Nevin Manimala

Injury. 2023 Mar 16:S0020-1383(23)00271-1. doi: 10.1016/j.injury.2023.03.020. Online ahead of print.

ABSTRACT

INTRODUCTION: Rotatory laxity acceleration still lacks objective classification due to interval grading superposition, resulting in a biased pivot shift grading prior to the Anterior Cruciate Ligament (ACL) reconstruction. However, data analysis might help improve data grading in the operative room. Therefore, we described the improvement of the pivot-shift categorization in Gerdy’s acceleration under anesthesia prior to ACL surgery using a support vector machine (SVM) classification, surgeon, and literature reference.

METHODS: Seventy-five patients (aged 30.3 ± 10.2 years, and IKDC 52.0 ± 16.5 points) with acute ACL rupture under anesthesia prior to ACL surgery were analyzed. Patients were graded with pivot-shift sign glide (+), clunk (++), and (+++) gross by senior orthopedic surgeons. At the same time, the tri-axial tibial plateau acceleration was measured. Categorical data were statistically described, and the accelerometry and categorical data were associated (α = 5%). A multiclass SVM kernel with the best accuracy trained by orthopedic surgeons and assisted from literature for missing data was compared with experienced surgeons and literature interval grading. The cubic SVM classifier achieved the best grading.

RESULTS: The intra-group proportions were different for each grading in the three compared strategies (p < 0.001). The inter-group proportions were different for all comparisons (p < 0.001). There were significant (p < 0.001) associations (Tau: 0.69, -0.28, and -0.50) between the surgeon and SVM, the surgeon and interval grading, and the interval and SVM, respectively.

CONCLUSION: The multiclass SVM classifier improves the acceleration categorization of the (+), (++), and (+++) pivot shift sign prior to the ACL surgery in agreement with surgeon criteria.

PMID:37003872 | DOI:10.1016/j.injury.2023.03.020

Injury. 2023 Mar 27:S0020-1383(23)00290-5. doi: 10.1016/j.injury.2023.03.034. Online ahead of print.

ABSTRACT

OBJECTIVE: The purpose of this study was to compare the effects of the selective serotonin reuptake inhibitor (SSRI) fluoxetine and the serotonin-norepinephrine reuptake inhibitor (SNRI) venlafaxine on bone defect healing.

MATERIALS AND METHODS: Wistar rats were randomly divided into three groups of eight animals each. The first received 0.1 ml/kg sterile saline solution, the second 5 mg/kg fluoxetine, and the third 5 mg/kg venlafaxine, daily by gastric gavage over 7 weeks. At week 3 of drug therapy, 5-mm diameter calvarial defects were created in the parietal bone of all of the animals. All rats were euthanized four weeks after surgery, micro-CT analysis and histomorphometric analysis were carried out to evaluate the following parameters: Bone volume fraction (BV/TV), bone surface (BS), bone surface density (BS/BV; bone surface/bone volume, 1/mm), trabecular number (Tb. N), trabecular thickness (Tb. Th), areas of new bone structure (positive areas), areas of mature bone structure (negative areas).

RESULTS: Micro-CT analysis showed the presence of similar levels of bone formation within the defect site in all three groups (p>0.05). Histomorphometric analysis revealed the presence of bone-forming cells at the defect periphery, with less activity indicating bone formation at the center. No statistically significant difference was observed between the groups (p>0.05).

CONCLUSION: Based on the findings of this study, it can be said that the use of both antidepressants hasn’t any effect on bone defect healing.

PMID:37003871 | DOI:10.1016/j.injury.2023.03.034

J Orthop Sci. 2023 Mar 30:S0949-2658(23)00063-5. doi: 10.1016/j.jos.2023.02.018. Online ahead of print.

ABSTRACT

INTRODUCTION: After surgical fixation of distal radius fractures, many patients are keen to return to driving. There are however limited guidelines assisting surgeons. The aims of this study were to determine when patients could return to driving safely after distal radius fracture fixation and determine the clinical parameters (range of motion and grip strength) that patients needed to achieve before return to safe driving could be advised.

MATERIALS AND METHODS: A prospective grant-funded clinical study was conducted. Patients above the age of 21 years who underwent surgical fixation with a volar plate, possessed a class 3 standard motorcar license, and were regular drivers were recruited in a single institution from 2017 to 2019. A hand surgeon and an occupational therapist who sees routine hand therapy cases, assessed the patients at regular intervals from 2 to 12-weeks post-surgery. Clinical parameters of pain, wrist range of motion and grip strength were measured. Patients underwent off and on-road driving assessments.

RESULTS: A total of 26 patients were recruited, with 21 successfully completing the driving assessment. Median time post-surgery to passing the driving test was 6 and 8-weeks for off and on-road assessments respectively. Pain score was observed to decrease over time, with a significant decrease from week 2 to week 4. Range of motion improved over time, with maximal improvement between 2 to 4-weeks post-surgery. When compared with the unaffected wrist, the difference in pronation, supination and radial deviation in the affected hand was consistently no longer statistically significant 4 to 6-weeks post-surgery.

CONCLUSION: Patients with isolated surgically treated distal radius fractures can be recommended for a driving assessment as early as 4-6 weeks post-surgery if pain control is adequate, and clinical parameters for pronation and supination are met.

PMID:37003851 | DOI:10.1016/j.jos.2023.02.018

Aust Crit Care. 2023 Mar 30:S1036-7314(23)00030-9. doi: 10.1016/j.aucc.2023.02.003. Online ahead of print.

ABSTRACT

BACKGROUND: Delirium is a common, yet underdiagnosed neuropsychiatric complication of intensive care unit (ICU) admission, associated with significant mortality and morbidity. Delirium can be difficult to diagnose, with gold standard assessments by a trained specialist being impractical and rarely performed. To address this, various tools have been developed, enabling bedside clinicians to assess for delirium efficiently and accurately. However, the performance of these tools varies depending on factors including the assessor’s training. To address the shortcomings of current tools, electronic tools have been developed.

AIMS AND OBJECTIVES: The aims of this validation study are to assess the feasibility, acceptability, and generalisability of a recently developed and pilot-tested electronic delirium screening tool (eDIS-ICU) and compare diagnostic concordance, sensitivity, and specificity between eDIS-ICU, Confusion Assessment Method for the ICU (CAM-ICU), and the Diagnostic and Statistical Manual of Mental Disorders – 5th edition (DSM-V) gold standard in diverse ICU settings.

METHODS: Seven hundred participants will be recruited across five sites in three countries. Participants will complete three assessments (eDIS-ICU, CAM-ICU, and DSM-V) twice within one 24-h period. At each time point, assessments will be completed within one hour. Assessments will be administered by three different people at any given time point, with the assessment order and assessor for eDIS-ICU and CAM-ICU randomly allocated. Assessors will be blinded to previous and concurrent assessment results.

RESULTS: The primary outcome is comparing diagnostic sensitivity of eDIS-ICU and CAM-ICU against the DSM-V.

RELEVANCE TO CLINICAL PRACTICE: This protocol describes a definitive validation study of an electronic diagnostic tool to assess for delirium in the ICU. Delirium remains a common and difficult challenge in the ICU and is linked with multiple neurocognitive sequelae. Various challenges to routine assessment mean many cases are still unrecognised or misdiagnosed. An improved ability for bedside clinicians to screen for delirium accurately and efficiently will support earlier diagnosis, identification of underlying cause(s) and timely treatments, and ultimately improved patient outcomes.

CLINICAL TRIAL REGISTRATION NUMBER: This study was prospectively registered on the Australian New Zealand Clinical Trials Registry (ANZCTR) on 8th February 2022 (ACTRN12622000220763).

PMID:37003849 | DOI:10.1016/j.aucc.2023.02.003

Chaos. 2023 Mar;33(3):033144. doi: 10.1063/5.0136240.

ABSTRACT

Divergences or similarity measures between probability distributions have become a very useful tool for studying different aspects of statistical objects, such as time series, networks, and images. Notably, not every divergence provides identical results when applied to the same problem. Therefore, it seems convenient to have the widest possible set of divergences to be applied to the problems under study. Besides this choice, an essential step in the analysis of every statistical object is the mapping of each one of their representing values into an alphabet of symbols conveniently chosen. In this work, we choose the family of divergences known as the Burbea-Rao centroids (BRCs). For the mapping of the original time series into a symbolic sequence, we work with the ordinal pattern scheme. We apply our proposals to analyze simulated and real time series and to real textured images. The main conclusion of our work is that the best BRC, at least in the studied cases, is the Jensen-Shannon divergence, besides the fact that it verifies some interesting formal properties.

PMID:37003832 | DOI:10.1063/5.0136240

Chaos. 2023 Mar;33(3):033128. doi: 10.1063/5.0141824.

ABSTRACT

Cooperation is a widespread phenomenon in human society and plays a significant role in achieving synchronization of various systems. However, there has been limited progress in studying the co-evolution of synchronization and cooperation. In this manuscript, we investigate how reinforcement learning affects the evolution of synchronization and cooperation. Namely, the payoff of an agent depends not only on the cooperation dynamic but also on the synchronization dynamic. Agents have the option to either cooperate or defect. While cooperation promotes synchronization among agents, defection does not. We report that the dynamic feature, which indicates the action switching frequency of the agent during interactions, promotes synchronization. We also find that cooperation and synchronization are mutually reinforcing. Furthermore, we thoroughly analyze the potential reasons for synchronization promotion due to the dynamic feature from both macro- and microperspectives. Additionally, we conduct experiments to illustrate the differences in the synchronization-promoting effects of cooperation and dynamic features.

PMID:37003824 | DOI:10.1063/5.0141824

Chaos. 2023 Mar;33(3):033106. doi: 10.1063/5.0134561.

ABSTRACT

The stochastic Hindmarsh-Rose model is studied in the parameter region where two bursting limit cycles of different types coexist. We show that under the influence of noise, transitions between basins of attractions appear, which generates stochastic bursting oscillations of mixed modes. The formation of this new regime is accompanied by anti-coherence and coherence resonances as well as by the transition to chaos. We investigate the probabilistic mechanism of the noise-driven bursting birhythmicity using the stochastic sensitivity functions and confidence domains method.

PMID:37003823 | DOI:10.1063/5.0134561

Chaos. 2023 Mar;33(3):032101. doi: 10.1063/5.0137223.

ABSTRACT

Delay embedding methods are a staple tool in the field of time series analysis and prediction. However, the selection of embedding parameters can have a big impact on the resulting analysis. This has led to the creation of a large number of methods to optimize the selection of parameters such as embedding lag. This paper aims to provide a comprehensive overview of the fundamentals of embedding theory for readers who are new to the subject. We outline a collection of existing methods for selecting embedding lag in both uniform and non-uniform delay embedding cases. Highlighting the poor dynamical explainability of existing methods of selecting non-uniform lags, we provide an alternative method of selecting embedding lags that includes a mixture of both dynamical and topological arguments. The proposed method, Significant Times on Persistent Strands (SToPS), uses persistent homology to construct a characteristic time spectrum that quantifies the relative dynamical significance of each time lag. We test our method on periodic, chaotic, and fast-slow time series and find that our method performs similar to existing automated non-uniform embedding methods. Additionally, n-step predictors trained on embeddings constructed with SToPS were found to outperform other embedding methods when predicting fast-slow time series.

PMID:37003815 | DOI:10.1063/5.0137223

Chaos. 2023 Mar;33(3):033120. doi: 10.1063/5.0134285.

ABSTRACT

Synchronization and resonance on networks are some of the most remarkable collective dynamical phenomena. The network topology, or the nature and distribution of the connections within an ensemble of coupled oscillators, plays a crucial role in shaping the local and global evolution of the two phenomena. This article further explores this relationship within a compact mathematical framework and provides new contributions on certain pivotal issues, including a closed bound for the average synchronization time in arbitrary topologies; new evidences of the effect of the coupling strength on this time; exact closed expressions for the resonance frequencies in terms of the eigenvalues of the Laplacian matrix; a measure of the effectiveness of an influencer node’s impact on the network; and, finally, a discussion on the existence of a resonant synchronized state. Some properties of the solution of the linear swing equation are also discussed within the same setting. Numerical experiments conducted on two distinct real networks-a social network and a power grid-illustrate the significance of these results and shed light on intriguing aspects of how these processes can be interpreted within networks of this kind.

PMID:37003810 | DOI:10.1063/5.0134285

Chaos. 2023 Mar;33(3):033143. doi: 10.1063/5.0135232.

ABSTRACT

This paper reports the novel results on fractional order-induced bifurcation of a tri-neuron fractional-order neural network (FONN) with delays and instantaneous self-connections by the intersection of implicit function curves to solve the bifurcation critical point. Firstly, it considers the distribution of the root of the characteristic equation in depth. Subsequently, it views fractional order as the bifurcation parameter and establishes the transversal condition and stability interval. The main novelties of this paper are to systematically analyze the order as a bifurcation parameter and concretely establish the order critical value through an implicit function array, which is a novel idea to solve the critical value. The derived results exhibit that once the value of the fractional order is greater than the bifurcation critical value, the stability of the system will be smashed and Hopf bifurcation will emerge. Ultimately, the validity of the developed key fruits is elucidated via two numerical experiments.

PMID:37003808 | DOI:10.1063/5.0135232