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OBJECTIVE: To analyse the trends in MS hospitalization rates in Spain (1998-2022) considering age, period, and birth cohort (A-P-C) effects. METHODS: This retrospective study used data on MS hospitalizations from the Spanish National Health System Minimum Basic Data Set (CMBD). Age-Standardized Hospitalization Rates (ASHRs) and Joinpoint analysis were used to assess trends. A-P-C analysis was performed to estimate age-specific rates, period and cohort effects. RESULTS: From 1998 to 2022, MS hospital admissions in Spain declined annually by -2.1 %, with women showing a slightly greater decrease (-2.3 %) than men (-1.7 %). Joinpoint analysis revealed non-parallel trends, with three inflection points indicating distinct periods of stabilization and decline. ASHR showed an overall decrease, with -2.0 % for men and -2.2 % for women annually. Risk of hospitalization peaked in the 25-29-year age group for men and 30-34-year age group for women, declining with age. Women consistently had higher risk ratios across age groups. Cohort analysis showed periods of stabilization and decline in MS hospitalization risk, aligning with joinpoint analysis findings. Risk increased for cohorts born in the early 20th century, peaking around 1938, followed by a progressive decline in later cohorts. CONCLUSIONS: Despite an aging population, MS hospitalization rates in Spain decreased. The risk of hospitalization for MS is affected by a person's age, the time period they were born in, the historical context of healthcare received, and potentially their sex.

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Numerous studies have been conducted in other countries on the health effects of exposure to particulate matter with a diameter of 10 microns or less P M 10 , but little research has been conducted in Malaysia, particularly during the haze season. This study intends to investigate how exposure of P M 10 influenced hospital admissions for respiratory diseases during the haze period in peninsula Malaysia and it was further stratified by age group, gender and respiratory diseases categories. The study includes data from all patients with respiratory diseases in 92 government hospitals, as well as P M 10 concentration and meteorological data from 92 monitoring stations in Peninsula Malaysia starting from 1st January 2000 to 31st December 2019. A quasi-poison time series regression with distributed lag nonlinear model (DLNM) was employed in this study to examine the relationship between exposure of P M 10 and hospital admissions for respiratory diseases during the haze period. Haze period for this study has been defined from June to September each year. According to the findings of this study, P M 10 was positively associated with hospitalisation of respiratory disease within 30 lag days under various lag patterns, with lag 25 showing the strongest association (RR = 1.001742, CI 1.001029,1.002456). Using median as a reference, it was discovered that females were more likely than males to be hospitalized for P M 10 exposure. Working age group will be the most affected by the increase in P M 10 exposure with a significant cumulative RR from lag 010 to lag 030. The study found that P M 10 had a significant influence on respiratory hospitalisation in peninsula Malaysia, particularly for lung diseases caused by external agents(CD5). Therefore, it is important to implement effective intervention measures to control P M 10 and reduce the burden of respiratory disease admissions.

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INTRODUCTION: Bipolar disorder (BD) hospitalization rates in children and adolescents vary greatly across place and over time. There are no population-based studies on youth BD hospitalizations in Spain. METHODS: We identified all patients aged 10-19 hospitalized due to BD in Spain between 2000 and 2021, examined their demographic and clinical characteristics, and assessed temporal trends in hospitalizations - overall and stratified by age and presence of additional psychiatric comorbidity. We used Joinpoint regressions to identify inflection points and quantify whole-period and annual percentage changes (APCs) in trends. RESULTS: Of 4770 BD hospitalizations in 10-19-year-olds between 2000 and 2021 (average annual rate: 4.8 per 100,000), over half indicated an additional psychiatric comorbidity, most frequently substance abuse (62.2%), mostly due to cannabis (72.4%). During the study period, admissions increased twofold with an inflection point: Rates increased annually only between 2000 and 2008, for APCs 34.0% (95% confidence interval: 20.0%, 71.1%) among 10-14-year-olds, 10.3% (6.4%, 14.3%) among 15-19-year-olds, and 15.5% (11.5%, 22.7%) among patients with additional psychiatric comorbidity. Between 2009 and 2021, rates decreased moderately among 10-14-year-olds - APC: -8.3% (-14.1%, -4.4%) and slightly among 15-19-year-olds without additional psychiatric comorbidity - APC: -2.6(-5.7, -1.0), remaining largely stable among 15-19-year-olds overall. CONCLUSIONS: Recent trends in hospitalization due to BD in 10-19-year-olds in Spain indicate salient increases in the early 2000s - especially among (i) patients aged 10-14 (decreasing moderately after 2009 among 10-14-year-olds and plateauing among 15-19-year-olds) and (ii) patients with additional psychiatric comorbidity (i.e., cannabis use disorder). These findings suggest links with recent changes in clinical practices for children and recent trends in substance use among Spanish youth.

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Despite progress in therapy, heart failure (HF) inflicts a heavy burden of hospital admissions. In this study, we identified among 1360 community-dwelling HF patients (mean age 70.7 ± 11.3 years, 72.5% men) subgroups sharing similar profiles of unplanned hospital admissions, based on the admission causes and frequency of each cause. Hospital discharge summaries were reviewed for the main admission cause. Patient subgroups were identified via cluster analysis. We investigated baseline predictors associated with these subgroups, using multinomial logistic models. During 3421 patient-years, there were 5192 hospital admissions, of which 4252 (82%) were unplanned. We identified five patient subgroups (clusters 1-5) with distinctive hospitalization profiles. HF accounted for approximately one-third of admissions in the first patient cluster (23% of the patient sample). In contrast, patients in the second cluster (39% of the patient sample) were hospitalized for various reasons, with no single prominent admission cause identified. The other three clusters, comprising 16% of the patient sample, accounted for 42% of all unplanned hospitalizations. While patients in the third cluster were hospitalized mainly due to ischemic heart disease and arrhythmia, patients in the fourth and fifth clusters shared a high burden of recurrent HF admissions. The five patient clusters differed by baseline predictors, including age, functional capacity, comorbidity burden, hemoglobin, and cause of HF. HF patients differ significantly in the causes and overall burden of unplanned hospitalizations. The patient subgroups identified and predictors for these subgroups may guide personalized interventions to reduce the burden of unplanned hospitalizations among HF patients. Trial registration: ClinicalTrials.gov, NCT00533013. Registered 20 September 2007. https://clinicaltrials.gov/study/NCT00533013 .

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Background: Neurodisability describes a broad set of conditions affecting the brain and nervous system which result in functional limitations. Children with neurodisability have more hospital admissions than their peers without neurodisability and higher rates of school absence. However, longitudinal evidence comparing rates of hospital admission and school absence in children with neurodisability to peers without neurodisability throughout school is limited, as is understanding about whether differences are greatest for planned care (e.g., scheduled appointments) or unplanned care. This study will describe rates of planned and unplanned hospital admissions and school absence due to illness and medical reasons throughout primary school (Reception to Year 6, ages 4 to 11 in England) for children with neurodisability and all other children, using linked individual-level health and education data. Methods: We will use the ECHILD (Education and Child Insights from Linked Data) database, which links educational and health records across England. We will define a primary school cohort of children who were born in National Health Service-funded hospitals in England between 1 st September 2003 and 31 st August 2008, and who were enrolled in Reception (age 4/5) at state-funded schools. We will use hospital admissions records to identify children who have recorded indicators of neurodisability from birth up to the end of primary school (Year 6, age 10/11). Results: We will describe rates of planned and unplanned hospital admissions and health-related school absence for three groups of children: those with a neurodisability indicator first recorded before beginning primary school, those with neurodisability first recorded during primary school, and those without a record of neurodisability before end of primary school. Conclusions: We will further explore whether differences between these group vary across primary school years and by socioeconomic and demographic characteristics.

Neurodisability encompasses a range of health conditions which affect the brain and nervous system and result in difficulties with everyday activities, including learning. Children with neurodisability are more likely to be admitted to hospital and spend longer periods of time in hospital than children without neurodisability. They are also more likely to be absent from school. Yet, in England, these is a lack of evidence comparing admissions and absence rates in children with and without neurodisability throughout their school years. Evidence is also lacking on whether differences are greatest for planned care (e.g., scheduled appointments) or unplanned care. We will use hospital and education records from state-funded hospitals and schools in England to describe rates of hospital admission and school absences for children with and without neurodisability during their primary school years.

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BACKGROUND: Non-communicable diseases (NCDs) pose a significant global health challenge, constituting over 80% of mortality and morbidity. This burden is particularly pronounced in low- and middle-income countries (LMICs), including Ethiopia. Despite this, there's limited research on this issue in Africa. This study aims to investigate the prevalence, patterns, and outcomes of NCDs in hospitalized populations across three tertiary hospitals in Ethiopia. METHODS: A hospital-based cohort study (August 2022 - January 2023) included patients aged 14 and older diagnosed with cardiovascular diseases (CVDs), diabetes mellitus (DM), chronic obstructive pulmonary disease (COPD), asthma, or cancer at three Ethiopian hospitals. Data on demographics, socio-economic factors, clinical characteristics, and outcomes were collected through medical records and interviews. Logistic regression identified factors independently associated with in-hospital mortality, with p ≤ 0.05 considered statistically significant. RESULTS: In the study across three tertiary hospitals involving 2,237 patients, we uncovered the impact of NCDs. About 23.4% of patients struggled with NCDs, with cardiovascular diseases (53.3%), cancer (29.6%), diabetes (6.1%), and respiratory diseases (6.5%) being the most prevalent. Notably, among those affected, women comprised a slight majority (55.1%), with the average patient age being 47.2 years. Unfortunately, 15.3% of patients with NCDs faced in-hospital mortality. Our analysis revealed predictors of mortality, including cancer diagnosis (adjusted odds ratio [AOR]:1.6, 95% CI: 1.2-1.8, p = 0.01), medication adherence ( AOR: 0.36, 95% CI: 0.21-0.64, p < 0.001), concurrent infections (AOR: 0.36, 95% CI: 0.16-0.86, p < 0.001), chronic kidney diseases (CKD) (AOR: 0.35, 95% CI: 0.14-0.85, p = 0.02), and complications during hospitalization (AOR: 6.36, 95% CI: 3.45-11.71, p < 0.001). CONCLUSION: Our study reveals a substantial prevalence of NCDs among hospitalized patients, affecting approximately one in four individuals, primarily with CVDs and cancer. Alarmingly, a significant proportion of these patients did not survive their hospitalization, emphasizing the urgent need for targeted interventions to enhance outcomes in this population.

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BACKGROUND: This paper investigates the consequences of the COVID-19 pandemic on mortality and hospitalization among nursing home residents in Norway. While existing evidence shows that nursing home residents were overrepresented among COVID-19-related deaths, suggesting inadequate protection measures, this study argues that the observed overrepresentation in mortality and hospitalization may partly stem from the inherent frailty of this demographic. Using nationwide administrative data, we assessed excess deaths and hospitalization by comparing pandemic-era rates to those of a pre-pandemic cohort. METHODS: We compared mortality and hospitalization rates between a pandemic cohort of nursing home residents as of September 2019 (N = 30,052), and a pre-pandemic cohort as of September 2017 (N = 30,429). Both cohorts were followed monthly for two years, beginning in September 2019 and 2017, respectively. This analysis was conducted at the national level and separately for nursing home residents in areas with low, medium, and high SARS-CoV-2 community transmission. Event studies and difference-in-difference models allowed us to separate the impact of the pandemic on mortality and hospitalization from secular and seasonal changes. RESULTS: The pandemic cohort experienced a non-significant 0.07 percentage points (95% confidence interval (CI): - 0.081 to 0.221) increase in all-cause mortality during the 18 months following pandemic onset, compared to the pre-pandemic cohort. Moreover, our findings indicate a substantial reduction in hospitalizations of 0.27 percentage points (95% CI: - 0.464 to - 0.135) and a non-significant decrease of 0.80 percentage points (95% CI: - 2.529 to 0.929) in the proportion of nursing home residents hospitalized before death. The effect on mortality remained consistent across regions with both high and low levels of SARS-CoV-2 community transmission. CONCLUSIONS: Our findings indicate no clear evidence of excess all-cause mortality in Norway during the pandemic, neither nationally nor in areas with high infection rates. This suggests that early implementation of nationwide and nursing home-specific infection control measures during the pandemic effectively protected nursing home residents. Furthermore, our results revealed a decrease in hospitalizations, both overall and prior to death, suggesting that nursing homes adhered to national guidelines promoting on-site treatment for residents.

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Background: Guidelines and risk scores have sought to standardize the management of syncope in the emergency department (ED), but variation in practice remains. Objective: The purpose of this study was to explore factors associated with admission for patients presenting to the ED with low-risk syncope. Methods: Our study population included adult patients in the Nationwide Emergency Department Sample between 2006 and 2019 who presented to an ED with a primary diagnosis of syncope. Multivariable hierarchical logistic regression analyses determined the association of patient or hospital factors with admission. Reference effect measures methodology assessed the relative contributions of patient, hospital, and unmeasured hospital factors. Results: Of the 3,206,739 qualifying encounters during the study period, 804,398 (25.1%) met low-risk criteria. Of these patients, 20,260 were admitted to the hospital (2.5%). Factors associated with increased odds of admission included increasing age and weekend presentation to the hospital, while female sex, lack of medical insurance, hospital region, teaching status, and higher ED volume decile were associated with lower odds of admission. Reference effect measures methodology demonstrated that unmeasured site variability contributed the widest range of odds for admission (odds ratio [OR] 5th percentile vs 95th percentile 0.23-4.38) compared with the composite patient (OR 0.33-3.68) or hospital (OR 0.65-1.30) factors. Conclusion: Admission patterns for low-risk syncope varies widely across institutions. Unmeasured site variation contributes significantly to the variability in admission rates, suggesting which hospital a patient presents to plays a disproportionate role in admission decisions. Further guidance to reduce practice variation in syncope care in the ED is needed.

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OBJECTIVE: Limited evidence exists regarding the impact of the COVID-19 pandemic on the onset and trajectory of eating disorders (EDs) among young in Spain. This study aims to analyze the characteristics and recent trends in hospital admissions for EDs within the pediatric population. METHODS: A retrospective analysis was conducted on hospital admissions for EDs among patients aged 10-19 years between 2016 and 2022. The main outcomes examined included hospital rates (overall, stratified by ED type and age group), psychiatric comorbidities, and length of stay. RESULTS: A total of 8275 hospitalizations due to EDs were identified, constituting 1 in 6 hospital admissions for mental illness and behavioral disorders. Predominant characteristics of this population included female sex (93%), aged 15-19 years (58.3%), admission primarily for anorexia nervosa (71.6%), and psychiatric comorbidity (35.6%). Hospital admissions for EDs in the pediatric population showed an increasing trend, with an annual average increase of 11.1% (95% CI: 2.6, 22.6). This rise was led by children aged 10-14 years, with a yearly increase in EDs hospitalization rates of 28.4% (95% CI: 13.5, 56.3) since 2019. Each discharge related to EDs was associated with a median stay of 24 days (IQR: 10, 40). DISCUSSION: Efforts in community healthcare should prioritize early detection and intervention for symptoms indicative of EDs in the pediatric population, aiming to mitigate the severity of cases requiring hospitalization. These findings underscore the necessity for targeted health planning policies to address the growing burden of EDs among Spanish youth.

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This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory diseases and the levels of PM10 and SO2 pollutants, as well as local meteorological conditions, using data from 2017 to 2019. The objective of this study is to clarify the impact of air pollution on the well-being of the general population, specifically focusing on respiratory ailments. An ANN called a multilayer perceptron (MLP) was used. The network was trained using the Levenberg-Marquardt (LM) backpropagation algorithm. The data revealed a substantial increase in hospital admissions for upper respiratory tract diseases, amounting to a total of 11,746 cases. There were clear seasonal fluctuations, with fall having the highest number of cases of bronchitis (N = 181), sinusitis (N = 83), and upper respiratory infections (N = 194). The study also found demographic differences, with females and people aged 18 to 65 years having greater admission rates. The performance of the ANN model, measured using R2 values, demonstrated a high level of predictive accuracy. Specifically, the R2 value was 0.91675 during training, 0.99182 during testing, and 0.95287 for validating the prediction of asthma. The comparative analysis revealed that the ANN-MLP model provided the most optimal result. The results emphasize the effectiveness of ANNs in representing the complex relationships between air quality, climatic conditions, and respiratory health. The results offer crucial insights for formulating focused healthcare policies and treatments to alleviate the detrimental impact of air pollution and meteorological factors.

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BACKGROUND: Race and ethnicity are important drivers of health inequalities worldwide. However, the recording of race/ethnicity in data systems is frequently insufficient, particularly in low- and middle-income countries. The aim of this study is to descriptively analyse trends in data completeness in race/color records in hospital admissions and the rates of hospitalizations by various causes for Blacks and Whites individuals. METHODS: We conducted a longitudinal analysis, examining hospital admission data from Brazil's Hospital Information System (SIH) between 2010 and 2022, and analysed trends in reporting completeness and racial inequalities. These hospitalization records were examined based on year, quarter, cause of admission (using International Classification of Diseases (ICD-10) codes), and race/color (categorized as Black, White, or missing). We examined the patterns in hospitalization rates and the prevalence of missing data over a period of time. RESULTS: Over the study period, there was a notable improvement in data completeness regarding race/color in hospital admissions in Brazil. The proportion of missing values on race decreased from 34.7% in 2010 to 21.2% in 2020. As data completeness improved, racial inequalities in hospitalization rates became more evident - across several causes, including assaults, tuberculosis, hypertensive diseases, at-risk hospitalizations during pregnancy and motorcycle accidents. CONCLUSIONS: The study highlights the critical role of data quality in identifying and addressing racial health inequalities. Improved data completeness has revealed previously hidden inequalities in health records, emphasizing the need for comprehensive data collection to inform equitable health policies and interventions. Policymakers working in areas where socioeconomic data reporting (including on race and ethnicity) is suboptimal, should address data completeness to fully understand the scale of health inequalities.

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Introduction: Complex chronic patients are prone to unplanned hospitalizations leading to a high burden on healthcare systems. To date, interventions to prevent unplanned admissions show inconclusive results. We report a qualitative analysis performed into the EU initiative JADECARE (2020-2023) to design a digitally enabled integrated care program aiming at preventing unplanned hospitalizations. Methods: A two-phase process with four design thinking (DT) sessions was conducted to analyse the management of complex chronic patients in the region of Catalonia (ES). In Phase I, Discovery, two DT sessions, October 2021 and February 2022, were done using as background information: i) the results of twenty structured interviews (five patients and fifteen professionals), ii) two governmental documents on regional deployment of integrated care and on the Catalan digital health strategy, respectively, and iii) the results of a cluster analysis of 761 hospitalizations. In Phase II, Confirmation, we examined the 30- and 90-day post-discharge periods of 49,604 hospitalizations as input for two additional DT sessions conducted in November and December 2022. Discussion: The qualitative analysis identified poor personalization of the interventions, the need for organizational changes, immature digitalization, and suboptimal services evaluation as main explanatory factors of the observed efficacy-effectiveness gap. Additionally, a program for prevention of unplanned hospitalizations, to be evaluated during the period 2024-2025, was generated. Conclusions: A digitally enabled adaptive case management approach to foster collaborative work and personalization of care, as well as organizational re-engineering, are endorsed for value-based prevention of unplanned hospitalizations.

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OBJECTIVE: An unprecedented rise in eating disorder presentations has been documented in several countries during the COVID-19 pandemic. We explored this phenomenon by analyzing nationwide psychiatric admissions over 5 years, controlling for demographic variables. METHODS: We retrospectively analyzed all hospitalizations in New Zealand with a primary psychiatric diagnosis from 2017 to 2021, using Poisson regression to calculate admission rates by diagnosis, before and during the pandemic. Using Fisher's exact test and Poisson modeling, national data were validated against a manually collected sample of eating disorder admissions. RESULTS: Eating disorder admissions rose significantly during the pandemic (RR 1.48, p < 0.0001), while other diagnoses remained unchanged or decreased slightly. Anorexia nervosa in 10 to 19-year-old females drove increases, with persistent elevations noted in the 10-14 age group. Pandemic-associated increases were more striking for Maori (RR 2.55), the indigenous Polynesian population, compared with non-Maori (RR 1.43). CONCLUSIONS: Eating disorder hospital presentations increased during the COVID-19 pandemic, while other psychiatric presentations to hospital remained relatively unchanged. Possible drivers include disrupted routines, barriers to healthcare access, altered social networks, and increased social media use. Clinical services require additional resources to manage the increased disease burden, especially in vulnerable pediatric and indigenous populations. Ongoing monitoring will be required to establish the time-course of pandemic-related clinical demand.

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Evidence on the impacts of PM1, PM2.5, and PM10 on the hospital admissions, length of hospital stays (LOS), and hospital expenses among patients with cardiovascular disease (CVD) is still limited in China, especially in rural areas. This study was performed in eight counties of Fuyang from 1 January 2015 to 30 June 2017. We use a three-stage time-series analysis to explore the effects of short-term exposure to PM1, PM2.5, and PM10 on hospital admissions, LOS, and hospital expenses for CVDs. An increment of 10 ug/m3 in PM1, PM2.5, and PM10 corresponded to an increment of 1.82% (95% CI: 1.34, 2.30), 0.96% (95% CI: 0.44, 1.48), and 0.79% (95% CI: 0.63%, 0.95%) in CVD hospital admissions, respectively. We observed that daily concentrations of PMs were associated with an increase in hospital admissions, LOS, and expenses for CVDs. Sustained endeavors are required to reduce air pollution so as to attenuate disease burdens from CVDs.

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PURPOSE: The effect of heat waves on mortality is well known, but current evidence on morbidity is limited. Establishing the consequences of these events in terms of morbidity is important to ensure communities and health systems can adapt to them. METHODS: We thus collected data on total daily emergency hospital admissions, admissions to critical care units, emergency department admissions, and emergency admissions for specific diagnoses to Hospital Universitario de Son Espases from 1 January 2005 to 31 December 2021. A heat wave was defined as a period of ≥ 2 days with a maximum temperature ≥ 35 °C, including a 7 day lag effect (inclusive). We used a quasi-Poisson generalized linear model to estimate relative risks (RRs; 95%CI) for heat wave-related hospital admissions. RESULTS: Results showed statistically significant increases in total emergency admissions (RR 1.06; 95%CI 1 - 1.12), emergency department admissions (RR 1.12; 95%CI 1.07 - 1.18), and admissions for ischemic stroke (RR 1.26; 95%CI 1.02 - 1.54), acute kidney injury (RR 1.67; 95%CI 1.16 - 2.35), and heat stroke (RR 18.73, 95%CI 6.48 - 45.83) during heat waves. CONCLUSION: Heat waves increase hospitalization risk, primarily for thromboembolic and renal diseases and heat strokes.

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PURPOSE: Upper gastrointestinal (GI) cancers contribute to 16.7% of UK cancer deaths. These patients make high use of acute hospital services, but detail about palliative care use is lacking. We aimed to determine the patterns of use of acute hospital and hospital specialist palliative care services in patients with advanced non-curative upper GI cancer. METHODS: We conducted a service evaluation of hospital use and palliative care for all patients with non-curative upper GI cancer seen in one large hospital, using routinely collected data (2019-2022). We report and characterise hospital admissions and palliative care within the study time period, using descriptive statistics, and multivariable Poisson regression to estimate the unadjusted and adjusted incidence rate ratio of hospital admissions. RESULTS: The total with non-curative upper GI cancer was 960. 86.7% had at least one hospital admission, with 1239 admissions in total. Patients had a higher risk of admission to hospital if: aged ≤ 65 (IRR for 66-75 years 0.71, IRR 76-85 years 0.68; IRR > 85 years 0.53; p < 0.05), or lived in an area of lower socioeconomic status (IMD Deciles 1-5) (IRR 0.90; p < 0.05). Over the 4-year period, the rate of re-admission was higher in patients not referred to palliative care (rate 0.52 readmissions/patient versus rate 1.47 readmissions/patient). CONCLUSION: People with advanced non-curative gastrointestinal cancer have frequent hospital admissions, especially if younger or from areas of lower socioeconomic status. There is clear association between specialist palliative care referral and reduced risk of hospitalisation. This evidence supports referral to specialist palliative care.

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BACKGROUND: Despite previous efforts, medication safety in paediatrics remains a major concern. To inform improvement strategies and further research especially in outpatient care, we systematically reviewed the literature on the frequency and nature of drug-related hospital admissions in children. METHODS: Searches covered Embase, Medline, Web of Science, grey literature sources and relevant article citations. Studies reporting epidemiological data on paediatric drug-related hospital admissions published between 01/2000 and 01/2024 were eligible. Study identification, data extraction, and critical appraisal were conducted independently in duplicate using templates based on the 'Joanna Briggs Institute' recommendations. RESULTS: The review included data from 45 studies reporting > 24,000 hospitalisations for adverse drug events (ADEs) or adverse drug reactions (ADRs). Due to different reference groups, a total of 52 relative frequency values were provided. We stratified these results by study characteristics. As a percentage of inpatients, the highest frequency of drug-related hospitalisation was found with 'intensive ADE monitoring', ranging from 3.1% to 5.8% (5 values), whereas with 'routine ADE monitoring', it ranged from 0.2% to 1.0% (3 values). The relative frequencies of 'ADR-related hospitalisations' ranged from 0.2% to 6.9% for 'intensive monitoring' (23 values) and from 0.04% to 3.8% for 'routine monitoring' (8 values). Per emergency department visits, five relative frequency values ranged from 0.1% to 3.8% in studies with 'intensive ADE monitoring', while all other eight values were ≤ 0.1%. Heterogeneity prevented pooled estimates. Studies rarely reported on the nature of the problems, or studies with broader objectives lacked disaggregated data. Limited data indicated that one in three (median) drug-related admissions could have been prevented, especially by more attentive prescribing. Besides polypharmacy and oncological therapy, no other risk factors could be clearly identified. Insufficient information and a high risk of bias, especially in retrospective and routine observational studies, hampered the assessment. CONCLUSION: Given the high frequency of drug-related hospitalisations, medication safety in paediatrics needs to be further improved. As routine identification appears unreliable, clinical awareness needs to be raised. To gain more profound insights especially for generating improvement strategies, we have to address under-reporting and methodological issues in future research. TRIAL REGISTRATION: PROSPERO (CRD42021296986).

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Aim: This retrospective study aimed to use mixed (qualitative and quantitative) methods to evaluate the role of FSL in reducing hospital admissions due to all causes, HbA1c, and reported hypoglycaemic episodes in people with diabetes living in a socially deprived region of Northwest England. Methods: Data were collected retrospectively from previous consultations, which coincided with the 6th -week, 6th -month and annual review including blood tests, hospital admissions due to any cause and reported hypoglycaemia. Also, FSL assessment and satisfaction semi-structured questionnaire was done to assess the impact of FSL on diabetes management and quality of life. Mixed-effects models were used to assess glycaemic control and reductions in hospital admissions and reported hypoglycaemic episodes. Results: Just 127 patients met the inclusion criteria. A multivariate linear mixed model method that analyses HbA1c data longitudinally revealed mean differences (mmol/mol) between baseline and post-FSL measurements, estimated by restricted maximum likelihood method (REML) of 9.64 (six weeks), 7.68 (six months) and 7.58 (annual review); all with a corresponding p-value of < 0.0001. For DKA patients, the bootstrap method revealed a significant reduction in mean HbA1c of 25.5, 95% confidence interval (CI) [8.8, 42.6] mmol/mol. It is demonstrated that FSL use for one year resulted in 59% reduction in hospital admissions and 46% reduction in reported hypoglycaemic episodes. Conclusion: The use of FSL resulted in statistically significant reductions in hospital admissions, HbA1c and reported hypoglycaemic episodes among diabetics in a socially deprived Northwest region of England. These outcomes show a direct association with a higher questionnaire score. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-024-01424-4.

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In many studies, linear methods were used to calculate health benefits of air quality improvement, but the relationship between air pollutants and diseases may be complex and nonlinear. In addition, previous studies using reference number as average number of diseases may overestimate the health benefits. Therefore, the nonlinear model estimation and resetting of the reference number were very important. Hospital admission data for coronary heart disease (CHD), meteorological data, and air pollutant data of Zibo City from 2015 to 2019 were collected. The generalized additive model (GAM) was used to explore the association between air pollutants and hospital admission for CHD, and to evaluate the effects on health benefits under different reference number settings. A total of 21,105 hospitalized cases for CHD were reported in Zibo during the study period. The results of the GAM showed there was a log-linear exposure-response relationship between O3 and hospital admissions for CHD, with RR (relative risk) of 1.0143 (95% CI: 1.0047 ~ 1.0239). There were log-nonlinear exposure-response relationships between PM10, PM2.5, SO2, and hospital admissions for CHD. With the increase of pollutants concentrations, the risk for hospital admission showed a trend of increasing first and then decreasing. Compared with the average hospital admissions as the reference number, health benefits calculated by hospital admissions predicted by the GAM model yielded lower. Using the World Health Organization air quality guidelines as reference, attributable fractions of O3, PM10, and PM2.5 were 1.97% (95% CI: 0.63 ~ 3.40%), 11.82% (95% CI: 8.60 ~ 15.24%), and 11.82% (95% CI: 8.79 ~ 15.04%), respectively. When quantifying health benefits brought by improving air quality, corresponding calculation methods should first be determined according to the exposure-response relationships between air pollutants and outcomes. Then, applying the average hospital admissions as reference number may overestimate health benefits resulting from improved air quality.

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The coming decades are likely to see of extreme weather events becoming more intense and frequent across Europe as a whole and around the Mediterranean in particular. The reproduction rate of some microorganisms, including the bacteria that cause foodborne diseases, will also be affected by these events. The aim of this study was thus to ascertain whether there might be a statistically significant relationship between emergency hospital admissions due to the principal bacterial foodborne diseases (BFDs) and the various meteorological variables, including heatwaves. We conducted a time-series study, with daily observations of both the dependent variable (emergency hospital admissions due to BFDs) and the independent variables (meteorological variables and control variables of chemical air pollution) across the period 2013-2018 in the Madrid Region (Spain), using Generalised Linear Models with Poisson regression, in which control and lag variables were included for the purpose of fitting the models. We calculated the threshold value of the maximum daily temperature above which such admissions increased statistically significantly, analysed data for the whole year and for the summer months alone, and estimated the relative and attributable risks. The estimated attributable risk was 3.6 % for every one-degree rise in the maximum daily temperature above 12 °C throughout the year, and 12.21 % for every one degree rise in temperature above the threshold heatwave definition temperature (34 °C) in summer. Furthermore, different meteorological variables displayed a statistically significant association. Whereas hours of sunlight and mean wind speed proved significant in the analyses of both the whole year and summer, the variables "rain" and "relative humidity", only showed a significant relationship in the analysis for the whole year. High ambient temperature is a risk factor that favours the increase in emergency hospitalisations attributable to the principal BFDs, with a greater impact being observed on days coinciding with heatwave periods. The results yielded by this study could serve as a basis for implementing BFD prevention strategies, especially on heatwave days.

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