Prevalence of dysphagia following posterior fossa tumor resection: a systematic review and meta­analysis.

OBJECTIVE: Dysphagia is common in individuals who have undergone posterior fossa tumor (PFT) resection and negatively impacts on the individual's quality of life, nutritional status, and overall health. We aimed to quantitatively synthesize data from studies of the prevalence of dysphagia following PFT resection. METHODS: PubMed, Web of Science, the Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang database, and VIP database were searched for case-control and cross-sectional studies that evaluated the prevalence of dysphagia after PFT surgery. Meta-analyses were performed to determine the prevalence of dysphagia. Subgroup and meta-regression analyses were performed to determine the sources of heterogeneity among the studies. RESULTS: A total of 22 studies were included, involving 20,921 cases. A meta-analysis of the random-effects model showed that the pooled global prevalence of dysphagia following PFT resection was 21.7% (95% confidence interval: 16.9-26.6). The subgroup and meta-regression analyses demonstrated that participant age (P < 0.001), assessment methods (P = 0.004), and geographical region of the study participants (P = 0.001) were sources of heterogeneity among the studies. CONCLUSIONS: Dysphagia has a high prevalence following PFT resection. Individuals with PFTs who are at a high risk for dysphagia should be identified early through screening. Multidisciplinary diagnosis and treatment of dysphagia are required to improve the outcomes in the early stages after PFT resection.

Risk factors of medical device-related pressure injury in intensive care units.

OBJECTIVES: Intensive care unit (ICU) patients are at high risk of medical device related pressure injury (MDRPI). This study aims to ascertain the MDRPI prevalence in ICU patients and analyse the risk factors of MDRPI. BACKGROUND: The occurrence of MDRPI not only increases hospitalisation time with pain and economic burden, but also causes medical disputes. A better understanding of this condition will increase knowledge and facilitate the ability to recognise and prevent MDRPI for clinical nursing staff. However, there are few multicentre studies of MDRPI prevalence in ICU patients in China. DESIGN: A cross-sectional study design was employed. METHODS: Data from 694 patients in 66 adult ICU at 30 hospitals in China were included between October 2018 and March 2019. The stage of each MDRPI was determined according to the definitions of National Pressure Ulcer Advisory Panel. The study methods were followed by the STORBE guidelines. RESULTS: The overall prevalence rate of MDRPI was 13.1% (91/694), with 98 anatomic locations in total. The most common stages of MDRPI were stage 1 (54.1%, 53/98), stage 2 (15.3%, 15/98) and mucosal membrane pressure injury (15.3%, 15/98). MDRPI mainly occurred in the finger (32.7%, 32/98), followed by nose (18.4%, 18/98). The prevalence rate of MDRPI caused by CPAP or BiPAP masks (25%) was highest. Lower Braden scores and having skin oedema were risk factors for MDRPI in adult ICU patients. CONCLUSION: The prevalence of MDRPI in this study was still high. Nurses should take these related factors into consideration when taking care of ICU patients, and appropriate prevention measures should be adopted to decrease the prevalence of MDRPI. RELEVANCE TO CLINICAL PRACTICE: The study can help to improve the PI prevention efforts in ICU patients specific to medical device related PI.

Risk factors for postoperative cerebrospinal fluid leakage after transsphenoidal surgery for pituitary adenoma: a meta-analysis and systematic review.

OBJECTIVE: Postoperative cerebrospinal fluid (CSF) leakage represents a challenge even for experienced pituitary surgeons. We aimed to quantitatively synthesize data from studies regarding the risk factors for postoperative CSF leakage after transsphenoidal surgery (TSS) for pituitary adenoma (PA). METHODS: PubMed, Web of Science, The Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang database, and VIP database were searched for case-control and cohort studies, focusing on the risk factors associated with postoperative CSF leakage after TSS for PA. Pooled odds ratios (ORs) and 95% confidence intervals were calculated to determine the risk factors. RESULTS: A total of 34 case-control and cohort studies involving a total of 9,144 patients with PA were included in this systematic review. The overall rate of postoperative CSF leakage after TSS for PA was 5.6%. Tumor size, adenoma consistency, revision surgery, and intraoperative CSF leakage were independent risk factors for postoperative CSF leakage (ORs, 3.18-6.33). By contrast, the endoscopic approach showed a slight protective benefit compared with the microscopic approach in TSS (OR, 0.69). CONCLUSIONS: This review provides a comprehensive overview of the quality of the evidence base, informing clinical staff of the importance of screening risk factors for postoperative CSF leakage after TSS for PA. More attention should be paid to PA patients at high risk for CSF leakage after TSS to reduce complications and improve prognosis.

Multidimensional fatigue in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy: incidence, severity, and risk factors.

PURPOSE: To explore the incidence, severity, and risk factors of multidimensional fatigue in patients with nasopharyngeal carcinoma (NPC) receiving concurrent chemoradiotherapy (CCRT). METHODS: This prospective study included 79 patients with NPC in Guangzhou (China) from June 2015 to July 2018. Data were collected before and after CCRT, including demographic and clinical characteristics, nutritional parameters, and fatigue scores, based on completion of the Multiple Dimensional Inventory-20 Questionnaire, with five subscales: General Fatigue, Mental Fatigue, Physical Fatigue, Reduced Activity, and Reduced Motivation. RESULTS: Increased general fatigue was found to be associated with lower lymphocyte count and body mass index <23 kg/m2. Increased physical fatigue was related to age > 42 years. Higher scores for reduced activity were associated with age > 42 years, female sex, and lower serum sodium. Increased mental fatigue was related with lower lymphocyte count and unemployment; and increased total fatigue was associated with lower lymphocyte count, age > 42 years, and 3-6 courses of treatment. Furthermore, 3-6 courses of treatment was an independent predictor of severe general fatigue, while age >42 years was an independent predictor of severe physical fatigue. Importantly, cancer stage IVB and 3-6 courses of treatment could predict severe total fatigue. CONCLUSIONS: Our data demonstrate that fatigue is increased in all dimensions in NPC patients following CCRT, and that the predictors differ for each fatigue dimension. These results could guide the development of targeted interventions that may reduce the impact of cancer-related fatigue in patients with NPC.

Construction of a comprehensive nutritional index and comparison of its prognostic performance with the PNI and NRI for survival in older patients with nasopharyngeal carcinoma: a retrospective study.

OBJECTIVES: To explore the relationship between the Comprehensive Nutritional Index (CNI) and survival in older patients with nasopharyngeal carcinoma (NPC) and to compare the prognostic performance of three nutritional indicators (CNI, Prognostic Nutritional Index (PNI), and Nutritional Risk Index (NRI)) for overall survival (OS). METHODS: This retrospective study involved 309 older NPC patients in Guangzhou (China) from November 2006 to November 2017. The CNI comprised five parameters: the body mass index (BMI), usual body weight percentage (UBW%), hemoglobin (Hb) level, albumin level, and total lymphocyte count (TLC). All single nutritional indicators were evaluated before and immediately after treatment. The principal component analysis (PCA) was used for calculation of the CNI by single nutritional indicators after treatment. The cutoff point for the CNI was evaluated and logistic regression used to explore the risk factors for the CNI. Univariable, multivariable Cox regression, and Kaplan-Meier methods were applied for OS and disease-free survival (DFS) analyses. Cox proportional hazards models were used to compare the prognostic value of the CNI, PNI, and NRI for OS. RESULTS: All single nutritional indicators decreased significantly after treatment (P < 0.05). The CNI cutoff point for mortality was 0.027, and the logistic regression indicated more complex treatments or higher cancer stage for NPC was associated with a low CNI (HR = 0.179; 95% CI: 0.037-0.856; 0.545, 0.367-0.811, respectively). In multivariable Cox regression, the CNI remained an independent prognostic factor of OS and DFS (HR = 0.468, 95% CI: 0.263-0.832; 0.527, 0.284-0.977, respectively). Kaplan-Meier curves showed that a low CNI was associated with worse OS and DFS (P = 0.001 and 0.013, respectively). The prognostic predictive performance of the CNI was superior to that of the PNI or NRI. CONCLUSIONS: The CNI can be recommended as an appropriate indicator reflecting the integrated nutritional status of older NPC patients. A low CNI predicted a poor survival outcome and the prognostic performance of CNI was superior to PNI or NRI.

Applications of Blockchain in the Medical Field: Narrative Review.

BACKGROUND: As a distributed technology, blockchain has attracted increasing attention from stakeholders in the medical industry. Although previous studies have analyzed blockchain applications from the perspectives of technology, business, or patient care, few studies have focused on actual use-case scenarios of blockchain in health care. In particular, the outbreak of COVID-19 has led to some new ideas for the application of blockchain in medical practice. OBJECTIVE: This paper aims to provide a systematic review of the current and projected uses of blockchain technology in health care, as well as directions for future research. In addition to the framework structure of blockchain and application scenarios, its integration with other emerging technologies in health care is discussed. METHODS: We searched databases such as PubMed, EMBASE, Scopus, IEEE, and Springer using a combination of terms related to blockchain and health care. Potentially relevant papers were then compared to determine their relevance and reviewed independently for inclusion. Through a literature review, we summarize the key medical scenarios using blockchain technology. RESULTS: We found a total of 1647 relevant studies, 60 of which were unique studies that were included in this review. These studies report a variety of uses for blockchain and their emphasis differs. According to the different technical characteristics and application scenarios of blockchain, we summarize some medical scenarios closely related to blockchain from the perspective of technical classification. Moreover, potential challenges are mentioned, including the confidentiality of privacy, the efficiency of the system, security issues, and regulatory policy. CONCLUSIONS: Blockchain technology can improve health care services in a decentralized, tamper-proof, transparent, and secure manner. With the development of this technology and its integration with other emerging technologies, blockchain has the potential to offer long-term benefits. Not only can it be a mechanism to secure electronic health records, but blockchain also provides a powerful tool that can empower users to control their own health data, enabling a foolproof health data history and establishing medical responsibility.

Deep learning-based algorithm improves radiologists' performance in lung cancer bone metastases detection on computed tomography.

Purpose: To develop and assess a deep convolutional neural network (DCNN) model for the automatic detection of bone metastases from lung cancer on computed tomography (CT). Methods: In this retrospective study, CT scans acquired from a single institution from June 2012 to May 2022 were included. In total, 126 patients were assigned to a training cohort (n = 76), a validation cohort (n = 12), and a testing cohort (n = 38). We trained and developed a DCNN model based on positive scans with bone metastases and negative scans without bone metastases to detect and segment the bone metastases of lung cancer on CT. We evaluated the clinical efficacy of the DCNN model in an observer study with five board-certified radiologists and three junior radiologists. The receiver operator characteristic curve was used to assess the sensitivity and false positives of the detection performance; the intersection-over-union and dice coefficient were used to evaluate the segmentation performance of predicted lung cancer bone metastases. Results: The DCNN model achieved a detection sensitivity of 0.894, with 5.24 average false positives per case, and a segmentation dice coefficient of 0.856 in the testing cohort. Through the radiologists-DCNN model collaboration, the detection accuracy of the three junior radiologists improved from 0.617 to 0.879 and the sensitivity from 0.680 to 0.902. Furthermore, the mean interpretation time per case of the junior radiologists was reduced by 228 s (p = 0.045). Conclusions: The proposed DCNN model for automatic lung cancer bone metastases detection can improve diagnostic efficiency and reduce the diagnosis time and workload of junior radiologists.

Mixed reality assists the fight against COVID-19.

Coronavirus disease 2019 (COVID-19) made a huge effect globally. With the assistance of mixed reality (MR) technology, complicated clinical works became easier to carry out and the condition had been greatly improved with high-tech advantages such as improved convenience, better understanding and communication, higher security, and medical resource saving. This study aimed to introduce one kind of MR application in the fight against COVID-19 and anticipate more feasible smart healthcare applications to enhance our strength for the final victory.

Application and Development of Intelligent Medicine in Traditional Chinese Medicine.

As modern science and technology constantly progresses, the fields of artificial intelligence, mixed reality technology, remote technology, etc. have rapidly developed. Meanwhile, these technologies have been gradually applied to the medical field, leading to the development of intelligent medicine. What's more, intelligent medicine has greatly promoted the development of traditional Chinese medicine (TCM), causing huge changes in the diagnosis of TCM ailments, remote treatment, teaching, etc. Therefore, there are both opportunities and challenges for inheriting and developing TCM. Herein, the related research progress of intelligent medicine in the TCM in China and abroad over the years is analyzed, with the purpose of introducing the present application status of intelligent medicine in TCM and providing reference for the inheritance and development of TCM in a new era.

Artificial Intelligence to Diagnose Tibial Plateau Fractures: An Intelligent Assistant for Orthopedic Physicians.

OBJECTIVE: To explore a new artificial intelligence (AI)-aided method to assist the clinical diagnosis of tibial plateau fractures (TPFs) and further measure its validity and feasibility. METHODS: A total of 542 X-rays of TPFs were collected as a reference database. An AI algorithm (RetinaNet) was trained to analyze and detect TPF on the X-rays. The ability of the AI algorithm was determined by indexes such as detection accuracy and time taken for analysis. The algorithm performance was also compared with orthopedic physicians. RESULTS: The AI algorithm showed a detection accuracy of 0.91 for the identification of TPF, which was similar to the performance of orthopedic physicians (0.92±0.03). The average time spent for analysis of the AI was 0.56 s, which was 16 times faster than human performance (8.44±3.26 s). CONCLUSION: The AI algorithm is a valid and efficient method for the clinical diagnosis of TPF. It can be a useful assistant for orthopedic physicians, which largely promotes clinical workflow and further guarantees the health and security of patients.

Application of Virtual Reality Technology in Disaster Medicine.

The occurrence of major emergencies often leads to environmental damage, property damage, health challenges and life threats. Despite the tremendous progress we have made in responding to the many challenges posed by disasters in recent years, there are still many shortcomings. As an emerging technology widely used in recent years, virtual reality (VR) technology is very suitable for many fields of disaster medicine, such as basic education, professional training, psychotherapy, etc. The purpose of this review article is to introduce the application of VR technology in the disaster medical field and prospect its trend in the future.