Decline in hospitalization for childhood asthma in different air pollution regions in Taiwan, 2001-2012.

This study aimed to investigate the trends in childhood asthma hospitalization in regions with differing levels of air pollution in Taiwan, 2001-2012. Joinpoint regression was used to identify significant trend changes. The hospitalization rate varied according to gender, geographic region, and age. The incidence of childhood asthma hospitalization decreased from 127.99 to 76.67 (/100,000 population), with an average annual percentage change of around -4.1%; in the Yilan region, the average air pollution concentrations were 19.92 µg/m3, 39.47 µg/m3, 25.99 ppb, 2.19 ppb, and 11.23 ppb for PM2.5, PM10, O3, SO2, and NO2, respectively, which were lower than Taiwan's average values; however, the childhood asthma hospitalization rate was the highest (179.75/100,000 population). The national trend in childhood asthma hospitalization exhibited a significant decrease. The effects of air pollution on childhood asthma were greater in the higher-level air pollution regions, while less association was observed in the lower-level air pollution regions.

Deep learning approaches for sleep disorder prediction in an asthma cohort.

OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore, sleep disturbance may lead to fatigue and lower productivity. This study examined 1 million samples included in the Taiwan National Health Insurance Research Database (NHIRD) in order to predict sleep disorder in an asthma cohort from 2002-2010. METHODS: The disease histories of the asthma patients were transferred to sequences and matrices for the prediction of sleep disorder by applying machine learning (ML) algorithms, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest (RF), and deep learning (DL) models, including Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and Convolution Neural Network (CNN). RESULTS: Among 14,818 new asthma subjects in 2002, there were 4469 sleep disorder subjects from 2002 to 2010. The KNN, SVM, and RF algorithms were demonstrated to be successful sleep disorder prediction models, with accuracies of 0.798, 0.793, and 0.813, respectively (AUC: 0.737, 0.690, and 0.719, respectively). The results of the DL models showed the accuracies of the RNN, LSTM, GRU, and CNN to be 0.744, 0.815, 0.782, and 0.951, respectively (AUC: 0.658, 0.750, 0.732, and 0.934, respectively). CONCLUSIONS: The results showed that the CNN model had the best performance for sleep disorder prediction in the asthma cohort.

A survey of ambulatory-treated asthma and correlation with weather and air pollution conditions within Taiwan during 2001-2010.

Objective: This study of asthma was performed to evaluate annual trends in emergency department (ED) for 10 years. Weather and air pollution factors affecting asthma were also studied in order to identify the important factors and alert the public in advance. Methods: A survey of ambulatory-treated asthma patients was performed and the correlations with weather and air pollution factors examined in a cohort of one million patients in 2010. The fixed-cohort study analyzed trends, medical costs, and annual prevalence grouped by age and gender. Results: The number of asthma patients visiting EDs and non-emergency (non-ED) clinics significantly increased, with average annual percentage changes (AAPCs) of 2.3 and 4.6%, respectively. The average direct medical cost for EDs was increased significantly as compared with that of non-ED visits. Classification of asthma visits by hospital level indicated that local hospitals and others exhibited a significantly increasing trend (AAPC =15.3% [95% CI: 14.3-16.2]). The annual prevalence of asthma in males, females, and children was significantly increased (AAPCs of 1.5, 1.8, and 3.9%, respectively). Asthma patient hospitalizations were significantly correlated with temperature, humidity, and air pollution factors. Conclusions: The number of non-ED visits due to asthma increased, and the average direct medical cost for ED admissions also increased. Asthma patients tended to visit local hospitals primarily. Asthma visits by children increased, but a decrease was observed in adults. The number of hospitalized asthma patients was negatively correlated with temperature and humidity but positively correlated with the levels of PM2.5, PM10, and NO2.

The Short-Term Effects of Ambient Air Pollutants on Childhood Asthma Hospitalization in Taiwan: A National Study.

This investigation determined the effects of air pollution on childhood asthma hospitalization in regions with differing air pollution levels in Taiwan over a long time period. Data of childhood hospital admissions for asthma in patients aged 0⁻18 years and air quality in eight regions for the period 2001⁻2012 in Taiwan were collected. Poisson generalized linear regression analysis was employed to identify the relative risks of hospitalization due to asthma in children associated with exposure to varying levels of air pollutants with a change in the interquartile range after adjusting for temperature and relative humidity. Particulate matter ≤2.5 µm (PM2.5), particulate matter ≤10 µm (PM10), ozone (O3), sulfur dioxide (SO2), and nitrogen dioxide (NO2), were positively associated with childhood asthma hospitalization, while O3 was negatively associated with childhood asthma hospitalization. SO2 was identified as the most significant risk factor. The relative risks for asthma hospitalization associated with air pollutants were higher among children aged 0⁻5 years than aged 6⁻18 years and were higher among males than females. The effects of air pollution on childhood asthma were greater in the higher-level air pollution regions, while no association was observed in the lower-level air pollution regions. These findings may prove important for policymakers involved in implementing policies to reduce air pollution.

Comparison of Models for the Prediction of Medical Costs of Spinal Fusion in Taiwan Diagnosis-Related Groups by Machine Learning Algorithms.

OBJECTIVES: The aims of this study were to compare the performance of machine learning methods for the prediction of the medical costs associated with spinal fusion in terms of profit or loss in Taiwan Diagnosis-Related Groups (Tw-DRGs) and to apply these methods to explore the important factors associated with the medical costs of spinal fusion. METHODS: A data set was obtained from a regional hospital in Taoyuan city in Taiwan, which contained data from 2010 to 2013 on patients of Tw-DRG49702 (posterior and other spinal fusion without complications or comorbidities). Naïve-Bayesian, support vector machines, logistic regression, C4.5 decision tree, and random forest methods were employed for prediction using WEKA 3.8.1. RESULTS: Five hundred thirty-two cases were categorized as belonging to the Tw-DRG49702 group. The mean medical cost was US $4,549.7, and the mean age of the patients was 62.4 years. The mean length of stay was 9.3 days. The length of stay was an important variable in terms of determining medical costs for patients undergoing spinal fusion. The random forest method had the best predictive performance in comparison to the other methods, achieving an accuracy of 84.30%, a sensitivity of 71.4%, a specificity of 92.2%, and an AUC of 0.904. CONCLUSIONS: Our study demonstrated that the random forest model can be employed to predict the medical costs of Tw-DRG49702, and could inform hospital strategy in terms of increasing the financial management efficiency of this operation.

Application of a Time-Stratified Case-Crossover Design to Explore the Effects of Air Pollution and Season on Childhood Asthma Hospitalization in Cities of Differing Urban Patterns: Big Data Analytics of Government Open Data.

Few studies have assessed the lagged effects of levels of different urban city air pollutants and seasons on asthma hospitalization in children. This study used big data analysis to explore the effects of daily changes in air pollution and season on childhood asthma hospitalization from 2001 to 2010 in Taipei and Kaohsiung City, Taiwan. A time-stratified case-crossover study and conditional logistic regression analysis were employed to identify associations between the risk of hospitalization due to asthma in children and the levels of air pollutants (PM2.5, PM10, O3, SO2, and NO2) in the days preceding hospitalization. During the study period, 2900 children in Taipei and 1337 in Kaohsiung aged ≤15 years were hospitalized due to asthma for the first time. The results indicated that the levels of air pollutants were significantly associated with the risk of asthma hospitalization in children, and seasonal effects were observed. High levels of air pollution in Kaohsiung had greater effects than in Taipei after adjusting for seasonal variation. The most important factor was O3 in spring in Taipei. In children aged 0-6 years, asthma was associated with O3 in Taipei and SO2 in Kaohsiung, after controlling for the daily mean temperature and relative humidity.

Usefulness of brilliant cresyl blue staining as an auxiliary method of screening for alpha-thalassemia.

Hemoglobin (Hb) electrophoresis is widely used in thalassemia screening. Most Hb variants express a specific abnormal band on the cellulose acetate membrane. The technique is useful in the diagnosis of the type of thalassemia but is not sensitive enough to detect alpha-thalassemia minor because the quantity of the HbH is too small to be expressed on the supporting medium. We used simple staining of blood smears rather than the sophisticated molecular method to detect HbH inclusions. To evaluate the effectiveness of this method, we used brilliant cresyl blue (BCB) staining of red blood cells in 509 patients with microcytosis and erythrocytosis caused by various conditions. The results indicate that BCB staining is useful in the identification of subjects who possess alpha-thalassemia traits. Coexisting conditions such as beta-thalassemia and iron-deficiency anemia did not affect the detection of the HbH inclusions with the use of BCB staining. We conclude that BCB staining is helpful and reliable as an auxiliary method of detecting HbH inclusions in the diagnosis of alpha-thalassemia traits, especially in places where medical resources are limited.