Body Mass Index, Periprocedural Bleeding, and Outcome Following Percutaneous Coronary Intervention (from the British Columbia Cardiac Registry)

Byrne, Jonathan; Spence, Mark S.; Fretz, Eric; Mildenberger, Richard R.; Chase, Alex; Berry, Brian; Pi, David; Janßen, Christian; Klinke, Peter; Hilton, David

doi:10.1016/j.amjcard.2008.10.027

Cited by 51 publications

(42 citation statements)

References 23 publications

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“…Applications of imputation by chained equations have now appeared in quite diverse fields: addiction (Schnoll et al 2006;MacLeod et al 2008;Adamczyk and Palmer 2008;Caria et al 2009;Morgenstern et al 2009), arthritis and rheumatology (Wolfe et al 2006;Rahman et al 2008;van den Hout et al 2009), atherosclerosis (Tiemeier et al 2004;van Oijen et al 2007;McClelland et al 2008), cardiovascular system (Ambler et al 2005;van Buuren et al 2006a;Chase et al 2008;Byrne et al 2009;Klein et al 2009), cancer (Clark et al 2001Royston et al 2004;Barosi et al 2007;Fernandes et al 2008;Sharma et al 2008;McCaul et al 2008;Huo et al 2008;Gerestein et al 2009), epidemiology (Cummings et al 2006;Hindorff et al 2008;Mueller et al 2008;Ton et al 2009), endocrinology (Rouxel et al 2004;Prompers et al 2008), infectious diseases (Cottrell et al 2005;Walker et al 2006;Cottrell et al 2007;Kekitiinwa et al 2008;Nash et al 2008;Sabin et al 2008;Thein et al 2008;Garabed et al 2008;Michel et al 2009), genetics …”

Section: Applications Of Chained Equationsmentioning

confidence: 99%

mice: Multivariate Imputation by Chained Equations inR

Buuren¹,

2011

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The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice 2.9, which extends the functionality of mice 1.0 in several ways. In mice 2.9, the analysis of imputed data is made completely general, whereas the range of models under which pooling works is substantially extended. mice 2.9 adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs. Imputation of categorical data is improved in order to bypass problems caused by perfect prediction. Special attention is paid to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. mice 2.9 can be downloaded from the Comprehensive R Archive Network. This article provides a hands-on, stepwise approach to solve applied incomplete data problems.

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Section: Applications Of Chained Equationsmentioning

confidence: 99%

mice: Multivariate Imputation by Chained Equations inR

Buuren¹,

2011

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“…17 These reports include patients with both clinically evident and clinically silent (subclinical) peri-procedural bleeding events. 1,7,8,11,12,[18][19][20][21] Recent studies have shown that clinically silent peri-procedural blood loss is strongly associated with increased mortality and contrast-induced nephropathy. 22,23 The predictors of a clinically silent or subclinical periprocedural drop in hemoglobin have not been defined.…”

Section: Introductionmentioning

confidence: 99%

Factors related to a clinically silent peri-procedural drop in hemoglobin with coronary and peripheral vascular interventions

et al. 2011

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Clinically evident and subclinical peri-procedural bleeding following interventional therapies are associated with adverse cardiovascular outcomes. The risk factors for clinically evident bleeding have been well described. Despite the welldocumented association of adverse outcomes for patients with a subclinical peri-procedural hemoglobin drop, the clinical predictors have not yet been defined. We identified 1176 consecutive patients with a subclinical drop in hemoglobin (fall of ≥ 1 g/dl in patients without clinical bleeding) following percutaneous coronary interventions (PCI) and peripheral vascular interventions (PVI). Multivariate logistic regression analysis was performed. A subclinical peri-procedural hemoglobin drop ≥ 1 g/dl was identified in 41% (400/972) of PCI and in 49% (213/435) of PVI. More than one access site predicted a higher risk of a subclinical drop in hemoglobin in both groups. A body mass index ≥ 30 predicted a lower risk of a subclinical drop in hemoglobin in both groups. For PCI, creatinine clearance < 60 ml/min was associated with a higher risk of a subclinical drop in hemoglobin. In conclusion, clinically silent peri-procedural hemoglobin fall ≥ 1 g/dl is common in patients undergoing both coronary and peripheral percutaneous intervention. Predictors identified in our study will need prospective validation.

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“…As in other populations, obesity is presumed to be a risk factor for post-operative morbidity and mortality; however, data has been confl icting at best. One study examining a registry in British Columbia, Canada, demonstrates a "U" shaped relation between BMI and mortality, which was particularly evident in underweight patients (Byrne et al 2009 ) . However, Oreopoulos further examined the impact of obesity on both short and long-term mortality following PCI in a meta-analysis of 22 studies (Oreopoulos et al 2008b ) .…”

Section: Bmi and Cardiac Surgerymentioning

confidence: 98%