INTRODUCTION: Paediatric patients admitted to the inpatient units from the emergency department (ED) are increasing, but the mean length of stay has fallen significantly. We aimed to determine the reasons behind paediatric one-day admissions in Singapore and to assess their necessity. METHODS: A retrospective study involving paediatric patients who were admitted from a general ED of an adult tertiary hospital to a paediatric tertiary hospital between 1 August 2018 and 30 April 2020. One-day admission was defined as an inpatient stay of less than 24 h from the time of admission to discharge. An unnecessary admission was defined as one with no diagnostic test ordered, intravenous medication administered, therapeutic procedure performed or specialty review made in the inpatient unit. Data were captured in a standardised form and analysed. RESULTS: There were 13,944 paediatric attendances - 1,160 (8.3%) paediatric patients were admitted. Among these, 481 (41.4%) were one-day admissions. Upper respiratory tract infection (62, 12.9%), gastroenteritis (60, 12.5%) and head injury (52, 10.8%) were the three most common conditions. The three most common reasons for ED admissions were inpatient treatment (203, 42.2%), inpatient monitoring (185, 38.5%) and inpatient diagnostic investigations (32, 12.3%). Ninety-six (20.0%) one-day admissions were unnecessary. CONCLUSION Paediatric one-day admissions present an opportunity to develop and implement interventions targeted at the healthcare system, the ED, the paediatric patient and their caregiver, in order to safely slow down and perhaps reverse the trend of increased hospital admissions.
Humans ; Retrospective Studies ; Singapore ; Child ; Emergency Service, Hospital/statistics & numerical data* ; Patient Admission/statistics & numerical data* ; Female ; Male ; Child, Preschool ; Length of Stay/statistics & numerical data* ; Infant ; Adolescent ; Tertiary Care Centers ; Hospitalization/statistics & numerical data* ; Infant, Newborn ; Gastroenteritis/therapy* ; Respiratory Tract Infections

INTRODUCTION: In December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus emerged and caused a worldwide pandemic, leading to measures being imposed by many countries to reduce its transmission. Singapore implemented the 'circuit breaker', which restricted all movements except for access to necessities and healthcare services. We aimed to investigate the impact of lockdown measures on the pattern of trauma and its effects. METHODS: An observational, retrospective, single-centre descriptive study was conducted using the trauma registry in Singapore General Hospital. It included patients above 18 years old who presented to the emergency department with trauma and were subsequently admitted. Patients admitted from 1 February 2020 to 31 July 2020 and those admitted during the same timeframe in 2019 were studied. Subgroup analyses were performed for patients aged ≥65 years and those <65 years. RESULTS: A total of 1,037 patients were included for analysis. A 17.6% increase in trauma presentations was seen from 2019 to 2020. Patients aged ≥65 years accounted for the rise in admissions. The predominant mechanism of injury was falls at home for older patients and vehicular accidents in patients <65 years. There were no significant differences in injury severity score, intensive care/high-dependency unit admission rates, length of stay, mortality rate, and subsequent need for inpatient rehabilitation. CONCLUSION Our study provided information on differences in trauma presentations before and during the COVID-19 pandemic. Further studies are required to better inform on additional precautionary measures needed to reduce trauma and improve safety during future lockdowns and pandemics.
Humans ; COVID-19/prevention & control* ; Aged ; Retrospective Studies ; Singapore/epidemiology* ; Male ; Female ; Wounds and Injuries/epidemiology* ; Aged, 80 and over ; Middle Aged ; SARS-CoV-2 ; Hospitalization/statistics & numerical data* ; Adult ; Emergency Service, Hospital/statistics & numerical data* ; Registries ; Accidental Falls/statistics & numerical data* ; Pandemics ; Patient Admission/statistics & numerical data* ; Length of Stay ; Accidents, Traffic/statistics & numerical data*

INTRODUCTION: Degenerative mitral stenosis (DMS) is frequently cited as increasing in prevalence in the developed world, although comparatively little is known about DMS in comparison to rheumatic mitral stenosis (RMS). METHOD: A retrospective observational study was conducted on 745 cases of native-valve mitral stenosis (MS) with median follow-up time of 7.25 years. Clinical and echocardiographic parameters were compared. Univariate and multivariate Cox regression analyses were performed for a composite of all-cause mortality and heart failure hospitalisation. RESULTS: Patients with DMS compared to RMS were older (age, mean ± standard deviation: 69.6 ± 12.3 versus [vs] 51.6 ± 14.3 years, respectively; P<0.001) and a greater proportion had medical comorbidities such as diabetes mellitus (78 [41.9%] vs 112 [20.0%], P<0.001). The proportion of cases of degenerative aetiology increased from 1.1% in 1991-1995 to 41.0% in 2016-2017. In multivariate analysis for the composite outcome, age (hazard ratio [HR] 95% confidence interval [CI] of 1.032 [1.020-1.044]; P<0.001), diabetes mellitus (HR 1.443, 95% CI 1.068-1.948; P=0.017), chronic kidney disease (HR 2.043, 95% CI 1.470-2.841; P<0.001) and pulmonary artery systolic pressure (HR 1.019, 95% CI 1.010- 1.027; P<0.001) demonstrated significant indepen-dent associations. The aetiology of MS was not independently associated with the composite outcome. CONCLUSION DMS is becoming an increasingly common cause of native-valve MS. Despite numerous clinical differences between RMS and DMS, the aetiology of MS did not independently influence a composite of mortality or heart failure hospitalisation.
Humans ; Mitral Valve Stenosis/etiology* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Rheumatic Heart Disease/mortality* ; Echocardiography ; Hospitalization/statistics & numerical data* ; Heart Failure/epidemiology* ; Singapore/epidemiology* ; Proportional Hazards Models ; Diabetes Mellitus/epidemiology*

INTRODUCTION: Outcomes after SARS-CoV-2 Omicron infection in patients with heart failure (HF) and ischaemic heart disease (IHD) remain poorly defined. METHOD: In a highly vaccinated cohort of adult Singapore citizens and permanent residents, we used Cox proportional hazards models (adjusted for sociodemographic variables and comorbidities) to compare the risks of Omicron infection, COVID-19- related hospitalisation, and severe COVID-19 between indivi-duals with HF or IHD and matched controls without these conditions. RESULTS: From national databases, we identified 15,426 HF patients matched 1:∼3 to 41,221 controls, and 110,442 IHD patients matched 1:∼2 to 223,843 controls. Over 80% of HF and IHD patients had received at least 3 vaccine doses. During the Omicron-predominant period, both HF and IHD cohorts demonstrated higher adjusted risks of COVID-19 hospitalisation compared with matched controls (HF: adjusted hazard ratio [aHR] 1.77, 95% confidence interval [CI] 1.65-1.90; IHD: aHR 1.21, 95% CI 1.17-1.26). Among those with at least 1 HF-or IHD-related admission in the prior year, hospitalisation risk was further elevated (HF: aHR 1.27, 95% CI 1.13-1.42; IHD: aHR 1.11, 95% CI 1.01-1.23). Receipt of ≥3 vaccine doses was associated with substantially lower risk of severe COVID-19 versus only 2 doses (HF: aHR 0.35, 95% CI 0.28-0.43; IHD: aHR 0.27, 95% CI 0.23-0.32). A fourth dose conferred additional reductions in infection and adverse outcomes, though CIs for infection overlapped with those for 3 doses. CONCLUSION During Omicron predominance, HF and IHD patients experienced greater risk of COVID-19 hospitalisation and severe COVID-19 versus matched controls. Booster vaccinations attenuated these risks. Individuals with recent HF/IHD admissions should be prioritised for receipt of booster vaccine doses.
Humans ; COVID-19/complications* ; Male ; Heart Failure/complications* ; Myocardial Ischemia/complications* ; Female ; Middle Aged ; Hospitalization/statistics & numerical data* ; Aged ; COVID-19 Vaccines/administration & dosage* ; Singapore/epidemiology* ; SARS-CoV-2 ; Proportional Hazards Models ; Adult ; Case-Control Studies ; Vaccination/statistics & numerical data*

BACKGROUND: Hemorrhagic stroke (HS) is associated with significant disability and mortality. However, the relationship between meteorological factors and hemorrhagic stroke, as well as the potential moderating role of these factors, remains unclear. METHODS: Daily data on HS, air pollution, and meteorological conditions were collected from January 2015 to December 2021 in Ganzhou to analyze the relationship between meteorological factors and HS admissions. This analysis employed a time-stratified case-crossover design in conjunction with a distributional lag nonlinear model. Additionally, a bivariate response surface modelling was utilized to further investigate the interaction between meteorological factors and particulate matter. The study also stratified the analyses by gender and age. To investigate the potential impact of extreme weather conditions on HS, this study defined the 97.5th percentile as representing extremely high weather conditions, while the 2.5th percentile was classified as extremely low. RESULTS: In single-day lags, the risk of admissions for HS was significantly associated with extremely low temperature (lag 1-2 and lag 13-14), extremely low humidity (lag 1 and lag 9-12), and extremely high precipitation (lag 2-7). Females exhibited greater susceptibility to extremely low temperature than males within the single-day lag pattern in the subcomponent layer, with a maximum relative risk (RR) that was 7% higher. In the cumulative lag analysis, the risk of HS admissions was significantly associated with extremely high temperature (lag 0-8∼lag 0-14), extremely low humidity (lag 0-2∼lag 0-14), and extremely high precipitation (lag 0-4∼lag 0-14). Within the cumulative lag day structure of the subcomponent layer, both extremely low and extremely high temperature had a more pronounced effect on females and aged ≥65 years. The risk of HS admissions was positively associated with extremely high barometric pressure in the female subgroups (lag 0-1 and lag 0-2). The highest number of HS admissions occurred when high PM_2.5 concentrations coexisted with low precipitation. CONCLUSIONS Meteorological factors were significantly associated with the risk of hospital admissions for HS. Individuals who were female and aged ≥65 years were found to be more susceptible to these meteorological influences. Additionally, an interaction was observed between airborne particulate matter and meteorological factors. These findings contributed new evidence to the association between meteorological factors and HS.
China/epidemiology* ; Humans ; Female ; Male ; Aged ; Middle Aged ; Cross-Over Studies ; Hospitalization/statistics & numerical data* ; Adult ; Hemorrhagic Stroke/etiology* ; Meteorological Concepts ; Weather ; Particulate Matter/analysis* ; Air Pollution/adverse effects* ; Environmental Exposure/adverse effects* ; Aged, 80 and over ; Young Adult

BACKGROUND: Previous studies have demonstrated that short-term exposure to ambient particulate matter elevates the risk of ischemic stroke in major urban areas of various countries. However, there is a notable gap in research focusing on remote areas inhabited by ethnic minorities and the cumulative effects of air pollutants. Our study conducted in the area aims to explore the potential association between ischemic stroke and air pollutants and contribute to improving health outcomes among the community. METHODS: This retrospective observational study was conducted at the Xing'an League People's Hospital in Inner Mongolia. The medical records of 4,288 patients admitted for IS between November 1, 2019, and October 31, 2020, were reviewed. Data on demographics (age and sex), air pollutants (PM₁₀, PM_2.5, NO₂, NO, CO, and O₃), and meteorological factors (daily average temperature, daily average wind speed, and daily average atmosphere pressure) were collected and analyzed. The statistical analysis included descriptive statistics, Poisson distribution analysis to evaluate the adverse effects of atmospheric pollutants on daily hospitalizations, and subgroup analysis to determine whether gender and age could modify the impact on hospitalizations. RESULTS: A substantial correlation was revealed in single-day lags model. The peak delayed effects of PM₁₀, PM_2.5, SO₂, and NO₂ were observed at lag8 (PM₁₀ (OR = 1.016, 95%CI 1.002, 1.030), PM_2.5 (OR = 1.027, 95%CI 1.007, 1.048), SO₂ (OR = 1.153, 95%CI 1.040, 279) and NO₂ (OR = 1.054, 95%CI 1.005, 1.105)) while males exhibited a consistent trend from lag0 to lag8 (PM₁₀ (OR = 1.035, 95%CI 1.018, 1.053), PM_2.5 (OR = 1.056, 95%CI 1.030, 1.082), SO₂ (OR = 1.220, 95%CI 1.072, 1.389), NO₂ (OR = 1.126, 95%CI 1.061, 1.120), CO (OR = 10.059, 95%CI 1.697, 59.638) and O₃ (OR = 0.972, 95%CI 0.946, 0.999)). When gender and age were considered, a positive impact was also observed after three days cumulative effect in males. CONCLUSIONS There is a significant cumulative effect of exposure to air pollution on IS hospital admissions, especially the males and patients under the age of 65. Our results also suggested that a notable association between CO and NO₂ in two-pollutant models.
Humans ; Male ; Female ; Air Pollution/analysis* ; China/epidemiology* ; Retrospective Studies ; Middle Aged ; Air Pollutants/analysis* ; Aged ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Adult ; Ischemic Stroke/chemically induced* ; Environmental Exposure/adverse effects* ; Aged, 80 and over

BACKGROUND: Children's respiratory health demonstrates particular sensitivity to air pollution. Existing evidence investigating the association between short-term ozone (O₃) exposure and childhood pneumonia remains insufficient and inconsistent, especially in low- and middle-income countries (LMICs). METHOD: To provide more reliable and persuasive evidence, we implemented a multi-city, time-stratified case-crossover design with a large sample size, using data from seven representative children's hospitals across major geographical regions in China. To avoid the impact of the COVID-19 pandemic, individual-level medical records of inpatient children under 6 years of age diagnosed with pneumonia during 2016-2019 were collected. Conditional logistic regression models were fitted for each city, and city-specific estimates were pooled through a meta-analysis using a random-effects model. RESULTS: In total, the study included 137,470 pediatric pneumonia hospital admissions. The highest pooled estimate for O₃ occurred at lag0-1, with a 10 µg/m³ increase in O₃ associated with a 1.57% (95% CI: 0.67%-2.48%) higher risk of pediatric pneumonia hospital admissions. Stratified analyses indicated that the effects of O₃ were robust across different sexes, age groups, and admission seasons. We also observed a statistically significant increase in risk associated with O₃ concentrations exceeding the World Health Organization Air Quality Guidelines (WHO-AQGs). CONCLUSIONS This study revealed a significant positive association between O₃ and pediatric pneumonia hospital admissions. Our findings substantially strengthen the evidence base for the adverse health impacts of O₃, underscoring the importance of O₃ pollution control and management in reducing the public health burden of pediatric pneumonia.
Humans ; Ozone/analysis* ; China/epidemiology* ; Pneumonia/chemically induced* ; Child, Preschool ; Male ; Female ; Infant ; Cross-Over Studies ; Air Pollutants/analysis* ; Hospitalization/statistics & numerical data* ; Child ; Cities/epidemiology* ; Air Pollution/adverse effects* ; Infant, Newborn ; Environmental Exposure/adverse effects*

OBJECTIVE: To evaluate the effect of palliative care on drug use, medical service utilization and medical expenditure of patients with advanced cancer. METHODS: A cohort of patients including pal-liative care and standard care was constructed using the medical records of the patients in Peking University Cancer Hospital from 2018 to 2020, and coarsened exact matching was used to match the two groups of patients. The average monthly opioid consumption, hospitalization rate, intensive care unit (ICU) rate and operation rate, and the average monthly total cost were selected to evaluate drug use, medical service utilization and medical expenditure. Chi-square test and Wilcoxon signed rank test were used to compare the differences between the two groups before and after exposure and the change in the palliative care group. The net impact of palliative care on the patients was calculated using the difference-in-differences analysis. RESULTS: In this study, 180 patients in the palliative care group and 3 101 patients in the stan-dard care group were finally included in the matching, and the matching effect of the two groups was good (L₁ < 0.1). Before and after exposure, the average monthly opioid consumption in the palliative care group was significantly higher than that in the standard care group (Before exposure: 0.3 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; After exposure: 0.7 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; DDD refers to defined daily dose), palliative care significantly increased the average monthly opioid consumption in the patients (0.3 DDD/person-month, P < 0.01). The hospitalization rate (48.9% vs. 74.3%, P < 0.01) and operation rate (3.9% vs. 8.8%, P < 0.01) of the patients in palliative care group were significantly lower than those in standard care group, and the ICU rate became similar between the two groups (1.1% vs. 1.6%, P=0.634). Palliative care significantly reduced the patients ' hospitalization rate (-25.6%, P < 0.01), ICU rate (-4.9%, P < 0.01) and operation rate (-14.5%, P < 0.01). Before and after exposure, the average monthly total costs of pal-liative care group were slightly higher than those of standard care group (Before exposure: 20 092.3 yuan vs. 19 132.8 yuan, P=0.725; After exposure: 9 719.8 yuan vs. 8 818.8 yuan, P=0.165). Palliative care increased the average monthly total cost by 2 208.8 yuan, but it was not statistically significant (P=0.316). CONCLUSION Palliative care can increase the opioid consumption in advanced cancer patients, reduce the rates of hospitalization, ICU and surgery, but has no significant effect on medical expenditure.
Humans ; Palliative Care/economics* ; Neoplasms/drug therapy* ; Analgesics, Opioid/economics* ; Male ; Female ; Middle Aged ; Aged ; Hospitalization/economics* ; Intensive Care Units/statistics & numerical data* ; Health Expenditures/statistics & numerical data* ; Adult ; Drug Utilization/statistics & numerical data* ; Patient Acceptance of Health Care/statistics & numerical data*

OBJECTIVE: To assess relationships between cold spells and genitourinary hospitalization risk. METHODS: Hospitalization records for genitourinary system diseases (GUDs) from 16 districts in Beijing (2013-2018) were analyzed. Cold spells were defined based on varying intensity thresholds. A two-stage analytical method was employed: first, generalized linear models assessed district-specific associations between cold spells and hospitalizations; second, random-effects meta-analysis aggregated the district-level results. Subgroup analyses were performed by admission type (emergency vs. outpatient), age, and sex. RESULTS: A total of 271,579 GUD-related hospitalizations were recorded. Cold spells (p1day2，daily mean temperature below the 1 ^st percentiles of the daily mean temperature distribution from January 1, 2013, to December 31, 2018, lasting for two or more consecutive days) were linked to a significant rise in hospitalization risks: 1.43 (95% CI: 1.32-1.56) for all GUDs, 1.35 (95% CI: 1.23-1.49) for urinary system diseases, and 1.46 (95% CI: 1.28-1.67) for renal failure, when compared to non-cold spell days. Emergency admissions showed higher risk increases than outpatient admissions. CONCLUSION Extreme cold spells significantly elevate hospitalization risks for GUDs. This highlights the urgent need for targeted public health interventions to mitigate cold-related health impacts, especially for vulnerable populations.
Humans ; Hospitalization/statistics & numerical data* ; Male ; Female ; Cold Temperature/adverse effects* ; Infant ; Child, Preschool ; Middle Aged ; Adult ; Child ; Aged ; Adolescent ; Young Adult ; Beijing/epidemiology* ; Female Urogenital Diseases/etiology* ; Male Urogenital Diseases/etiology* ; Infant, Newborn ; Risk Factors

OBJECTIVE: To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases, and to develop deep learning-based models for daily hospital admission prediction. METHODS: A multi-city study was conducted in Tokyo's 23 wards, Osaka City, and Nagoya City. Random forest models were employed to assess the synergistic short-term lag effects (lag0, lag3, and lag7) of climate and air pollutants on hospitalization for five cardiovascular diseases (CVDs) and two respiratory diseases (RDs). Furthermore, we developed hybrid deep learning models that integrated an autoencoder (AE) with a Long Short-Term Memory network (AE+LSTM) to predict daily hospital admissions. RESULTS: On the day of exposure (lag0), air pollutants, particularly nitrogen oxides (NO x), exhibited the strongest influence on hospital admissions for CVD and RD, with pronounced effects observed for hypertension (I10-I15), ischemic heart disease (I20), arterial and capillary diseases (I70-I79), and lower respiratory infections (J20-J22 and J40-J47). At longer lags (lag3 and lag7), temperature and precipitation were more influential predictors. The AE+LSTM model outperformed the standard LSTM, improving the prediction accuracy by 32.4% for RD in Osaka and 20.94% for CVD in Nagoya. CONCLUSION Our findings reveal the dynamic, time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions. This framework can inform early warning systems, enhance healthcare resource allocation, and support climate-adaptive public health strategies.
Humans ; Hospitalization/statistics & numerical data* ; Cardiovascular Diseases/epidemiology* ; Japan/epidemiology* ; Air Pollutants/analysis* ; Air Pollution/adverse effects* ; Cities/epidemiology* ; Climate ; Respiratory Tract Diseases/epidemiology* ; Deep Learning ; Male