Value of risk scores in the decision to palliate patients with ruptured abdominal aortic aneurysm

El aneurisma de aorta abdominal roto (AAAr) es una entidad que aún ocasiona una elevada mortalidad a pesar de las mejoras en el cuidado intraoperatorio y posoperatorio de los pacientes y del beneficioso impacto del tratamiento endovascular. La implementación de un protocolo estandarizado de las medidas terapéuticas que incluya criterios de selección, abordaje multidisciplinar de equipo y adecuación científico-técnica en centros con experiencia ha mostrado claros beneficios. La creación de códigos específicos como herramienta de actuación protocolizada en la Comunidad de Madrid también ha generado beneficios en los resultados terapéuticos de las patologías seleccionadas. La Sociedad Madrileña de Angiología, Cirugía Vascular y Endovascular promueve la creación de un Código Aneurisma en una comunidad donde la existencia de múltiples centros eleva la complejidad en términos de traslado y circuitos de derivación con el objetivo de aumentar la sospecha diagnóstica, ordenar los traslados a centros de idoneidad y proporcionar asistencia protocolizada que asegure los mejores resultados tras el tratamiento del aneurisma de aorta abdominal roto.

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“…Algunas han sido comparadas (28). Sin embargo, a pesar de su uso, no siempre tienen suficiente capacidad de discriminación (29).…”

Section: ¿Hay Que Tratar a Todos Los Pacientes?unclassified

Late prognosis of surviving patients after open surgical repair of a ruptured abdominal aortic aneurysm

Fernández¹,

Vélez²,

Céniga³

et al. 2019

Angiologia

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“…In addition, only a few tools were validated externally 7 . It is an unfortunately common occurrence in the medical literature for outcome-prediction tools to be developed and not validated subsequently in an independent cohort 8 or found to be inaccurate in patient populations other than the development population 9 .…”

Section: Introductionmentioning

confidence: 99%

The PERCEIVE quantitative study: PrEdiction of Risk and Communication of outcome following major lower-limb amputation: protocol for a collaboratiVE study

et al. 2021

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Background Accurate prediction of outcomes following surgery with high morbidity and mortality rates is essential for informed shared decision-making between patients and clinicians. It is unknown how accurately healthcare professionals predict outcomes following major lower-limb amputation (MLLA). Several MLLA outcome-prediction tools have been developed. These could be valuable in clinical practice, but most require validation in independent cohorts before routine clinical use can be recommended. The primary aim of this study is to evaluate the accuracy of healthcare professionals’ predictions of outcomes in adult patients undergoing MLLA for complications of chronic limb-threatening ischaemia (CLTI) or diabetes. Secondary aims include the validation of existing outcome-prediction tools. Method This study is an international, multicentre prospective observational study including adult patients undergoing a primary MLLA for CLTI or diabetes. Healthcare professionals’ accuracy in predicting outcomes at 30-days (death, morbidity and MLLA revision) and 1-year (death, MLLA revision and ambulation) will be evaluated. Sixteen existing outcome-prediction tools specific to MLLA will be examined for validity. Data collection began on 1 October 2020; the end of follow-up will be 1 May 2022. The C-statistic, Hosmer–Lemeshow test, reclassification tables and Brier score will be used to evaluate the predictive performance of healthcare professionals and prediction tools, respectively. Study registration and dissemination This study will be registered locally at each centre in accordance with local policies before commencing data collection, overseen by local clinician leads. Results will be disseminated to all centres, and any subsequent presentation(s) and/or publication(s) will follow a collaborative co-authorship model.

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“…The various models of mortality prediction in hospital after elective cardiac surgery, including logistic regression model and a machine learning model, were compared by using ROC and DCA. In Sweeting et al, 15 data from patients in the IMPROVE (Immediate Management of the Patient With Ruptured Aneurysm: Open Versus Endovascular Repair) randomized trial were used to develop the risk score of ruptured aneurysm. Risk factors included age, sex, haemodynamic markers, and aortic morphology.…”

Section: Introductionmentioning

confidence: 99%

Statistical inference for decision curve analysis, with applications to cataract diagnosis

Sande

D’Agostino

et al. 2020

Statistics in Medicine

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Statistical learning methods are widely used in medical literature for the purpose of diagnosis or prediction. Conventional accuracy assessment via sensitivity, specificity, and ROC curves does not fully account for clinical utility of a specific model. Decision curve analysis (DCA) becomes a novel complement as it incorporates a clinical judgment of the relative value of benefits (treating a true positive case) and harms (treating a false positive case) associated with prediction models. The preference of a patient or a policy‐maker is formulated statistically as the underlying threshold probability, above which the patient would choose to be treated. Net benefit is then calculated for possible threshold probability, which places benefits and harms on the same scale. We consider the inference problems for DCA in this paper. Interval estimation procedure and inference methodology are provided after we derive the relevant asymptotic properties. Our formulation can accommodate the classification problems with multiple categories. We carry out numerical studies to assess the performance of the proposed methods. An eye disease dataset is analyzed to illustrate our proposals.

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Value of risk scores in the decision to palliate patients with ruptured abdominal aortic aneurysm

Cited by 23 publications

References 26 publications

Late prognosis of surviving patients after open surgical repair of a ruptured abdominal aortic aneurysm

Late prognosis of surviving patients after open surgical repair of a ruptured abdominal aortic aneurysm

The PERCEIVE quantitative study: PrEdiction of Risk and Communication of outcome following major lower-limb amputation: protocol for a collaboratiVE study

Statistical inference for decision curve analysis, with applications to cataract diagnosis

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