&lt;p&gt;Perceived Surgeon Stress During No-Sedation Topical Phacoemulsification&lt;/p&gt;

Mansour, Ahmad M.; Stewart, Michael W.; Charbaji, Abdul Razzak; Jawhari, Khalil M El; Zein, Lama El; Mansour, Mohamad A; Saade, Joanna S.

doi:10.2147/opth.s266516

Cited by 7 publications

(3 citation statements)

References 30 publications

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“…This type of anesthesia includes different sub-types, such as topical anesthesia [13][14][15] , subconjunctival anesthesia [16][17][18] , retrobulbar anesthesia, peribulbar anesthesia, sub-Tenon's anesthesia [9,[19][20] , medial canthus epiescleral anesthesia [21] and facial nerve block. Topical anesthesia has become a common form of anesthesia; however, it requires that the surgery is performed quickly and efficiently to minimize stress on the patients [22] , patient cooperation [23] , experienced surgeon [10] and it doesn't provide the same level of pain relief as peribulbar anesteshia [24][25] . We still prefer loco-regional anesthesia not only for posterior segment or glaucoma surgery but also because it is the preferred method for anterior segment surgery.…”

Section: Discussionmentioning

confidence: 99%

Globe penetration during loco-regional anesthesia: prevalence and review of cases

Gómez-Benlloch¹,

Nadal²,

Julio³

et al. 2022

Int J Ophthalmol

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AIM: To describe prevalence and different clinical signs and management of cases with penetrating eye injuries during loco-regional anesthesia for ophthalmic surgery. METHODS: A retrospective review of clinical records was carried out, identifying cases of globe penetration secondary to peribulbar anesthesia injection during 5y activity in Centro de Oftalmología Barraquer. RESULTS: A total of 17 460 needle-based ocular anesthesia procedures were performed in our centre and 4 cases of globe penetration were recorded with an estimated prevalence of 0.024%. Globe penetrations were always detected in the first 24h after surgery. Vitreous haemorrhage was found in all the cases. Two eyes presented retinal detachment and two eyes choroidal detachment (CD). The initial surgical approach was performed within the first 48h. Silicone oil was used as tamponade in three eyes and the fourth case remained only with air. Detachments were solved successfully in all the cases. Functional results varied among cases, depending on ocular remarkable antecedent and globe penetration with or without retinal or CD. CONCLUSION: Prevalence of globe penetration during loco-regional anesthesia is low in our centre. Physicians should consider the possibility of globe penetration in eyes with postoperative atypical appearance after loco-regional anesthesia. Immediate B-scan ultrasonography is recommended in suspicious cases with a dense vitreous haemorrhage. An early vitrectomy surgery in conjunction with laser or cryotherapy at the penetration sites is essential for good anatomical and functional results.

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Section: Discussionmentioning

confidence: 99%

Globe penetration during loco-regional anesthesia: prevalence and review of cases

Gómez-Benlloch¹,

Nadal²,

Julio³

et al. 2022

Int J Ophthalmol

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“…Moreover, work fatigue within physicians seems to be associated with higher level of everyday stress, high work load and depression. 82 , 83 Furthermore, there was a necessity for nursing stakeholders to introduce programs to regularly assess and enhance the resilience of nurses especially at time of crisis. Such programs would protect nurses from the perils of burnout and enhance their retention during times when they are most needed.…”

Section: Resultsmentioning

confidence: 99%

Mental Health During COVID-19: An Evaluation of Academic Universities’ Contribution to Existing Research

Tawil,

Haque,

Salameh

2024

JMDH

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Increases in mental health problems have been observed during COVID-19 pandemic. Therefore, this topic of research became a priority, especially at the academic level. The objectives of this review were to summarize academic contribution to mental health research during the era of COVID-19. A scoping review of studies conducted at different academic institutions and examining alterations in mental health during the pandemic during the last three years was conducted. Fifty-five studies were included. These focused on different mental health changes that occurred in the era of COVID-19 such as changes in work habits or existing psychological conditions, COVID-19-related fear depression, anxiety and stress. Most of the included studies were observational (76.7%). The majority of the publications were published in Scimago Journal Rank Q1 journals (57.1%). The average number of citations per publication was 15.3 ± 30.13 [0–125]. The number of citations was higher in papers with international collaboration of authors ( p = 0.031 ). Publications with COVID-19 as a main objective were more cited than papers not directly related to this subject (25.9 ± 39.45 vs 4.14 ± 3.2; p = 0.044 ). Mental health problems are a common response to the COVID-19 pandemic. The contribution of academic universities to different mental health research studies that took place during COVID-19 outbreak have underlined this reality. However, more representative research from other institutional settings will be needed, particularly in vulnerable populations.

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“…ML technologies have enabled numerous useful applications of AI, including ones in the medical industry, with incredible success [22]. Previous research has extensively investigated the development of stress detection methods such as Decision Trees (DT), K-Nearest Neighbors (KNN), Random Forests, and Logistic Regression [23][24][25][26][27]. Machine learning approaches often need a large enough quantity of data to operate effectively during training.…”

Section: Motivationmentioning

confidence: 99%

Wrist-Based Electrodermal Activity Monitoring for Stress Detection Using Federated Learning

Almadhor

Sampedro

Abisado

et al. 2023

Sensors

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With the most recent developments in wearable technology, the possibility of continually monitoring stress using various physiological factors has attracted much attention. By reducing the detrimental effects of chronic stress, early diagnosis of stress can enhance healthcare. Machine Learning (ML) models are trained for healthcare systems to track health status using adequate user data. Insufficient data is accessible, however, due to privacy concerns, making it challenging to use Artificial Intelligence (AI) models in the medical industry. This research aims to preserve the privacy of patient data while classifying wearable-based electrodermal activities. We propose a Federated Learning (FL) based approach using a Deep Neural Network (DNN) model. For experimentation, we use the Wearable Stress and Affect Detection (WESAD) dataset, which includes five data states: transient, baseline, stress, amusement, and meditation. We transform this raw dataset into a suitable form for the proposed methodology using the Synthetic Minority Oversampling Technique (SMOTE) and min-max normalization pre-processing methods. In the FL-based technique, the DNN algorithm is trained on the dataset individually after receiving model updates from two clients. To decrease the over-fitting effect, every client analyses the results three times. Accuracies, Precision, Recall, F1-scores, and Area Under the Receiver Operating Curve (AUROC) values are evaluated for each client. The experimental result shows the effectiveness of the federated learning-based technique on a DNN, reaching 86.82% accuracy while also providing privacy to the patient’s data. Using the FL-based DNN model over a WESAD dataset improves the detection accuracy compared to the previous studies while also providing the privacy of patient data.

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<p>Perceived Surgeon Stress During No-Sedation Topical Phacoemulsification</p>

Cited by 7 publications

References 30 publications

Globe penetration during loco-regional anesthesia: prevalence and review of cases

Globe penetration during loco-regional anesthesia: prevalence and review of cases

Mental Health During COVID-19: An Evaluation of Academic Universities’ Contribution to Existing Research

Wrist-Based Electrodermal Activity Monitoring for Stress Detection Using Federated Learning

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