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François Schiele , MD, PhD, Nicolas Meneveau , MD, PhD, PowerPoint Presentation
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François Schiele , MD, PhD, Nicolas Meneveau , MD, PhD,

François Schiele , MD, PhD, Nicolas Meneveau , MD, PhD,

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François Schiele , MD, PhD, Nicolas Meneveau , MD, PhD,

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  1. Effects of Clinical Characteristics and Treatments on Gender Difference in Outcomes after Acute Myocardial Infarction. A propensity score-matched analysis François Schiele, MD, PhD, Nicolas Meneveau, MD, PhD, Marie France Seronde, MD, Vincent Descotes-Genon, MD, Joanna Dutheil, MD, RomainChopard, MD, Fiona Ecarnot, and Jean-Pierre Bassand, MD. On behalf on the “Reseau de Cardiologie de FrancheComté” Department of Cardiology, University Hospital Jean Minjoz, Besançon, France. Conflict of Interest to Declare : Research Contracts and Consulting Servier, Sanofi, GSK, Astra-Zeneca, Takeda, Lilly

  2. Women fare worse than men after acute MI • Women admitted for acute MI have 40-100% higher mortality at 30 days, as compared with men. This over-mortality is reduced after adjustment for age and co-morbidities. Malacrida, ISIS-3, N Engl J Med 1998;338:8-14

  3. Women fare worse than men after acute MI • Women admitted for acute MI have 40-100% higher mortality at 30 days, as compared with men. This over-mortality is reduced after adjustment for age and co-morbidities. • Sex-age interaction : discrepancy between studies • Greater difference with older age • Decrease in difference with age Malacrida, N Engl J Med 1998;338:8-14 Vaccarino, N Engl J Med 1999;341:217-25

  4. Women fare worse than men after acute MI • Women admitted for acute MI have 40-100% higher mortality at 30 days, as compared with men. This over-mortality is reduced after adjustment for age and co-morbidities. • Sex-age interaction : discrepancy between studies • Sex-type of MI interaction : STEMI ≠ NSTEMI Berger, JAMA 2009;302:874-82

  5. Women fare worse than men after acute MI • Women admitted for acute MI have 40-100% higher mortality at 30 days, as compared with men. This over-mortality is reduced after adjustment for age and co-morbidities. • Sex-age interaction : discrepancy between studies • Sex-Type of MI interaction : STEMI ≠ NSTEMI • Women receive fewer treatments and no difference in mortality is observed after adjustment for co-morbidities and treatments Gan, N Engl J Med 2000;343:8-15

  6. Women fare worse than men after acute MI • Women admitted for acute MI have 40-100% higher mortality at 30 days, as compared with men. This over-mortality is reduced after adjustment for age and co-morbidities. • Sex-age interaction : discrepancy between studies • Sex-Type of MI interaction : STEMI ≠ NSTEMI • Women receive fewer treatments and no difference in mortality is observed after adjustment for co-morbidities and treatments Aim of the Study To assess the effects of Clinical Characteristics and Treatments on Gender Difference , using a Propensity Score-Matched Analysis.

  7. Methods • All consecutive patients admittedbetweenJanuary 2006 and December2007 • CARDS dataset, dedicated team of data managers. • Endpoint: 30 day all-cause mortality • Use of matched pairs comparison: • TwoPropensityscores for being male by logisticregression, • PS#1 withbaselinecharacteristics (16 variables) • PS#2 withbaselinecharacteristics and treatments • 1:1 matchingon best 8 digits of the propensity score (match allowed for PS<0.015) • 30 daymortality (Kaplan Meier curves and Oddsratios fromconditionallogisticregression) in unadjusted and matchedcohorts • Interactions : age, type of MI (STEMI vs NSTEMI).

  8. Baseline characteristics (1)

  9. Baseline characteristics (2)

  10. In-hospital Treatments

  11. Selection of the matched populations 3510 patients with Acute Myocardial Infarction 1578 (45%) STEMI, 1932 (55%) NSTEMI 1119 (32%) Women, 2391 (68%) Men Propensity score 1 (being male) with baseline characteristics Propensity score 2 (being male) with baseline characteristics and treatments Matching on propensity score 1 = 649 pairs Matching on propensity score 2 = 584 pairs Comparison of mortality Comparison of treatments Comparison of mortality

  12. Effect of matching on sex differences 0.05 P values for the differencebetween men and women Unmatcheddataset

  13. Effect of matching on sex differences 0.05 P values for the differencebetween men and women Unmatcheddataset Matched #1 dataset

  14. Effect of matching on sex differences 0.05 P values for the differencebetween men and women Unmatcheddataset Matched #1 dataset Matched #2 dataset

  15. Women Men Log-Rank test: p=0.95 Days 0 5 10 20 30 At risk 584 574 565 544 529 584 573 562 550 530 KM Cumulative mortality Unmatched n=3510 p=0.001 Matched #1 n=649 pairs p=0.23 Matched #2 n=584 pairs p=0.95 Unmatched n=3510 p=0.001 Unmatched n=3510 p=0.001 Matched #1 n=649 pairs p=0.23

  16. Aspirin unmatched OR= 1.35 [1.06; 1.80] Matched #1 OR= 1.10 [0.46; 2.62] Clopidogrel unmatched OR= 1.65 [1.38; 2.01] Matched #1 OR= 1.04 [0.58; 1.84] Aspirin and Clopidogel unmatched OR= 1.67 [1.40; 2.01] Matched #1 OR= 1.10 [0.46; 1.63] ACEI or ARB unmatched OR= 1.42 [1.24; 1.65] Matched #1 OR= 1.29 [0.97; 1.70] Beta blocker unmatched OR= 1.31 [1.15; 1.49] Matched #1 OR= 1.02 [0.64; 1.29] GPIIbIIIa (NSTEMI) unmatched OR= 1.66 [1.43; 1.96] Matched #1 OR= 1.40 [0.94; 1.56] CoronaryAngiography unmatched OR= 2.82 [2.40; 3.41] Matched #1 OR= 1.57 [1.10; 2.18] Reperfusion /PPCI unmatched OR= 1.56 [1.29; 1.89] Matched #1 OR= 1.24 [1.12; 1.71] Reperfusion /FL unmatched OR= 1.82 [1.24; 2.12] Matched #1 OR= 1.72 [1.08; 2.73] In-Hospitalmortality unmatched OR= 0.50 [0.37; 0.62] Matched #1 OR= 0.52 [0.32; 0.83] Matched #2 OR= 0.75 [0.45; 1.23] 30 daymortality unmatched OR= 0.53 [0.42; 0.57] Matched #1 OR= 0.70 [0.46; 1.01] Matched #2 OR= 0.89 [0.57; 1.36] 0.5 0.8 1 1.5 2 4 Odds ratios for men versus women

  17. Sub-groups (1) Interaction betweenGender and type of MI P=0.009 P=0.009 P=0.009 P=0.36 P=0.36 P=0.13 Mortality more than twice as high in womenthan in men in STEMI, but no difference in NSTEMI patients; significant interaction No highermortality and no interaction afteradjustment for characteristics No highermortality and no interaction afteradjustment for characteristics and treatments

  18. Sub-groups (2) Interaction betweenGender and Age: differenceaccording to meanage Unadjustedcohort Sex-age interaction P=0.002 Matched #1 Sex-age interaction P=0.005 Matched #2 No sex-age interaction P=0.16

  19. Discussion • Matchingon propensityscore withanalysisby pairs • Differences in characteristics, treatments and mortality • Sex-age interaction : significant interaction withgreatergenderdifference in older patients, disappearsaftermatching. • Sex-type of MI interaction disappearsaftermatching • Sexdifferences in aspirin, clopidogrel, betablockers, ACEI and statins are explained by characteristics. • Sexdifferences in coronaryangiography and reperfusion in STEMI are not explained by characteristics • No difference in mortalityaftermatching on characteristics and treatments. Vaccarino, New Engl J Med 1999 Austin, Use of PS.., Stat Med 2005 Blomkalns, CRUSADE, JACC 2005;45:832-7 RosengrenEur Heart J 2001; 22: 314–322, Milcent Circulation. 2007;115:833-839 Berger, JAMA 2009;302:874-82

  20. Conclusions • As comparedwith men, womenadmitted for acute MI receivefewer effective treatments and have a twofoldhigher 30 daymortality. • Comparison of cohortsmatched on baselinecharacteristics shows thatco-morbiditiesexplainthe lower use of treatments. Nevertheless, women are lessoftensubmitted to coronaryangiography and reperfusion (STEMI) and have a higher in-hospitalmortality. • Comparison of cohortsmatched on baselinecharacteristics and treatments shows similar in-hospital and 30 daymortalitybetweengenders, suggestingthat a higher use of invasive procedures and reperfusionstrategycouldreduce the difference in mortality.