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Objective: To investigate the role of MR imaging in detecting brachial plexus (BP) abnormalities in breast cancer patients with plexopathy but without palpable masses.Design: MR imaging of the BP was performed on 26 breast cancer patients with brachial plexopathy without palpable regional masses, using 0.5 T and 1.5 T imaging systems. Findings were correlated with the clinical diagnoses.Patients: Twenty-six patients with brachial plexopathy and history of breast cancer were enrolled in the study. All patients presented with plexopathy symptoms. Fourteen patients were positive and 12 patients were indeterminate for BP metastasis according to clinical criteria.Results and Conclusion: MR imaging demonstrated masses involving the BP representing metastases in two patients. Nine patients had other regional abnormalities with a normal brachial plexus. It is concluded that MR imaging is useful in the assessment and direction of therapy of brachial plexopathy in breast cancer patients by detecting both metastases to the BP as well as other abnormalities, unrelated to the BP, which may explain the patient's symptoms. [ABSTRACT FROM AUTHOR]

Out-of-hospital cardiac arrest (OHCA) is a global health problem affecting approximately 4.4 million individuals yearly. OHCA has a poor survival rate, specifically when unwitnessed (accounting for up to 75% of cases). Rapid recognition can significantly improve OHCA survival, and consumer wearables with continuous cardiopulmonary monitoring capabilities hold potential to "witness" cardiac arrest and activate emergency services. In this study, we used an arterial occlusion model to simulate cardiac arrest and investigated the ability of infrared photoplethysmogram (PPG) sensors, often utilized in consumer wearable devices, to differentiate normal cardiac pulsation, pulseless cardiac (i.e., resembling a cardiac arrest), and non-physiologic (i.e., off-body) states. Across the classification models trained and evaluated on three anatomical locations, higher classification performances were observed on the finger (macro average F1-score of 0.964 on the fingertip and 0.954 on the finger base) compared to the wrist (macro average F1-score of 0.837). The wrist-based classification model, which was trained and evaluated using all PPG measurements, including both high- and low-quality recordings, achieved a macro average precision and recall of 0.922 and 0.800, respectively. This wrist-based model, which represents the most common form factor in consumer wearables, could only capture about 43.8% of pulseless events. However, models trained and tested exclusively on high-quality recordings achieved higher classification outcomes (macro average F1-score of 0.975 on the fingertip, 0.973 on the finger base, and 0.934 on the wrist). The fingertip model had the highest performance to differentiate arterial occlusion pulselessness from normal cardiac pulsation and off-body measurements with macro average precision and recall of 0.978 and 0.972, respectively. This model was able to identify 93.7% of pulseless states (i.e., resembling a cardiac arrest event), with a 0.4% false positive rate. All classification models relied on a combination of time-, power spectral density (PSD)-, and frequency-domain features to differentiate normal cardiac pulsation, pulseless cardiac, and off-body PPG recordings. However, our best model represented an idealized detection condition, relying on ensuring high-quality PPG data for training and evaluation of machine learning algorithms. While 90.7% of our PPG recordings from the fingertip were considered of high quality, only 53.2% of the measurements from the wrist passed the quality criteria. Our findings have implications for adapting consumer wearables to provide OHCA detection, involving advancements in hardware and software to ensure high-quality measurements in real-world settings, as well as development of wearables with form factors that enable high-quality PPG data acquisition more consistently. Given these improvements, we demonstrate that OHCA detection can feasibly be made available to anyone using PPG-based consumer wearables., (© 2024. The Author(s).)

Objectives: When an out-of-hospital cardiac arrest (OHCA) occurs, the first step in the chain of survival is detection. However, 75% of OHCAs are unwitnessed, representing the largest barrier to activating the chain of survival. Wearable devices have the potential to be "artificial bystanders," detecting OHCA and alerting 9-1-1. We sought to understand factors impacting users' willingness for continuous use of a wearable device through an online survey to inform future use of these systems for automated OHCA detection., Methods: Data were collected from October 2022 to June 2023 through voluntary response sampling. The survey investigated user convenience and perception of urgency to understand design preferences and willingness to adhere to continuous wearable use across different hypothetical risk levels. Associations between categorical variables and willingness were evaluated through nonparametric tests. Logistic models were fit to evaluate the association between continuous variables and willingness at different hypothetical risk levels., Results: The survey was completed by 359 participants. Participants preferred hand-based devices (wristbands: 87%, watches: 86%, rings: 62%) and prioritized comfort (94%), cost (83%), and size (72%). Participants were more willing to adhere at higher levels of hypothetical risk. At the baseline risk of 0.1%, older individuals with prior wearable use were most willing to adhere to continuous wearable use., Conclusion: Individuals were willing to continuously wear wearable devices for OHCA detection, especially at increased hypothetical risk of OHCA. Optimizing willingness is not just a matter of adjusting for user preferences, but also increasing perception of urgency through awareness and education about OHCA., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Author(s). Journal of the American College of Emergency Physicians Open published by Wiley Periodicals LLC on behalf of American College of Emergency Physicians.)

Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2-11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2-4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices., (© 2024. The Author(s) under exclusive licence to Biomedical Engineering Society.)

Background: Biosensor technologies have been proposed as a solution to provide recognition and facilitate earlier responses to unwitnessed out-of-hospital cardiac arrest (OHCA) cases. We sought to estimate the effect of recognition on survival and modelled the potential incremental impact of increased recognition of unwitnessed cases on survival to hospital discharge, to demonstrate the potential benefit of biosensor technologies., Methods: We included cases from the British Columbia Cardiac Arrest Registry (2019-2020), which includes Emergency Medical Services (EMS)-assessed OHCAs. We excluded cases that would not have benefitted from early recognition (EMS-witnessed, terminal illness, or do-not-resuscitate). Using a mediation analysis, we estimated the relative benefits on survival of a witness recognizing vs. intervening in an OHCA; and estimated the expected additional number of survivors resulting from increasing recognition alone using a bootstrap logistic regression framework., Results: Of 13,655 EMS-assessed cases, 11,412 were included (6314 EMS-treated, 5098 EMS-untreated). Survival to hospital discharge was 191/8879 (2.2%) in unwitnessed cases and 429/2533 (17%) in bystander-witnessed cases. Of the total effect attributable to a bystander witness, recognition accounted for 84% (95% CI: 72, 86) of the benefit. If all previously unwitnessed cases had been bystander witnessed, we would expect 1198 additional survivors. If these cases had been recognized, but no interventions performed, we would expect 912 additional survivors., Conclusion: Unwitnessed OHCA account for the majority of OHCAs, yet survival is dismal. Methods to improve recognition, such as with biosensor technologies, may lead to substantial improvements in overall survival., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Sudden cardiac arrest (SCA) is a leading cause of mortality worldwide. The SCA-to-resuscitation interval is a key determinant of patient outcomes, highlighting the clinical need for reliable and timely detection of SCA. Near-infrared spectroscopy (NIRS), a non-invasive optical technique, may have utility for this application. We investigated transcutaneous NIRS as a method to detect pentobarbital-induced changes during cardiac arrest in eight Yucatan miniature pigs. NIRS measurements during cardiac arrest were compared to invasively acquired carotid blood pressure and partial oxygen pressure (PO 2 ) of spinal cord tissues. We observed statistically significant decreases in mean arterial pressure (MAP) 64.68 mmHg ± 13.08, p < 0.0001), spinal cord PO 2 (38.16 mmHg ± 20.04, p = 0.0028), and NIRS-derived tissue oxygen saturation (TSI%) (14.50% ± 3.80, p < 0.0001) from baseline to 5 min after pentobarbital administration. Euthanasia-to-first change in hemodynamics for MAP and TSI (%) were similar [MAP (10.43 ± 4.73 s) vs TSI (%) (12.04 ± 1.85 s), p = 0.3714]. No significant difference was detected between NIRS and blood pressure-derived pulse rates during baseline periods (p > 0.99) and following pentobarbital administration (p = 0.97). Transcutaneous NIRS demonstrated the potential to identify rapid hemodynamic changes due to cardiac arrest in periods similar to invasive indices. We conclude that transcutaneous NIRS monitoring may present a novel, non-invasive approach for SCA detection, which warrants further investigation., (© 2023. The Author(s).)

Aim: Cardiac arrest (CA) is the cessation of circulation to vital organs that can only be reversed with rapid and appropriate interventions. Sensor technologies for early detection and activation of the emergency medical system could enable rapid response to CA and increase the probability of survival. We conducted a systematic review to summarize the literature surrounding the performance of sensor technologies in detecting OHCA., Methods: We searched the academic and grey literature using keywords related to cardiac arrest, sensor technologies, and recognition/detection. We included English articles published up until June 6, 2022, including investigations and patent filings that reported the sensitivity and specificity of sensor technologies to detect cardiac arrest on human or animal subjects. (Prospero# CRD42021267797)., Results: We screened 1666 articles and included four publications examining sensor technologies. One tested the performance of a physical sensor on human participants in simulated CA, one tested performance on audio recordings of patients in cardiac arrest, and two utilized a hybrid design for testing including human participants and ECG databases. Three of the devices were wearable and one was an audio detection algorithm utilizing household smart technologies. Real-world testing was limited in all studies. Sensitivity and specificity for the sensors ranged from 97.2 to 100% and 90.3 to 99.9%, respectively. All included studies had a medium/high risk of bias, with 2/4 having a high risk of bias., Conclusions: Sensor technologies show promise for cardiac arrest detection. However, current evidence is sparse and of high risk of bias. Small sample sizes and databases with low external validity limit the generalizability of findings., Competing Interests: The authors declare no conflicts of interest., (© 2022 The Authors.)

Background: Migraine is one of the most common complaints encountered in neurology clinics. Accurate diagnoses of migraine are usually informed by the patient's history, and neuroimaging is only performed in cases of atypical or severe, medically intractable headache to rule out underlying pathologies. Our study aimed to identify the spectrum of brain magnetic resonance imaging (MRI) findings characteristic of chronic headache., Methods: This retrospective study of adult patients referred to the First Scan radiology clinic in Jeddah, Saudi Arabia, for brain MRI with a known diagnosis of migraine headache was performed between April 2016 to May 2017., Results: We included 275 adults (115 men; median age, 38 years, IQR 30-52) with known diagnoses of chronic migraine. Incidental MRI findings were discovered in 157 (57 %) of the scans; 23 (8.3 %) of these were clinically significant, indicating the need for an intervention. Patients aged >40 years were more likely to have an abnormal scan. There were no significant differences related to sex or duration of headaches for more than one year., Conclusion: The performance of brain MRI warrants consideration in patients who do not respond as expected to migraine and headache treatment. We found clinically significant MRI findings in up to 8 % of such patients. Abnormal imaging findings were the most common among patients of >40 years of age., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Odontoid process fractures are commonly classified as types I through III according to the Anderson & D'Alonzo scheme. A fourth type of fracture not included in this classification has been described as "vertical odontoid fracture". These fractures are located in the vertical plan of the dens. We describe a new case of an oblique coronally oriented fracture through the odontoid process with extension to the body of C2. Our patient is a 22-year-old lady who sustained a road traffic accident with head, facial and cervical trauma. Computed tomography with 2D and 3D reconstruction characterized the fracture. We suppose that the mechanism of injury was an axial load associated with dorsal to ventral force. The patient was placed on a halo-vest for 12 weeks with good healing and no evidence of instability on flexion-extension studies 6 months later. This case demonstrates that the odontoid and C2 vertebral body fractures belong to the same spectrum and are determined by the patient's anatomy and the mechanism of the injury.

A case of infantile nephrotic syndrome (NS) with advanced membranoproliferative glomerulonephritis (MPGN), type I, and bilateral congenital glaucoma, is presented. The patient also had persistent thrombocytopenia and subclinical hypothyroidism. The parents were second-degree cousins and the affected infant had a sibling who was born with congenital glaucoma. His mother had an aunt and uncle on the maternal side who were born with congenital glaucoma. In addition, there was a history of infantile death in five family members of unknown causes (pedigree). To the best of our knowledge, the association of congenital glaucoma and infantile NS due to MPGN has not been reported previously.

Purpose: To describe the use of an endovascular therapeutic technique in the management of a giant carotid cavernous aneurysm., Methods: We reviewed the clinical and neuroradiologic findings of a patient with an unusual case of carotid cavernous aneurysm and intraorbital rupture. The medical literature was searched for similar cases and to review the use of endovascular techniques., Results: The patient was treated by balloon occlusion of the left internal carotid artery., Conclusions: Endovascular techniques can be used to treat complex giant cranioorbital cavernous aneurysms.

Purpose: To evaluate the accuracy of focused abdominal ultrasonography (US) in detecting abdominal injuries that require in-hospital patient treatment in the setting of blunt abdominal trauma., Materials and Methods: One thousand ninety patients with blunt abdominal trauma were assessed with focused abdominal US within 30 minutes of arrival at the hospital. Focused abdominal US results were positive if intra- or retroperitoneal fluid was detected. Patients with negative US results and no other major injuries were observed in the emergency department for 12 hours before discharge. Patients who deteriorated clinically after negative initial US underwent repeat US and/or emergency abdominopelvic computed tomography (CT). Patients with positive or indeterminate US results underwent emergency abdominopelvic CT., Results: Nine hundred seventy-four (89%) patients had negative focused abdominal US results; eight of these underwent CT. Sixty-six (6%) had positive US results. Four (0.4%) had false-negative and 19 (1.7%) had false-positive US results. Twenty-seven (2.5%) had indeterminate US results; of these, five (18.5%) had positive CT results. One hundred twenty-four (11.4%) required emergency CT. After indeterminate cases were excluded, focused abdominal US had 94% sensitivity, 98% specificity, 78% positive predictive value, 100% negative predictive value, and 95% accuracy., Conclusion: Focused abdominal US has a high negative predictive value for major abdominal injury in patients with blunt abdominal trauma.