1. Clickbait title but content worth discussing- my thoughts over the next few tweets
➡️Questions around AMI definition.
Dr Taggart and others were part of the discussions that agreed to AMI definition. I think it was right because- see2.
medscape.com/viewarticle/93… via @medscape
2. an endpoint should have same prognostic impact in each trial arm. EXCEL definition does, UDMI doesnt
however:
➡️Should probably only include spontaneous AMI post procedure (>72 hrs), whatever definition you use, CABG better in long term
3. ➡️I personally dont think perceived COI have had any impact on the running / outcomes of the trial. Without industry support this trial would never have happened, nor would have many other fundamental trials. This is a smoke screen
4. ➡️Question around data & safety monitoring board (DSMB) requesting an analysis without time capping is a concern.
- why was this request turned down? would be interested 2 see arguments against this.
Investigators should be duty bound to address concerns of DSMB where poss.
5. ➡️Question around guidelines
The authors of guidelines should not be the ones that have run the RCTs - there is a clear COI. If they are, then should not be involved in the parts that pertain to their trials, ie LMS recommendations.
6. ➡️Independent reviews
When independent reviews are sought, in areas of stalemate- then these independent reviews should be circulated to all stakeholders. If this was not the case, then this is a serious problem of guideline committee, not the trialists.
7. ➡️Need for change in guidelines
Absolutely! because of the evidence that has accumulated from trials like EXCEL. @GreggWStone and colleagues should be congratulated for bring us this trial. but in my view, totality of evidence now does not support equivalence for PCI and CABG
8. ➡️It is my view that CABG should be class 1, PCI IIa for LMS.

CABG associated with long term ⬇️in spont AMI, need for rpt procedures (that have prognostic impact) and possibly a mortality impact (but not seen in totality of data)
9. Tone of article including "grubby" is unprofessional. LMS represents 3% of all PCI. LMS PCI is not a big market for stent companies.
10. There are some questions to be answered both around decsions taken by EXCEL but also guideline committee (see above)
➡️Remember, #EXCEL has given us wonderful data to inform management of this group of pts, but also discuss which endpoints to use and their impacts in trials
11. Penultimately EXCEL has given us the data for much needed change in guidelines. In my view these should swing back towards CABG.
➡️EXCEL trialists should be congratulated in bring this trial to community
➡️But 2 questions above need to be answered

Finally...
12. ➡️Need to think carefully about how guidelines are created and who is on them. Shouldnt be trialists that have run the trials.

To my mind this is the greatest COI, not the trial. Any external review should be transparent and available to all members of committee. The end 😉

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More from @mmamas1973

11 Oct
1. My talk today at #SHA2020 surgeon session re what #EXCEL really shows. To begin- need to understand importance of endpoints
➡️clinically relevant
➡️related to intervention
➡️relevant to pt
➡️similar prognostic impact in each arm
@SVRaoMD @ajaykirtane @RodrigoBagur @jedicath
2. A significant proportion of LMS wont be suitable for either surgery / CABG. As heart teams we have to do better in stratifying by extent of disease - 1/4 of pts included in #EXCEL didnt meet inclusion criteria (low/ intermediate risk) @ovidiogarciav @aspergian1 @cardioPCImom
3. The question of periporcedural AMI definition- depends on how you define re UDMI or protocol definition, will impact whether CABG 2x greater or 1/3 less. Personally i think protocol definition better as prognostic impact of AMI the same then in both arms (see pt 1)- BUT ➡️
Read 11 tweets
23 Jul
1. Our analysis of 144,000 deaths in UK during #COVID19 1st march-12th May published today mayoclinicproceedings.org/article/S0025-… . First national study of causes of death and underlying medical conditions. led by @dr_mosama with @dataevan @cpgale3 @TomLuscher only 25% of deaths due to COVID.
2. Age standardised mortality rates in UK ⬆️⬆️ for non-covid deaths than covid deaths during pandemic for all age groups @TheBHF @amibanerjee1 @DailyMailUK @guardian @ncurzen @ErinMichos @EricSecemskyMD @venkmurthy @DavidLBrownMD @BBCWorld @KeeleComms @AnastasiaSMihai @jcspratt
3. #COVID19 had the highest ASMR at each age group apart from young women where cancer was the commonest cause of death @SkyNews @Telegraph @Pooh_Velagapudi @poojaotherwise @adityadoc1 @onco_cardiology @mirvatalasnag @DrJenniferCo_Vu @jedicath @RodrigoBagur @VietHeartPA
Read 8 tweets
29 Jan
1. Our analysis of >70,000 pts with rheumatological disease undergoing pci (RA, SLA, SSC) led by @saraceciliamtz and @dr_mosama with collobaration with rheumatologists. 1.4% of pts have rheumaological diseases @DocSavageTJU @adityadoc1 @RodrigoBagur RA increasing over time
2. Patients with SLE have ⬆️ bleeding whilst pts with SSC highest risk, with ⬆️ mortality and stroke. Pts with RA not at increased risk once demographics adjusted. @Hragy @DBelardoMD @purviparwani @aspergian1 @stefan_harb @AnastasiaSMihai @drandrewsharp @billgogas @VijayKunadian
3. Summary slide. Analyses of nationwide databases provide a real- world vantage of outcomes on performed procedures, supplementing controlled trials and prospective cohorts and often answering questions on populations excluded from trials or at low prevalence. @mirvatalasnag
Read 4 tweets
1 Aug 19
1. Our work led by the v talented @Claire_A_Lawson with @kamleshkhunti et al studying 20 yr trends in outcomes in 88,000 pts with incident HF in UK. thelancet.com/journals/lanpu… Hospitalization rates ⬆️ particularly in areas of deprivation & older pts. @hvanspall @ShelleyZieroth
@Claire_A_Lawson @kamleshkhunti @hvanspall @ShelleyZieroth @GiuseppeGalati_ @bogdienache @DrMarthaGulati @purviparwani @AChoiHeart @onco_cardiology @avolgman @gina_lundberg @rwyeh @ErinMichos 2. >70% of Hospitalisations are non-CV. greater risk for those diagnosed in hospital vs community. Of CV causes of hospitalisation, HF related admissions becoming increasingly common. Data for mortality even more interesting ➡️ @iamritu @AnastasiaSMihai @mirvatalasnag @jedicath
Read 4 tweets
2 Dec 18
1. My Big Data talk in pci at #ICI18 meeting in Tel Aviv. Guidelines tell us to take comorbidity, cancer, frailty into account to guide practice, but not found in contemporary risk scores. Data from EHR can help guide. @DrMauricioCohen @Uqayyum123 @SmithElliotjs @jodiel0ve
2. Cardiologists have narrow view of comorbidity. consider individual conditions & not global comorbid burden. Non-CV death and readmissions more common than CV death following PCI. Driven by comorbidity. @mirvatalasnag @akhojaMD @Dralkutshan @jedicath @MBalghith @DocSavageTJU
3. Global comorbid burden such as Charlson, Elixhouser provide important prognostic information for PCI. 1 in 10 pts in PCI have a current or prior hx of cancer, yet we dont use any of this information in our risk models / to guide decisions. Unmet Need @DrFernandoCohen
Read 4 tweets

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