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Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P < 0.05). For patients with referral DR, those in the PCP+DeepDR-LLM arm were more likely to adhere to DR referrals (P < 0.01). Additionally, DeepDR-LLM deployment improved the quality and empathy level of management recommendations. Given its multifaceted performance, DeepDR-LLM holds promise as a digital solution for enhancing primary diabetes care and DR screening.

This study aimed to evaluate the predictive value of diabetic retinopathy (DR) and its stages with the incidence of major cardiovascular events and all-cause mortality in type 2 diabetes mellitus (T2DM) persons in our large primary healthcare database from Catalonia (Spain). A retrospective cohort study with pseudo-anonymized routinely collected health data from SIDIAP was conducted from 2008 to 2016. We calculated incidence rates of major cardiovascular events [coronary heart disease (CHD), stroke, or both-macrovascular events] and all-cause mortality for subjects with and without DR and for different stages of DR. The proportional hazards regression analysis was done to assess the probability of occurrence between DR and the study events. About 22,402 T2DM subjects with DR were identified in the database and 196,983 subjects without DR. During the follow-up period among the subjects with DR, we observed the highest incidence of all-cause mortally. In the second place were the macrovascular events among the subjects with DR. In the multivariable analysis, fully adjusted for DR, sex, age, body mass index (BMI), tobacco, duration of T2DM, an antiplatelet or antihypertensive drug, and HbA1c, we observed that subjects with any stage of DR had higher risks for all of the study events, except for stroke. We observed the highest probability of all-cause death events (adjusted hazard ratios, AHRs: 1.34, 95% CI: 1.28; 1.41). In conclusion, our results show that DR is related to CHD, macrovascular events, and all-cause mortality among persons with T2DM.

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Item does not contain fulltext, Up to 85% of the patients with nasopharyngeal carcinoma present with regional nodal metastasis. Although excellent nodal control is achieved with radiotherapy, a thorough understanding of the current TNM staging criteria and pattern of nodal spread is essential to optimize target delineation and minimize unnecessary irradiation to adjacent normal tissue. Selective nodal irradiation with sparing of the lower neck and submandibular region according to individual nodal risk is now emerging as the preferred treatment option. There has also been continual refinement in staging classification by incorporating relevant adverse nodal features. As for the uncommon occurrence of recurrent nodal metastasis after radiotherapy, surgery remains the standard of care.

Contains fulltext : 237728.pdf (Publisher’s version ) (Open Access), PURPOSE: To review the current options in the management of Warthin tumors (WTs) and to propose a working management protocol. METHODS: A systematic literature search was conducted using PubMed and ScienceDirect database. A total of 141 publications were selected and have been included in this review. Publications were selected based on relevance, scientific evidence, and actuality. RESULTS: The importance of parotid WTs is increasing due to its rising incidence in many countries, becoming the most frequently encountered benign parotid tumor in certain parts of the world. In the past, all WTs were treated with surgery, but because of their slow growth rate, often minimal clinical symptoms, and the advanced age of many patients, active observation has gradually become more widely used. In order to decide on active surveillance, the diagnosis of WT must be reliable, and clinical, imaging, and cytological data should be concordant. There are four clear indications for upfront surgery: uncertain diagnosis; cosmetic problems; clinical complaints, such as pain, ulceration, or recurrent infection; and the patient's wish to have the tumor removed. In the remaining cases, surgery can be elective. Active surveillance is often suggested as the first approach, with surgery being considered if the tumor progresses and/or causes clinical complaints. The extent of surgery is another controversial topic, and the current trend is to minimize the resection using partial parotidectomies and extracapsular dissections when possible. Recently, non-surgical options such as microwave ablation, radiofrequency ablation, and ultrasound-guided ethanol sclerotherapy have been proposed for selected cases. CONCLUSIONS: The management of WT is gradually shifting from superficial or total parotidectomy to more conservative approaches, with more limited resections, and to active surveillance in an increasing number of patients. Additionally, non-surgical treatments are emerging, but their role needs

Human papilloma virus (HPV) is a well-established causative factor in a subset of squamous cell carcinomas of the head and neck (HNSCC). Although HPV can be detected in various anatomical subsites, HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) is the most common HPV-related malignancy of the head and neck, and its worldwide incidence is constantly rising. Patients with OPSCC are generally younger, have less co-morbidities and generally have better prognosis due to different biological mechanisms of carcinogenesis. These facts have generated hypotheses on potential treatment modifications, aiming to minimize treatment-related toxicities without compromising therapy efficacy. Numerous randomized clinical trials have been designed to verify this strategy and increasingly real-world evidence data from retrospective, observational studies is becoming available. Until now, the data do not support any modification in contemporary treatment protocols. In this narrative review, we outline recent data provided by both randomized controlled trials and real-world evidence of HPV-positive OPSCC in terms of clinical value. We critically analyze the potential value and drawbacks of the available data and highlight future research directions. This article was written by members and invitees of the International Head and Neck Scientific Group.(www.IHNSG.com).

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutr