy gy,, Karo olinska Inst tittutet, t,, Stockholm, Sto ock c hoolm lm,, Sweden Swed Sw e en Technology, Karolinska Institutet, Addres Address Addr esss for f r Correspondence: fo C rrres Co e pond ponden ence cee: Johan Sundström, Sundström MD, MD PhD Department of Medical Sciences Uppsala University Hospital 751 85 Uppsala, Sweden Tel: +46704225220 Fax: +4618509297 E-mail: [email protected] Journal Subject Terms: Obesity; Heart Failure; Cardiomyopathy; Primary Prevention; Lifestyle 1 10.1161/CIRCULATIONAHA.116.025629 Abstract Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 Background—Associations of obesity with incidence of heart failure have been observed, but the causality is uncertain. We hypothesized that gastric bypass surgery leads to lower incidence of heart failure compared to intensive lifestyle modification in obese people. Methods—We included obese people without previous heart failure from a Swedish nationwide registry of people treated with a structured intensive lifestyle program, and the Scandinavian Obesity Surgery Registry. All analyses used inverse probability weights, based on baseline bodymass index and a propensity score estimated using baseline variables. Treatment groups were well balanced regarding weight, body mass index and most potential confounders. Associations of treatment with heart failure incidence, as defined in the National Patient Register, were analyzed using Cox regression. Results—The 25,804 gastric bypass surgery patients had on average lost 18.8 kg more weight after 1 year, and 22.6 kg more after 2 years, than the 13,701 lifestyle modification patients. During a median of 4.1 years, surgery patients had lower heart failure incidence than lifestyle modification patients (hazard ratio 0.54, 95% CI 0.36-0.82). A 10 kg achieved weight loss after 1 year was related to a hazard ratio for heart failure of 0.77, 95% confidence interval 0.60 to 0.97, inn both treatment groups combined. Results were robust in sensitivity analyses. Conclusions—Gastric bypass surgery was associated with approximately one half lf the the incidence inci in cide ci denc de n e nc of heart failure compared with intensive lifestyle modification in this study of twoo llarge a gee ar nationwide registries. We also observed a graded association between increasing weight loss and decreasing risk of heart failure. Key-Words: Key-W -Wor -W ords or ds:: he ds hheart arrt failure; bariatric surgery, gastric gastrricc bypass, low calorie caloriie diet, weight loss ca 2 10.1161/CIRCULATIONAHA.116.025629 Clinical Perspective What is new? x In this study of nearly 40,000 obese people without previous heart failure from two Swedish nationwide registries, gastric bypass surgery was associated with approximately one half the incidence of heart failure compared with intensive lifestyle treatment including low and very low calorie diets. x The associations were to a large extent mediated by weight loss, partly mediated by effects of treatment on interim atrial fibrillation, diabetes, and hypertension, but likely not mediated by the effects of treatment on myocardial infarction. Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 x Results were robust in multiple sensitivity analyses. What are the clinical implications? x Taken together with previous Mendelian randomization findings, this supports a causal effect of obesity on heart failure. x With (currently W Wi th increasing increa in easing obesity prevalence (current r ntly affecting half hal alf a billion bill bi l ion people worldwide) and heart fa ffailure iluuree be bbeing in ng th thee le lead leading a in ing caus cause se off hos hospitalization osspi pita tali ali liza zatiionn and and hhospital ospi pita pi tall co ta cost costs s s in W st Western esste tern r societies, strong incentive societie es, th the pu public hhealth ealth implicationn ooff tthese hese see oobservations b erv bs errvation ons is a str t ong inc tr centiv cen ive for prev pr prevention even ev enttionn aand en ndd aaggressive ggress gg ssiv ss ivee tr iv tre treatment eatm men entt of oobesity. beesity ty y. 3 10.1161/CIRCULATIONAHA.116.025629 Introduction One billion people worldwide are overweight and another half billion obese, and these numbers are increasing.1 Obesity may lead to heart failure, the leading cause of hospitalization in Western societies.2 The association was observed in the Framingham Heart Study,3 has since been confirmed by multiple other observational studies4 and is backed by experimental evidence.5 In support of a causal association are Mendelian randomization study findings6 and observational findings of beneficial effects of bariatric surgery on cardiac function in obese patients.7 The effect of substantial intentional weight reduction on heart failure incidence among Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 obese people is unknown. Such evidence is unlikely to be produced by randomized trials, as heart failure is rare in middle-aged, requiring long follow-up in large samples. We hypothesized that gastric bypass surgery leads to lower incidence of heart failure compared with intensive lifestyle modification among obese people, due to its larger effect on weig weight ighht loss. We hence ig hen encee aimed en aim imed ed to to compare comp co m ar are the in incide incidence dencee of hheart eartt ffailure ea ailu ai lure re iin n a na nati nationwide tion ti onwi on w dee rregistry egis eg isstr tryy of o obe obese ese persons tr trea treated eateed w with ith a structured d iintensive ntensiive llifestyle iffessty tyle le m modification odificcationn pprogram od rog ogram ve og versus erssus those inn a nationwide quality of care registry of bariatric surgeryy who und derwent gastric bypass surgery. underwent Methods Study design and participants The cohorts used in the present study were the Scandinavian Obesity Surgery Registry (SOReg)8 and the Itrim Health Database.9, 10 SOReg is a nationwide, prospective electronically captured quality of care registry for bariatric surgery,8 started in 2007 and estimated to cover 98.5% of all bariatric surgery procedures in Sweden. For this study, data were available between 2007 and 2012. 4 10.1161/CIRCULATIONAHA.116.025629 The Itrim Health Database is a registry of individuals treated with low- or very-lowcalorie-diets (LCD/VLCD) and lifestyle modification.9, 10 The registry prospectively collects data on individuals participating in the commercial weight loss programs at 38 Itrim franchise centers across Sweden, using a common electronic platform for quarterly follow-up of a standardized set of clinical variables. For this study, data were available from 2006 to 2013. In the present study, people aged 18 or older with a baseline BMI between 30 and 49.9 were included from SOReg and Itrim (Supplemental Figure 1). We excluded people who crossed over from Itrim to SOReg (n=811), and people with missing data on education or marital status Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 (n=254). No participant had a history of heart failure before baseline, as determined in the same way as the outcome, described below. The study was approved by the regional ethics committee in Stockholm, Sweden. All analyses were performed on de-identified data. Interventions nteerventions All SOReg SOReg participants parrtic i ip ipants ts und underwent der erwent pprimary rima mary ga gastric astricc bbypass ypaass yp s ffor or wei weight ight lo loss oss purposes, purposess, 96.0% 96. 6.0% off which were conducted d laparoscopi ically. laparoscopically. All Itrim participants started with a 3-month weight loss phase with either LCD or VLCD treatment, determined based on baseline BMI, personal preference, and contraindications. The structured weight-loss program is presented in detail in the Supplemental Methods. In short, VLCD treatment was a liquid-based formula diet of 500kcal/day for 3-10 weeks followed by 2-8 weeks gradual introduction of normal food. In June, 2009, the program was changed to 600kcal/day for 3 weeks followed by 800kcal/day for up to 9 weeks. The LCD treatment included 2 calorie-restricted normal food meals and 2 formula-diet meal replacement sachets per day providing a total caloric intake of about 1200-1500kcal. 5 10.1161/CIRCULATIONAHA.116.025629 After the weight-loss phase, patients entered a 9-month weight maintenance program of exercise, dietary advice, and behavioral therapy. Covariables Participants were linked to nationwide health registers using the unique Swedish personal identity number. From these registries, data were obtained on socioeconomic variables, diseases, and drug treatments. Data sources and definitions using the International Classification of Diseases (ICD) and Anatomical Therapeutical Chemical (ATC) classification system codes used are given in the Supplemental Table 1. In SOReg, blood pressure was measured as part of routine Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 healthcare; in Itrim, blood pressure was measured using a standardized protocol (Supplemental Table 1). We imputed missing data for smoking and systolic blood pressure (eachh mi miss missing s in ingg in approximately 25% of participants) using multiple imputation from all other complete baseline data. Baseline characteristics in persons with complete data versus those with any missing data are pr presented in Sup Supplemental uppllem up men e taal Table Tabl Ta blee 2.. bl Foll lloow-up and ll d out utco ome Follow-up outcome Participants were followed f llowed in the National fo N tional P Na Patient atient Register Register andd the Causes off Death Re R Register gister until December 31, 2014. Patients were followed from the treatment date until the first instance of the outcome, death, emigration, or end of follow-up. Itrim participants who during follow-up crossed over to bariatric surgery were censored at the cross-over date. During follow-up, 135 participants emigrated, making register-based follow-up complete for 99.5%. The primary outcome was the first hospitalization for heart failure, ICD-10 I50 as main reason for hospitalization, retrieved from the National Patient Register. We have previously shown this outcome to have 95% positive predictive value in a validation study.11 The secondary outcome was non-ischemic heart failure, defined as the first hospitalization of heart failure that 6 10.1161/CIRCULATIONAHA.116.025629 was not preceded by a myocardial infarction (censoring patients at time of myocardial infarction). In mediation analyses, interim instances of myocardial infarction and atrial fibrillation were obtained from the National Patient Register, and diabetes and hypertension were defined based on drug treatment at one-year follow-up. Statistical analysis We estimated a propensity score for treatment (surgery/lifestyle), see Supplement for variables included in the analysis (Supplemental Methods). Common support was observed over the Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 majority of the propensity score distribution but 988 persons (2.3%) had to be dropped at the lower ower end and 3291 (7.5%) at the upper end of the distribution. We checked for balance bal alan ance an ce iin n covariables covariabl a es between the treatment groups using weighted analyses described below, and using standardized tandardized differences in means. We the then en us used sed e coarsened coar co arse ar sene nedd ex ne exac exact a t ma m matching tching n 12 too as ng assign ssi sign gn iinverse n er nv erse se pprobability roba ro b bili lity li ty w weights eights ei t ((IPW) ts IPW) IP W) to the he participants pa ts based bas ased oon n baseline baaseline see BMII and and thee pro propensity ope pens nsit ns ityy score. it sccore. T This his procedure proccedure as pr assigns ssign gns an IPW PW too each partic participant i ipant ba bbased sed on the number of parti participants icipants in the two treatment groups in strata off the variables chosen for the matching. This weight was used in all further analyses. We excluded 11 persons who could not be matched. The resulting study sample consisted of 39,505 persons. Associations between treatment and weight loss were described using mixed models with body weight at baseline and one- and two-year follow-up visits as dependent variables, fixed effects for time and treatment and a random intercept for participant identification. Associations of treatment with heart failure incidence were estimated using Cox proportional hazard models. Proportionality of hazards was investigated using Schoenfeld’s tests. 7 10.1161/CIRCULATIONAHA.116.025629 We analyzed if the association of treatment with heart failure incidence was mediated by weight loss per se in two ways. Both analyses made use of a weight measurement at the one-year visit, and start of follow-up was reset to the one-year visit. First, we studied if there was a graded association between achieved weight loss at one year with the incidence of heart failure. To the total sample, including both treatment groups, we fit a model that included the three independent variables of baseline weight, treatment group, and achieved weight loss at one year (modeled using a linear term due to the limited number of cases). Second, we re-weighted the sample and included body mass index at one year, in addition to the other weighting variables (baseline Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 characteristics of that sample are provided in Supplemental Table 3), in order to investigate if achieved weight loss was a major mediator of the effect. We used generalizedd structural equation modelling modelling to investigate if parts of the associations between weight loss and incident heart failure were mediated by myocardial infarction, nfaarcction, atri atrial ial fib fibrillation ibrilllattio ib ionn (b (bot (both othh as tim ot time-updated me-updat a ed at d variables), varia iabl ia bles bl es), es ), dia diabetes iabe bete be tes or o hyp hypertension yper yp e te er tens n ionn (b ns (bot (both o h at ot a the he on one-year visit), viisi sit)), each ch in a separate analyses, analysess, assu assuming sumi ming mi ng ssequential eq quenttiaal igno ignorability norrab rability inn tthe hee associations of weight lloss oss with mediators and heart heart failure and d no post-weight-l post-weight-loss loss confounders. confoundders In order to investigate potential competing risk, we constructed a composite outcome consisting of the first instance of heart failure, myocardial infarction or cardiovascular death. In a sensitivity analysis, we also adjusted the main model for variables that differed between the weighted groups (standardized difference in means 0.1). IPW is an effective way of minimizing selection bias, but relies on a correctly specified propensity score. Therefore, as sensitivity analyses, we also investigated associations of treatment with heart failure incidence using Cox analyses stratified by levels of a combination of the propensity score and baseline 8 10.1161/CIRCULATIONAHA.116.025629 BMI, and using Cox analyses adjusted for restricted cubic splines of the propensity score and BMI. We also investigated the multiplicative interaction term treatment group*sex. In a secondary analysis, we restricted the sample to patients usually determined to be eligible for bariatric surgery (BMI above 40, or BMI between 35 and 40 with significant obesityrelated comorbidity defined as hypertension, diabetes, and previous myocardial infarction). For comparisons of heart failure rates in the obese samples with a general population sample, we matched up to 10 comparators from the Swedish Total Population Registry13 to each patient who had gastric bypass surgery, on birth year, intervention year, sex, and place of Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 residence (county, commune, parish). Two-sided tests with a 5% alpha level were considered statistically signif significant. fic ican antt. St an Stat Stata ataa 14 at was used for all analyses. Results Resu sullts su Participant Part rtiicipant characteristics rt ch harac acteeriisticss In with 13,701 n this study, 25,8044 persons were treated d wit i h gastric bypass surgery and 13 3,7011 with h lifestyle modification. Baseline characteristics of the study sample are outlined in Table 1. Weight and BMI were perfectly balanced between the weighted treatment groups. Minor differences in systolic blood pressure, income, and use of antihypertensive, antidiabetic, and lipid-lowering drugs were still apparent between the weighted treatment groups, all favoring the lifestyle participants (Table 1). Effects of treatment on weight loss and heart failure On average, surgery led to 18.8 kg more weight loss than lifestyle treatment at the one-year follow-up and 22.6 kg more weight loss at the two-year follow-up visit. Development of weight, 9 10.1161/CIRCULATIONAHA.116.025629 waist circumference and body fat during the first two years of the study are displayed in Figure 1. During a median follow-up of 4.1 years (range 0.0 to 9.0), 73 new heart failure cases occurred with an incidence rate of 5.4 per 10,000 person-years at risk (95% confidence interval 3.5 to 8.7). Of these, 29 occurred in the lifestyle group and 44 in the surgery group, with incidence rates of 7.6 (3.4 to 21.3) and 4.1 (3.1 to 5.6) per 10,000 person-years at risk, respectively. Surgical treatment was hence associated with lower incidence of heart failure than lifestyle treatment (hazard ratio 0.54, 95% confidence interval 0.36 to 0.82). Cumulative hazards Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 are presented in Figure 2. The absolute five-year risk of heart failure was 0.4 % among the lifestyle ifestyle modification patients and 0.2% among surgery patients. The incidence of heart failure in the age-, sex- and place-ofplace-of-residence-matched f residence-matched general population sample was 3.0 (2.7 to 3.4) per 10,000 person-years at risk. Mediation Me edi diation anal analyses alysses al e In n aanalyses n lyses using na usin ingg on in oneone-year -year achieved ac weight weiight loss lo osss and an setting sett se ttin tt ing start in st of of follow-up folllo ow-up to the h one-year he one-yearr visit, 31,347 311,3477 persons participated and 500 cases of he hheart art failure occurred. We ffound ound a ddoseoseresponse relationship between one-year weight loss and risk of heart failure with a hazard ratio for a 10 kg weight loss of 0.77, 95% confidence interval 0.60 to 0.97, in a model adjusting for baseline weight and treatment fitted to the two treatment groups combined (Figure 3). In an analysis weighted also for BMI at one year, no association of treatment group with risk of heart failure was seen (hazard ratio 1.09, 95% confidence interval 0.62 to 1.92), supporting that the achieved weight loss is a major mediator of the effect. Among 39,114 persons without myocardial infarction before baseline, 67 heart failure cases occurred without an interim myocardial infarction. Surgery was associated with lower 10 10.1161/CIRCULATIONAHA.116.025629 incidence also of this non-ischemic heart failure (hazard ratio 0.48, 95% confidence interval 0.31 to 0.74). The association of treatment with heart failure in the total sample was not mediated by the effects of treatment on myocardial infarction to any substantial extent, but appeared to be partly mediated by effects of treatment on interim atrial fibrillation, diabetes and hypertension (Table 2). Sensitivity analyses In a sensitivity analysis investigating potential competing risk, we included 39,114 persons Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 without prior heart failure or myocardial infarction. Of these, 244 suffered a composite endpoint of a first instance of heart failure, myocardial infarction or cardiovascular death (69 (669 experienced expe ex peri pe rien ri ence en ced ce heart failure, 113 a myocardial infarction, and 72 died from cardiovascular disease; patients could expe experience p rience more than one outcome). The surgery group experienced a lower rate also of this hiss composite compositee endpoint; endp dpoiint nt;; hazard hazaard rratio ha atio at i 00.58 .58 (95% .5 % cconfidence onfide denc de ncee in nc iinterval teerval rval a 0.4 0.46 .46 to o 00.74). .74) .7 4).. Off tthe 4) he 1113 13 myoc myocardial ocardial inf oc infarctions, far arcttio onss, 51 occurred occurred in th the he lifest lifestyle tylee m modification odif od ific if icat atio on group gr p (rate (raate 9.2 pe per er 10 10,000 0,000 person-years at risk risk; k; 95 95% confidence interval 4.2 to 23.7), and 62 iinn the surgery group (rate 5.9 59 5. per 10,000 person-years at risk; 95% confidence interval 4.6 to 7.7). In a sensitivity analysis adjusting the main model for variables that differed between the weighted groups (use of antihypertensive, antidiabetic, and lipid-lowering drugs, loop diuretics, education level and inclusion year), results were similar to the main model (hazard ratio 0.45, 95% confidence interval 0.27 to 0.76). In sensitivity analyses, we substituted the weighted analyses for models stratified according to matching weights, with essentially the same results (hazard ratio 0.46, 95% confidence interval 0.23 to 0.92). We also performed analyses adjusting for splines of baseline BMI and the propensity score instead. This again produced similar results 11 10.1161/CIRCULATIONAHA.116.025629 (hazard ratio 0.47, 95% confidence interval 0.24 to 0.93). No deviation from proportionality of hazards was observed (all p>0.9). In a model including a multiplicative interaction term treatment group*sex, similar main results were observed (hazard ratio 0.37, 95% confidence interval 0.19 to 0.72), and no treatment*sex interaction (p=0.17). In a sample of 21,620 persons typically determined to be eligible for bariatric surgery (BMI above 40, or BMI between 35 and 40 with significant obesity-related comorbidity), 57 cases of heart failure occurred. In this sample, surgery was associated with a hazard ratio of 0.53, Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 95% confidence interval 0.35 to 0.82, for heart failure. Discussion Principal observations In n tthis hiis study off a large lar argee sample sam ampl am plee of pl o obese obe b see ppeople eoplee wi w without thoutt previous th prev pr evio ev iouss hheart io e rt ea r ffailure a lure ai re ffrom room twoo Sw Swed Swedish edis ed ih is nationwide nati ion o wide registries, reg gisstrriees, gastric gastriic bypass surgery sur urgery was was associated assoc ocia oc iate ia tedd with with a nea nearly arlly hhalved alved inc incidence n id nc dence of heart fail failure i ure comparedd to intensive lifestyle treatment including LCD/VLCD. LC CD/VL V CD D. Th The he associations were to a large extent mediated by weight loss, partly mediated by effects of treatment on interim atrial fibrillation, diabetes, and hypertension, but likely not mediated by the effects of treatment on myocardial infarction. Results were robust in multiple sensitivity analyses. Comparisons with previous studies Associations of obesity with incident heart failure are well-established,3, 4, 6 but the effect of substantial weight loss on incident heart failure is unknown. Patient series have suggested beneficial effects on cardiac function7 and prognosis14 of bariatric surgery in patients with heart failure, but other studies have shown an inverse association of BMI with mortality among people 12 10.1161/CIRCULATIONAHA.116.025629 with heart failure.15, 16 The present study only included people without heart failure at baseline and hence gives no implications for treatment of obese people with heart failure. Potential mechanisms The association of treatment with heart failure was mainly mediated by weight loss, as supported by the strong dose-response relationship and the absence of a treatment effect when accounting for one-year weight loss in the models. Bariatric surgery, compared to conventional treatment, has been associated with lower incidence of myocardial infarctions17 and improvement in several other risk factors for heart Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 failure, including diabetes, hypertriglyceridemia, and high blood pressure18 in the nonandomized prospective Swedish Obese Subjects study. All of these may contribute contribut utee to the the randomized associations observed in the present study,19, 20 but in our data the effects appeared less likely to be mediated by the effects of treatment on myocardial infarction (although myocardial infarction rate atee w was as lowerr aamong mongg ssurgery mo urge ur g ry ppatients), ge atie at ient ie n s)), and mo m more ree llikely ikel elyy by eeffects el fffecctss ooff tr treatm treatment men entt on int interim terrim aatrial trial tr fibrillation, fibr ril illa l tion, diabetes diab abettess aand ab n blo nd blood ood pressure. e. This iss in n line lin ne with with t the thhe known kn n substantial suubs b tantial effects efffeccts of 24 bariatric surgery on diabetes dia i betes prevention2211 and remission.22-24 It should, however, h wever, be noted that ho the mediation analyses had low and differential statistical power. Another potential mode of action is a direct effect of weight loss on cardiac stress, such as hemodynamic load. Cardiac troponin-I is a biomarker of cardiac stress and an important risk marker for heart failure.25 Recent data have shown that gastric bypass reduces cardiac troponin-I concentration, as compared to intensive lifestyle intervention.26 In addition to the mediation by effects on risk factors, there may be effects of weight loss on obesity cardiomyopathy per se. Fatty acids are the major oxidative fuel for the heart,27 and myocardial fDWW\DFLGȕ-oxidation is mainly regulated by peroxisome proliferator-activated 13 10.1161/CIRCULATIONAHA.116.025629 receptor-D (PPAR-D).28 ,QH[SHULPHQWDOPRGHOVREHVLW\LPSDLUVP\RFDUGLDOIDWW\DFLGȕoxidation regulation.29 This leads to lipid deposition in cardiomyocytes, contractile dysfunction,29 myocardial fibrosis,28 and cardiomyocyte apoptosis.5, 30 In experimental models, weight loss leads to an upregulation of myocardial PPARs, improved lipid metabolism, and increased ejection fraction.31 In the recent EMPA-REG OUTCOME study, empagliflozin treatment led to a modest weight loss and a strong preventive effect against heart failure in persons with diabetes.32 In light of the present study, it should be considered whether it is the energy loss and consequent weight Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 loss with the sodium/glucose cotransporter-2 inhibitors that underpins their protection against heart failure. In the present study, surgically treated patients on average lost 20 kgg m oree th or than an more patients in the lifestyle program. It will be important to follow the full effect of this on the ncidence of heart failure over longer time periods. incidence Stre ren re ngths and d limitations lim mit i attio ions n ns Strengths Stre eng ngths include includ ude two ud tw wo largee prospectively prospect c iv ct i el ely desi igned ed nationwide nat atio at ionwid io ide registries reegistriies of of bariatric bariatrric su surgery and an nd Strengths designed ntensive lifestyle treatment with a program that is a relevant comparator to gastric bypass intensive surgery,33 and a validated outcome ascertained using nationwide health registries with complete coverage and negligible loss to follow-up. Weaknesses include the observational nature of the study. It is unlikely that randomized trials of bariatric surgery will provide evidence for a relatively rare event such as heart failure. Further, the low number of outcomes is a limitation. In spite of balance in most of the available baseline factors between the treatment groups after weighting, residual confounding may have affected our observations. This would likely result in a conservative bias as participants in the lifestyle program had higher educational level and income, and can be assumed to be more health 14 10.1161/CIRCULATIONAHA.116.025629 conscious. They are also likely more motivated, as they paid out-of-pocket for their treatment, whereas the government paid for 90% of the bariatric surgery procedures. Further, the gastric bypass surgery group had worse clinical profile in terms of diabetes, dyslipidemia and hypertension. The statistical modelling accounted well for differences between groups, and results were robust in sensitivity analyses further adjusting for group differences and using other statistical techniques. We did not have data on ethnicity, and it is reasonable to assume that the participants were predominantly Caucasian. Generalizability to other ethnic groups is unknown. We also lacked data on exercise and dietary advice as well as compliance to such advice in the Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 surgery group, and measurements of physical activity in either group. Further, generalizability to other bariatric surgery methods than gastric bypass is unknown, and it should be nnoted oted ot ed tthat hatt the ha the preferred type of bariatric surgery may differ over time and between geographic regions. Unsurprisingly, the incidence of heart failure was higher in both of the obese samples than han n in in the in the the age-, age g -, sexsex ex- and an nd place-of-residence-matched plac pl ace-oofac f resideenc n e-maatc tche h d ge he ggeneral neeraal po popu population, p lati tion ti on,, likely on liike k ly y explained exp xpla laain ined by higher hig igher prev prevalence val alen nce ooff obes obesity-related esity-relatedd rrisk es isk fa factors. actorrs. Ne Neve Nevertheless, vert ve rthe h lesss, the lo low w hheart eart fai failure ilur ure rate inn this his sample led l d to a mere 0.2% five-year riskk difference le diifference (corresponding to a number needed to treat of 534) in this comparison of two groups that both had an effective weight loss treatment. Conclusions Gastric bypass surgery was associated with a nearly halved incidence of heart failure compared to an intensive lifestyle modification program including LCD/VLCD, in this study of nationwide registries including almost 40,000 individuals. We also observed a dose-response relationship between weight loss and risk of heart failure. Taken together with Mendelian randomization findings, this supports a causal effect of obesity on heart failure, the leading cause of hospitalization in Western societies. 15 10.1161/CIRCULATIONAHA.116.025629 Acknowledgements MN co-designed the study, and is the principal investigator of the SOReg/Itrim study; JS designed the study, performed statistical analyses, interpreted the data and wrote the first draft of the manuscript. All authors contributed to interpreting the results and contributed with significant intellectual input in the manuscript. JS, GB, and MN had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The corresponding author had final responsibility for the decision to submit for publication. Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 Sources of Funding Research reported in this publication was supported by the National Institute of Diabetes Diaabe bete tees An Andd Digestive And Kidney Diseases of the National Institutes of Health under Award Number R01DK105948. The content is solely the responsibility of the authors and does not necessarily eprres esent the of off fici cial ci a vviews iews ie w off th ws thee Na N tion onal Ins sti titu utees of Health. Hea ealt lth. A lt u ho ut h rs of th this is sstudy tudy w tu eree also er als represent official National Institutes Authors were upp pppor o ted by tthe he S wedi dish R esearch Co ouncil (M MN:22013 13-3 13 -377 -3 7 0; 77 0; JS: 2010–1078). 2010– 0–10078). The Thhe funder fun under off the the supported Swedish Research Council (MN:2013-3770; tudy had no role in i study design, ddata ata collection, da ddata ta analysis, data interpretation, or writing of study the report. Disclosures CM, MN and JS report receiving consulting fees (modest) for participation in the scientific advisory committee of Itrim. IN is the previous director of the Scandinavian Obesity Surgery Registry. JO is its current director. GB has nothing to disclose. 16 10.1161/CIRCULATIONAHA.116.025629 References 1. 2. 3. Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 4. 5. 6. 7. NCD Risk Factor Collaboration (NCD-RisC), Di Cesare M, Bentham J, Stevens GA, Zhou B, Danaei G, Lu Y, Bixby H, Cowan MJ, Riley LM, Hajifathalian K, Fortunato L, Taddei C, Bennett JE, Ikeda N, Khang YH, Kyobutungi C, Laxmaiah A, Li Y, Lin HH, Miranda JJ, Mostafa A, Turley ML, Paciorek CJ, Gunter M, Ezzati M. Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet. 2016;387:1377-1396. Ambrosy AP, Fonarow GC, Butler J, Chioncel O, Greene SJ, Vaduganathan M, Nodari S, Lam CS, Sato N, Shah AN, Gheorghiade M. The global health and economic burden of hospitalizations for heart failure: Lessons learned from hospitalized heart failure registries. J Am Coll Cardiol. 2014;63:1123-1133. Kenchaiah S, Evans JC, Levy D, Wilson PWF, Benjamin EJ, Larson MG, Kannel WB, Vasan RS. Obesity and the risk of heart failure. N Engl J Med. 2002;347:305-313 Aune D, Sen A, Norat T, Janszky I, Romundstad P, Tonstad S, Vatten LJ. Body mass index, abdominal fatness and heart failure incidence and mortality: A systematic review aand d dose espo se meta-analysis e a a a ys s oof pprospective ospec ve sstudies. ud es. Ci culation. 2016;133:639-49. 0 6; 33:639 9. dose-response Circulation. Orc rcii L, L U nger ng er Zhou YT, Grayburn P, Karim A, Shimabukuro M, Higa M, Baetens D, Orci Unger RH. Lipotoxic heart disease in obese rats: Implications for human obesity. Pr Proc occ N Natl atll at Acad Sci U S A. 2000;97:1784-1789. Fall T, Hagg S, Magi R, Ploner A, Fischer K, Horikoshi M, Sarin AP, Thorleifsson G, Ladenvall C, Kals M, Kuningas M, Draisma HH, Ried JS, van Zuydam NR, Huikari V, Mangino Mang Ma ngin ng ino M, in M Sonestedt E, Benyamin B, Nelson Neelson CP, Rivera Riverra NV, NV V, Kristiansson K, Shen Havulinna Donnelly LA, Kaakinen M,, Nu ML, Robertson N,, HY, Ha avuli linn n a AS AS,, Dehghan Dehg De hgha hg hann A, Donne ha n ll ne lyL A,, Ka Kaak akin ak i en M Nuotio oM L, R ober erts er tson ts on N MA, Balmforth PS, de Bruijn RF RF, Ikram Ik kram mM A, Am Amin n N, Balm lmfoorth AJ, AJ, Braund Brraund au u dP S, Doney Donney e AS, Doring Dorrin ng A, Elliott P, Esko Eskoo T, T, Franco Fra ranc ra n o OH,, Gretarsdottir Gretarsddottiir S,, Hartikainen Gr Har a ti tika k inen n AL, Heikkila Heikkila K,, Herzig Her erzig KH, KH H, Holm Hypponen A,, Is Isomaa B,, Ka Karssen Kettunen H Ho lm m H, H, Hottenga Hotten Ho enga JJ, J, H yppo yp poneen E, po E IIllig llig ll i T, ig T, Isaacs Issaa aacs c A som maa a B ars rsse s n LC LC, Ke K ttunen J, Koenig Kuulasmaa Laatikainen T,, La Laitinen K Ko enig W, Ku K ulasmaa K, L aatika k inen T L itinen J, Lindgren C, C, Lyssenko k V, Laara L ara E, La E Rayner NW, Mannisto S, Pouta A, Rathmann W, Rivadeneira F, Ruokonen A, Savolainen MJ, Sijbrands EJ, Small KS, Smit JH, Steinthorsdottir V, Syvanen AC, Taanila A, Tobin MD, Uitterlinden AG, Willems SM, Willemsen G, Witteman J, Perola M, Evans A, Ferrieres J, Virtamo J, Kee F, Tregouet DA, Arveiler D, Amouyel P, Ferrario MM, Brambilla P, Hall AS, Heath AC, Madden PA, Martin NG, Montgomery GW, Whitfield JB, Jula A, Knekt P, Oostra B, van Duijn CM, Penninx BW, Smith GD, Kaprio J, Samani NJ, Gieger C, Peters A, Wichmann HE, Boomsma DI, de Geus EJ, Tuomi T, Power C, Hammond CJ, Spector TD, Lind L, Orho-Melander M, Palmer CN, Morris AD, Groop L, Jarvelin MR, Salomaa V, Vartiainen E, Hofman A, Ripatti S, Metspalu A, Thorsteinsdottir U, Stefansson K, Pedersen NL, McCarthy MI, Ingelsson E, Prokopenko I, European Network for G, Genomic Epidemiology c. The role of adiposity in cardiometabolic traits: A mendelian randomization analysis. PLoS Medicine. 2013;10:e1001474. Aggarwal R, Harling L, Efthimiou E, Darzi A, Athanasiou T, Ashrafian H. The effects of bariatric surgery on cardiac structure and function: A systematic review of cardiac imaging outcomes. Obes Surg. 2016;26:1030-40. 17 10.1161/CIRCULATIONAHA.116.025629 8. 9. 10. 11. 12. Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 13. 14. 15. 16. 17. 18. 19. 20. 21. Hedenbro JL, Naslund E, Boman L, Lundegardh G, Bylund A, Ekelund M, Laurenius A, Moller P, Olbers T, Sundbom M, Ottosson J, Naslund I. Formation of the Scandinavian Obesity Surgery Registry, SOReg. Obes Surg. 2015;25:1893-1900. Johansson K, Sundstrom J, Marcus C, Hemmingsson E, Neovius M. Risk of symptomatic gallstones and cholecystectomy after a very-low-calorie diet or low-calorie diet in a commercial weight loss program: 1-year matched cohort study. Int J Obes (Lond).. 2014;38:279-284. Hemmingsson E, Johansson K, Eriksson J, Sundstrom J, Neovius M, Marcus C. Weight loss and dropout during a commercial weight-loss program including a very-low-calorie diet, a low-calorie diet, or restricted normal food: Observational cohort study. Am J Clin Nutr. 2012;96:953-961. Ingelsson E, Arnlov J, Sundstrom J, Lind L. The validity of a diagnosis of heart failure in a hospital discharge register. Eur J Heart Fail. 2005;7:787-791. Blackwell M, Iacus S, King G, Porro G. CEM: Coarsened exact matching in Stata. Stata J. 2009;9:524-546. Ludvigsson JF, Almqvist C, Bonamy AK, Ljung R, Michaelsson K, Neovius M, Stephansson O, Ye W. Registers of the swedish total population and their use in medical research. esea c . Eur u J Epidemiol. pidemiol. 2016;31:125-136. 0 6;3 : 5 36. Lim CP, Fisher OM, Falkenback D, Boyd D, Hayward CS, Keogh A, Samaras Sama mara rass K, ra MacDonald P, Lord RV. Bariatric surgery provides a "bridge to transplant" transplantt" for f r morbidly fo morb mo rbid rb idly id ly obese patients with advanced heart failure and may obviate the need for transplantation. Obes Surg. 2016;26:486-93. Oreopoulos A, Padwal R, Kalantar-Zadeh K, Fonarow GC, Norris CM, McAlister FA. Body mass meta-analysis. B Bo ody dy m asss index index and mortality in heart failure: faiilu ure: A meta-an nal a ysis is. Am Heart J. J 2008;156:13-22. 2008;1 156 56:1 133 22 2 . Sharma A,, L Lavie CJ, Vallakati A,, Goel F,, Arbab-Zadeh avi viie CJ J, Borer Borer JS JS, V allakaati A Go S, Lopez-Jimenez Lopeez-Jime Lo meneez F Arbbab ab-Za Zadeh A, Za A Mukherjee D,, L Lazar Meta-analysis mass Mukher erje er j eD azarr JJM. M. Meta-a -annalysiss off the he rrelation elat el atiionn of bbody at ody ma m ss index to to all-cause alll-causee cardiovascular mortality with chronic heart Am aand an d ca card rdiova rd vasccular m orta or t liity and nd hhospitalization osspi pitaaliza zatiion inn patients pati pa tiien ents ts w itth ch hro roni n c he hea art ffailure. ailure.. A m J Cardiol. 20 22015;115:1428-1434. 15;115:1428-1434. 15 Sjostrom L, Peltonen M, Jacobson P, Sjostrom CD, Karason K, Wedel H, Ahlin S, Anveden A, Bengtsson C, Bergmark G, Bouchard C, Carlsson B, Dahlgren S, Karlsson J, Lindroos AK, Lonroth H, Narbro K, Naslund I, Olbers T, Svensson PA, Carlsson LM. Bariatric surgery and long-term cardiovascular events. JAMA. 2012;307:56-65. Sjostrom L, Lindroos AK, Peltonen M, Torgerson J, Bouchard C, Carlsson B, Dahlgren S, Larsson B, Narbro K, Sjostrom CD, Sullivan M, Wedel H, Swedish Obese Subjects Study Scientific G. Lifestyle, diabetes, and cardiovascular risk factors 10 years after bariatric surgery. N Engl J Med. 2004;351:2683-2693. Ingelsson E, Bjorklund-Bodegard K, Lind L, Arnlov J, Sundstrom J. Diurnal blood pressure pattern and risk of congestive heart failure. JAMA. 2006;295:2859-2866. Ingelsson E, Sundstrom J, Arnlov J, Zethelius B, Lind L. Insulin resistance and risk of congestive heart failure. JAMA. 2005;294:334-341. Carlsson LM, Peltonen M, Ahlin S, Anveden A, Bouchard C, Carlsson B, Jacobson P, Lonroth H, Maglio C, Naslund I, Pirazzi C, Romeo S, Sjoholm K, Sjostrom E, Wedel H, Svensson PA, Sjostrom L. Bariatric surgery and prevention of type 2 diabetes in Swedish obese subjects. N Engl J Med. 2012;367:695-704. 18 10.1161/CIRCULATIONAHA.116.025629 22. 23. 24. 25. 26. Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 27. 28. 29. 30. 31. 32. 33. Sjostrom L, Peltonen M, Jacobson P, Ahlin S, Andersson-Assarsson J, Anveden A, Bouchard C, Carlsson B, Karason K, Lonroth H, Naslund I, Sjostrom E, Taube M, Wedel H, Svensson PA, Sjoholm K, Carlsson LM. Association of bariatric surgery with longterm remission of type 2 diabetes and with microvascular and macrovascular complications. JAMA. 2014;311:2297-2304. Schauer PR, Bhatt DL, Kashyap SR. Bariatric surgery versus intensive medical therapy for diabetes. N Engl J Med. 2014;371:682. Mingrone G, Panunzi S, De Gaetano A, Guidone C, Iaconelli A, Leccesi L, Nanni G, Pomp A, Castagneto M, Ghirlanda G, Rubino F. Bariatric surgery versus conventional medical therapy for type 2 diabetes. N Engl J Med. 2012;366:1577-1585. Sundstrom J, Ingelsson E, Berglund L, Zethelius B, Lind L, Venge P, Arnlov J. Cardiac troponin-I and risk of heart failure: A community-based cohort study. Eur Heart J. 2009;30:773-781. Lyngbakken MN, Omland T, Nordstrand N, Norseth J, Hjelmesaeth J, Hofso D. Effect of weight loss on subclinical myocardial injury: A clinical trial comparing gastric bypass surgery and intensive lifestyle intervention. Eur J Prev Cardiol. 2016;23:874-880. Stanley WC, Lopaschuk GD, Hall JL, McCormack JG. Regulation of myocardial carbohydrate conditions; ca bo yd a e metabolism e abo s under u de normal o a aandd ischaemic sc ae c co d o s; potential po e a for o pharmacological interventions. Cardiovasc Res. 1997;33:243-257. Watanabe K, Fujii H, Takahashi T, Kodama M, Aizawa Y, Ohta Y, Ono T, Hasegawa Hasseg egaw awaa G, aw Naito M, Nakajima T, Kamijo Y, Gonzalez FJ, Aoyama T. Constitutive regulation of cardiac fatty acid metabolism through peroxisome proliferator-activated receptor alpha associated with age-dependent cardiac toxicity. J Biol Chem. 2000;275:22293-22299. Young ME,, Guthrie PH, Razeghi P, Leighton Youn Yo ungg ME un M Leigh hto on B, Abbasi S, Patil il S, Youker KA, Taegtmeyer Impaired fatty contractile dysfunction Taegtm meyer H. H. Im mpa p irred long-chain lon ongg-ccha h in fat atty at t acid acid oxidation oxid ox i at id atio i n and and co cont n ract ctil ct ilee dy il dysfun nct ctio ionn in io Diabetes. the obese Zucker Zucke keer ratt he hheart. eart. Di Diab betes. 22002;51:2587-2595. 0022;5 51::2587-22595.. Lu MC, Wu C Tzang C, Tza zangg BS, BS, Kuo Kuo WW, W u FL,, Chen Chen en YS, YS, Tsai Tsaai CH, CH H, Huang Huan ang CY, CY, Leee SD. SD More cardiac mitochondrial-dependent aactivated ac tiva vate va tedd ca te cardia iac mito toch to chonndr ch driiall-d -dep ep pen ende d ntt aapoptotic de poopt ptottic pathway pat a hw way in in obese obbes esee Zucker Zuc uckkerr rrats. ats. Obesity (Silver 2007;15:2634-2642. O Ob esity (S Sil ilver Spring). 20 007 0 ;15:2634 3 -226442. 2 Verreth W, De Keyzer D, Pelat M, Verhamme P, Ganame J, Bielicki JK, Mertens A, Quarck R, Benhabiles N, Marguerie G, Mackness B, Mackness M, Ninio E, Herregods MC, Balligand JL, Holvoet P. Weight-loss-associated induction of peroxisome proliferator-activated receptor-alpha and peroxisome proliferator-activated receptorgamma correlate with reduced atherosclerosis and improved cardiovascular function in obese insulin-resistant mice. Circulation. 2004;110:3259-3269. Fitchett D, Zinman B, Wanner C, Lachin JM, Hantel S, Salsali A, Johansen OE, Woerle HJ, Broedl UC, Inzucchi SE, EMPA-REG OUTCOME® trial investigators. Heart failure outcomes with empagliflozin in patients with type 2 diabetes at high cardiovascular risk: Results of the EMPA-REG OUTCOME trial. Eur Heart J. 2016;37:1526-34. Ludwig DS, Ebbeling CB, Livingston EH. Surgical vs lifestyle treatment for type 2 diabetes. JAMA. 2012;308:981-982. 19 Table 1. Baseline characteristics Gastric Bypass Surgery Lifestyle (n=25,804) (n=13,701) Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 Difference surgery – lifestyle Standardized differences in means Age (years) 41.3 (41.2 to 41.4) 41.5 (41.3 to 41.7) -0.2 (-0.4 to 0.0) 0.006 Male sex (%) 23.7 (23.2 to 24.2) 22.3 (22.1 to 23.5) 0.9 (0.0 to 1.8) 0.055 Weight (kg) 119.1 (118.9 to 119.3) 119.0 (118.7 to 119.3) 0.1 (-0.3 to 0.5) 0.029 Body-mass index (kg/m2) 41.5 (41.4 to 41.5) 41.4 (41.4 to 41.5) 0.0 (-0.1 to 0.1) 0.023 Systolic blood pressure (mmHg) 134.9 (134.6 to 135.1) 133.9 (133.5 to 134.2) 1.0 (0.5 to 1.4) 0.050 Married (%) 43.2 (42.6 to 43.8) 44.3 (43.5 to 45.1) -1.1 (-2.1 to -0.0) -0.022 Current smoker (%) 16.2 (15.6 to 16.8) 17.1 (16.4 to 17.7) -0.9 (-1.8 to 0.0) -0.028 Prior myocardial infarction (%) 1.1 (0.9 to 1.2) 0.8 (0.7 to 1.0) 0.2 (0.0 to 0.4) 0.036 Prior atrial fibrillation (%) 1.0 (0.8 to 1.1) 1.0 (0.8 to 1.2) -0.0 (-0.2 to 0.2) -0.003 Prior valve disease (%) 0.1 (0.1 to 0.2) 0.1 (0.1 to 0.2) 0.0 (-0.0 to 0.1) 0.035 Prior substance abuse (%) 0.8 (0.7 to 0.9) 0.9 (0.8 to 1.1) -0.1 (-0.3 to 0.1) -0.024 Lipid-lowering drugs (%) 13.9 (13.5 to 14.3) 10.4 (9.9 to 10.9) 3.5 (2.9 to 4.2) 0.123 Antihyperglycemic drugs (%) 15.0 (14.6 to 15.4) 9.4 (8.9 to 9.9) 5.6 (5.0 to 6.2) 0.256 Oral antihyperglycemic drugs (%) 13.8 (13.4 to 14.2) 9.1 (8.6 to 9.6) 4.7 (4.0 to 5.3) 0.233 Insulin ulin (%) 6.5 (6.2 to 6.8) 1.9 (1.7 to 2.2) 4.6 (4.2 to 5.0) 0.262 0.26 Aspirin in (%) 6.9 (6.6 to 7.2) 4.9 (4.5 to 5.2) 2.0 (1.4 to 2.4) 00.091 .09 Thyroid oid hormones (%) 9.5 (9.1 to 9.9) 8.0 (7.6 to 8.5) 1.5 (0.9 to 2.1) 0.054 0.05 0. 05 Antihypertensive hypertensive drugs (%) 30.0 (29.4 to 30.6) 26.5 (25.8 to 27.2) 3.5 (2.5 to 4.4) 0.11 0.118 Beta-blockers ta-blockers (%) 14.2 (13.8 to 14.6) 13.9 (13.3 to 14.5) 0.3 (-0.4 to 1.0) 0.03 0.033 Calcium lcium channel blockers (%) 9.4 (9.0 to 9.7) 6.9 (6.5 to 7.4) 2.5 (1.9 to 3.0) 0.113 0.11 RAAS AAS blockers blo ock c errs (% (%) 22.0 (21.5 to 22.5) 18.3 .3 3 (17.7 to 19.0) 3.7 (2.9 (2 to 4.5) 0.12 0.123 Thiazide iazide de ddiuretics iureticss ((%) %) 6·5 (6·2 to 6·8) 5·9 9 (5·5 to 6·3) 0·6 (0 (0·1 to 1·1) 0.018 0.01 Loop diuretics diu uretics ree (%) 7.7 7..7 (7.4 (7.4 4 to to 8.1) 1) 5.1 1 (4.7 (4.7 7 to to 55.5) .5) 5) 2.6 (2 2. (2.1 to o 3. 3.1) 1) 00.112 0. 11 Education atio on -0 -0.154 0.15 <10 0 ye years ear ars (%) 177 (17.4 to 18 17.8 18.2) 14 14.4 4.4 4 (13 (13.9 13.9 13 .9 9 tto o 14.9 14 14.9) 4 9) 3.4 (2 (2.9 to o 3.9) 0. 0.104 .10 10 to 122 years yea e rs (%) %) 61.0 61 .0 (60.5 .5 tto o 61 61.5) 59.8 8 (59 (59.3 59.3 to 60.3) 59 60.3 60 3) 1.1 (0.9 (0 to to 1.4) 1 4) 1. 0. 0.019 .01 >12 2 ye year years arss (% ((%)) 21 21.2 .2 2 (20.8 8 tto o 21 21.7) 1.7 7) 25 25.8 5.8 8 ((25.1 255.1 to 26 26.4)) -4. -4.5 4 5 ((-5.3 -5.3 3 to -3.8) 8)) -0. -0.097 0 09 Income me (1000 USD/year) 30 30.5 5 (30 (30.2 2 to 30 30.6) 6) 32 32.5 5 (32 (32.11 to 32.8) 32 8) -2.1 2 1 (-2.5 ( 2 5 to -1.7) 1 7) -0.093 0 09 Inclusion year 0.260 2006 (%) 0.4 (0.3 to 0.5) 0.4 (0.3 to 0.4) 0.0 (-0.0 to 0.0) -0.021 2007 (%) 2.8 (2.7 to 3.0) 2.8 (2.6 to 3.0) 0.0 (-0.1 to 0.1) -0.017 2008 (%) 9.1 (8.7 to 9.4) 9.2 (8.9 to 9.5) 0.1 (-0.2 to 0.4) -0.015 2009 (%) 13.3 (12.9 to 13.6) 13.1 (12.8 to 13.5) 0.1 (-0.2 to 0.4) 0.016 2010 (%) 23.1 (22.7 to 23.5) 23.0 (22.6 to 23.5) 0.1 (-0.1 to 0.3) 0.018 2011 (%) 26.3 (25.9 to 26.8) 26.4 (26.0 to 26.9) -0.1 (-0.3 to 0.1) 0.037 2012 (%) 24.9 (24.4 to 25.4) 25.2 (24.6 to 25.8) -0.3 (-1.0 to 0.4) -0.042 Data are means or percent, difference, and standardized differences in means between surgery and lifestyle groups (95% confidence intervals) from an inverse probability-weighted sample. 10.1161/CIRCULATIONAHA.116.025629 Table 2. Mediation analysis Occurrence of the Hazard ratio (95% confidence P for an indirect effect of potential mediator interval) for treatment adjusted the potential mediator during follow-up for the potential mediator N (%) 0.54 (0.36 to 0.82) 130 (0.3) 0.54 (0.35 to 0.82) 0.18 Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 Main model Adjusted for interim myocardial infarction Adjusted for interim 641 (1.6) 0.63 (0.41 to 0.96) atrial fibrillation Adjusted for use of diabetes 1,235 (3.1) 0.64 (0.42 to 0.97) drugs at one-year follow-up Adjusted for use of blood 6,353 (16.1) 0.65 (0.43 to 0.99) pressure-lowering drugs at one-year follow-up P-values are from generalized structural equation models 21 <0.0001 <0.0001 <0.0001 10.1161/CIRCULATIONAHA.116.025629 Figure Legends Figure 1. Changes in weight, waist circumference and body fat during the first two years of the study. Data are from an inverse probability-weighted sample. Error bars are 95% confidence intervals. Body fat data were not available for the gastric bypass surgery patients. Figure 2. Cumulative hazard of heart failure in persons treated with lifestyle or gastric bypass surgery. Data are from an inverse probability-weighted sample. Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 Figure 3. Hazard ratio of heart failure in relation to achieved weight loss at one onee year. yea ear. r Data are from an inverse probability-weighted sample of both lifestyle and gastric bypass urgery pa ppatients tients combined. The model included the three variables: baseline weight, treatment surgery grou up, and achieved ach hie ieveed we w ight ig ht los osss at one os onee year. year. S h de ha ded ar rea iiss 95 995% % co conf n id idencee iinterval. nter nt erva er v l. group, weight loss Shaded area confidence 22 ϭϮϬ ϴϬ ϵϬ tĞŝŐŚƚ;ŬŐͿ ϭϬϬ ϭϭϬ >ŝĨĞƐƚLJůĞ ^ƵƌŐĞƌLJ ϲ ϭϯ Ϯϲ ϯϵ ϱϮ ϲϱ dŝŵĞ;ǁĞĞŬƐͿ ϳϴ ϵϭ ϭϬϰ ϭϮϬ ϭϭϬ ϭϬϬ ϵϬ tĂŝƐƚĐŝƌĐƵŵĨĞƌĞŶĐĞ;ĐŵͿ >ŝĨĞƐƚLJůĞ ^ƵƌŐĞƌLJ ϲ ϭϯ Ϯϲ ϯϵ ϱϮ ϲϱ dŝŵĞ;ǁĞĞŬƐͿ ϳϴ ϵϭ ϭϬϰ ϰϴ Ϭ ϰϬ ϰϮ ϰϰ ϰϲ >ŝĨĞƐƚLJůĞ ŽĚLJĨĂƚ;йͿ Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 ϭϯϬ Ϭ Ϭ ϭϯ Ϯϲ ϯϵ ϱϮ ϲϱ dŝŵĞ;ǁĞĞŬƐͿ ϳϴ ϵϭ ϭϬϰ ϭ͘ϱ ϭ Ϭ͘ϱ ϱ Ϭ ƵŵƵůĂƟǀĞ,ĂnjĂƌĚ;йͿ ƵŵƵůĂƟǀĞ,Ănj Ϯ 017 >ŝĨĞƐƚLJůĞ ^ƵƌŐĞƌLJ Ϭ EƵŵďĞƌĂƚƌŝƐŬ >ŝĨĞƐƚLJůĞ ϭϯ͕ϳϬϭ ^ƵƌŐĞƌLJ Ϯϱ͕ϴϬϰ Ϯ ϰ dŝŵĞ;LJĞĂƌƐͿ ϲ ϴ ϭϯ͕ϲϯϳ Ϯϱ͕ϳϭϱ ϲ͕ϱϱϳ ϭϮ͕ϰϳϲ ϭ͕ϳϯϭ ϯ͕Ϭϰϳ ϳϰ ϳϴ оϲ ůŶ;,ĂnjĂƌĚƌĂƟŽŽĨŚĞĂƌƚĨĂŝůƵƌĞͿ оϰ оϮ Ϭ Ϯ 017 Ϭ ϱϬ tĞŝŐŚƚůŽƐƐĂƚŽŶĞLJĞĂƌ;ŬŐͿ ϭϬϬ Weight Loss and Heart Failure: A Nationwide Study of Gastric Bypass Surgery Versus Intensive Lifestyle Treatment Johan Sundström, Gustaf Bruze, Johan Ottosson, Claude Marcus, Ingmar Näslund and Martin Neovius Downloaded from http://circ.ahajournals.org/ by guest on June 18, 2017 Circulation. published online March 3, 2017; Circulation is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231 Copyright © 2017 American Heart Association, Inc. All rights reserved. Print ISSN: 0009-7322. Online ISSN: 1524-4539 The online version of this article, along with updated information and services, is located on the World Wide Web at: http://circ.ahajournals.org/content/early/2017/03/03/CIRCULATIONAHA.116.025629 Data Supplement (unedited) at: http://circ.ahajournals.org/content/suppl/2017/03/03/CIRCULATIONAHA.116.025629.DC1 Permissions: Requests for permissions to reproduce figures, tables, or portions of articles originally published in Circulation can be obtained via RightsLink, a service of the Copyright Clearance Center, not the Editorial Office. Once the online version of the published article for which permission is being requested is located, click Request Permissions in the middle column of the Web page under Services. Further information about this process is available in the Permissions and Rights Question and Answer document. Reprints: Information about reprints can be found online at: http://www.lww.com/reprints Subscriptions: Information about subscribing to Circulation is online at: http://circ.ahajournals.org//subscriptions/ SUPPLEMENTAL MATERIAL Weight loss and heart failure: a nationwide study of gastric bypass surgery versus intensive lifestyle treatment Johan Sundström,1 Gustaf Bruze,2 Johan Ottosson,3 Claude Marcus,4 Ingmar Näslund,3 Martin Neovius2 1 Department of Medical Sciences, Uppsala University, and Uppsala Clinical Research center (UCR). Uppsala, Sweden 2 Department of Medicine, Solna, Clinical Epidemiology Unit, Karolinska Institutet, Stockholm, Sweden 3 4 Department of Surgery, Faculty of Medicine and Health, Örebro University, Örebro, Sweden Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden Table of Contents Item Description Supplemental Methods Weight-loss program 2 Statistical methods 2 Supplemental Table 1 Variable sources and definitions 3 Supplemental Table 2 4 Supplemental Figure 1 Baseline characteristics in persons with complete data vs those with any missing data Baseline characteristics of sample re-weighted also by one-year BMI Flow chart for definition of the study sample Supplemental figure titles and legends Supplemental Figure 1 7 Supplemental Table 3 Page 5 6 Weight loss and heart failure Sundström et al. Supplemental Methods Weight-loss program The VLCD treatment was a liquid-based formula diet of 500kcal/day for 3-10 weeks (125kcal/sachet, 4 sachets/day, approved as sole source VLCD by the Swedish National Food Agency) followed by 2-8 weeks gradual introduction of normal food. Early introduction of normal food occurred if patients were satisfied with the achieved weight loss or reached BMI<25. In June, 2009, the program was changed to 600kcal/day for 3 weeks followed by 800kcal/day for up to 9 weeks. The LCD treatment included 2 calorie-restricted normal food meals and 2 formula-diet meal replacement sachets per day providing a total caloric intake of about 1200-1500kcal. After the weight- loss phase, patients entered a 9-month weight maintenance program of exercise (circuit training at the center 2-3 times/week for 30-45 minutes, and pedometer use to encourage walking), dietary advice, and behavioral therapy (a structured program of 20 1- hour group sessions, initiated during the weight-loss phase). There were also face-to-face counselling sessions throughout the program. Statistical methods Variables included in the propensity score analysis were baseline variables age, systolic blood pressure, smoking, previous myocardial infarction, previous atrial fibrillation, weight, BMI, educational level, marital status, income, sex, antihypertensive drugs, lipid-lowering drugs, antidiabetic drugs, previous substance abuse, previous valve disease, and treatment year, with non-linear modelling of some variables, and interaction terms for several variables including BMI. 2 2 1 Weight loss and heart failure Sundström et al. Supplemental Table 1. Variable sources and definitions Variables obtained from nationwide health registries Atrial fibrillation ICD-10: I48·9, diagnosed in ambulatory or in-patient care Myocardial infarction ICD-10: I21, diagnosed in in-patient care Valve disease ICD-10: I34, I35, I36, I37, diagnosed in in-patient care Heart failure ICD-10: I50, diagnosed in in-patient care, only as main cause of hospitalization Substance abuse ICD-10: F10-F19, diagnosed in ambulatory or in-patient care Lipid-lowering drug treatment ATC: C10 Antidiabetic drug treatment ATC: A10 Aspirin treatment ATC: B01AC06 Thyroid hormone treatment ATC: H03A Antihypertensive drug ATC: C02, C03A, C03B, C03EA01, C07 except treatment C07AA07, C08C, C09 Beta-receptor blocker treatment ATC: C07 except C07AA07 Calcium antagonist treatment ATC: C08C RAAS blocker treatment ATC: C09 Thiazide diuretic treatment ATC: C03A, C03B, C03EA01 Loop diuretic treatment ATC: C03C Income level Mean of previous 2 calendar years from income & taxation register Education level Age Sex Marital status Emigration date Death date Source National Patient Register Prescribed Drug Register (dispensed prescriptions) Income and Taxation Register Education Register Total Population Register Causes of Death Register Variables obtained in the SOReg or Itrim registries Baseline weight, waist Screening weight was used for the SOReg participants, circumference & body-mass since almost all are treated with VLCD in the months index before surgery. Weight at start of intervention was used for Itrim participants. Intervention date Date of first visit in Itrim. Date of surgery in SOReg. Systolic blood pressure According to the Itrim protocol, coffee and smoking should be avoided 30 minutes before the measurement. Blood pressures were measured in the left upper arm using an Omron 1240 oscillometric device with the cuff at heart level, in the sitting position with the back against the backrest and without crossed legs, after 5 minutes’ rest. If the first recording was elevated (SBP>=140 mmHg or DBP>=90 mmHg), a second measurement was obtained; the mean of those two measurements recorded. Registered in the SOReg protocol, without further instructions. Smoking Structured questionnaire in Itrim and SOReg. Weight & waist circumference Structured protocol in Itrim and SOReg. during follow-up Percent body fat during follow-up Structured protocol in Itrim, using a Tanita body impedance meter. 3 SOReg Itrim 2 1 Weight loss and heart failure Sundström et al. Supplemental Table 2. Baseline characteristics in persons with complete data vs those with any missing data Age (years) Male sex Weight (kg) Baseline body-mass index (kg/m2) Systolic blood pressure (mmHg) Married (%) Current smoker (%) Prior myocardial infarction (%) Prior atrial fibrillation (%) Prior valve disease (%) Prior substance abuse (%) Lipid-lowering drugs (%) Antidiabetic drugs (%) Antihypertensive drugs (%) Education <10 years (%) 10 to 12 years (%) >12 years (%) Income (1000 USD/year) Complete data (n= 23,700) 41.4 (41.2 to 41.5) 23.3 (22.7 to 23.8) 118.7 (118.5 to 118.9) 41.4 (41.3 to 41.4) 134.4 (134.2 to 134.6) 43.7 (43.1 to 44.3) 16.5 (16.0 to 16.9) 0.9 (0.7 to 1.0) 0.9 (0.8 to 1.0) 0.1 (0.0 to 0.1) 0.9 (0.8 to 1.0) 12.3 (11.9 to 12.7) 12.4 (12.0 to 12.8) 28.4 (27.9 to 29.0) Any missing data (n=15,805) 41.3 (41.1 to 41.5) 23.7 (23.0 to 24.4) 119.8 (119.5 to 120.1) 41.6 (41.5 to 41.6) 135.7 (134.7 to 136.7) 43.3 (42.5 to 44.1) 17.5 (15.9 to 19.1) 1.2 (1.0 to 1.3) 1.1 (0.9 to 1.3) 0.2 (0.1 to 0.3) 0.8 (0.6 to 0.9) 13.4 (12.9 to 14.0) 14.2 (13.7 to 14.8) 29.5 (28.7 to 30.2) Difference complete – missing 0.1 (-0.2 to 0.3) -0.4 (-1.3 to 0.5) -1.1 (-1.5 to -0.7) -0.2 (-0.3 to -0.1) -1.3 (-2.3 to -0.3) 0.4 (-0.6 to 1.4) -1.1 (-2.7 to 0.6) -0.3 (-0.5 to -0.1) -0.2 (-0.4 to -0.0) -0.1 (-0.2 to -0.0) 0.1 (-0.1 to 0.3) -1.2 (-1.9 to -0.5) -1.9 (-2.6 to -1.2) -1.0 (-1.9 to -0.1) 16.3 (15.8 to 16.7) 60.5 (60.0 to 61.0) 23.3 (22.8 to 23.8) 31.1 (30.9 to 31.4) 17.2 (16.7 to 17.8) 60.7 (60.2 to 61.2) 22.0 (21.4 to 22.6) 30.9 (30.6 to 31.2) -1.0 (-1.6 to -0.4) -0.3 (-0.4 to -0.1) 1.2 (0.5 to 1.9) 0.2 (-0.2 to 0.6) Data are means or percent and difference between persons with complete data on all variables and those with any missing data (95% confidence intervals) from an inverse probability-weighted sample. 4 Weight loss and heart failure Sundström et al. Supplemental Table 3. Baseline characteristics of sample re-weighted also by one-year BMI Age (years) Male sex Weight (kg) Baseline body-mass index (kg/m2) One-year body-mass index (kg/m2) Systolic blood pressure (mmHg) Married (%) Current smoker (%) Prior myocardial infarction (%) Prior atrial fibrillation (%) Prior valve disease (%) Prior substance abuse (%) Lipid-lowering drugs (%) Antidiabetic drugs (%) Antihypertensive drugs (%) Education <10 years (%) 10 to 12 years (%) >12 years (%) Income (1000 USD/year) Surgery (n=22,694) 41.5 (41.4 to 41.7) 25.2 (24.6 to 25.8) 119.5 (119.2 to 119.7) 41.4 (41.4 to 41.5) 29.2 (29.1 to 29.2) 135.0 (134.7 to 135.3) 43.0 (42.4 to 43.7) 15.5 (14.9 to 16.1) 1.0 (0.9 to 1.2) 1.0 (0.9 to 1.1) 0.2 (0.1 to 0.2) 0.8 (0.6 to 0.9) 13.7 (13.2 to 14.1) 14.0 (13.6 to 14.5) 30.3 (29.7 to 30.9) Lifestyle (n=8,653) 40.4 (40.2 to 40.6) 20.8 (20.1 to 21.5) 119.7 (119.4 to 120.0) 41.3 (41.3 to 41.4) 29.7 (29.6 to 29.8) 133.1 (132.8 to 133.4) 45.7 (44.8 to 46.5) 16.5 (15.8 to 17.2) 0.7 (0.6 to 0.9) 0.4 (0.3 to 0.5) 0.0 (-0.0 to 0.01) 0.6 (0.5 to 0.8) 8.2 (7.7 to 8.7) 7.7 (7.2 to 8.1) 23.0 (22.2 to 23.7) Difference surgery – lifestyle 1.1 (0.9 to 1.4) 4.4 (3.5 to 5.3) -0.2 (-0.7 to 0.2) 0.1 (0.1 to 0.2) -0.5 (-0.6 to -0.4) 1.9 (1.4 to 2.3) -2.6 (-3.7 to -1.5) -1.0 (-2.0 to -0.04) 0.3 (0.1 to 0.5) 0.6 (0.4 to 0.8) 0.1 (0.1 to 0.2) 0.1 (-0.1 to 0.3) 5.5 (4.8 to 6.2) 6.4 (5.7 to 7.0) 7.3 (6.4 to 8.3) 16.8 (16.3 to 17.3) 61.8 (61.3 to 62.3) 21.4 (20.8 to 21.9) 30.6 (30.4 to 30.9) 14.4 (13.9 to 14.9) 61.0 (60.5 to 61.6) 24.6 (23.9 to 25.3) 30.7 (30.3 to 40.0) 2.4 (1.8 to 3.0) 0.8 (0.6 to 1.0) -3.2 (-4.0 to -2.4) -0.02 (-0.4 to 0.4) Data are means or percent and difference between surgery and lifestyle groups (95% confidence intervals) from an inverse probability-weighted sample. 5 Weight loss and heart failure Sundström et al. Supplemental Figure 1. 6 Sundström et al. Weight loss and heart failure Supplemental Figure titles and legends Supplemental Figure 1. Flow chart for definition of the study sample Intervention years 2006-2013. BMI, body-mass index. 7 Dr Carolyn Lam: Welcome to Circulation on the Run, your weekly podcast summary and backstage pass to the journal and its editors. I'm Dr. Carolyn Lam, associate editor from the National Heart Center and Duke National University of Singapore. Our feature paper this week really adds to our understanding of the cause/effect relationship between obesity and heart failure, this time by comparing the effects of gastric bypass surgery versus intensive lifetime treatment on heart failure risk. Before we talk about that, though, let me give you your summary of this week's journal. The first paper brings us one step closer to understanding cardiac recovery in response to mechanical unloading by left ventricular assist devices and it does this by showing that this process may involve the transverse tubular system, which is a micro structural feature of ventricular cardiomyocytes important for contractility and consisting of tubular invaginations of the sarcolemma predominantly located at the Z‐lines of sarcomeres. This transverse tubular system is crucial for efficient excitation contraction coupling by bringing L‐type calcium channels in the sarcolemma in proximity to clusters of ryanodine receptors in the sarcoplasmic reticulum. In the current study by co‐corresponding authors, Dr. Seidel and Drakos and Sachse from University of Utah, the authors studied left ventricular biopsies obtained from five donors and 26 patients with chronic heart failure undergoing implantation of left ventricular assist devices or LVAD's. They used three dimensional confocal microscopy and computational image analysis to assess the transverse tubular system's structure, density, and distance of ryanodine receptor clusters to the sarcolemma. They found that the majority of heart failure myocytes showed remarkable transverse tubular system remodeling, particular sheet‐like invaginations of the sarcolemma, which is previously unknown phenotype. This sheet‐like transverse tubular system remodeling led to increased distances of ryanodine receptors to the sarcolemma causing heterogeneous intracellular calcium release and consequently inefficient excitation contraction coupling. High degrees of transverse tubular remodeling at the time of LVAD implantation was associated with absence of functional cardiac recovery during mechanical unloading, whereas preserved transverse tubular systems structure was associated with recovery. In summary, cardiac recovery during unloading may require an intact transverse tubular system at the time of LVAD implantation. And characterizing this system may help to identify patients with a high probability of functional cardiac recovery in response to mechanical unloading. There have been a proliferation of algorithms based in high sensitivity assays for cardiac troponins for the diagnosis or exclusion of myocardial infarction. All Need Help? mailto:[email protected] Get this transcript with table formatting these algorithms have the potential to overwhelm clinicians with options. Well, there is help in this week's issue with two observational studies directly comparing the diagnostic performances of multiple high‐sensitivity troponin testing strategies. Now, before I describe these two studies in detail, here are some important reminders. Remember that as of early 2017, although high‐sensitivity troponin assays are routinely used in many regions of the world, they are not available in the United States. Thus, the specific algorithms discussed here are not applicable with the contemporary sensitive assays that are presently used in the United States. Next, let's remind ourselves that both the United States and European professional guidelines recommend serial measurement of cardiac troponins at presentation or zero hours and three to six hours later with additional testing beyond six hours in patients who have electrocardiographic changes, or intermediate or high clinical risk features. The 2015 European Society of Cardiology Guidelines also included an alternative strategy reducing the sampling interval to one hour when using a high sensitivity troponin assay with a validated zero and one hour algorithm based on the 99 percentile cutoff of these high sensitivity troponin assays. Now to the two studies in the current issue, which tie together the expanding evidence with direct comparisons of several of the strategies using the same high sensitivity cardiac troponin assay by Abbott. Dr. Chapman and colleagues from the royal infirmary of Edinburgh, United Kingdom, compared the standard ECS zero and three hour strategy based on the 99th percentile upper reference limit at both time points with the high sensitivity troponin in the evaluation of patients with acute coronary syndrome, or high stakes algorithm, and that would be a zero, three, and six hour algorithm that incorporates a zero hour criteria and at a very low cutoff of five nanogram per liter and a three hour criterion that directs patients with either a rising concentration or with an absolute concentration above the upper reference limit to additional testing. Among 1,218 patients with suspected myocardial infarction, the high stakes algorithm delivered both a higher proportion ruled out for myocardial infarction at zero hours and a higher negative predictive value of 99.5% versus 97.9%. The ESC pathway missed 18 index and two recurrent myocardial infarction events, whereas the high stakes pathway missed two index and two recurrent myocardial infarction events. These findings demonstrate the value of adding a very low zero hour cutoff to facilitate earlier rule out as well as the value of a delta criterion to exclude increasing values among patients that progress to three hour sampling. In the next study, first author, Dr. Boeddinghaus, corresponding author Dr. Mueller and colleagues from University Hospital of Basel, Switzerland compared the ESC alternative zero and one hour strategy with three other approaches COTR135_17 For Review Page 2 of 6 using either a single cutoff at zero hours, or the one hour strategy. Among 2,828 patients with symptoms suspicious for myocardial infarction and no ST elevation, each of these four approaches delivered a negative predicted value above 99% comparing favorably to the ESC zero and three hour algorithm that had a negative predictive value of 98.4%. Now, although each of the strategies performed similarly among patients presenting more than two hours after symptom onset, among the early presenters, the negative predictive value and sensitivity were diminished using the single zero hour cutoff of five nanograms per liter. The authors concluded that the single cutoff strategy, the one hour algorithm, and the zero and one hour algorithm, allow the triage towards rule out of myocardial infarction in more than half of consecutive patients presenting with suspected MI to the emergency department. However, the single cutoff strategy should not be used in patients presenting early after chest pain onset. These papers are discussed in an excellent editorial, which also puts everything in perspective by Dr. David Morrow from Brigham and Women’s Hospital in Boston, Massachusetts. I particularity want to refer all of you to the figure that's found in its editorial which really helps you to understand the different strategies involved. The final study tells us about potential death averted and serious adverse events occurred from the adoption of the SPRINT intensive blood pressure regimen in the United States. As a reminder, the systolic blood pressure intervention trial, or SPRINT demonstrated a 27% reduction in all caused mortality with a systolic blood pressure goal of less than 120 versus less than 140 mm Hg among American adults at high cardiovascular risk, but without diabetes, stroke, or heart failure. In the current study, Dr. Bress and colleagues from the University of Utah School of Medicine applied the SPRINT eligibility criteria to the 1999 to 2006 National Health and Nutrition Examination Survey or NHANES and linked this with the national death index through December, 2011. They found that if fully implemented in eligible US adults, intensive blood pressure treatment was projected to prevent about 107,500 deaths and 46,100 of heart failure per year. But, you also give rise to about 56,100 episodes of hypertension. 34,400 episodes of syncope, 43,400 serious electrolyte disorders, and 88,700 of acute kidney injury per year compared to standard blood pressure treatment. Thus, they take home message is careful patients selection and implementation are important because intensive treatment while preventing deaths is associated with increased risks of hypertension, syncope, electrolyte abnormalities and acute kidney injury. Well, that brings us to a close for the summaries, now for our feature discussion. COTR135_17 For Review Page 3 of 6 We are discussing obesity and heart failure. Now, we've heard of the obesity paradox, but we also know that obesity may be a risk factor for heart failure and the study today really puts perspective on this and is really one of the largest most convincing studies I've read on this topic. I am so pleased to have the person corresponding author, Dr. Johan Sundstrom from Uppsala University Hospital in Sweden. Welcome, Johan. Dr Johan Sundstrom: Thank you, lovely to talk to you. Dr Carolyn Lam: And especially pleased to have back on the show again, Dr. Torbjorn Omland from University of Oslo, Norway. Hi, welcome back, Torbjorn. Dr Torbjorn Omland: Thank you very much. It's a great pleasure being here. Dr Carolyn Lam: Johan, you know what? Could you just start by telling us about your study? Dr Johan Sundstrom: So, we were fortunate enough to have two great databases here in Sweden. One was the obesity surgery registry called SOREG in which all people have a gastric bypass surgery, for people who are registered. And we also have a company called Itrim who provide intensive lifestyle program, which takes people down on average about 11 kilos, and they have a very structured database as well. So, we were able to pull this data in order to try and understand the effects of intentional weight loss to two different levels of weight loss, what that does to the heart failure incidence. This is a bit of a comparative effectiveness study, so it's of course necessary to make the examples as similar as possible to apply exclusion criteria. We took away everyone who had a body mass index of less than 30 and above 50 and then we applied propensity scores to those two data sets and we had to trim the data sets a little bit further in order to get so called region of common support, which means that we were left with two samples who could have either had surgery or a lifestyle intervention. And then we applied an inverse probability weighting scheme to that. It's statistically complicated but what that does, is it's a matching, but it's not as complicated as matching. With matching, you just give people a weight of 1 or 0, but this gives people other weights as well. So, we end up with characteristics that were very similar at baseline. So, we tried to mimic as close as possible what a randomized clinical trial looks like, but of course we did it posthoc and it’s observational. So, we get our table one, sort of, in this paper that shows very similar characteristics of the two groups. So, what we did then is we noted what happened to the people in these two groups in terms of heart failure incidence and we followed them in our national inpatient registry. So, all the Swedish citizens get a personal identification number so we can use that to follow people in our patient registry. So, we know exactly what drugs people will collect from pharmacies, and we know what they died from, and we know all of their hospitalizations. And we COTR135_17 For Review Page 4 of 6 previously validated their heart failure diagnosis in the Swedish Inpatient Registry and we noted that you were in a pretty good position if you were hospitalized with heart failure as the main cause of hospitalization and we noted that people who had agreed to do surgery, had about half the incidence of heart failure than people who were in the intensive lifestyle program. We also noted, if you looked at the achieved weight loss one year after baseline, we noted that a ten kilo weight loss after one year was related to about a 23% lower risk of heart failure. So we noted a litany of association between the achieved weight loss and heart failure incidence. It should said, though, that heart failure in this age group, they are only 41 on average, 41 years old. Heart failure's still very unusual at this age, even in many of these people. We only had 73 cases of heart failure. So, the exact numbers need to be taken with a pinch of salt and have wide confidence intervals around them. Dr Carolyn Lam: Johan, this is exactly why I'm so impressed with your data. First you showed a dose response relationship between the weight loss and risk of heart failure. You also show that it's not an event that occurs very often and so, it would be very difficult to imagine doing a randomized controlled trial for example in this setting and having to wait very long for these events. So, it really goes to show your observational data are extremely important. And I really like the way you took the pains to describe how you tried to overcome the differences that exist between the groups and try to make it as much resembling a randomized trial setting as you could. So, maybe I could turn it over to you, Torbjorn. Could you tell us what you think the implications of this paper are? Dr Torbjorn Omland: First, I will say that that this paper has all the characteristics of a very high quality study. It's a very timely topic that interests a lot of people. The paper's very well written. It's a large sample size as you said and it was very clinically meaningful difference between the groups and that translated into very clear and robust answers. So, I think that this has every mark of high quality paper. But, of course, the very important question is how will this translate into actions? How can we use this information to prevent problems? We know heart failure is a very prevalent disease, especially in the elderly and although the incidence was lower here, I think my question for Johan at least is what would be the next step? What changes can we implement to reduce heart failure among the obese? Dr Johan Sundstrom: That's a great question. I think in this study puts a little piece of the puzzle on the table and that's trying to add a little more evidence towards a causal association between obesity and heart failure. I'm not sure about what we can offer these patients and what will be the translation to lower heart failure incidence in the long run. Of course, we need to follow this sample for longer to have more heart failure cases, because I don't think we've seen the full impact of weight loss in these two samples. We might need to follow them into older age where they would have a higher heart failure incidence. COTR135_17 For Review Page 5 of 6 But, how to tackle obesity, I think we'll need accommodate population strategies and high risk strategies. I think if the general consensus in the scientific community after reading this and other important papers, is that there's causal link between obesity and heart failure, then we might need to understand that people who are obese and who have shortness of breath and perhaps swelling or what not, may not just be having low fitness, they might actually behaving signs of heart failure. So, I think as a sort of increased diligence on heart failure, these people might be one thing. But, we didn't really study that. So, I wouldn't draw conclusion. But, otherwise I think it's more of a causal inference piece of the puzzle that we've laid rather than a clinical care piece of the puzzle. Dr Torbjorn Omland: No, I agree, and here you won't to make any recommendations in regards to what interventions you should recommend particularly based on this particular study. Dr Johan Sundstrom: No, because I think there are so many other things that need to be taken into account when it comes to treatment of obesity. Heart failure is actually one of the uncommon outcomes in this age group. We're looking at other outcomes after they present. Myocardial infarction, ventral fibrillation and mortality are actually much more common. So, I think a lot of other data should go into decisions on how to treat patients, not just for heart failure, which is still fairly uncommon at this age. Dr Carolyn Lam: Going back to the other question that Torbjorn asked, do you think that this question still needs to be answered in any way? You've got the Mendelian randomization data. Now, you've got your data. Do you think it's still a question of whether obesity is a risk factor for heart failure? And just in case there's any confusion out there, would you put that together with the so called obesity paradox in heart failure? Dr Johan Sundstrom: To answer the first one, I think we're not going to have any randomized evidence. Treatment of heart failure with intensive programs and prevention of heart failure ... It needs for huge samples that I don't think we're going to have any much better observational evidence anytime soon either. So, we can probably set that question aside a little bit. But, when it comes to the obesity paradox, first of all that's not what we studied here. We didn't have anyone with heart failure in this sample. We included all those people. We can only speculate. I'm a clinical epidemiologist myself, but I'm envious of people who have animal and other models because I think there's a lot more work to do in terms of ppars and and lipid metabolism in obesity and in heart failure. So, I think there'll be more interesting experimental research to come that can help us answer the obesity paradox. Dr Carolyn Lam: Please don't forget to tell your friends about this podcast, and tune in again next week. COTR135_17 For Review Page 6 of 6