Influence of diabetes on the risk of deep vein thrombosis of patients after total knee arthroplasty: a meta-analysis.

BACKGROUND: Previous studies evaluating the influence of diabetes on the risk of deep vein thrombosis (DVT) after total knee arthroplasty (TKA) showed inconsistent results. The aim of the study was to systematically evaluate the association between diabetes and DVT after TKA in a meta-analysis. METHODS: An extensive search was conducted in PubMed, Embase, and Web of Science to identify relevant cohort studies. Random-effects models were employed to pool the results after taking account of the potential influence of heterogeneity. RESULTS: Thirteen cohort studies involving 546,156 patients receiving TKA were included, with 71,110 (13.0%) diabetic patients before surgery and 1479 (2.1%) patients diagnosed as DVT after surgery. Overall, diabetes was associated with an increased risk of DVT after TKA (risk ratio [RR]: 1.43, 95% confidence interval [CI]: 1.12-1.84, p = 0.004; I2 = 44%). Sensitivity analysis limited to studies with chemoprophylaxis (RR: 1.96, 95% CI: 1.50-2.54), and studies with multivariate analysis (RR: 1.54, 95% CI: 1.12-2.11) showed consistent results. Subgroup analysis showed that diabetes was associated with higher risk of postoperative DVT in Asian countries (RR: 1.93, 95% CI: 1.49-2.52, p < 0.001; I2 = 1%) but not in Western countries (RR: 1.07, 95% CI: 0.86-1.34, p = 0.52; I2 = 0%; p for subgroup difference < 0.001). CONCLUSION: Diabetes may be a risk factor for DVT after TKA, even with the chemoprophylaxis of anticoagulants. The association between diabetes and DVT after TKA may be more remarkable in patients from Asian countries.

Student Leaders Today, Professional Leaders Tomorrow.

One of the core missions of the IEEE Engineering in Medicine and Biology Society (EMBS) is to be a platform for enhancing the personal and professional development of its members. This month we focus on two related priority areas of the IEEE EMBS Student Activities Committee (SAC) [1], namely Leadership Development and Professional Development Portfolios, and bring you up close to the student and professional leaders actively building these programs. The Leadership Development Portfolio, currently led by Agnieszka Lach from Silesian University of Technology, Gliwice, Poland, focuses on nurturing and supporting student leaders of the EMBS globally. The Professional Development Portfolio, currently led by Josée Rosset from the University of Manitoba, Winnipeg, MB, Canada, aims to help EMBS student members develop their skills and experiences in the practice of biomedical engineering.

Identification of the metabolites of rhapontigenin in rat and human by ultra-high-performance liquid chromatography-high-resolution mass spectrometry.

RATIONALE: Rhapontigenin, a stilbene compound isolated from the medicinal plant of rhubarb rhizomes, has shown a variety of biological activities. The purpose of this study was to identify and characterize the metabolites of rhapontigenin in rat liver microsomes, hepatocytes, urine, and human liver microsomes and hepatocytes. METHODS: The samples were analyzed by ultra-high-performance liquid chromatography combined with electrospray ionization quadrupole/orbitrap high-resolution mass spectrometry (UPLC-Q/Orbitrap-HRMS). The structures of the metabolites were interpreted by MS, MS/MS data, and elemental compositions. RESULTS: A total of 11 metabolites were detected and tentatively identified. M1, identified as piceatannol, was unambiguously identified using reference standard. Our results suggested that rhapontigenin was metabolized through the following pathways: (a) demethylation to produce piceatannol (M1), which further underwent oxidation to form ortho-quinone intermediate. This intermediate was reactive and conjugated with GSH (M10 and M11), which were further converted into N-acetyl-cysteine and excreted in urine. M1 also underwent sulfation (M8) and glucuronidation (M5); (b) direct sulfation, forming M6 and M7; and (c) direct glucuronidation to form M2, M3, and M4. Glucuronidation was a major metabolic pathway in hepatocytes and urine. CONCLUSIONS: The current study provides an overview of the metabolism of rhapontigenin, which is of great importance for us to understand the disposition of this compound.

Interested in Volunteering for EMBS? Here Are Two Students' Exciting Experiences.

The IEEE Engineering in Medicine and Biology Society (EMBS) is the world's largest international society of biomedical engineers. Volunteering for IEEE EMBS can be an enriching experience for students. We recently interviewed two exceptional EMBS volunteers to gain insight on their volunteering experience with EMBS.

Crafting the Future-Opportunities for Students by the Reinvigorated IEEE EMBS Student Activities Committee.

"As we look ahead into the next century, leaders will be those who empower others."-Bill Gates.

Local Staging of Colon Cancer: A Cross-Sectional Analysis for Diagnostic Performance of Magnetic Resonance Imaging and by Experience.

Preoperative magnetic resonance imaging was analyzed by four radiologists regarding local tumor staging (T and N) and the presence of extramural vascular involvement. An astonishingly high sensitivity for the detection of T 3/4 tumors (κ (quadratic weighted statistics constant) = 0.67), with considerably lower sensitivity for T 3 cd/4 tumors (κ = 0.51), high sensitivity for serosal involvement 76-87% (κ = 0.65) and extramural vascular involvement (87-98%, κ = 0.56). Sensitivity and specificity for lymph node involvement is lower (κ = 0.57). Magnetic resonance imaging with adequate experience can accurately detect tumors with invasion through the bowel wall and their prognostic factors.

Evaluation of Clinical Infusion Pump Performance Through Downstream Microdrop Monitoring: A Preliminary Study.

As low-flow infusion is becoming more prevalent for clinical care, there is an increasing need for better evaluation of clinical infusion pump performance at low flow rates and in ways that are accessible to the clinical community. However, the current method in international standard require specialized facilities, costly equipment, long durations of testing, and the data produced is hard to interpret. We propose downstream microdrop monitoring (DMM) as a low-cost, easy-to-perform, and easy-to-interpret alternative. In particular, we show that the count and timing of microdrops are useful for evaluating flow accuracy and flow uniformity at low flow rates.

Electroencephalogram dynamics during general anesthesia predict the later incidence and duration of burst-suppression during cardiopulmonary bypass.

OBJECTIVE: Electroencephalogram burst-suppression during general anesthesia is associated with post-operative delirium (POD). Whether burst-suppression causes POD or merely reflects susceptibility to POD is unclear. We hypothesized decreased intraoperative alpha (8-12 Hz) and beta (13-33 Hz) power prior to the occurrence of burst-suppression in susceptible patients. METHODS: We analyzed intraoperative electroencephalogram data of cardiac surgical patients undergoing cardiopulmonary bypass (CPB). We detected the incidence and duration of CPB burst-suppression with an automated burst-suppression detection algorithm. We analyzed EEG data with multitaper spectral estimation methods. We assessed associations between patient characteristics and burst-suppression using Binomial and Zero-inflated Poisson Regression Models. RESULTS: We found significantly decreased alpha and beta power (7.8-22.95 Hz) in the CPB burst-suppression cohort. The odds ratio for the association between point estimates for alpha and beta power (7.8-22.95 Hz) and the incidence of burst-suppression was 0.88 (95% CI: 0.79-0.98). The incidence rate ratio for the association between point estimates for power between the alpha and beta range and the duration of burst-suppression was 0.89 (95% CI: 0.84-0.93). CONCLUSION: Decreased intra-operative power within the alpha and beta range was associated with susceptibility to burst-suppression during CPB. SIGNIFICANCE: This dynamic may be used to develop principled neurophysiological-based approaches to aid the preemptive identification and targeted care of POD vulnerable patients.

A hidden semi-Markov model for estimating burst suppression EEG.

Burst suppression is an electroencephalogram (EEG) pattern associated with profoundly inactivated brain states characterized by cerebral metabolic depression. This pattern is distinguished by short-duration band-limited electrical activity (bursts) interspersed between relatively near-isoelectric periods (suppressions). Prior work in neurophysiology suggests that burst and suppression segments are respectively associated with consumption and regeneration of adenosine triphosphate resource in cortical networks. This indicates that once a suppression (or, burst) segment begins, the propensity to switch out of the state gradually increases with duration spent in the state. Prior EEG monitoring frameworks that track the brain state during burst suppression by tracking the estimated fraction of time spent in suppression, relative to bursts, do not incorporate this information. In this work, we incorporate this information within a hidden semi-Markov model (HSMM) wherein two states (burst & suppression) stochastically switch between each other using sojourn-time dependent transition probabilities. We demonstrate the HSMM's utility in analyzing clinical data by estimating the state probabilities, the optimal state sequence, and the brain's metabolic activation level characterized by parameters governing sojourn-time dependence in transition probabilities. The HSMM-based approach proposed here provides a novel statistical framework that advances the state-of-the-art in analyzing burst suppression EEG.

Automated Assessment of Loss of Consciousness Using Whisker And Paw Movements During Anesthetic Dosing in Head-Fixed Rodents.

The precise identification of loss of consciousness (LOC) is key to studying the effects of anesthetic drugs in neural systems. The standard behavioral assay for identifying LOC in rodents is the Loss of Righting Reflex (LORR), assessed by placing the animal in the supine position every minute until it fails to right itself. However, this assay cannot be used when the rodents are head-fixed, which limits the use of powerful techniques such as multi-electrode recordings, in vivo patch clamp, and neuronal imaging. In these situations, an alternative way to assess LOC is needed. We propose that loss of movement (LOM) in whiskers and paws of head-fixed animals can be used as an alternative behavioral assay in head-fixed animals. Unlike LORR, LOM in whiskers and paws is much harder to detect by visual inspection. Therefore, we developed a method to automatically assess for LOM of whiskers and paws in head fixed rodents during in vivo patch clamp recordings. Our method uses an algorithm based on optical flow and point-process filtering which can be run on images acquired on regular cameras at low frame-rates. We show that the algorithm can achieve at least comparable accuracy in detecting LOC when compared with consensus among human observers, as well as improved precision when compared with individual observers. In the future, we aim to to expand the method to detect more behavioral end-points during anesthesia such as paradoxical excitation. Eventually, we hope to enable multi-modal anesthesia studies, which incorporates behavioral and neurophysiological data.

Variability in pharmacologically-induced coma for treatment of refractory status epilepticus.

OBJECTIVE: To characterize the amount of EEG suppression achieved in refractory status epilepticus (RSE) patients treated with pharmacologically-induced coma (PIC). METHODS: We analyzed EEG recordings from 35 RSE patients between 21-84 years-old who received PIC that target burst suppression and quantified the amount of EEG suppression using the burst suppression probability (BSP). Then we measured the variability of BSPs with respect to a reference level of BSP 0.8 ± 0.15. Finally, we also measured the variability of BSPs with respect to the amount of intravenous anesthetic drugs (IVADs) received by the patients. RESULTS: Patients remained in the reference BSP range for only 8% (median, interquartile range IQR [0, 29] %) of the total time under treatment. The median time with BSP below the reference range was 84% (IQR [37, 100] %). BSPs in some patients drifted significantly over time despite constant infusion rates of IVADs. Similar weight-normalized infusion rates of IVADs in different patients nearly always resulted in distinct BSPs (probability 0.93 (IQR [0.82, 1.0]). CONCLUSION: This study quantitatively identified high variability in the amount of EEG suppression achieved in clinical practice when treating RSE patients. While some of this variability may arise from clinicians purposefully deviating from clinical practice guidelines, our results show that the high variability also arises in part from significant inter- and intra- individual pharmacokinetic/pharmacodynamic variation. Our results indicate that the delicate balance between maintaining sufficient EEG suppression in RSE patients and minimizing IVAD exposure in clinical practice is challenging to achieve. This may affect patient outcomes and confound studies seeking to determine an optimal amount of EEG suppression for treatment of RSE. Therefore, our analysis points to the need for developing an alternative paradigm, such as vigilant anesthetic management as happens in operating rooms, or closed-loop anesthesia delivery, for investigating and providing induced-coma therapy to RSE patients.

Imaging Intelligence: AI Is Transforming Medical Imaging Across the Imaging Spectrum.

Artificial intelligence (AI) and machine learning (ML) have influenced medicine in myriad ways, and medical imaging is at the forefront of technological transformation. Recent advances in AI/ML fields have made an impact on imaging and image analysis across the board, from microscopy to radiology. AI has been an active field of research since the 1950s; however, for most of this period, algorithms achieved subhuman performance and were not broadly adopted in medicine. Recent enhancements for computational hardware is enabling researchers to revisit old AI algorithms and experiment with new mathematical ideas. Researchers are applying these methods to a broad array of medical technologies, ranging from microscopic image analysis to tomographic image reconstruction and diagnostic planning.

Spatial variation in automated burst suppression detection in pharmacologically induced coma.

Burst suppression is actively studied as a control signal to guide anesthetic dosing in patients undergoing medically induced coma. The ability to automatically identify periods of EEG suppression and compactly summarize the depth of coma using the burst suppression probability (BSP) is crucial to effective and safe monitoring and control of medical coma. Current literature however does not explicitly account for the potential variation in burst suppression parameters across different scalp locations. In this study we analyzed standard 19-channel EEG recordings from 8 patients with refractory status epilepticus who underwent pharmacologically induced burst suppression as medical treatment for refractory seizures. We found that although burst suppression is generally considered a global phenomenon, BSP obtained using a previously validated algorithm varies systematically across different channels. A global representation of information from individual channels is proposed that takes into account the burst suppression characteristics recorded at multiple electrodes. BSP computed from this representative burst suppression pattern may be more resilient to noise and a better representation of the brain state of patients. Multichannel data integration may enhance the reliability of estimates of the depth of medical coma.

Implantable polyimide cable for multichannel high-data-rate neural recording microsystems.

To avoid or minimize postimplantation injury as a result of brain micromotion relative to the skull, a flexible multichannel polyimide (PI) cable was designed and microfabricated for data and power transmission between an intracranial IC recording from a neural probe array and an extracranial IC exchanging power and data wirelessly with an external unit. Surface characteristics, electrical properties, and cytocompatibility of the PI ribbon cable were investigated in this study. Scanning electron microscopic examination and atomic force microscopy analyses showed that the surface of the PI ribbon cable became significantly rougher due to the reactive oxygen ion etching process to open bonding pads. The enhanced surface roughness was also responsible for the increase in wettability and water absorption rate. However, water permeability measurement revealed that the micromachining fabrication process did not meaningfully affect the acceptable water vapor transmission rate of PI. Moreover, electrical properties, such as insertion loss, isolation between channels and data transmission capacity, were assessed for each channel of the PI ribbon cable on the basis of scattering parameter (S-parameter) measurement. Finally, 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide assay and live/dead intracellular staining tests were carried out to evaluate cell behaviors on the PI ribbon cable, indicating that the PI ribbon cable did not have acute cytotoxicity and appeared to be as cytocompatible as blank PI foils.