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Purpose: The purpose of this study was to develop a scale that can measure the concerns of cancer patients undergoing outpatient radiation therapy. Method: First, items were created based on a review of the literature, and a draft scale was created by examining content validity using the Item-level Content Validity Index (I-CVI). In the main study, researcher conducted an anonymous, self-administered questionnaire survey on 400 cancer patients undergoing outpatient radiation therapy at five institutions, and examined the reliability and validity of the scale. Result: Exploratory factor analysis identified nine items with two factors (concern about living with cancer and concern about living with irradiation). The Cronbach's alpha coefficient for the entire scale was 0.848. The goodness of fit in confirmatory factor analysis showed GFI=0.930, AGFI=0.879, CFI=0.926 and SRMR=0.058. No correlation was observed with STAI Y-1, and a certain level of discriminant validity was confirmed. Conclusion: We generally confirmed the reliability and validity results of a concern scale for cancer patients receiving outpatient radiotherapy.
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Background Air quality health index (AQHI) is derived from exposure-response coefficients calculated from air pollution and morbidity/mortality time series, which helps to understand the overall short-term health impacts of air pollution. Objective To study the effects of common air pollutants on respiratory diseases in Urumqi and to develop an AQHI for the risk of respiratory diseases in the city. Methods The daily outpatient volume data of respiratory diseases from The First Affiliated Hospital of Xinjiang Medical University, meteorological data (daily mean temperature and daily mean relative humidity), and air pollutants [fine particulate matter (PM2.5), inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO), and ozone (O3)] in Urumqi City, Xinjiang, China were collected from January 1, 2017 to December 31, 2021. A distributed lag nonlinear model based on quasi-Poisson distribution was constructed by time-stratified case crossover design. Adopting zero concentration of air pollutants as reference, the exposure-response coefficient (β value) was used to quantify the impact of included air pollutants on the risk of seeking medical treatment for respiratory diseases, and the AQHI was established. The association of between AQHI and the incidence of respiratory diseases and between air quality index (AQI) and the incidence of respiratory diseases was compared to evaluate the prediction effect of AQHI. Results Each 10 µg·m−3 increase in PM10, SO2, NO2, and O3 concentrations presented the highest excess risk of seeking outpatient services at 3 d cumulative lag (Lag03) and 2d cumulative lag (Lag02), with increased risks of morbidity of 0.687% (95%CI: 0.101%, 1.276%), 17.609% (95%CI: 3.253%, 33.961%), 13.344% (95%CI: 8.619%, 18.275%), and 4.921% (95%CI: 1.401%, 8.502%), respectively. There was no statistically significant PM2.5 or CO lag effect. An AQHI was constructed based on a model containing PM10, SO2, NO2, and O3, and the results showed that the excess risk of respiratory disease consultation for the whole population, different genders, ages, or seasons for each inter-quartile range increase in the AQHI was higher than the corresponding value of AQI. Conclusion PM10, SO2, NO2, and O3 impact the number of outpatient visits for respiratory diseases in Urumqi, and the constructed AQHI for the risk of respiratory diseases in Urumqi outperforms the AQI in predicting the effect of air pollution on respiratory health.
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Background Nitrogen dioxide (NO2), a crucial component of traffic pollutants, has been shown in studies to exert toxic effects on the nervous system. However, there is a limited body of research examining the relationship between NO2 exposure and neurological disorders in children. Objective To explore the impact of short-term NO2 exposure on the outpatient visits due to pediatric neurological diseases in Shijiazhuang. Methods From 2013 to 2021, we collected outpatient data related to neurological diseases at the Children's Hospital in Shijiazhuang, Hebei Province. We also collected air pollution data and meteorological data of the same city. The air pollution data included daily average concentrations of inhalable particles (PM10), fine particulate matter (PM2.5), sulfur dioxide (SO2), NO2, carbon monoxide (CO), and daily maximum 8-hour average concentration of ozone (O3). The meteorological data comprised daily average atmospheric pressure, temperature, relative humidity, wind speed, and sunshine duration. Employing a time-stratified case-crossover design, we used conditional logistic regression models to analyze the association between NO2 and pediatric outpatient visits for neurological diseases. Stratification analyses were conducted based on gender (male, female) and age groups (0-6 years, 7-14 years). Results The study included a total of 154348 valid pediatric outpatient visits for neurological diseases. The daily average concentration of NO2 was 49.3 μg·m−3 for the study period. The results from the single-pollutant model indicated that NO2 increased the risk of pediatric neurological outpatient visits, with the highest association observed at lag0. Specifically, for every 10 μg·m⁻³ increase in atmospheric NO2 exposure, there was a 1.40% increase (95%CI: 1.05%, 1.74%) in pediatric neurological outpatient visits. The stratification analyses revealed that increased atmospheric NO2 exposure was associated with an elevated risk of neurological outpatient visits for girls (ER=1.54, 95%CI: 1.01, 2.08) and children aged 7-14 years (ER=2.35, 95%CI: 1.68, 3.02). Even after introducing PM2.5 (ER=1.96, 95%CI: 1.49, 2.43), SO2 (ER=2.09, 95%CI: 1.62, 2.55), and O3 (ER=1.40, 95%CI: 1.06, 1.74) to the models, the impact of NO2 exposure on pediatric neurological outpatient visits remained statistically significant. The results of the multi-pollutant model also indicated a significant association (ER=2.53, 95%CI: 1.97, 3.08). Conclusion The effect of short-term exposure to atmospheric NO2 on the outpatient visits of children with neurological diseases in Shijiazhuang is acute and independent, especially for children aged 7-14.
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ObjectiveTo explore the association between air pollutants and hospital outpatient visits in a district of Shanghai. MethodsDaily meteorological data， environmental data， data of outpatient visits to two secondary hospitals and two tertiary hospitals in this district from January 1， 2015 to December 31， 2019 were collected. A Poisson regression generalized linear model was used to analyze the exposure-response relationship between the air pollutants and hospital outpatient visits in this area. ResultsDuring the study period， the total number of outpatient visits in the included hospitals was 17 802 634， with an average daily total of （9 750±4 191） outpatient visits，and an average daily of （761±341） respiratory outpatient visits. In the lag effect of single pollutant model， when the concentration of air pollutant increased by 10 μg·m-3， PM2.5， SO2， NO2 had the maximum lag effect on the number of outpatient visits in the department of internal medicine for respiratory diseases on lag day 4， day 5 and day 7， respectively. And the RR values and 95%CI were 1.002 0（1.001 3‒1.002 6）， 1.0154（1.012 3‒1.018 5）， and 1.006 1（1.005 3‒1.006 9）， respectively. ConclusionThere is a exposure-response relationship between air pollutants and the number of outpatient visits in each department of the hospitals， and different pollutants have different degrees of lag effects.
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Objective @#To examine the association between acute exposure to traffic-related air pollutants (TRAP) NOX and NO2 and outpatient visits of pediatric respiratory diseases. @*Methods @#Data regarding outpatient visits to Department of Respiratory Diseases of Beijing Children's Hospital from 2015 to 2020 were collected, and the concentrations of nitrogen oxides (NOX), nitrogen dioxide (NO2) and other TRAP were collected from the surveillance sites assigned by the Peking University Health Science Center. A time-stratified case-crossover design was employed, and a conditional logistic regression model was created to examine the association between NOX and NO2 acute exposure and outpatient visits of pediatric respiratory diseases. @*Results @#The daily mean outpatient visits of pediatric respiratory diseases were 571 (interquartile range, 554) person-times among children at ages of 0 to 14 years in Beijing Children's Hospital from 2015 to 2020, and the daily mean outpatient visits for upper respiratory tract infections (URI), bronchitis, and pneumonia were 265 (interquartile range, 282), 143 (interquartile range, 178) and 128 (interquartile range, 120) person-times, respectively. The daily mean concentrations of atmospheric NOX and NO2 were 67.8 (interquartile range, 50.7) and 49.3 (interquartile range, 30.7) μg/m3, respectively. Conditional logistic regression analysis showed the largest lagged effect of NOX and NO2 on pediatric respiratory diseases at cumulative lags of 0 to 7 days. An increase in NOX concentrations by an interquartile range resulted in the excess risks of URI, bronchitis and pneumonia by 6.87% (95%CI: 6.37%-7.38%), 7.25% (95%CI: 6.51%-7.99%), and 5.51% (95%CI: 4.69%-6.33%), and an increase in NO2 concentrations by an interquartile range resulted in excess risks of URI, bronchitis and pneumonia by 5.71% (95%CI: 5.12%-6.31%), 5.32% (95%CI: 4.51%-6.14%), and 4.83% (95%CI: 3.91%-5.75%), respectively. NOX and NO2 presented a more remarkable effect on outpatient visits of pediatric respiratory diseases among children at ages of over 5 years. @*Conclusion @#NOx and NO2 acute exposure may increase the outpatient visits of pediatric respiratory diseases.
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ObjectiveTo analyze the effect of O3 pollution on outpatient visits for respiratory diseases in a district of Shanghai. MethodsWe collected the respiratory disease outpatient data， and atmospheric and meteorological data of from a suburban general hospital in Shanghai from 2015 to 2017. A time-series analysis by generalized additive model was conducted to examine the relationship between O3 pollution and daily outpatient visits. ResultsThe daily outpatient volume for respiratory diseases was 831. The daily 8 h median concentration of O3 was 101.04 μg·m-3. The excess relative risk was 0.461% （95%CI： 0.240%‒0.682%） at lag3. Stratified by gender and age， females， child and the aged had higher risk of respiratory diseases. In the double-pollutant model， PM2.5 and PM10 increased health effects， while CO reduced health effects. ConclusionThe increase of O3 concentration can increase the daily outpatient volume of respiratory diseases.
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Background Air quality health index (AQHI) has been widely used to quantify the health effects of multiple pollutants observed in population-based epidemiological studies, and can better reflect the widespread linear non-threshold between air pollution and health effects. Objective To explore an AQHI for pediatric respiratory diseases (AQHIr) in Shanghai and evaluate its feasibility. Methods The daily numbers of hospital outpatient visits for pediatric respiratory diseases from 2015 to 2019 were obtained from five general hospitals in Xuhui, Baoshan, Hongkou, Jinshan, and Chongming Districts of Shanghai. Monitoring data on air pollutants (PM2.5, PM10, SO2, NO2, and O3), air quality index (AQI), and meteorological variables (temperature, relative humidity, air pressure, and wind speed) were collected from five air quality monitoring sites nearest to selected hospitals. Time-series analysis using generalized additive model (GAM) was conducted to estimate the associations between respiratory-related pediatric outpatient visits and the concentrations of air pollutants. The sum of excess risk (ER) of hospital outpatient visits was used to construct AQHIr. To assess the predictive power of AQHIr, the associations of AQHIr and AQI with the number of pediatric respiratory outpatient visits in three hospitals in Xuhui, Hongkou, and Chongming districts were compared. Results Air pollutants had various effects on respiratory diseases outpatient visits. PM2.5, NO2, and O3 had most significant impacts on lag0 day and the associated ERs of hospital outpatient visits for each 10 μg·m−3 increase in pollutant concentration were 1.27% (95%CI: 0.88%-1.66%), 0.75% (95%CI: 0.40%-1.11%), and 0.36% (95%CI: 0.10%-0.62%), respectively. PM10 and SO2 had most significant impacts on lag3 day and the associated ERs of hospital outpatient visits for each 10 μg·m−3 increase in pollutant concentration were 0.81% (95%CI: 0.51%-1.12%) and 5.64% (95%CI: 3.37%-7.96%), respectively. There were significant effects of combinations of two pollutants among PM2.5, PM10, NO2, SO2, and O3 except for PM10+NO2, SO2+PM2.5, and SO2+NO2 (P<0.05). According to the results of single-pollutant and two-pollutant models, PM2.5, NO2, SO2, and O3 were selected to construct AQHIr. The comparison showed that for every interquartile range increase in AQHIr, the ER for pediatric outpatient visits was higher than that for the value corresponding to AQI. Conclusion Air pollutants in Shanghai have an impact on the number of pediatric respiratory outpatient visits. The AQHIr based on and outpatient visits for pediatric respiratory diseases can be a sensitive index to predict the effects of air pollution on children's respiratory health.
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We report a case of a patient with chronic stroke who improved his gait ability through weekly gait training using Gait Exercise Assist Robot (GEAR). A man in his 70s, who developed cerebral infarction 27 years ago, presented with right-sided hemiplegia. Before gait training, the patient's gait ability was assessed to be independent, but poor toe clearance was observed on the paralyzed side during the swing phase. Therefore, we started gait training using GEAR with the goal of improving his gait pattern. The patient underwent gait training using GEAR for 20 min/day, 1 day/week for 12 weeks, wherein the treadmill speed was increased as much as possible in order to improve the swing of the paralyzed lower limbs, and the visual and auditory feedback functions were also used to promote the load and swing of the paralyzed lower limbs. As a result, the overground gait velocity, Timed Up and Go Test, and 6-minute walking distance increased after 4 weeks. However, poor toe clearance was observed on the paralyzed side during the swing phase even after 12 weeks of the training. These results suggest that 4 weeks of gait training using GEAR (performed only 1 day/week) may effectively improve the gait ability of patients with chronic stroke. On the other hand, no improvement in gait pattern was observed, and further investigation is required in the future.
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We report a case of a patient with chronic stroke who improved his gait ability through weekly gait training using Gait Exercise Assist Robot (GEAR). A man in his 70s, who developed cerebral infarction 27 years ago, presented with right-sided hemiplegia. Before gait training, the patient's gait ability was assessed to be independent, but poor toe clearance was observed on the paralyzed side during the swing phase. Therefore, we started gait training using GEAR with the goal of improving his gait pattern. The patient underwent gait training using GEAR for 20 min/day, 1 day/week for 12 weeks, wherein the treadmill speed was increased as much as possible in order to improve the swing of the paralyzed lower limbs, and the visual and auditory feedback functions were also used to promote the load and swing of the paralyzed lower limbs. As a result, the overground gait velocity, Timed Up and Go Test, and 6-minute walking distance increased after 4 weeks. However, poor toe clearance was observed on the paralyzed side during the swing phase even after 12 weeks of the training. These results suggest that 4 weeks of gait training using GEAR (performed only 1 day/week) may effectively improve the gait ability of patients with chronic stroke. On the other hand, no improvement in gait pattern was observed, and further investigation is required in the future.
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Objective To explore associations between short-term exposure to ambient nitrogen dioxide (NO2) and hospital outpatient visits. Methods Daily outpatient visit data were obtained from 5 hospitals in Beijing, Shanghai, and Guangzhou, the three major cities in China.The study period was from 2013 to 2015.The causes of disease were determined in accordance to the International Classification of Disease 10th version, with the codes A00-R99.Daily air pollution data were from the nearest state-controlled environmental monitoring stations.City-level environmental factors were acquired, including temperature and relative humidity.A time-series generalized additive model (GAM) was adopted to explore the effect of daily NO2 exposure on hospital outpatient visits, after controlling the time trends, day of week (DOW), holiday, and environmental factors.Then a random-effect meta-analysis was used to pool the results across cities.We also explored the lag structure, two-pollutant models, and potential seasonal effect. Results During the study period, the average daily outpatient visits were 3 949.The average NO2 exposure level was 55.3 μg/m3.The lag analysis showed that NO2 exposure had the greatest effect on outpatient visits every day. For a 10 μg/m3 increase in NO2, outpatient visits remarkably increased by 0.85% (95%CI:0.51%-1.19%).The associations of NO2 remained robust after controlling co-pollutants, including fine particulate matter, ozone, sulfur dioxide and carbon monoxide.The effects of NO2 were more in cool seasons, and the exposure-response curves between NO2 and outpatient visits were nearly linear. Conclusions Short-term exposure to NO2 increases the risk of hospital outpatient visits in major cities, suggesting a need to further lower exposure levels of NO2 in China.
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Objective @#To explore season-specific association between ambient PM2.5 and outpatient visits for asthma in the urban areas of Ningbo.@*Methods @#Based on the platform of population health information,we collected daily outpatient visits for asthma in four general hospitals in the urban areas of Ningbo from 2014 to 2016. We also collected data of meteorological indicators and air pollutants during the same period from local weather bureau and environmental monitoring center. Generalized additive model（GAM）was applied to examining the relationship and lag effects between ambient PM2.5 and outpatient visits for asthma in different seasons. @*Results @#A total of 45 184 outpatients with asthma were reported from 2014 to 2016,with an average of 41.23 cases per day. The annual average concentration of PM2.5 in Ningbo was（43.12± 26.40）μg/m3 ,with the peak as（65.27± 34.51）μg/m3 in winter and the though as（27.34± 12.70）μg/m3 in summer. A 10 μg/m3 increase of PM2.5 were associated with 1.14%（95%CI：0.48%-1.81%）,2.40%（95%CI：0.22%-4.63%）and 1.37%（95%CI：0.28%-2.48%）increase of outpatient volume for asthma on the day in the whole year,summer and winter,respectively. In summer,males were at higher risk compared to females（P< 0.05）;in winter,people under 65 years old were at higher risk（P< 0.05）. Including NO2,the effect of PM2.5 on the excess risk of outpatient visits for asthma in summer was enhanced in two-pollutant models（P< 0.05）. @*Conclusion @#PM2.5 pollution might increase the outpatient volume for asthma in summer and winter. NO2 might have synergistic effect with PM2.5 on asthma.
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BACKGROUND: This study purposed to analyze and understand how spatial accessibility of patients influenced the number of outpatient visits for the internal medicine of a hospital. METHODS: A hospital with 100 beds in Seoul, South Korea provided data from 2013 January 1 to 2013 June 30. Euclidean distance and road ares were used to represent the spatial accessibility. Patient level data and dong level data were collected and used in spatial analysis. Dong level data was converted into grid level (500×500 m) for the multivariate analysis. Hot-spot analysis and generalized linear model were applied to the data collected. RESULTS: Hot-spots of outpatient visits were found around the study hospital, and cold-spots were not found. Number of outpatient visits was varied by the distance between patient resident and hospitals, and about 80% of total outpatient visits was occurred in within the 5 km from study hospital, and 50% was occurred in within 1.6 km. Spatial accessibility had significant influences on the outpatient visits. CONCLUSION: Findings provide evidences that spatial accessibility had influences on the patients' behaviors in utilizing the outpatient care of internal medicine in a hospital. Results can provide useful information to health policy makers as well as hospital managers for their decision making.
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Humanos , Atención Ambulatoria , Toma de Decisiones , Política de Salud , Medicina Interna , Corea (Geográfico) , Modelos Lineales , Análisis Multivariante , Pacientes Ambulatorios , Seúl , Análisis EspacialRESUMEN
Indonesian government secures the access of the poor towards health services through subsidised schemes. This study is aimed to describe the pattern of health expenditure by households and to describe the pattern of health service utilisation across household’s socioeconomic level in the city of Padang after seven years of the introduction of subsidised schemes. A household survey was conducted involving 918 households, with multistage random sampling method. The proportion of out-of-pocket (OOP) health spending as a share of household’s capacity to pay was regressive across consumption quintiles. The proportion of households with catastrophic health expenditure was 1.6% while 1.1% faced impoverished health expenses. Among those who need health care, the utilisation among the rich was higher than the poor. Health insurance schemes in Padang provides financial protection, however with regards to household’s capacity to pay, the poor has the higher burden of health payment. The gap on health service utilisation between the poor and the better-offs was still apparent for outpatient services and it has been narrowed for inpatient care. This study suggests that the subsidised schemes for the poor are highly needed and the possibility of the leakage of subsidies to the rich should be considered by the government.
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Objective To explore the effects of air pollution on daily outpatient vivits of hospital. Methods Correlation analysis was carried out based on data of daily outpatient visits of Taiyuan Central Hospital(TCH) and monitoring data on the concentration of TSP and SO2 in air and temeprature and humidity area of Xinghualing district where TCH was located by the time series analysis. Results The concentiations of TSP and SO2 in air exceeded the corresponding standards recommended by WHO. SO2 was the statistically significant forecasting factor for the daily outpatient visits of the department of respiratory disease, emergency and piediatrics. TSP was the statistically singnificant forecasting factor for the daily outpatient visits of department of cardiovascular disease and other departments. Conclusion Severe air pollution by TSP and SO2 effected the dialy outpatient visits in a certain degree.