Survival Disparity Following Abdominal Aortic Aneurysm Repair Highlights Inequality in Ethnic and Socio-economic Status

Khashram, Manar; Pitama, Suzanne; Williman, Jonathan; Jones, Gregory T.; Roake, Justin

doi:10.1016/j.ejvs.2017.08.018

Cited by 21 publications

(22 citation statements)

References 33 publications

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“…Ethnicity, smoking status, and socioeconomic status did not contribute to the models as previously hypothesised. Ethnicity has been seen to correlate with surgical outcomes in New Zealand, 25 and it was found to be an important covariable in the original NZRISK model. 12 There is also increasing appreciation of the importance of socioeconomic status to health outcomes in the medical literature.…”

Section: Discussionmentioning

confidence: 99%

Editor's Choice – Development and Validation of a Multivariable Prediction Model of Peri-operative Mortality in Vascular Surgery: The New Zealand Vascular Surgical Risk Tool (NZRISK-VASC)

Kim

Boyle

Khashram

et al. 2021

European Journal of Vascular and Endovascular Surgery

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Pre-operative decision making is a crucial part of a patient's management plan, and risk calculators and prediction models are available to assist clinicians and patients during this process to optimise the outcome. There are numerous surgery specific risk prediction tools for vascular surgical patients; however, their general clinical utility is limited. A multivariable risk prediction model was developed that can predict 30 day, one year, and two year mortality in vascular surgical patients. It requires only 10 easily obtainable covariables in the pre-operative setting, making it potentially practical and easy to use.Objective: Risk calculators and prediction models are available to assist clinicians and patients with perioperative decision making to optimise outcomes. In a vascular surgical setting, the majority of these models is based on open AAA repair outcomes, and in general their clinical use is limited. The objective of this study was to develop and validate a simple and accurate vascular surgical risk prediction model. Methods: A national administrative database was accessed to collect information on all adult patients undergoing vascular surgery between 1 July 2011 and 30 June 2016 in New Zealand. The primary outcomes were mortality at 30 days, one year, and two years. Previously established covariables including American Society of Anaesthesiologists (ASA) physical status score, sex, surgical urgency, cancer status and ethnicity were tested, and other covariables such as smoking status, presence of renal failure, diabetes, anatomical site of operation, structure operated, and type of procedures (open or endovascular) were explored. LASSO regression was used to select variables for inclusion in the model. Results: A total of 21 597 cases formed the final risk prediction models, with covariables including ASA score, gender, surgical urgency, cancer status, presence of renal failure, diabetes, anatomical site, structure operated, and endovascular procedure. The area under the receiver operating curve (AUROC) for 30 day, one year, and two year mortality using L-min model was 0.869, 0.833, and 0.824, respectively, demonstrating very good discrimination. Calibration with the validation dataset was also excellent, with slopes of 0.971, 1.129, and 1.011, respectively, and McFadden's pseudo-R 2 statistics of 0.250, 0.227, and 0.227, respectively. Conclusion: A simple and accurate multivariable risk calculator for vascular surgical patients was developed and validated using the New Zealand national dataset, with excellent discrimination and calibration for 30 day, one year, and two year mortality.

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Section: Discussionmentioning

confidence: 99%

Editor's Choice – Development and Validation of a Multivariable Prediction Model of Peri-operative Mortality in Vascular Surgery: The New Zealand Vascular Surgical Risk Tool (NZRISK-VASC)

Kim

Boyle

Khashram

et al. 2021

European Journal of Vascular and Endovascular Surgery

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“…Other important risk factors contributing to mortality in people with mental disorders include age, gender, marital status, socioeconomic deprivation and ethnicity [21][22][23][24][25][26][27]. However, these risk factor influence mortality in people with physical diseases, too [28][29][30]. Therefore, they seem to be general factors which modify mortality.…”

Section: Mortality For People With Anmentioning

confidence: 99%

Psychiatric comorbidity as a risk factor for mortality in people with anorexia nervosa

Himmerich

Hotopf

Shetty

et al. 2018

Eur Arch Psychiatry Clin Neurosci

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Anorexia nervosa (AN) is found associated with increased mortality. Frequent comorbidities of AN include substance use disorders (SUD), affective disorders (AD) and personality disorders (PD). We investigated the influence of these psychiatric comorbidities on all-cause mortality with demographic and socioeconomic factors considered as confounders in the observation window between January 2007 and March 2016 for 1970 people with AN, using data from the case register of the South London and Maudsley (SLaM) NHS Foundation Trust, an almost monopoly-secondary mental healthcare service provider in southeast London. We retrieved data from its Clinical Records Interactive Search (CRIS) system as data source. Mortality was ascertained through nationwide tracing by the UK Office for National Statistics (ONS) linked to CRIS database on a monthly basis. A total of 43 people with AN died during the observation period. Standardized Mortality Ratio (SMR) with England and Wales population in 2012 as standard population for our study cohort was 5.21 (95% CI 3.77, 7.02). In univariate analyses, the comorbidity of SUD or PD was found to significantly increase the relative risks of mortality (HRs = 3.10, 95% CI 1.21, 7.92; and 2.58, 95% CI 1.23, 5.40, respectively). After adjustment for demographic and socioeconomic covariates as confounders, moderately but not significantly elevated risks were identified for SUD (adjusted HR = 1.39, 95% CI 0.53, 3.65) and PD (adjusted HR = 1.58, 95% CI 0.70, 3.56). These results suggest an elevated mortality in people with AN, which might be, at least partially, explained by the existence of the comorbidities SUD or PD.

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“…Low SES has been linked with a higher prevalence of multiple cardiovascular conditions, including AS [7], rheumatic heart disease [8], and abdominal aortic aneurysm (AAA) [9], as well as worse morbidity and/ or mortality in the setting of aortic aneurysm [10], aortic dissection [11], stable coronary artery disease [12], and acute coronary syndromes [13,14]. Low SES has also been associated with delayed and/or absent referral for cardiac procedures [15,16] as well as poor outcomes following multiple cardiovascular interventions including PCI [17][18][19], CABG [20][21][22], aortic and/or mitral valve surgery [21,[23][24][25], infrainguinal bypass [26,27], and aortic aneurysm repair [28][29][30].…”

Section: Discussionmentioning

confidence: 99%

Distressed Communities Index in Patients Undergoing Transcatheter Aortic Valve Implantation in an Affluent County in New York

Bilfinger

Nemesure

Pyo

et al. 2021

Journal of Interventional Cardiology

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Background. The clinical impact of the distressed communities index (DCI), a composite measure of economic well-being based on the U.S. zip code, is becoming increasingly recognized. Ranging from 0 (prosperous) to 100 (distressed), DCI’s association with cardiovascular outcomes remains unknown. We aimed to study the association of the DCI with presentation and outcomes in adults with severe symptomatic aortic stenosis (AS) undergoing transcatheter aortic valve intervention (TAVR) in an affluent county in New York. Methods. The study population included 286 patients with severe symptomatic AS or degeneration of a bioprosthetic valve who underwent TAVR with a newer generation transcatheter heart valve (THV) from December 2015 to June 2018 at an academic tertiary medical center. DCI for each patient was derived from their primary residence zip code. Patients were classified into DCI deciles and then categorized into 4 groups. The primary and secondary outcomes of interest were 30-day, 1-year, and 3-year mortality, respectively. Results. Among 286 patients studied, 26%, 28%, 28%, and 18% were categorized into DCI groups 1–4, respectively (DCI <10: n = 73; DCI 10–20: n = 81; DCI 20–30: n = 80; DCI >30: n = 52). Patients in group 4 were younger with worse kidney function compared to patients in groups 1 and 2. They also had smaller aortic annuli and were more likely to receive a smaller THV. No significant difference in hospital length of stay or distribution of in-hospital, 30-day, 1-year, and 3-year mortality was demonstrated. Conclusions. While the DCI was associated with differences in the clinical and anatomic profile, it was not associated with differences in clinical outcomes in this prospective observational study of adults undergoing TAVR suggesting that access to care is the likely discriminator.

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Survival Disparity Following Abdominal Aortic Aneurysm Repair Highlights Inequality in Ethnic and Socio-economic Status

Cited by 21 publications

References 33 publications

Editor's Choice – Development and Validation of a Multivariable Prediction Model of Peri-operative Mortality in Vascular Surgery: The New Zealand Vascular Surgical Risk Tool (NZRISK-VASC)

Editor's Choice – Development and Validation of a Multivariable Prediction Model of Peri-operative Mortality in Vascular Surgery: The New Zealand Vascular Surgical Risk Tool (NZRISK-VASC)

Psychiatric comorbidity as a risk factor for mortality in people with anorexia nervosa

Distressed Communities Index in Patients Undergoing Transcatheter Aortic Valve Implantation in an Affluent County in New York

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