Proportion of Angle Closure Glaucoma in Tamale, Ghana.

PRCIS: In the largest clinic-based study to date, our review of 588 patients presenting with glaucoma in Northern Ghana revealed 36% of these had primary angle closure glaucoma (PACG). OBJECTIVE: Glaucoma is the second leading cause of blindness worldwide. In Africa, glaucoma is an established public health problem, and PACG is not commonly discussed. Recognizing it is important because of its negative impact on visual morbidity, and also because its treatment is different from primary open angle glaucoma. In response to the observation of many PACG cases at the Northern Community Eye Hospital in Tamale, Ghana, we investigated the proportion of those attending with a first diagnosis of glaucoma who had PACG. PATIENTS AND METHODS: Using the electronic records, we identified 976 patients who attended with a first diagnosis of glaucoma between January 2021 and October 2022. Of these, 588 met the inclusion criterion of a clear glaucoma subtype diagnosis. RESULTS: Of these 316 (53.7%) had primary open angle glaucoma, 210 (35.7%) PACG, and 62 (10.5%) secondary glaucoma. Thus, over a third of presenting glaucomas had PACG. CONCLUSION: This study highlights that PACG is present in about a third of patients presenting to our clinic in North Ghana. Our study demonstrates the importance of a clear diagnostic pathway including gonioscopy in the assessment of glaucoma patients and the consideration of wider training on angle closure glaucoma diagnosis and management.

ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data.

OBJECTIVE: Bio-Signals such as electroencephalography (EEG) and electromyography (EMG) are widely used for the rehabilitation of physically disabled people and for the characterization of cognitive impairments. Successful decoding of these bio-signals is however non-trivial because of the time-varying and non-stationary characteristics. Furthermore, existence of short- and long-range dependencies in these time-series signal makes the decoding even more challenging. State-of-the-art studies proposed Convolutional Neural Networks (CNNs) based architectures for the classification of these bio-signals, which are proven useful to learn spatial representations. However, CNNs because of the fixed size convolutional kernels and shared weights pay only uniform attention and are also suboptimal in learning short-long term dependencies, simultaneously, which could be pivotal in decoding EEG and EMG signals. Therefore, it is important to address these limitations of CNNs. To learn short- and long-range dependencies simultaneously and to pay more attention to more relevant part of the input signal, Transformer neural network-based architectures can play a significant role. Nonetheless, it requires a large corpus of training data. However, EEG and EMG decoding studies produce limited amount of the data. Therefore, using standalone transformers neural networks produce ordinary results. In this study, we ask a question whether we can fix the limitations of CNN and transformer neural networks and provide a robust and generalized model that can simultaneously learn spatial patterns, long-short term dependencies, pay variable amount of attention to time-varying non-stationary input signal with limited training data. APPROACH: In this work, we introduce a novel single hybrid model called ConTraNet, which is based on CNN and Transformer architectures that contains the strengths of both CNN and Transformer neural networks. ConTraNet uses a CNN block to introduce inductive bias in the model and learn local dependencies, whereas the Transformer block uses the self-attention mechanism to learn the short- and long-range or global dependencies in the signal and learn to pay different attention to different parts of the signals. MAIN RESULTS: We evaluated and compared the ConTraNet with state-of-the-art methods on four publicly available datasets (BCI Competition IV dataset 2b, Physionet MI-EEG dataset, Mendeley sEMG dataset, Mendeley sEMG V1 dataset) which belong to EEG-HMI and EMG-HMI paradigms. ConTraNet outperformed its counterparts in all the different category tasks (2-class, 3-class, 4-class, 7-class, and 10-class decoding tasks). SIGNIFICANCE: With limited training data ConTraNet significantly improves classification performance on four publicly available datasets for 2, 3, 4, 7, and 10-classes compared to its counterparts.

The Impact of Electromagnetic Interference from Charging All-electric Vehicles on Implantable Cardioverter-defibrillator Performance.

Electric vehicles (EVs) are growing in popularity and in general use. The effect of electromagnetic interference (EMI) caused by supercharging all-electric vehicles on implantable cardioverter-defibrillator (ICD) function has not been studied. The objective of this study was to determine the extent of the effect of EMI from charging Tesla all-electric vehicles (Tesla, Inc., Austin, TX, USA) on cardiac implantable electronic device function. A proof-of-concept study was performed to explore the potential effect of EMI from Tesla vehicles while charging the battery using a 220-V wall charger and a 480-V Supercharger. Tesla Model S and Model X vehicles were used for this study. We enrolled 34 patients with stable ICD function for the initial phase using the standard wall charger, followed by an additional 35 patients for the second phase using the Supercharger. Tracings were obtained at nominal and highest sensitivity settings while patients sat in the driver's seat, passenger seat, back seats, and facing the charging port. In each position, the device and the patient were monitored in real time by a certified technician for any inappropriate sensing and/or delivery of therapies. A medical magnet was also available on site. Emergency medical services and physician supervision were available at all times, and patients were contacted the following day to ensure their well-being. No device interactions were identified at both the nominal and highest sensitivity settings of each ICD during exposure to vehicle charging using a Tesla 220-V wall charger and a 480-V Supercharger at any of the five positions in and around each vehicle. Interaction was defined as oversensing, undersensing, mode switch, or upper rate tracking behavior. There was also no damage to any ICD, and no inappropriate shocks were administered to any patient. In conclusion, transvenous ICD function is not interrupted by EMI transmitted while charging Tesla vehicles using either the 220-V wall charger or the 480-V Supercharger.

Left Ventricular Support for Unprotected Left Main Coronary Artery Interventions (The Dayton Heart and Vascular Impella Registry).

Background: Coronary artery bypass grafting is the standard of care for patients with obstructive left main (LM) coronary disease. In poor surgical candidates, high-risk percutaneous coronary artery intervention (PCI) is an alternative. Methods: We investigated a retrospective cohort of patients who underwent LM PCI from January 2010 to March 2014 (n = 89). Obstructive LM disease was defined as 50% angiographic obstruction of luminal flow, and the primary endpoint was inhospital mortality. Ventricular assist device (VAD) was defined as the use of either intra-aortic balloon pump (IABP) or Impella 2.5 devices before, during, or following PCI. Results: A total of 89 patients with LM PCI were divided into those with (n = 39) and without (n = 50) VAD support. The former group was further divided into those with support from either Impella 2.5 (n = 28) or IABP (n = 11). Age, race, and gender did not differ between patients who received unassisted LM-PCI from those with VAD support (P = 0.142, 1.0, and 0.776, respectively). The angiographic stenosis of atherosclerotic lesions in LM, proximal left anterior descending artery, and other native/surgical coronary vessels was similar between the groups. The duration of hospitalization was significantly longer for patients with VAD support compared to those without (7.19 ± 6.89 vs. 2.78 ± 3.39, P < 0.001). The incidence of cardiogenic shock and inhospital mortality was significantly higher in the VAD group (P = 0.009 and 0.001, respectively). Overall, inhospital mortality was 9% (8/89). The IABP and Impella 2.5 groups had mortality proportions of 46% (5/11) and 11% (3/28), respectively; P = 0.028. For all patients, inhospital mortality was higher for those with versus without cardiogenic shock (56% or 5/9 vs. 4% or 3/80; P < 0.001), and for those with versus without left ventricular systolic function <40% (17% vs. 2%;P < 0.025). Conclusion: In a selected group of patients with LM disease, unsupported PCI appears to be a feasible and safe procedure. In high-risk patients, the use of Impella 2.5 appears to be superior to IABP in LM PCI resulting in favorable short-term outcomes.

Enhancing the decoding accuracy of EEG signals by the introduction of anchored-STFT and adversarial data augmentation method.

Brain-computer interfaces (BCIs) enable communication between humans and machines by translating brain activity into control commands. Electroencephalography (EEG) signals are one of the most used brain signals in non-invasive BCI applications but are often contaminated with noise. Therefore, it is possible that meaningful patterns for classifying EEG signals are deeply hidden. State-of-the-art deep-learning algorithms are successful in learning hidden, meaningful patterns. However, the quality and the quantity of the presented inputs are pivotal. Here, we propose a feature extraction method called anchored Short Time Fourier Transform (anchored-STFT), which is an advanced version of STFT, as it minimizes the trade-off between temporal and spectral resolution presented by STFT. In addition, we propose a data augmentation method derived from l2-norm fast gradient sign method (FGSM), called gradient norm adversarial augmentation (GNAA). GNAA is not only an augmentation method but is also used to harness adversarial inputs in EEG data, which not only improves the classification accuracy but also enhances the robustness of the classifier. In addition, we also propose a CNN architecture, namely Skip-Net, for the classification of EEG signals. The proposed pipeline outperforms the current state-of-the-art methods and yields classification accuracies of 90.7% on BCI competition II dataset III and 89.5%, 81.8%, 76.0% and 85.4%, 69.1%, 80.9% on different data distributions of BCI Competition IV dataset 2b and 2a, respectively.

Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain-computer-interface setup.

Invasive brain-computer-interfaces (BCIs) aim to improve severely paralyzed patient's (e.g. tetraplegics) quality of life by using decoded movement intentions to let them interact with robotic limbs. We argue that the performance in controlling an end-effector using a BCI depends on three major factors: decoding error, missing somatosensory feedback and alignment error caused by translation and/or rotation of the end-effector relative to the real or perceived body. Using a virtual reality (VR) model of an ideal BCI decoder with healthy participants, we found that a significant performance loss might be attributed solely to the alignment error. We used a shape-drawing task to investigate and quantify the effects of robot arm misalignment on motor performance independent from the other error sources. We found that a 90° rotation of the robot arm relative to the participant leads to the worst performance, while we did not find a significant difference between a 45° rotation and no rotation. Additionally, we compared a group of subjects with indirect haptic feedback with a group without indirect haptic feedback to investigate the feedback-error. In the group without feedback, we found a significant difference in performance only when no rotation was applied to the robot arm, supporting that a form of haptic feedback is another important factor to be considered in BCI control.

SpikeDeep-classifier: a deep-learning based fully automatic offline spike sorting algorithm.

Objective.Advancements in electrode design have resulted in micro-electrode arrays with hundreds of channels for single cell recordings. In the resulting electrophysiological recordings, each implanted electrode can record spike activity (SA) of one or more neurons along with background activity (BA). The aim of this study is to isolate SA of each neural source. This process is called spike sorting or spike classification. Advanced spike sorting algorithms are time consuming because of the human intervention at various stages of the pipeline. Current approaches lack generalization because the values of hyperparameters are not fixed, even for multiple recording sessions of the same subject. In this study, a fully automatic spike sorting algorithm called 'SpikeDeep-Classifier' is proposed. The values of hyperparameters remain fixed for all the evaluation data.Approach.The proposed approach is based on our previous study (SpikeDeeptector) and a novel background activity rejector (BAR), which are both supervised learning algorithms and an unsupervised learning algorithm (K-means). SpikeDeeptector and BAR are used to extract meaningful channels and remove BA from the extracted meaningful channels, respectively. The process of clustering becomes straight-forward once the BA is completely removed from the data. Then, K-means with a predefined maximum number of clusters is applied on the remaining data originating from neural sources only. Lastly, a similarity-based criterion and a threshold are used to keep distinct clusters and merge similar looking clusters. The proposed approach is called cluster accept or merge (CAOM) and it has only two hyperparameters (maximum number of clusters and similarity threshold) which are kept fixed for all the evaluation data after tuning.Main results.We compared the results of our algorithm with ground-truth labels. The algorithm is evaluated on data of human patients and publicly available labeled non-human primates (NHPs) datasets. The average accuracy of BAR on datasets of human patients is 92.3% which is further reduced to 88.03% after (K-means + CAOM). In addition, the average accuracy of BAR on a publicly available labeled dataset of NHPs is 95.40% which reduces to 86.95% after (K-mean + CAOM). Lastly, we compared the performance of the SpikeDeep-Classifier with two human experts, where SpikeDeep-Classifier has produced comparable results.Significance.The SpikeDeep-Classifier is evaluated on the datasets of multiple recording sessions of different species, different brain areas and different electrode types without further retraining. The results demonstrate that 'SpikeDeep-Classifier' possesses the ability to generalize well on a versatile dataset and henceforth provides a generalized and fully automated solution to offline spike sorting.Clinical trial registration numberThe clinical trial registration number for patients implanted with the Utah array isNCT 01849822.For the epilepsy patients, approval from the local ethics committee at the Ruhr-University Bochum, Germany, was obtained prior to implantation. The Clinical trial registration number for the epilepsy patients implanted with microwires is16-5670.

Correction to: Vitamin D and Heart Failure.

The original version of this article, published in Current Heart Failure Reports, Volume 14, Issue 5, October 2017, erroneously cited an author's name as Marshall Brinkley, D" when it should be "Brinkley, DM."

Vitamin D and Heart Failure.

PURPOSE: Vitamin D is principally known for its role in calcium homeostasis, but preclinical studies implicate multiple pathways through which vitamin D may affect cardiovascular function and influence risk for heart failure. Many adults with cardiovascular disease have low vitamin D status, making it a potential therapeutic target. We review the rationale and potential role of vitamin D supplementation in the prevention and treatment of chronic heart failure. RECENT FINDINGS: Substantial observational evidence has associated low vitamin D status with the risk of heart failure, ventricular remodeling, and clinical outcomes in heart failure, including mortality. However, trials assessing the influence of vitamin D supplementation on surrogate markers and clinical outcomes in heart failure have generally been small and inconclusive. There are insufficient data to recommend routine assessment or supplementation of vitamin D for the prevention or treatment of chronic heart failure. Prospective trials powered for clinical outcomes are warranted.

Polarizable Material from a Conjunctival Biopsy in a Patient with Sarcoidosis.

PURPOSE: Conjunctival biopsies may contain polarizable material in patients with sarcoidosis despite no history of prior trauma or eye surgeries. PROCEDURES: A 39-year-old male with uveitic glaucoma presented with decreased vision and throbbing pain in his right eye. His intraocular pressure was elevated, and his vision was reduced to hand motion. Due to persistently elevated intraocular pressure refractory to medical treatment, the patient underwent a glaucoma drainage device procedure. During the procedure, a yellow, nodular conjunctival growth was noted and biopsied. RESULTS: Histopathological examination revealed multiple nonnecrotizing granulomata, some of which contained polarizable material. CONCLUSIONS: Biopsies of patients with sarcoidosis may contain polarizable material without evidence of foreign body inoculation.

Effect of aspirin on models of retinal pigment epithelium pathology.

BACKGROUND: To characterize the effect of aspirin (ASA) in mouse models of choroidal neovascularization (CNV) and retinal degeneration. METHODS: In vivo: Male C57BL/6 mice were given ASA in food or regular rodent diet. CNV was induced by argon laser photocoagulation. Subretinal injections of polyethylene glycol 400 (PEG-400) were administered to induce retinal degeneration. CNV size, laser spot area and mean intensity of VEGF in the laser injured zones were measured. In the PEG injected eyes the thickness of retinal pigment epithelium (RPE) and choroid was measured. In vitro: Human ARPE-19 cells were treated with 0.5 or 2.0 mM/L of ASA for 72 h. ELISA was used to measure the concentration of VEGF and CCL-2 in the supernatants. Additionally, damaged RPE monolayer was treated with ASA (0.5 or 2.0 mM/L) and vehicle separately. Size of damaged area was measured. ELISA was used to measure secretion of VEGF-A and CCL-2 by damaged cells after 24 h. RESULTS: No statistically significant effect of ASA on CNV size, laser spot size or VEGF expression was noted in CNV model. In the PEG model, ASA did not have any effect on RPE and choroid thickness; however, a significant increase in RPE atrophy was observed (P = 0.02 + 38%). In addition, ASA had a significant effect on the ability of the RPE cells to regenerate and become confluent after mechanical damage. CONCLUSIONS: ASA at doses consumed clinically for various medical causes may not worsen CNV in human subjects. However, ASA may increase RPE atrophy when consumed over long periods of time.

Out in the cold: the hypothermic heart response.

We present an interesting case of a 49-year-old woman with hypothermia and associated Osborn waves (also called J waves) on ECG. She was found on the floor of her home and difficult to arouse. On arrival to the emergency department (ED), her rectal temperature was 87.5°F. ECG showed Osborn waves in diffuse leads. She was intubated in the ED and was started on vasopressor support for hypotension refractory to intravenous fluid boluses. She was transferred to the critical care unit for continued respiratory and cardiovascular support. With active external rewarming her core body temperature continued to improve. Blood pressure also improved and vasopressor was tapered off. She was extubated and was transferred to the medical floor for continued supportive care. Osborn waves on ECG resolved within 12 h of achieving normal range body temperature. The patient was eventually discharged home with medical follow-up.

Bedside cardiac testing in acute cor pulmonale.

We present a case where an ECG and echocardiogram suggested pulmonary embolism and early treatment led to a positive outcome.

Xanthogranulomatous cholecystitis mimicking gallbladder cancer.

Xanthogranulomatous cholecystitis (XGC) is a benign, uncommon variant of chronic cholecystitis characterised by focal or diffuse destructive inflammatory process of the gallbladder (GB). Macroscopically, it appears like yellowish tumour-like masses in the wall of the GB. This article reports on a 74-year-old woman with XGC mimicking GB cancer.

A One-Sided Affair: Unoriginal Origin of the Left Coronary Artery, a Case Report.

Coronary artery anomalies constitute a group of congenital malformations that have a multitude of clinical manifestations and highly variable pathophysiology. We report a 56-year-old male with angina due to an anomalous origin of the left main coronary artery; approach and management.

A hiding in the lining: painful pericardial cyst.

A pericardial cyst is a rare and benign congenital malformation, usually discovered in the third or fourth decade of life. Its clinical presentation is variable, as it may be asymptomatic or present with chest pain, shortness of breath, or rarely with cardiac tamponade and arrhythmias. We present an interesting case of a woman presenting with chest pain who was found to have a pericardial cyst.

Platypnea orthodeoxia: a 'laid-back' case of dyspnoea.

A man with end-stage liver disease who presented with shortness of breath. He exhibited clinical platypnea (worsening shortness of breath on sitting up) and orthodeoxia (oxygen desaturation on sitting up). Follow-up investigations led to the diagnosis of hepatopulmonary syndrome.

Anomalous venous circuit: a detour to the heart.

We report a case of a complicated vascular access secondary to systemic venous defects, which have not been previously reported. Evaluation revealed an atypical coursing of a subclavian vein-persistent superior vena caval system into the hemizygos-azygos system and ultimately into the right (proper) superior vena cava. The clinical and surgical considerations of such an anomaly are discussed therein. We look at embryological origins of such a merger and share our experience in troubleshooting through the anomaly.

Trapdoor ischaemia: coronary ostial occlusion by an aortic dissection.

We present an interesting case of an elderly man with acute myocardial infarction due to retrograde dissection of the aortic root occluding the coronary ostia.