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Introduction: Continuous renal replacement therapy (CRRT) is a primary form of renal support for patients with acute kidney injury in an intensive care unit. Making an accurate decision of discontinuation is crucial for the prognosis of patients. Previous research has mostly focused on the univariate and multivariate analysis of factors in CRRT, without the capacity to capture the complexity of the decision-making process. The present study thus developed a dynamic, interpretable decision model for CRRT discontinuation. Method: The study adopted a cohort of 1,234 adult patients admitted to an intensive care unit in the MIMIC-IV database. We used the eXtreme Gradient Boosting (XGBoost) machine learning algorithm to construct dynamic discontinuation decision models across 4 time points. SHapley Additive exPlanation (SHAP) analysis was conducted to exhibit the contributions of individual features to the model output. Result: Of the 1,234 included patients with CRRT, 596 (48.3%) successfully discontinued CRRT. The dynamic prediction by the XGBoost model produced an area under the curve of 0.848, with accuracy, sensitivity, and specificity of 0.782, 0.786, and 0.776, respectively. The performance of the XGBoost model was far superior to other test models. SHAP demonstrated that the features that contributed most to the model results were the Sequential Organ Failure Assessment score, serum lactate level, and 24-h urine output. Conclusion: Dynamic decision models supported by machine learning are capable of dealing with complex factors in CRRT and effectively predicting the outcome of discontinuation. [ABSTRACT FROM AUTHOR]

Objective: Designing physiologically adequate microvascular trees is of crucial relevance for bioengineering functional tissues and organs. Yet, currently available methods are poorly suited to replicate the morphological and topological heterogeneity of real microvascular trees because the parameters used to control tree generation are too simplistic to mimic results of the complex angiogenetic and structural adaptation processes in vivo. Methods: We propose a method to overcome this limitation by integrating a conditional deep convolutional generative adversarial network (cDCGAN) with a local fractal dimension‐oriented constrained constructive optimization (LFDO‐CCO) strategy. The cDCGAN learns the patterns of real microvascular bifurcations allowing for their artificial replication. The LFDO‐CCO strategy connects the generated bifurcations hierarchically to form microvascular trees with a vessel density corresponding to that observed in healthy tissues. Results: The generated artificial microvascular trees are consistent with real microvascular trees regarding characteristics such as fractal dimension, vascular density, and coefficient of variation of diameter, length, and tortuosity. Conclusions: These results support the adoption of the proposed strategy for the generation of artificial microvascular trees in tissue engineering as well as for computational modeling and simulations of microcirculatory physiology. [ABSTRACT FROM AUTHOR]

Early detection of falls is important for reducing fall injuries. However, existing fall detection strategies mostly focus on reducing impact injuries rather than avoiding falls. This study proposed the concept of identifying "Imbalance Point" to warn the body imbalance, allowing sufficient time to recover balance. And if falling cannot be avoided, an impact sign is released by detecting the "Fall Point" prior to the impact. To achieve this goal, motion prediction model and balance recovery model are integrated into a spatiotemporal framework to analyze dynamic and kinematic features of body motion. Eight healthy young volunteers participated in three sets of experiment: Normal trial, Recovery trial and Fall trial. The body motion in the trials was recorded using Microsoft Azure Kinect. The results show that the developed algorithm for Fall Point detection achieved 100% sensitivity and 98.6% specificity, along with an average lead time of 297 ms. Moreover, Imbalance Point was successfully detected in all Fall trials, and the average time interval between Imbalance Point and Fall Point was 315 ms, longer than reported step reaction time for elderly (approximately 270 ms). The experiment results demonstrate that the developed algorithm have great potential for fall warning and protection in the elderly. [ABSTRACT FROM AUTHOR]

Margin of stability (MOS) is one of the essential indices for evaluating dynamic stability. However, there are indications that MOS was affected by body height and its application in identifying factors on dynamic stability other than body height is restricted. An inverted pendulum model was used to simulate human walking and investigate the relevance between MOS and body height. Eventually, a height-independent index in dynamic stability assessment (named as Angled Margin of Stability, AMOS) was proposed. For testing, fifteen healthy young volunteers performed walking trials with normal arm swing, holding arms, and anti-normal arm swing. Kinematic parameters were recorded using a gait analysis system with a Microsoft Kinect V2.0 and instrumented walkway. Both simulation and test results show that MOS had a significant correlation with height during walking with normal arm swing, while AMOS had no such significant correlation. Walking with normal arm swing produced significantly larger AMOS than holding arms and anti-normal arm swing. However, no significant difference showed up in MOS between normal arm swing and holding arms. The results suggest that AMOS is not affected by body height and has the potential to identify the variations in dynamic stability caused by physiological factors other than body height. [ABSTRACT FROM AUTHOR]

Objective: To establish methods for providing a comprehensive and detailed description of the spatial distribution of the vascular networks, and to reveal the spatiotemporal pattern of the yolk sac membrane vascular network during the angiogenic procedure. Methods: Addressing the limitations in the conventional local fractal analysis, an improved approach, named scanning average local fractal dimension, was proposed. This method was conducted on 6 high‐resolution vascular images of the yolk sac membrane for 3 eggs at two stages (E3 and E4) to characterize the spatial distribution of the complexity of the vascular network. Results: With the proposed method, the spatial distribution of the complexity of the yolk sac membrane vascular network was visualized. From E3 to E4, the local fractal dimension increased in 3 eggs, 1.80 ± 0.02 vs. 1.85 ± 0.02, 1.72 ± 0.03 vs. 1.83 ± 0.02, and 1.77 ± 0.03 vs. 1.82 ± 0.02, respectively. The mean local fractal dimension in the most distal area from the embryo proper was the lowest at E3 while the highest at E4. At E3, the most peaks of the local fractal dimension were located in the vein territories and shifted to artery territories at E4. Conclusions: The spatial distribution of the complexity of the yolk sac membrane vascular network exhibited diverse patterns at different stages. In addition from E3 to E4, the increment of complexity at the intersection areas between arteries and sinus terminalis was with the most advance. This is consistent with the physiologic evidence. The present work provides a potential approach for investigating the spatiotemporal pattern of the angiogenic process. [ABSTRACT FROM AUTHOR]

Blood perfusion is an important index for the function of the cardiovascular system and it can be indicated by the blood flow distribution in the vascular tree. As the blood flow in a vascular tree varies in a large range of scales and fractal analysis owns the ability to describe multi-scale properties, it is reasonable to apply fractal analysis to depict the blood flow distribution. The objective of this study is to establish fractal methods for analyzing the blood flow distribution which can be applied to real vascular trees. For this purpose, the modified methods in fractal geometry were applied and a special strategy was raised to make sure that these methods are applicable to an arbitrary vascular tree. The validation of the proposed methods on real arterial trees verified the ability of the produced parameters (fractal dimension and multifractal spectrum) in distinguishing the blood flow distribution under different physiological states. Furthermore, the physiological significance of the fractal parameters was investigated in two situations. For the first situation, the vascular tree was set as a perfect binary tree and the blood flow distribution was adjusted by the split ratio. As the split ratio of the vascular tree decreases, the fractal dimension decreases and the multifractal spectrum expands. The results indicate that both fractal parameters can quantify the degree of blood flow heterogeneity. While for the second situation, artificial vascular trees with different structures were constructed and the hemodynamics in these vascular trees was simulated. The results suggest that both the vascular structure and the blood flow distribution affect the fractal parameters for blood flow. The fractal dimension declares the integrated information about the heterogeneity of vascular structure and blood flow distribution. In contrast, the multifractal spectrum identifies the heterogeneity features in blood flow distribution or vascular structure by its width and height. The results verified that the proposed methods are capable of depicting the multi-scale features of the blood flow distribution in the vascular tree and further are potential for investigating vascular physiology. [ABSTRACT FROM AUTHOR]

To date, the human balance assessment is mainly achieved by measuring the center of pressure (COP) trajectory of upright posture. However, COP-based metrics provide inconclusive results under certain circumstances, due to the lack of relevance with the body balance mechanism. This paper developed a novel framework to measure the variability in body sway based on the Poincaré analysis to enhance the balance assessment. It provided nonlinear parameters SD1, SD2, and their ratio SD1/SD2 as quantitative indicators of the local and global balance regulation capacities. 136 healthy adults were categorized into young and elderly groups and received test on a force platform. COP signals were recorded for 30 s under eyes-opened and eyes-closed vision conditions. The results were analyzed using the two-way mixed-design analysis of variance and show that the technology is able to reveal the effect of age and vision on the balance control by SD1, SD2, and SD1/SD2. SD1 mainly responded to vision, and SD2 was more influenced by age. Due to the information about the subtle adjustment during quiet standing, these Poincaré indexes surpassed the conventional COP measurements in demonstrating the balance control behavior. It can be concluded that the supposed method of estimating the local and global variabilities is a valuable approach for the balance assessment. [ABSTRACT FROM AUTHOR]

Abstract: Objective: PWV is the speed of pulse wave propagation through the circulatory system. mPWV emerges as a novel indicator of hypertension, yet it remains unclear how different vascular properties affect mPWV. We aim to identify the biomechanical determinants of mPWV. Methods: A 1D model was used to simulate PWV in a rat mesenteric microvascular network and, for comparison, in a human macrovascular arterial network. Sensitivity analysis was performed to assess the relationship between PWV and vascular compliance and resistance. Results: The 1D model enabled adequate simulation of PWV in both micro‐ and macrovascular networks. Simulated arterial PWV changed as a function of vascular compliance but not resistance, in that arterial PWV varied at a rate of 0.30 m/s and −6.18 × 10−3 m/s per 10% increase in vascular compliance and resistance, respectively. In contrast, mPWV depended on both vascular compliance and resistance, as it varied at a rate of 2.79 and −2.64 cm/s per 10% increase in the respective parameters. Conclusions: The present study identifies vascular compliance and resistance in microvascular networks as critical determinants of mPWV. We anticipate that mPWV can be utilized as an effective indicator for the assessment of microvascular biomechanical properties. [ABSTRACT FROM AUTHOR]

Despite increased application of the deceleration capacity (DC) and acceleration capacity (AC) of heart rate indices as indicators of autonomic nervous system (ANS) function, it remains controversial as to whether they reflect cardiac sympathetic or vagal activity. We addressed this problem using a cardiovascular system model that allows analysis of DC and AC under controllable levels of sympathetic and vagal activities. Multi-scale DCs and ACs with various timescales T and wavelet scales s were computed from the simulated RR interval series under randomly fluctuating levels of ANS activity, and the correlations of the indices to ANS functions were assessed. Results showed that under the conventional scales (T = 1, s = 2), both DC and AC were solely dependent on vagal activity. With higher scales (T = 3, s = 5), both DC and AC were positively correlated to sympathetic activity and negatively correlated to vagal activity. These data suggest that DC and AC provide information on the same aspects of ANS activity and that their physiological significance is highly influenced by the timescales and wavelet scales used in the computation. [ABSTRACT FROM AUTHOR]

This study was to develop an objective method to stratify cardiovascular risk in hypertension. Stratification for cardiovascular risk is crucial in deciding treatment strategy for hypertension but has yielded undesirable results in clinic due to its low accuracy which is caused by physicians' subjective experience and the uncertainty of patients' statements. Our model proposed herein overcomes these disadvantages by applying artificial neural network based on a classic back propagation net. The model input is derived from the clinical investigation. The target output is the stratification level of total cardiovascular risk, which is learned from the guidelines of hypertension treatment. Study in 348 normotensive and hypertensive subjects showed that the results of model stratification are consistent with the standard stratification suggested by hypertension guidelines in 81.61% cases. The results confirm the accuracy of the model and demonstrate its ability in risk evaluation for hypertension. [ABSTRACT FROM AUTHOR]