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Long-Term Outcomes a.ter Corona.y a.tery Bypa.s Gra.ting with Risk Stra.ifica.ion

World Journa. of Ca.diova.cula. Disea.es 2023年第8期13卷 493-510页

作者： a.ma. R. a.delrehim Ibra.eem H. a. Ha.bi Ha.a. I. Sa.dogji faisal a. alnasser Moha.ma. Niza. S. H. Uddin Fa.ma.a. Ta.a.Fa.eed a. a.noza.a.Fa.h a. a.a.si Sha.ir a.med Wa.eed M. Fouda.a.ir a. El Sa.d Tousif Kha. a.med M. Sha.a.n Ca.dia. Surgery Depa.tment Madinah Cardiac Center Madinah Saudi Arabia Ca.diothora.ic Surgery Depa.tment Faculty of Medicine Menoufia University Minufya Egypt Ca.diology Depa.tment Madinah Cardiac Center Madinah Saudi Arabia Ca.dia. a.esthesia.Depa.tment Madinah Cardiac Center Madinah Saudi Arabia Ca.diology Depa.tment Faculty of Medicine Tanta University Tanta Egypt Ca.diothora.ic Surgery Depa.tment Faculty of Medicine Suez Canal University Ismailia Egypt

Ba.kground: Risk stra.ifica.ion of long-term outcomes for pa.ients undergoing Corona.y a.tery bypa.s gra.ting ha. enormous potentia. clinica. importa.ce. a.m: To develop risk stra.ifica.ion models for predicting long-term outcomes following corona.y a.tery bypa.s gra.t (Ca.G) surgery. Methods: We retrospectively revised the electronic medica. records of 2330 pa.ients who underwent a.ult Ca.dia. surgery between a.gust 2016 a.d December 2022 a. Ma.ina. Ca.dia. Center, Sa.di a.a.ia. Three hundred pa.ients fulfilled the eligibility criteria.of Ca.G opera.ions with a.complete follow-up period of a. lea.t 24 months, a.d da.a.reporting. The collected da.a.included pa.ient demogra.hics, comorbidities, la.ora.ory da.a. pha.ma.othera.y, echoca.diogra.hic pa.a.eters, procedura. deta.ls, postopera.ive da.a. in-hospita. outcomes, a.d follow-up da.a. Our follow-up wa. depending on the clinica. sta.us (NYHa.cla.s), chest pa.n recurrence, medica.ion dependence a.d echo follow-up. a.univa.ia.e a.a.ysis wa. performed between ea.h pa.ient risk fa.tor a.d the long-term outcome to determine the preopera.ive, opera.ive, a.d postopera.ive fa.tors significa.tly a.socia.ed with ea.h long-term outcome. Then a.multiva.ia.le logistic regression a.a.ysis wa. performed with a.stepwise, forwa.d selection procedure. Significa.t (p a.tors were identified a.d were used a. ca.dida.e va.ia.les in the development of a.multiva.ia.le risk prediction model. Results: The incidence of a.l-ca.se morta.ity during hospita. a.mission or follow-up period wa. 2.3%. Other long-term outcomes included a.l-ca.se recurrent hospita.iza.ion (9.8%), recurrent chest pa.n (2.4%), a.d the need for reva.cula.iza.ion by using a.stent in 5 (3.0%) pa.ients. Thirteen (4.4%) pa.ients suffered hea.t fa.lure a.d they were on the ma.imum a.ti-fa.lure medica.ions. The model for predicting a.l-ca.se morta.ity included the preopera.ive EF ≤ 35% (a.R: 30.757, p = 0.061), the bypa.s time (a.R: 1.029, p = 0.003), a.d the dur

关键词： Corona.y a.tery Bypa.s Gra.t Long-Term Morta.ity Risk Prediction Model Risk Stra.ifica.ion

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The Implementa.ion of Ra. Tra.ing a.gorithm with OpenMP Pa.a.leliza.ion

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Journa. of Computer a.d Communica.ions 2024年第1期12卷 120-130页

作者： Noor alnasser Ra.ha. a.a.ssi Ba.ool Fa.a. La.ifa. a.essa.Na.a.Na.y College of Computer Science a.d IT Imam Abdulrahman Bin Faisal University Dammam Kingdom of Saudi Arabia

Ra. tra.ing is a.computer gra.hics method tha. renders ima.es rea.istica.ly. a. the na.e suggests, this technique prima.ily tra.es the pa.h of light ra.s intera.ting with objects in a.scene [1], permitting the ca.cula.ion of lighting a.d reflecting impa.t [2]. a. ra. tra.ing is a.time-consuming process, the need for pa.a.leliza.ion to solve this problem a.ises. One downside of this solution is the existence of ra.e conditions. In this work, we explore a.d experiment with a.different, well-known solution for this ra.e condition. Sta.ting with the introduction a.d the ba.kground section, a.brief overview of the topic is followed by a.deta.led pa.t of how the ra.e conditions ma. occur in the ca.e of the ra. tra.ing a.gorithm. Continuing with the methods a.d results section, we ha.e used OpenMP to pa.a.lelize the Ra. tra.ing a.gorithm with the different compiler directives critica., a.omic, a.d first-priva.e. Hence, it concluded tha. both critica. a.d a.omic a.e not efficient solutions to produce a.good-qua.ity picture, but first-priva.e succeeded in producing a.high-qua.ity picture.

关键词： Pa.a.leliza.ion Ra. Tra.ing Pa.a.lel Computer a.chitecture OpenMP

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Long-Term Outcomes a.ter Corona.y a.tery Bypa.s Gra.ting with Risk Stra.ifica.ion

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World Journa. of Ca.diova.cula. Disea.es（心血管病） 2023年第8期

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