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Allometric considerations when assessing aortic aneurysms in Turner syndrome: Implications for activity recommendations and medical decision-making.

ABSTRACT: In Turner syndrome, the potential to form thoracic aortic aneurysms requires routine patient monitoring. However, the short stature that typically occurs complicates the assessment of severity and risk because the relationship of body size to aortic dimensions is different in Turner syndrome compared to the general population. Three allometric formula have been proposed to adjust aortic dimensions, all employing body surface area: aortic size index, Turner syndrome-specific Z-scores, and Z-scores based on a general pediatric and young adult population. In order to understand the differences between these formula we evaluated the relationship between age and aortic size index and compared Turner syndrome-specific Z-scores and pediatric/young adult based Z-scores in a group of girls and women with Turner syndrome. Our results suggest that the aortic size index is highly age-dependent for those under 15 years; and that Turner-specific Z-scores are significantly lower than Z-scores referenced to the general population. Higher Z-scores derived from the general reference population could result in stigmatization, inappropriate restriction from sports, and increasing the risk of unneeded medical or operative treatments. We propose that when estimating aortic dissection risk clinicians use Turner syndrome-specific Z-score for those under fifteen years of age.

SUBMITTER: Corbitt H

PROVIDER: S-EPMC5831410 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Allometric considerations when assessing aortic aneurysms in Turner syndrome: Implications for activity recommendations and medical decision-making.

Corbitt Holly H Maslen Cheryl C Prakash Siddharth S Morris Shaine A SA Silberbach Michael M

American journal of medical genetics. Part A 20171215 2

In Turner syndrome, the potential to form thoracic aortic aneurysms requires routine patient monitoring. However, the short stature that typically occurs complicates the assessment of severity and risk because the relationship of body size to aortic dimensions is different in Turner syndrome compared to the general population. Three allometric formula have been proposed to adjust aortic dimensions, all employing body surface area: aortic size index, Turner syndrome-specific Z-scores, and Z-score ...[more]

PMID: 29243875

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Project description:BackgroundDual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease.MethodsWe developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice.ResultsWe show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice.ConclusionsWe have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories).

Project description:Abdominal aortic aneurysm (AAA) is an asymptomatic aortic disease with a survival rate of 20% after rupture. It is a vascular degenerative condition different from occlusive arterial diseases. The size of the aneurysm is the most important determining factor in its clinical management. However, other measures of the AAA geometry that are currently not used clinically may also influence its rupture risk. With this in mind, the objectives of this work are to develop an algorithm to calculate the AAA wall thickness and abdominal aortic diameter at planes orthogonal to the vessel centerline, and to quantify the effect of geometric indices derived from this algorithm on the overall classification accuracy of AAA based on whether they were electively or emergently repaired. Such quantification was performed based on a retrospective review of existing medical records of 150 AAA patients (75 electively repaired and 75 emergently repaired). Using an algorithm implemented within the MATLAB computing environment, 10 diameter- and wall thickness-related indices had a significant difference in their means when calculated relative to the AAA centerline compared to calculating them relative to the medial axis. Of these 10 indices, nine were wall thickness-related while the remaining one was the maximum diameter (Dmax). Dmax calculated with respect to the medial axis is over-estimated for both electively and emergently repaired AAA compared to its counterpart with respect to the centerline. C5.0 decision trees, a machine learning classification algorithm implemented in the R environment, were used to construct a statistical classifier. The decision trees were built by splitting the data into 70% for training and 30% for testing, and the properties of the classifier were estimated based on 1000 random combinations of the 70/30 data split. The ensuing model had average and maximum classification accuracies of 81.0 and 95.6%, respectively, and revealed that the three most significant indices in classifying AAA are, in order of importance: AAA centerline length, L2-norm of the Gaussian curvature, and AAA wall surface area. Therefore, we infer that the aforementioned three geometric indices could be used in a clinical setting to assess the risk of AAA rupture by means of a decision tree classifier. This work provides support for calculating cross-sectional diameters and wall thicknesses relative to the AAA centerline and using size and surface curvature based indices in classification studies of AAA.

Dataset Information

Allometric considerations when assessing aortic aneurysms in Turner syndrome: Implications for activity recommendations and medical decision-making.

Publications

Allometric considerations when assessing aortic aneurysms in Turner syndrome: Implications for activity recommendations and medical decision-making.

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