Objective To analyze the relationship between the body mass index(BMI)and anal fistula occurrence based on the results of cross-sectional survey.Methods The clinical data of 545 patients with a-nal fistula visiting in the proctology department of this hospital from March 2022 to November 2023 were ana-lyzed.The patients were divided into 4 groups based on BMI:skinny group(BMI＜18.5 kg/m2),normal group(BMI 18.5-＜24.0 kg/m2),overweight group(BMI 24.0-＜28.0 kg/m2)and obese group(BMI ≥28.0 kg/m2).The logistic regression was used to analyze the influencing factors of fistula occurrence.The dose-response relationship between BMI and the occurrence risk of anal fistula was analyzed by combining with the restricted cubic spline(RCS)model.Results The logistic regression analysis results showed that obese was the risk factor of anal fistula occurrence(OR=2.08,95％CI:1.08-3.99,P=0.028).The combining RCS a-nalysis results showed that there was a"J"shaped trend between the BMI and the risk of anal fistula.In addi-tion,smoking could increase the risk of anal fistula occurrence in obese population.Conclusion Overweight and obesity are the risk factors for anal fistula occurrence.It is suggested that the susceptible population should control their body weight reasonably to prevent the occurrence of anal fistula.

Objective:To explore the mediating role of disease progression′s fear and positive affect in the relationship between disease perception and demoralization in patients with chronic heart failure. It provided a theoretical basis for targeted interventions for healthcare workers.Methods:From October 2022 to March 2023, 320 patients with chronic heart failure in the First Affiliated Hospital of Zhengzhou University were selected as the research objects by convenience sampling. The General Information Questionnaire, Demoralization Scale Redacted Mandarin Version, Brief Illness Perception Questionnaire, Fear of Progression Questionnaire-Short Form, Positive and Negative Affect Schedule (Positive Affect Schedule) were used to conduct the questionnaire survey exploring the mediating effects of fear of disease progression and positive emotions between disease perception and disorientation by construction structural equation model.Results:There were 268 valid questionnaires. Of the 268 patients, 168 were male and 100 were female, 3.36% (9/268) were ≤40 years old, 55.22% (148/268) were 41-65 years old, and 41.42% (111/268) were >65 years old. Correlation analysis showed that disease perception was positively correlated with disease progression ′s fear, and every dimension of demoralization ( r values were 0.300-0.586, all P<0.01), and negatively correlated with positive affect ( r=-0.374, P<0.01); disease progression′s fear was negatively correlated with positive affect ( r=-0.318, P<0.01), and positively correlated with every dimension of demoralization ( r values were 0.339-0.464, all P<0.01); positive affect was negatively correlated with every dimension of demoralization ( r values were -0.430--0.334, all P<0.01). Structural equation model analysis showed that the direct effect of disease perception on demoralization was significant ( β=0.407, P<0.01), and both mediating effects of disease progression ′s fear and positive affect between disease perception and demoralization in patients with chronic heart failure were significant ( β=0.074, 0.079, both P<0.01). The chain mediating effect of disease progression ′s fear and positive effect was also significant ( β=0.019, P<0.01). Conclusions:Disease perception could directly predict the demoralization of patients with chronic heart failure and indirectly predict the demoralization of patients with chronic heart failure through the mediating effect of disease progression ′s fear, positive affect, and the chain mediating effect of disease progression ′s fear and positive affect.

The rapid development of artificial intelligence in the field of healthcare has greatly improved diagnosis accuracy, disease prediction, personalized treatment and healthcare resource management. However, with the widespread application of medical artificial intelligence, challenges has emerged in the aspects of medical data, model development and evaluation, and societal considerations. Therefore, this study aims to explore challenges in the application of artificial intelligence in healthcare and suggest a series of feasible solutions to improve medical professional and researchers' understanding of medical artificial intelligence and enhance the quality of healthcare in clinical practice

Objective:To analyze the research hotspots and trends of swallowing disorders in patients with head and neck tumors both domestically and internationally, to provide reference for future research directions.Methods:Using the China National Knowledge Infrastructure and Web of Science core collection databases as data sources, research literature related to swallowing disorders in head and neck tumor patients published from January 1, 2013, to December 31, 2022, was retrieved. A knowledge graph was drawn using Cite Space 6.2 R3 software, and the graph was interpreted and analyzed from the aspects of publication volume, publication country, and institution, high-frequency keyword co-occurrence and clustering, and emergent words.Results:A total of 427 English literature were included. The overall number of publications is on the rise. The countries with a high volume of collaborative publications were the United States, Australia, the Netherlands, and the United Kingdom. The top three institutions in terms of publication volume were the University of Queensland in Australia, the University of Newcastle in the UK, and the Amsterdam Institute in the Netherlands. A total of 10 cluster clusters and 25 prominent keywords were obtained. The hot topics of research and analysis were "swallowing dysfunction" "associated complications" and "long-term effects", with the forefront being "radiation-induced dry mouth syndrome".Conclusions:Compared to foreign countries, China currently has a relatively small number of publications, loose cooperation between research authors and institutions, and a need for more diverse disciplines and research methods. Focusing on hot topics and cutting-edge content, exploring the mechanism of swallowing disorders in head and neck tumors, implementing targeted interventions, strengthening health education, predicting postoperative dangerous complications, constructing feasible nursing plans, and improving the quality of life of patients will become the development trend of future research.

Body temperature is an essential physiological parameter. Conducting non-contact, fast and accurate measurement of temperature is increasing important under the background of COVID-19. The study introduces an infrared temperature measurement system based on the thermopile infrared temperature sensor ZTP-135SR. Extracting original temperature date of sensor, post-amplification and filter processing have been performed to ensure accuracy of the system. In addition, the temperature data of environmental compensation which obtained by polynomial fitting is added to the system to further improve measurement accuracy.
Algorithms ; Body Temperature ; COVID-19 ; Humans ; Temperature ; Thermometers

Fetal ECG monitoring is a routine clinical detection method that can reflect the changes of fetal heart in utero in real time. At present, most of the clinical fetal heart rate detection adopts the ultrasonic Doppler method, which is technically difficult and highly specialized in operation and expensive. This study introduces a fetal ECG detection system based on the maternal abdominal electrode method. The weak fetal ECG changes are sensed through the maternal abdominal electrode, and the mixed ECG signal is obtained through the corresponding amplification and filtering circuit. Finally, the obtained signal is passed through WiFi, transmitted to the host computer. The host computer uses the adaptive filtering algorithm to estimate the fetal ECG signal. The system has strong feasibility, low operation expertise, low cost, and is more convenient.

Body temperature is an important physiological parameter of the human body and is used in medicine to reflect the physiological state and health status of the human body. At present, the commonly used clinical thermometers on the market are mainly divided into contact and non-contact types. Most of them are used for rapid body temperature measurement, and it is not easy to monitor body temperature changes in real time. This article introduces a new wearable wireless body temperature monitoring system based on NTC, which senses through NTC. The temperature changes are amplified and filtered, zeroed, and calibrated, and then the temperature data is uploaded to the mobile phone APP via Bluetooth in real time to achieve real-time accurate measurement of body temperature.
Body Temperature ; Cell Phone ; Humans ; Monitoring, Physiologic ; Temperature ; Wearable Electronic Devices ; Wireless Technology

ECG signals and sleep monitoring parameters complement each other and can be used for qualitative diagnosis of sleep apnea syndrome and cardio-related diseases.However,due to the limitations of the instrument volume and the detection environment,it is often challenging to integrate these two functions in practical applications.In this paper,a 12-lead dynamic electrocardiograph integrated with sleep monitoring is designed.The system's volume is reduced by combining the integrated ECG simulation front end with a miniature sensor.The system achieves the extraction,conditioning,and calculation of 12-lead ECG signals and sleep-related parameters and writes the data to a memory card in real time,which offers convenience for users and doctors in the diagnostic process.

BACKGROUNDEpstein-Barr virus (EBV) infection is one of the most important factors of nasopharyngeal carcinoma (NPC) endemic areas. Transcription of EBV-encoded non-polyadenylated RNAs (EBERs) are presented in most of NPC tumors. Exploring EBERs as a prognostic marker for NPC might further be informative about the biology and the progression of the disease. The aim of this study was to analyze the role of EBV latency in the clinical management of nasopharyngeal carcinoma (NPC), by detecting EBERs.

METHODSRNA in situ hybridization (ISH) for detecting EBERs was carried out on 908 NPC tumor tissues. Overall survival (OS) curves were analyzed with the Kaplan-Meier method and the Cox proportional-hazards regression models.

RESULTSThe median follow-up time was 70 months (1-120 months). Eight hundred and sixteen (89.9%) from a total of 908 consecutive NPC cases were found to be EBV-EBER positive. EBER-ISH staining revealed nuclear localization in NPC cells. In the Kaplan-Meier analysis for OS, high EBER expression levels in NPC patients were statistically significant positive prognostic factors for survival (log-rank, P = 0.022), especially in adults aged 17-40 years (P = 0.023) and in those with advanced stage disease (log-rank, P = 0.002). Cox proportional-hazards regression model analysis showed that the EBER expression level was an independent risk factor for OS (hazard ratio 0.724, P = 0.005).

CONCLUSIONSEBERs were frequently detected in NPC tumor tissues, and high-level EBER expression correlated with good prognosis in NPC patients, especially in adult patients and in those with advanced stage disease. EBER may serve as a potential prognostic predictor in NPC.

Adolescent ; Adult ; Aged ; Carcinoma ; Epstein-Barr Virus Infections ; virology ; Female ; Herpesvirus 4, Human ; genetics ; pathogenicity ; Humans ; In Situ Hybridization ; Male ; Middle Aged ; Nasopharyngeal Neoplasms ; mortality ; virology ; RNA, Viral ; genetics ; Young Adult

This study introduces a portable multi-channel EEG signal acquisition system. The system is mainly composed of EEG electrode connector, signal conditioning circuit, EEG acquisition part, main control MCU and power supply part. The low-power EEG acquisition front-end ADS1299 and STM32 are used to form the signal acquisition and data communication part. The collected EEG signal can be transmitted to the PC for real-time display. After relevant tests, the system has small volume, low power consumption, high signal-to-noise ratio, and meets the requirements of portable wearable medical devices.
Electric Power Supplies ; Electrodes ; Electroencephalography ; Signal Processing, Computer-Assisted ; Signal-To-Noise Ratio