A case of neoadjuvant chemotherapy in pregnancy with cervical cancer (IB3).

Compared with the early symptoms of non-pregnancy, the early pregnancy with cervical cancer is often confused with threatened abortion, so it is difficult to diagnose and delay the time of treatment. At present, compared with cervical cancer, there is no clear and standard treatment for cervical cancer in pregnancy. At present, the diagnosis and treatment plan is mainly made according to the pathological examination, staging, fetal development (whether there is abnormality on ultrasound and whether the chromosome karyotype is normal or not) and the pregnant women and their family members' pregnancy wishes. A case of pregnancy complicated with cervical cancer who was terminated by planned cesarean section after neoadjuvant chemotherapy (NACT) with irregular vaginal bleeding as the first symptom was analyzed retrospectively.

A Scoping Review of Tools and Techniques on Evaluating Population Health and Healthy Life Expectancy.

The concept of healthy life expectancy (HLE) integrates the ideas of life expectancy and health status, providing a valuable metric to evaluate both the length and quality of life. This paper seeks to aid policymakers in creating an inclusive HLE indicator system through a systematic review of methodologies for defining and measuring HLE, along with relevant published studies' descriptions. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews statement, two English language literature databases were researched from January 2020 to April 2023. Findings from empirical HLE-related studies were analyzed by extracting data on the study area, design, population, healthy state measurement tools, and results of studies using HLE indicators. The current analysis encompassed 48 empirical studies. Researchers discerned 11 unique HLE indicators within this corpus, each concentrating on a particular aspect. Furthermore, the analysis revealed 18 diverse instruments for evaluating health statuses, each varying in its definition of a healthy state, dimensions of measurement, and the categories of data employed. Therefore, merging global health concepts, HLE indicators, methodologies for assessing healthy states, and applied research demonstrations are essential for a consolidated HLE indicator system creation.

Development and Evaluation of the Quality of Life Scale for Children With Visual Impairments in China.

Background: Visual impairments related to non-correctable vision loss, including blindness and low vision, have been consistently shown to lower a person's health-related quality of life. This study assessed the reliability, validity, and discrimination of the Quality of Life Scale for Children with Visual Impairments (QOLS-CVI) in China. Methods: The Pediatric Quality of Life Inventory™ 4.0 and World Health Organization Quality of Life-Disability Scale for physical disability were selected to define conceptual frameworks and item libraries based on relevant existing studies. According to two rounds of expert consultations and group discussions, some items were modified, and the draft scale was developed. Two item selection processes based on classical test theory and item response theory were used to conduct a preliminary survey and a formal survey in special schools in Shanxi and Hebei Provinces. Finally, the reliability and validity of the quality of life scale for visually impaired children in China were verified. Results: The final QOLS-CVI consisted of 38 items, 10 subdomains, and 6 domains. Reliability was verified by Cronbach's alpha coefficient, split-half reliability, and test-retest reliability (Cronbach's alpha for the full scale, 0.841; split-half reliability, 0.629; and test-retest reliability, 0.888). The validity results showed that the multidimensional scale met expectations: exploratory factor analysis and confirmatory factor analysis indicated good fitting models for children with visual impairments. Conclusions: The QOLS-CVI was determined to be reliable and valid and to have strong feasibility and effectiveness. This scale can be used as an evaluation tool to study the QOL and social-participation ability of children with visual impairments.

Compliance with COVID-19-preventive behaviours among employees returning to work in the post-epidemic period.

BACKGROUND: The COVID-19 pandemic has underscored the importance of behaviours such as social distancing in controlling pandemics. Currently, the epidemic is under control in China and production has resumed in various industries. This study investigates the behavioural compliance and related factors for COVID-19 prevention among employees returning to the workplace and provide strategic recommendations for improving individual-level preventive behaviour to prevent a new outbreak. METHODS: A cross-sectional study design was used. Data were gathered from returning employees in China using an online questionnaire survey, from March to May, 2020. The questionnaire covered participants' COVID-19-related knowledge, compliance with recommended preventive behaviours, and levels of depression and anxiety. Univariate and multi-factor methods were used to analyse the data and identify factors influencing behaviour compliance. RESULTS: Of the 1300 participants completing the full survey, more than half were male (71.92%) and 61% were aged between 31 and 50 years. Six hundred and ninety-eight (53.7%) participants showed high compliance, while 602 (46.3%) showed low compliance. In models adjusted for demographic and socio-economic factors, high education level (odds ratio [OR] = 0.23, 95% confidence interval [CI]: 0.07-0.70), office staff (OR = 0.51, 95% CI: 0.33-0.78), higher knowledge of COVID-19 (OR = 0.74, 95% CI: 0.67-0.81), and quarantining (OR = 0.74, 95% CI: 0.57-0.96) predicted better compliance with preventive behaviours (P <  0.05), while high anxiety levels (OR = 1.55, 95% CI: 1.10-2.18) predicted lower compliance with preventive behaviours (P <  0.05). CONCLUSION: For employees returning to work during the post-COVID-19-epidemic period, compliance with recommended preventive behaviours requires improvement. Consequently, comprehensive intervention measures, including the provision of health education and psychological counselling, as well as the continuance of a strict isolation policy, could enhance such compliance.

Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China.

BACKGROUND: This study intends to identify the best model for predicting the incidence of hand, foot and mouth disease (HFMD) in Ningbo by comparing Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory Neural Network (LSTM) models combined and uncombined with exogenous meteorological variables. METHODS: The data of daily HFMD incidence in Ningbo from January 2014 to November 2017 were set as the training set, and the data of December 2017 were set as the test set. ARIMA and LSTM models combined and uncombined with exogenous meteorological variables were adopted to fit the daily incidence of HFMD by using the data of the training set. The forecasting performances of the four fitted models were verified by using the data of the test set. Root mean square error (RMSE) was selected as the main measure to evaluate the performance of the models. RESULTS: The RMSE for multivariate LSTM, univariate LSTM, ARIMA and ARIMAX (Autoregressive Integrated Moving Average Model with Exogenous Input Variables) was 10.78, 11.20, 12.43 and 14.73, respectively. The LSTM model with exogenous meteorological variables has the best performance among the four models and meteorological variables can increase the prediction accuracy of LSTM model. For the ARIMA model, exogenous meteorological variables did not increase the prediction accuracy but became the interference factor of the model. CONCLUSIONS: Multivariate LSTM is the best among the four models to fit the daily incidence of HFMD in Ningbo. It can provide a scientific method to build the HFMD early warning system and the methodology can also be applied to other communicable diseases.

An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens.

It is very important to have a comprehensive understanding of the health status of a country's population, which helps to develop corresponding public health policies. Correct inference of the underlying cause-of-death for citizens is essential to achieve a comprehensive understanding of the health status of a country's population. Traditionally, this relies mainly on manual methods based on medical staff's experiences, which require a lot of resources and is not very efficient. In this work, we present our efforts to construct an automatic method to perform inferences of the underlying causes-of-death for citizens. A sink algorithm is introduced, which could perform automatic inference of the underlying cause-of-death for citizens. The results show that our sink algorithm could generate a reasonable output and outperforms other stat-of-the-art algorithms. We believe it would be very useful to greatly enhance the efficiency of correct inferences of the underlying causes-of-death for citizens.