Introduction of a Pre-admission Pharmacist Service Utilising the Surgical Ward Pharmacist.

Background: The challenge with obtaining a best possible medication history (BPMH) post-surgery is the delay in clarifying medications due to decreased post-operative cognitive status and pain, which can lead to missed or late administration of medications. Studies have suggested that unintentional medication discrepancies at the time of admission are common in general medical patients. Objectives: To investigate if a pre-admission pharmacist completing BPMHs for adult elective surgery patients with planned overnight admission increases the proportion of patients with (i) a BPMH completed, (ii) medication reconciliation completed and (iii) all home medications charted correctly within 24 hours of admission. Methods: Patients in the pre-intervention group had a BPMH completed on admission as standard of care. Patients in the post-intervention group were contacted by the pre-admission pharmacist 1 to 3 business days prior to admission to complete a BPMH. The pre-admission pharmacist role was performed by a surgical ward pharmacist in addition to their daily workload. Descriptive statistics, Chi-squared test and Mann-Whitney U test were used to analyse the data. Results: The post-intervention group had more patients with a completed BPMH (47.2% vs 25.3%, P = .005), medication reconciliation (43.8% vs 15.5%, P = .0001) and all home medications charted correctly (36% vs 16.9%, P = .007) within 24 hours of admission compared with the pre-intervention group. Conclusion: The introduction of a pre-admission service utilising the surgical ward pharmacist increased the proportion of patients with a completed BPMH, medication reconciliation and home medications charted correctly within 24 hours of admission.

Improving Laryngoscopy Image Analysis Through Integration of Global Information and Local Features in VoFoCD Dataset.

The diagnosis and treatment of vocal fold disorders heavily rely on the use of laryngoscopy. A comprehensive vocal fold diagnosis requires accurate identification of crucial anatomical structures and potential lesions during laryngoscopy observation. However, existing approaches have yet to explore the joint optimization of the decision-making process, including object detection and image classification tasks simultaneously. In this study, we provide a new dataset, VoFoCD, with 1724 laryngology images designed explicitly for object detection and image classification in laryngoscopy images. Images in the VoFoCD dataset are categorized into four classes and comprise six glottic object types. Moreover, we propose a novel Multitask Efficient trAnsformer network for Laryngoscopy (MEAL) to classify vocal fold images and detect glottic landmarks and lesions. To further facilitate interpretability for clinicians, MEAL provides attention maps to visualize important learned regions for explainable artificial intelligence results toward supporting clinical decision-making. We also analyze our model's effectiveness in simulated clinical scenarios where shaking of the laryngoscopy process occurs. The proposed model demonstrates outstanding performance on our VoFoCD dataset. The accuracy for image classification and mean average precision at an intersection over a union threshold of 0.5 (mAP50) for object detection are 0.951 and 0.874, respectively. Our MEAL method integrates global knowledge, encompassing general laryngoscopy image classification, into local features, which refer to distinct anatomical regions of the vocal fold, particularly abnormal regions, including benign and malignant lesions. Our contribution can effectively aid laryngologists in identifying benign or malignant lesions of vocal folds and classifying images in the laryngeal endoscopy process visually.

Vision-Based Assistance for Vocal Fold Identification in Laryngoscopy with Knowledge Distillation.

Laryngoscopy images play a vital role in merging computer vision and otorhinolaryngology research. However, limited studies offer laryngeal datasets for comparative evaluation. Hence, this study introduces a novel dataset focusing on vocal fold images. Additionally, we propose a lightweight network utilizing knowledge distillation, with our student model achieving around 98.4% accuracy-comparable to the original EfficientNetB1 while reducing model weights by up to 88%. We also present an AI-assisted smartphone solution, enabling a portable and intelligent laryngoscopy system that aids laryngoscopists in efficiently targeting vocal fold areas for observation and diagnosis. To sum up, our contribution includes a laryngeal image dataset and a compressed version of the efficient model, suitable for handheld laryngoscopy devices.

MANet: Multi-branch attention auxiliary learning for lung nodule detection and segmentation.

BACKGROUND AND OBJECTIVE: Pulmonary nodule detection and segmentation are currently two primary tasks in analyzing chest computed tomography (Chest CT) in order to detect signs of lung cancer, thereby providing early treatment measures to reduce mortality. Even though there are many proposed methods to reduce false positives for obtaining effective detection results, distinguishing between the pulmonary nodule and background region remains challenging because their biological characteristics are similar and varied in size. The purpose of our work is to propose a method for automatic nodule detection and segmentation in Chest CT by enhancing the feature information of pulmonary nodules. METHODS: We propose a new UNet-based backbone with multi-branch attention auxiliary learning mechanism, which contains three novel modules, namely, Projection module, Fast Cascading Context module, and Boundary Enhancement module, to further enhance the nodule feature representation. Based on that, we build MANet, a lung nodule localization network that simultaneously detects and segments precise nodule positions. Furthermore, our MANet contains a Proposal Refinement step which refines initially generated proposals to effectively reduce false positives and thereby produce the segmentation quality. RESULTS: Comprehensive experiments on the combination of two benchmarks LUNA16 and LIDC-IDRI show that our proposed model outperforms state-of-the-art methods in the tasks of nodule detection and segmentation tasks in terms of FROC, IoU, and DSC metrics. Our method reports an average FROC score of 88.11% in lung nodule detection. For the lung nodule segmentation, the results reach an average IoU score of 71.29% and a DSC score of 82.74%. The ablation study also shows the effectiveness of the new modules which can be integrated into other UNet-based models. CONCLUSIONS: The experiments demonstrated our method with multi-branch attention auxiliary learning ability are a promising approach for detecting and segmenting the pulmonary nodule instances compared to the original UNet design.

Support of deep learning to classify vocal fold images in flexible laryngoscopy.

PURPOSE: To collect a dataset with adequate laryngoscopy images and identify the appearance of vocal folds and their lesions in flexible laryngoscopy images by objective deep learning models. METHODS: We adopted a number of novel deep learning models to train and classify 4549 flexible laryngoscopy images as no vocal fold, normal vocal folds, and abnormal vocal folds. This could help these models recognize vocal folds and their lesions within these images. Ultimately, we made a comparison between the results of the state-of-the-art deep learning models, and another comparison of the results between the computer-aided classification system and ENT doctors. RESULTS: This study exhibited the performance of the deep learning models by evaluating laryngoscopy images collected from 876 patients. The efficiency of the Xception model was higher and steadier than almost the rest of the models. The accuracy of no vocal fold, normal vocal folds, and vocal fold abnormalities on this model were 98.90 %, 97.36 %, and 96.26 %, respectively. Compared to our ENT doctors, the Xception model produced better results than a junior doctor and was near an expert. CONCLUSION: Our results show that current deep learning models can classify vocal fold images well and effectively assist physicians in vocal fold identification and classification of normal or abnormal vocal folds.

Survey Anatomical Features and Related Factors of the Sphenopalatine Foramen on Computed Tomography.

The aim of the research is to define anatomical features of the sphenopalatine foramen (SPF) and be related to the SPF on computed tomography (CT) such as shape, location, size of the SPF, the appearance of the ethmoidal crest, and the distance from SPF to some landmarks in the nasal cavity. As a result, surgeons could quickly determine the SPF location in transnasal endoscopic sphenopalatine artery ligation (TESPAL). A cross-sectional study was conducted. This study was carried out at Cho Ray hospital from August 2019 to June 2020. Image data from 55 patients who had been indicated sinuses CT. Results show that the SPF had a wide range of shapes: oval (20.9%), triangle (19.1%), circle (18.2%), racket shape (7.3%), hourglass shape (6.4%), and other shapes. In the anteroposterior dimension, the mean SPF was 5.72 ± 1.22 mm. In the craniocaudal dimension, the mean SPF measured 5.62 ± 1.99 mm. The SPF was mainly located in the superior meatus and in the transition between the middle and superior meatus. The most reliable anatomical landmark to find the SPF was the ethmoidal crest with an appearance rate of about 95.5%. The mean distances from SPF to anterior nasal spine, nasal floor, nasal septum, maxillary line, anterior head of the middle turbinate, choanal arch, and base lamella were 57.04 ± 3.11, 24.71 ± 2.90, 11.26 ± 2.09, 34.93 ± 2.07, 32.69 ± 3.30, 8.82 ± 1.65, and 8.07 ± 1.28 mm, respectively. CT scan images in this study can provide information about anatomical features of the SPF, which contribute to the quick and efficient identification of the SPF before and during TESPAL.

Fatherhood Experiences of Men With Inflammatory Arthritis: A Preliminary Grounded Theory.

OBJECTIVE: Minimal prior research has examined the impact of inflammatory arthritis (IA) on men's perspectives on parenting. We aimed to describe fathering roles and experiences, the effect of IA on parenting activities, and strategies used by fathers with IA to fulfill this role. METHODS: A grounded theory approach guided data gathering and analysis. Nine men with IA, parenting at least 1 child age <19 years, were recruited through rheumatology practices, therapy clinics, and social media. Each engaged in 1 in-depth personal interview. Transcripts were analyzed using inductive and iterative steps to identify key themes and a preliminary explanatory framework of fathering experiences of men with IA. RESULTS: All men were married, ages 31-62 years, with 1 to 5 children ages 6 months to 28 years. "Being an involved father" describes participants' perspectives on fulfilling their role as hands-on parents, role models, and financial providers. "Taking ownership" explains how participants managed daily life, comprising 2 subthemes, "taking care of yourself," using strategies like exercise and communicating with loved ones, and "redefining yourself," a process of adapting to reframed identity and lifestyle adjustments. "Accessing support" indicates men who felt well-supported by social networks (most critically their wives), health care providers, and informational and educational resources. CONCLUSION: This small, grounded theory study offers an enriched understanding of fatherhood experiences of men with IA. When social, practical, and educational supports are in place, these men found parenting joyful and rewarding. Despite task limitations, their perspectives on being involved fathers was unrestricted by arthritis.

MiR-21 enhances melanoma invasiveness via inhibition of tissue inhibitor of metalloproteinases 3 expression: in vivo effects of MiR-21 inhibitor.

Metastatic melanoma is the most aggressive form of this cancer. It is important to understand factors that increase or decrease metastatic activity in order to more effectively research and implement treatments for melanoma. Increased cell invasion through the extracellular matrix is required for metastasis and is enhanced by matrix metalloproteinases (MMPs). Tissue inhibitor of metalloproteinases 3 (TIMP3) inhibits MMP activity. It was previously shown by our group that miR-21, a potential regulator of TIMP3, is over-expressed in cutaneous melanoma. It was therefore hypothesized that increased levels of miR-21 expression would lead to decreased expression of TIMP3 and thereby enhance the invasiveness of melanoma cells. miR-21 over-expression in the melanoma cell lines WM1552c, WM793b, A375 and MEL 39 was accomplished via transfection with pre-miR-21. Immunoblot analysis of miR-21-overexpressing cell lines revealed reduced expression of TIMP3 as compared to controls. This in turn led to a significant increase in the invasiveness of the radial growth phase cell line WM1552c and the vertical growth phase cell line WM793b (p < 0.05), but not in the metastatic cell lines A375 or MEL 39. The proliferation and migration of miR-21 over-expressing cell lines was not affected. Reduced expression of TIMP3 was achieved by siRNA knockdown and significantly enhanced invasion of melanoma cell lines, mimicking the effects of miR-21 over-expression. Treatment of tumor cells with a linked nucleic acid antagomir to miR-21 inhibited tumor growth and increased tumor expression of TIMP3 in vivo in 01B74 Athymic NCr-nu/nu mice. Intra-tumoral injections of anti-miR-21 produced similar effects. This data shows that increased expression of miR-21 enhanced the invasive potential of melanoma cell lines through TIMP3 inhibition. Therefore, inhibition of miR-21 in melanoma may reduce melanoma invasiveness.

A phase I trial of bortezomib and interferon-α-2b in metastatic melanoma.

The possibility that cytokine administration could enhance the antitumor effects of proteasome inhibition was explored. It was found that coadministration of bortezomib and interferon-α (IFN-α) induced synergistic apoptosis in human melanoma cell lines and prolonged survival in a murine model of melanoma. A phase I study was conducted to determine the tolerability and the maximum tolerated dose of bortezomib when administered in combination with IFN-α-2b to patients with metastatic melanoma. Patients were treated on a 5-week cycle. In week 1 of cycle 1, patients received 5 million U/m(2) IFN-α subcutaneously thrice weekly. During weeks 2-4 of cycle 1, bortezomib was administered intravenously weekly along with IFN-α thrice weekly. There was a treatment break during week 5. After cycle 1, bortezomib was administered in combination with IFN-α. Bortezomib was administered in escalating doses (1.0, 1.3, or 1.6 mg/m) to cohorts of 3 patients. Sixteen patients were treated (8 women, 8 men; median age 59 y). Common grade 3 toxicities included fatigue (5), vomiting (3), and diarrhea (3). Grade 4 toxicities included fatigue (3) and lymphopenia (1). The maximum tolerated dose for bortezomib was 1.3 mg/m(2). One patient had a partial response, and 7 had stable disease. Progression-free survival was 2.5 months, and overall survival was 10.3 months. Bortezomib administration did not augment the ability of IFN-α to induce phosphorylation of STAT1 in circulating immune cells; however, it did lead to reduced plasma levels of proangiogenic cytokines. The combination of bortezomib and IFN-α can be safely administered to melanoma patients.