Mean Arterial Pressure: Getting It Right

Interaction Between Obesity and Hypertension on Arteriosclerosis in Chinese Urban Adults: A Population-Based Cross-Sectional Study

This study recruited 9,830 participants to identify whether the interaction between obesity and hypertension affects the occurrence of arteriosclerosis in Chinese adults. Brachial-ankle pulse wave velocity (baPWV) was measured to diagnose arteriosclerosis. Unconditional logistic regression was used for multiplicative interaction. The additive interaction was represented by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy (S). Hypertension was an independent risk factor for baPWV (p < .01), but obesity was not (p = .08). The interaction between obesity and hypertension on arteriosclerosis was not multiplicative (adjusted odds ratio = 0.89 (0.79-1.01), p = .07), but a negative additive interaction (RERI = -4.33, AP = -2.91, S = 0.10; p < .01) exists. Therefore, obesity may reduce the risk of arteriosclerosis caused by hypertension when hypertension and obesity coexist, especially in women and middle-aged people, which supports the obesity paradox.

Increased variability of mean arterial pressure is associated with increased risk of short-term mortality in intensive care unit: A retrospective study

Background

In intensive care unit (ICU), what thresholds of MAP variability are effective in distinguishing low- and high-risk patients for short-term mortality (in-hospital and 28-day) remains unclear.

Methods

Fifteen thousand five hundred sixty adult subjects admitted to ICU at Beth Israel Deaconess Medical Center (Boston, USA) between 2001 and 2012 were included in this retrospective study from MIMIC-III database. MAP within the first 24 h after admission were collected. Quantiles of MAP variability from 10% to 90% with 10% increasement each were considered to divide study participants into two groups, either having coefficients of variation of MAP greater or less than the given threshold. The threshold of MAP variability was identified by maximizing the odds ratio associated with increased risk of short-term mortality (in-hospital and 28-day). Logistic regression and Cox regression models were further applied to evaluate the association between increased variability of MAP and short-term mortality (in-hospital and 28-day).

Results

90% quantile of MAP variability was determined as the threshold generating the largest odds ratio associated with the increased risk of short-term mortality. Increased MAP variability, especially over 90% of MAP variability, was associated with increased risk of in-hospital mortality (odds ratio: 2.351, 95% CI: 2.064–2.673), and 28-day mortality (hazard ratio: 2.064, 95% CI: 1.820–2.337).

Conclusion

Increased MAP variability, especially over 90% of MAP variability, is associated with short-term mortality. Our proposed threshold of MAP variability may aid in the early identification of critically ill patients with a high risk of mortality.