An obesity paradox: an inverse correlation between body mass index and atherosclerosis of the aorta.

BACKGROUND AND AIMS: Morbid obesity generally has been associated with higher morbidity and mortality for a variety of diseases. However, a number of exceptions to this have been reported and referred to as the "obesity paradox." The purpose of the present study was to obtain objective data on aortic atherosclerosis and its relationship to body mass index (BMI, kg/m2), based on autopsy findings in a large cohort of overweight and obese decedents. METHODS: Decedents were ≥18 years who had autopsies between 2003 and 2014, a subset of whom were morbidly obese (BMI≥40). Autopsy findings were reviewed and compared to a control group (BMI<40) who had consecutive autopsies performed between January 2013 and June 2014. Atherosclerosis was assessed by gross pathologic examination using a semiquantitative grading scale (from 0 to 3), and for statistical analysis, the scores were stratified into two groups: nonsevere (<2) or severe (≥2). RESULTS: There were 304 decedents in the study: 66 were morbidly obese (BMI≥40), 94 were either Class I or II obese (BMI 30-40), 127 were either overweight (BMI 25.0-29.9) or normal weight (BMI 20-24.9), and 17 were underweight (BMI<20). Decedents with mild atherosclerosis were significantly younger than those with severe disease (55.2 vs. 67.3, P<.0001). Decedents were further stratified by age and BMI. Univariate analysis revealed that decedents >60 years were more likely to have severe atherosclerosis than those ≤60 years (61% vs. 30%, P<.0001). There was a highly significant (P=.008) inverse relationship between severe aortic atherosclerosis and BMI. Twenty of 66 decedents (30%) with a BMI≥40 had severe atherosclerosis vs. 122 of 238 decedents (51%) with BMIs<40 (P=.001). As BMI increased, the probability of developing severe disease decreased. Hypertension increased the probability of having severe atherosclerosis (54% vs. 33%, P=.007). After adjusting for other covariates, multivariable analysis revealed that age and hypertension were still positively correlated with the severity of atherosclerosis (P=.014 and 0.028, respectively), and the inverse relationship between BMI and atherosclerosis remained (adjusted relative risk of BMI≥40 vs. <40=0.64, 95% confidence interval: 0.4-1; P=.03). CONCLUSIONS: Our data extend the previously described obesity paradox to another disease entity, atherosclerosis of the aorta. Morbid obesity appeared to have a protective effect for developing severe aortic atherosclerosis, for the reasons for which are yet to be determined. However, the mean age at death of decedents with BMIs≥40 was younger than those with BMIs in the 20-30 range (55.9 vs. 63.2 years, P=.001), confirming that morbid obesity was not associated with increased longevity.

Intraoperative MRI electrical noise and monitor ECG filters affect arrhythmia detection and identification.

Most electrical equipment in the modern operating room (OR) radiates electrical noise (EN) that can interfere with patient monitors. We have described the EN that an intraoperative magnetic resonance imaging (iMRI) system emits and have shown that this high-energy EN diminishes the quality of the ECG waveform during iMRI scans in our neurosurgical OR. We have also shown that the ECG signal filters in our iMRI-compatible patient monitor reduce this interference but, in the process, disturb the true morphology of the displayed waveform. This simulation study evaluates how iMRI-generated EN affects the ability of the anesthetist to detect and identify ECG arrhythmias and whether the patient monitor's ECG signal filters can improve arrhythmia recognition. Using an ECG simulator, we generated Lead II and V5 ECG signal segments that contained either no arrhythmia or one of four common cardiac arrhythmias. We filtered the ECG segments with four filters available on our iMRI-compatible monitor (Veris MR, MEDRAD Inc., Indianola, PA USA). We then digitized the segments and mixed simulated iMRI EN into the resultant tracings. With institutional approval and written informed consent, board-certified anesthesiologists reviewed the tracings, determined if an arrhythmia was present and identified the arrhythmia. We conducted the study anonymously. We reported the data as percent correct arrhythmia detection and correct arrhythmia identification. Thirty-one anesthesiologists completed the study. Overall, the participants correctly detected 79.5% (95% CI: 77.2, 81.7%) of the arrhythmias and correctly identified 62.5% (95% CI: 59.8, 65.3%) of the arrhythmias, regardless of EN presence. Although the proportions among monitor noise filters studied were not significant, the manufacturer-designated MR5 Veris MR filter optimized arrhythmia detection and arrhythmia identification for our participants, regardless if EN was present in the ECG tracings. In the neurosurgical OR, the anesthetist must be able to effectively monitor a patient in the presence of iMRI-generated EN. Depending on the OR design, the patient may be out of the anesthetist's direct view during a scan procedure. The anesthetist must rely on monitored physiologic parameters to assess patient status during this time. He/she should be familiar with his/her monitor's filtering capabilities and routinely adjust the ECG filters to achieve the best compromise between minimized EN effects and maximized displayed ECG signal quality.