Optimized venous return with a self-expanding cannula: from computational fluid dynamics to clinical application.

The Smart canula concept allows for collapsed cannula insertion, and self-expansion within a vein of the body. (A) Computational fluid dynamics, and (B) bovine experiments (76+/-3.8 kg) were performed for comparative analyses, prior to (C) the first clinical application. For an 18F access, a given flow of 4 l/min (A) resulted in a pressure drop of 49 mmHg for smart cannula versus 140 mmHg for control. The corresponding Reynolds numbers are 680 versus 1170, respectively. (B) For an access of 28F, the maximal flow for smart cannula was 5.8+/-0.5 l/min versus 4.0+/-0.1 l/min for standard (P<0.0001), for 24F 5.5+/-0.6 l/min versus 3.2+/-0.4 l/min (P<0.0001), and for 20F 4.1+/-0.3 l/min versus 1.6+/-0.3 l/min (P<0.0001). The flow obtained with the smart cannula was 270+/-45% (20F), 172+/-26% (24F), and 134+/-13% (28F) of standard (one-way ANOVA, P=0.014). (C) First clinical application (1.42 m2) with a smart cannula showed 3.55 l/min (100% predicted) without additional fluids. All three assessment steps confirm the superior performance of the smart cannula design.

Impact of clinical practice guidelines on priorisation for intensive care beds allocation in high-risk acute coronary syndrome patients: does age play a role?

QUESTION UNDER STUDY: To assess which high-risk acute coronary syndrome (ACS) patient characteristics played a role in prioritising access to intensive care unit (ICU), and whether introducing clinical practice guidelines (CPG) explicitly stating ICU admission criteria altered this practice. PATIENTS AND METHODS: All consecutive patients with ACS admitted to our medical emergency centre over 3 months before and after CPG implementation were prospectively assessed. The impact of demographic and clinical characteristics (age, gender, cardiovascular risk factors, and clinical parameters upon admission) on ICU hospitalisation of high-risk patients (defined as retrosternal pain of prolonged duration with ECG changes and/or positive troponin blood level) was studied by logistic regression. RESULTS: Before and after CPG implementation, 328 and 364 patients, respectively, were assessed for suspicion of ACS. Before CPG implementation, 36 of the 81 high-risk patients (44.4%) were admitted to ICU. After CPG implementation, 35 of the 90 high-risk patients (38.9%) were admitted to ICU. Male patients were more frequently admitted to ICU before CPG implementation (OR=7.45, 95% CI 2.10-26.44), but not after (OR=0.73, 95% CI 0.20-2.66). Age played a significant role in both periods (OR=1.57, 95% CI 1.24-1.99), both young and advanced ages significantly reducing ICU admission, but to a lesser extent after CPG implementation. CONCLUSION: Prioritisation of access to ICU for high-risk ACS patients was age-dependent, but focused on the cardiovascular risk factor profile. CPG implementation explicitly stating ICU admission criteria decreased discrimination against women, but other factors are likely to play a role in bed allocation.