Trends in admission rates of primary angle closure diseases for the urban population in China, 2011-2021.

Background: Cataract surgery and laser peripheral iridotomy (LPI) are effective approaches for preventing primary angle closure diseases (PACDs), as well as acute primary angle closure (APAC). Due to the development of population screening and increases in cataract surgery rates, this study aimed to examine trends in the admission rates of PACD among the urban population in China. Methods: This cross-sectional study examined patients who were admitted to a hospital for PACD, and who underwent cataract surgery or LPI operations. The data were obtained from the Yinzhou Regional Health Information Platform (YRHIP) from 2011 to 2021. The annual rates of PACD and APAC admissions, cataract surgery and LPI were analyzed, with the number of cases used as numerators and the annual resident population in Yinzhou district used as denominators. Results: A total of 2,979 patients with PACD admissions, 1,023 patients with APAC admissions, 53,635 patients who underwent cataract surgery and 16,450 patients who underwent LPI were included. The number of annual admissions for PACD gradually increased from 22 cases (1.6/100000) in 2011 to 387 cases (30.8/100000) in 2016, after which it decreased to 232 cases (16.2/100000) in 2019 and then increased to 505 cases (30.6/100000) in 2021. The number of cataract surgeries gradually increased from 1728 (127.7/100000) in 2011 to 7002 (424.9/100000) in 2021. Similarly, the number of LPI gradually increased from 109 (8.0/100000) in 2011 to 3704 (224.8/100000) in 2021. Conclusion: The admission rates of PACD for the urban population in China have declined in recent years after a long increasing trend in the rates of cataract surgery and LPI. However, it increased rapidly during the COVID-19 epidemic. The national health database should be further utilized to investigate temporal trends in the prevalence of PACD.

An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.

BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients. METHODS: This was a retrospective study on patients admitted into a University Hospital in China between November 2008 and November 2021. Patients were included if they were diagnosed with CAP and CTD during admission and hospitalization. Data related to demographics, CTD types, comorbidities, vital signs and laboratory results during the first 24 h of hospitalization were collected. The baseline variables were screened to identify potential predictors via three methods, including univariate analysis, least absolute shrinkage and selection operator (Lasso) regression and Boruta algorithm. Nine supervised machine learning algorithms were used to build prediction models. We evaluated the performances of differentiation, calibration, and clinical utility of all models to determine the optimal model. The Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) techniques were performed to interpret the optimal model. RESULTS: The included patients were randomly divided into the training set (1070 patients) and the testing set (459 patients) at a ratio of 70:30. The intersection results of three feature selection approaches yielded 16 predictors. The eXtreme gradient boosting (XGBoost) model achieved the highest area under the receiver operating characteristic curve (AUC) (0.941) and accuracy (0.913) among various models. The calibration curve and decision curve analysis (DCA) both suggested that the XGBoost model outperformed other models. The SHAP summary plots illustrated the top 6 features with the greatest importance, including higher N-terminal pro-B-type natriuretic peptide (NT-proBNP) and C-reactive protein (CRP), lower level of CD4 + T cell, lymphocyte and serum sodium, and positive serum (1,3)-ß-D-glucan test (G test). CONCLUSION: We successfully developed, evaluated and explained a machine learning-based model for predicting ICU admission in patients with CAP and CTD. The XGBoost model could be clinical referenced after external validation and improvement.

COVID-19 Admission Rates and Changes in Care Quality in US Hospitals.

Importance: Unprecedented increases in hospital occupancy rates during COVID-19 surges in 2020 caused concern over hospital care quality for patients without COVID-19. Objective: To examine changes in hospital nonsurgical care quality for patients without COVID-19 during periods of high and low COVID-19 admissions. Design, Setting, and Participants: This cross-sectional study used data from the 2019 and 2020 Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project State Inpatient Databases. Data were obtained for all nonfederal, acute care hospitals in 36 states with admissions in 2019 and 2020, and patients without a diagnosis of COVID-19 or pneumonia who were at risk for selected quality indicators were included. The data analysis was performed between January 1, 2023, and March 15, 2024. Exposure: Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds: less than 1.0, 1.0 to 4.9, 5.0 to 9.9, 10.0 to 14.9, and 15.0 or greater. Main Outcomes and Measures: The main outcomes were rates of adverse outcomes for selected quality indicators, including pressure ulcers and in-hospital mortality for acute myocardial infarction, heart failure, acute stroke, gastrointestinal hemorrhage, hip fracture, and percutaneous coronary intervention. Changes in 2020 compared with 2019 were calculated for each level of the weekly COVID-19 admission rate, adjusting for case-mix and hospital-month fixed effects. Changes during weeks with high COVID-19 admissions (≥15 per 100 beds) were compared with changes during weeks with low COVID-19 admissions (<1 per 100 beds). Results: The analysis included 19 111 629 discharges (50.3% female; mean [SD] age, 63.0 [18.0] years) from 3283 hospitals in 36 states. In weeks 18 to 48 of 2020, 35 851 hospital-weeks (36.7%) had low COVID-19 admission rates, and 8094 (8.3%) had high rates. Quality indicators for patients without COVID-19 significantly worsened in 2020 during weeks with high vs low COVID-19 admissions. Pressure ulcer rates increased by 0.09 per 1000 admissions (95% CI, 0.01-0.17 per 1000 admissions; relative change, 24.3%), heart failure mortality increased by 0.40 per 100 admissions (95% CI, 0.18-0.63 per 100 admissions; relative change, 21.1%), hip fracture mortality increased by 0.40 per 100 admissions (95% CI, 0.04-0.77 per 100 admissions; relative change, 29.4%), and a weighted mean of mortality for the selected indicators increased by 0.30 per 100 admissions (95% CI, 0.14-0.45 per 100 admissions; relative change, 10.6%). Conclusions and Relevance: In this cross-sectional study, COVID-19 surges were associated with declines in hospital quality, highlighting the importance of identifying and implementing strategies to maintain care quality during periods of high hospital use.

Changes in admission rates to an Aotearoa New Zealand hospital general medical service during COVID-19 lockdowns.

AIM: To better understand the reasons for reduced hospital admissions to a hospital general medicine service during COVID-19 lockdowns. METHODS: A statistical model for admission rates to the General Medicine Service at Wellington Hospital, Aotearoa New Zealand, since 2015 was constructed. This model was used to estimate changes in admission rates for transmissible and non-transmissible diagnoses during and following COVID-19 lockdowns for total admissions and various sub-groups. RESULTS: For the 2020 lockdown (n=734 admissions), the overall rate ratio of admissions was 0.71 compared to the pre-lockdown rate. Non-transmissible diagnoses, which constitute 87% of admissions, had an admission rate ratio of 0.77. Transmissible diagnoses, constituting 13% of admissions, had an admission rate ratio of 0.44. Reductions in admissions did not exacerbate existing ethnic disparities in access to health services. The lag in recovery of admission rates was more pronounced for transmissible than non-transmissible diagnoses. The 2021 lockdown (n=105 admissions) followed this pattern, but was of shorter duration with small numbers, and therefore measures were frequently not statistically significant. CONCLUSIONS: The biggest relative reduction in hospital admission was due to a reduction in transmissible illness admissions, likely due to COVID-related public health measures. However, the biggest reduction in absolute terms was in non-transmissible illnesses, where hospital avoidance may be associated with increased morbidity or mortality.

Unveiling the evolving landscape of stroke care costs: A time-driven analysis.

INTRODUCTION: Stroke is a common cause of mortality in the United States. However, the economic burden of stroke on the healthcare system is not well known. In this study, we aim to calculate the annual cumulative and per-patient cost of stroke. METHODS: We conducted a retrospective analysis of Nationwide Emergency Department Sample (NEDS). We calculate annual trends in cost for stroke patients from 2006 to 2019. A multivariate linear regression with patient characteristics (e.g. age, sex, Charlson Comorbidity Index) as covariates was used to identify factors for higher costs. RESULTS: In this study time-period, 2,998,237 stroke patients presented to the ED and 2,481,171 (83 %) were admitted. From 2006 to 2019, the cumulative ED cost increased by a factor of 7.0 from 0.49 ± 0.03 to 3.91 ± 0.16 billion dollars (p < 0.001). The cumulative inpatient (IP) cost increased by a factor of 2.7 from 14.42 ± 0.78 to 37.06 ± 2.26 billion dollars (p < 0.001. Per-patient ED charges increased by a factor of 3.0 from 1950 ± 64 to 7818 ± 260 dollars (p < 0.001). Per-patient IP charges increased by 89 % from 40.22 +/- 1.12 to 76.06 ± 3.18 thousand dollars (p < 0.001). CONCLUSION: Strokes place an increasing financial burden on the US healthcare system. Certain patient demographics including age, male gender, more comorbidities, and insurance type were significantly associated with increased cost of care.

Bushfire-smoke trigger hospital admissions with cerebrovascular diseases: Evidence from 2019-20 bushfire in Australia.

INTRODUCTION: Exposure to ambient air pollution is strongly associated with increased cerebrovascular diseases. The 2019-20 bushfire season in Australia burnt 5.4 million hectares of land in New South Wales alone, with smoke so severe it affected cities in Argentina, 11,000 km away. The smoke emitted by bushfires consists of both gaseous and particle components. It is important to note that exposure to particulate matter has been shown to be linked to a heightened risk of stroke, which is the primary kind of cerebrovascular illness, as well as an increased likelihood of hospitalisations and mortality. However, the available data is inadequate in terms of documenting the response of patients diagnosed with a proven cerebrovascular illness to bushfire smoke. Additionally, there is a lack of information about the health effects associated with particulate matter throughout the bushfire season and on days when smoke was present in 2019 and 2020.Therefore, we aimed to determine the effects of (i) short-term air pollution triggered by bushfires and (ii) high smoke days in increasing the daily number of hospital admissions with cerebrovascular diseases. MATERIALS AND METHODS: Hospitalisation data were accessed from the admitted patient dataset from seven local Government areas of Hunter New England Local Health District. The bushfire period was defined from 1 October 2019 to 10 February 2020, and a same period from 2018-19 as the control. High bushfire smoke days were days when the average daily concentration of particulate matter was higher than the 95th percentile of the control period. Poisson regression models and fixed effect meta-analysis were used to analyse the data. RESULTS: In total, 275 patients with cerebrovascular admissions were identified, with 147 (53.5%) during the bushfire (2019-20) and 128 (46.5%) in the control period (2018-19). There was no significant increase in daily admissions for cerebrovascular disease (Incidence Rate Ratio, IRR: 1.04; 95% CI: 0.81-1.34; p-value: 0.73), acute stroke (IRR: 1.15; 95% CI: 0.88-1.50; p-value: 0.29) or acute ischaemic stroke (IRR: 1.18; 95% CI: 0.87-1.59; p-value: 0.28), over the entire bushfire period. However, the high bushfire smoke days were associated with increased acute ischaemic stroke-related hospital admissions across lead 0-3 and the highest cumulative effect was observed with lead 0 (IRR:1.52; 95% CI: 1.01-2.29; p-value: 0.04). In addition, during the bushfire period, particulate matter, both PM10 and PM2.5 (defined as particulates that have an effective aerodynamic diameter of 10, and 2.5 microns, respectively), were also associated with increased acute ischaemic stroke admissions with a lag of 0-3 days. DISCUSSION AND CONCLUSION: The results suggested a possible association between particulate matter and high smoke days with increased hospital admissions due to acute ischaemic stroke during the recent Australian bushfire season.

Variations in Hospital Admissions of Non-Communicable Disease Patients Before and During The COVID-19 Pandemic (A Tertiary Care Setting, January 2018-June 2021).

BACKGROUND: This study aimed to analyze the variations (if any) in hospital admissions of patients with any of the five common non-communicable diseases (NCDs), based on secondary analysis of electronic health records of patients admitted to Hacettepe University Hospitals at least once, from January 1, 2018 through June 15, 2021. DESIGN: Data were recruited from hospital's electronic health records on patients with diagnoses of ischemic heart disease, hypertension, diabetes, cancer, and chronic obstructive pulmonary disease, using relevant ICD-10 codes. RESULTS: Compared to the corresponding time span in the pre-pandemic period, the number of hospital admissions of patients with selected five NCDs significantly decreased during the pandemic, with an official start in Turkey on March 11, 2020. Number of total-, out-patient-, and in-patient admissions of NCD patients were significantly lower in the pandemic period compared to the expected values in time series analysis, controlling for patient characteristics, and seasonality. CONCLUSIONS: Study findings suggest that there has been a prominent impediment in NCD patients' access to, and/or use of health care services over the pandemic, which might evolve to higher admission rates, severity and fatality of such patients in the upcoming years. Further studies are warranted for confirmation of our findings in other care settings, with individual-based data on care compensation through settings other than regular admission sites (if any), and/or the reasons for under-use of services.

Trends in hospital admissions among children with asthma in Spain (2011-2020).

The purpose of this study is to describe and assess changes in incidence, clinical conditions, use of mechanical ventilation, length of hospital stay (LOHS), and in-hospital mortality (IHM) among children hospitalized with asthma in Spain from 2011 to 2020. We analyzed children aged 0 to 15 years hospitalized with an ICD code for asthma included in the Spanish National Hospital Discharge Database (SNHDD). The analysis was conducted for asthma as the primary diagnosis and with asthma in any diagnosis position. Joinpoint regression was used to assess time trends in incidence. We included a total of 85,664 children hospitalized with asthma; of these, 46,727 (54.55%) had asthma coded as the primary diagnosis. The number of boys was higher than the number of girls, irrespective of age group or diagnostic position. The frequency of asthma as primary diagnosis decreased from 55.7% in 2011 to 43.96% in 2020 (p < 0.001). The incidence of hospitalizations because of asthma decreased significantly from 2011 to 2020, with a faster decrease from 2018 onwards. Over time, the proportion of older children increased. In the year 2020, only 55 children had codes for asthma and COVID-19 in their discharge report, and this infection had no effect on hospitalizations this year. A significant increase in the use of non-invasive ventilation (NIV) was observed over time. Irrespective of the diagnostic position, LOHS and IHM remained stable over time, with the IHM under 0.1%.  Conclusion: Our results show a decrease in the incidence of hospital admissions with asthma either as the primary diagnosis or in any position. The age of children hospitalized seems to be increasing as the use of NIV. Better management of the disease from primary care and the emergency department as is the use of NIV could explain the reduction in incidence. What is Known: • Asthma is the most common chronic respiratory in childhood in high income countries. • The incidence of hospital admissions with asthma and associated factors is one of the best sources of information on morbidity trends and prognosis. What is New: • The incidence of hospital admissions for asthma in Spain decreased in children between 2011 and 2020 with a more frequent use of non-invasive mechanical ventilation and low mortality rates. • COVID-19 did not cause an increase in admissions with asthma in the year 2020.

Severe maternal morbidity: admission shift from intensive care unit to obstetric high-dependency unit.

BACKGROUND: To study temporal trends of intensive care unit (ICU) admission in obstetric population after the introduction of obstetric high-dependency unit (HDU). METHODS: This is a retrospective study of consecutive obstetric patients admitted to the ICU/HDU in a provincial referral center in China from January 2014 to December 2019. The collected information included maternal demographic characteristics, indications for ICU and HDU admission, the length of ICU stay, the total length of in-hospital stay and APACHE II score. Chi-square and ANOVA tests were used to determine statistical significance. The temporal changes were assessed with chi-square test for linear trend. RESULTS: A total of 40,412 women delivered and 447 (1.11%) women were admitted to ICU in this 6-year period. The rate of ICU admission peaked at 1.59% in 2016 and then dropped to 0.67% in 2019 with the introduction of obstetric HDU. The average APACHE II score increased significantly from 6.8 to 12.3 (P < 0.001) and the average length of ICU stay increased from 1.7 to 7.1 days (P < 0.001). The main indications for maternal ICU admissions were hypertensive disorders in pregnancy (39.8%), cardiac diseases (24.8%), and other medical disorders (21.5%); while the most common reasons for referring to HDU were hypertensive disorders of pregnancy (46.5%) and obstetric hemorrhage (43.0%). The establishment of HDU led to 20% reduction in ICU admission, which was mainly related to obstetric indications. CONCLUSIONS: The introduction of HDU helps to reduce ICU utilization in obstetric population.

Predicting regional COVID-19 hospital admissions in Sweden using mobility data.

The transmission of COVID-19 is dependent on social mixing, the basic rate of which varies with sociodemographic, cultural, and geographic factors. Alterations in social mixing and subsequent changes in transmission dynamics eventually affect hospital admissions. We employ these observations to model and predict regional hospital admissions in Sweden during the COVID-19 pandemic. We use an SEIR-model for each region in Sweden in which the social mixing is assumed to depend on mobility data from public transport utilisation and locations for mobile phone usage. The results show that the model could capture the timing of the first and beginning of the second wave of the pandemic 3 weeks in advance without any additional assumptions about seasonality. Further, we show that for two major regions of Sweden, models with public transport data outperform models using mobile phone usage. We conclude that a model based on routinely collected mobility data makes it possible to predict future hospital admissions for COVID-19 3 weeks in advance.

A novel benchmark for COVID-19 pandemic testing effectiveness enables the accurate prediction of new Intensive Care Unit admissions.

The positivity rate of testing is currently used both as a benchmark of testing adequacy and for assessing the evolution of the COVID-19 pandemic. However, since the former is a prerequisite for the latter, its interpretation is often conflicting. We propose as a benchmark for COVID-19 testing effectiveness a new metric, termed 'Severity Detection Rate' (SDR), that represents the daily needs for new Intensive Care Unit (ICU) admissions, per 100 cases detected (t - i) days ago, per 10,000 tests performed (t - i) days ago. Based on the announced COVID-19 monitoring data in Greece from May 2020 until August 2021, we show that beyond a certain threshold of daily tests, SDR reaches a plateau of very low variability that begins to reflect testing adequacy. Due to the stabilization of SDR, it was possible to predict with great accuracy the daily needs for new ICU admissions, 12 days ahead of each testing data point, over a period of 10 months, with Pearson r = 0.98 (p = 10-197), RMSE = 7.16. We strongly believe that this metric will help guide the timely decisions of both scientists and government officials to tackle pandemic spread and prevent ICU overload by setting effective testing requirements for accurate pandemic monitoring. We propose further study of this novel metric with data from more countries to confirm the validity of the current findings.

Changes in admissions, and hospitalization outcomes of IBD patients in an Italian tertiary referral center over a 13-year period.

OBJECTIVE: The management of Inflammatory Bowel Disease (IBD) has changed significantly in recent years, mainly due to the introduction of biologic medications, however, other factors may also have a role. The aim of this study was to evaluate the evolution of IBD admissions, including trends, modality of admission and rates of surgical intervention, in a tertiary care center. PATIENTS AND METHODS: Hospitalization of patients with a diagnosis of Crohn's disease (CD) or ulcerative colitis (UC) were identified between 2000 and 2013, using ICD-9-CM codes for IBD, from our hospital database. The following parameters were evaluated for each admission: type of admission (ordinary vs. day care service), mode of admission (elective vs. emergency care, for ordinary admissions only), admission code, surgical procedures and complication rates. Comparison between pre- and post-biologic therapy introduction years was also performed. RESULTS: Between 2000 and 2013 a total of 8834 IBD-related admissions were recorded. Hospitalizations increased linearly reaching a peak in 2006, with a downward trend in the following years. The downward trend was especially marked for patients younger than 40 years. No significant differences in hospitalization trends between CD and UC were recorded. Disease flare represented the cause of hospitalization in approximately 50% of cases. Overall, 10.8% of patients underwent surgery with no difference between the two conditions. Complications occurred in 28.7% of admissions. CONCLUSIONS: Hospitalizations for IBD patients have decreased in recent years, especially in younger patients. However, a significant proportion of patients are still admitted to complete diagnostic workup, indicating the need to better implement outpatient services. A clear reduction in surgery occurrence over time could not be observed in our study.

Comparative study between admission, orthopaedic surgery, and economic trends during Covid-19 and non-Covid-19 pandemic in an Italian tertiary hospital: a retrospective review.

BACKGROUND: The COVID-19 pandemic represents one of the most massive health emergencies in the last century and has caused millions of deaths worldwide and a massive economic and social burden. The aim of this study was to evaluate how the COVID-19 pandemic-during the Italian lockdown period between 8 March and 4 May 2020-influenced orthopaedic access for traumatic events to the Emergency Department (ER). METHODS: A retrospective review of the admission to the emergency room and the discharge of the trauma patients' records was performed during the period between 8 March and 4 May 2020 (block in Italy), compared to the same period of the previous year (2019). Patients accesses, admissions, days of hospitalisation, frequency, fracture site, number and type of surgery, the time between admission and surgery, days of hospitalisation, and treatment cost according to the diagnosis-related group were collected. Chi-Square and ANOVA test were used to compare the groups. RESULTS: No significant statistical difference was found for the number of emergency room visits and orthopaedic hospitalisations (p < 0.53) between the year 2019 (9.5%) and 2020 (10.81%). The total number of surgeries in 2019 was 119, while in 2020, this was just 48 (p < 0.48). A significant decrease in the mean cost of orthopaedic hospitalisations was detected in 2020 compared (261.431 euros, equal to - 52.07%) relative to the same period in 2019 (p = 0.005). Although all the surgical performances have suffered a major decline, the most frequent surgery in 2020 was intramedullary femoral nailing. CONCLUSION: We detected a decrease in traumatic occasions during the lockdown period, with a decrease in fractures in each district and a consequent decrease in the diagnosis-related group (DRG).

Temporal trends in emergency admissions for diabetic ketoacidosis in people with diabetes in England before and during the COVID-19 pandemic: a population-based study.

BACKGROUND: Diabetic ketoacidosis (DKA) has been reported to be increasing in frequency during the COVID-19 pandemic. We aimed to examine the rates of DKA hospital admissions and the patient demographics associated with DKA during the pandemic compared with in prepandemic years. METHODS: Using a comprehensive, multiethnic, national dataset, the Secondary Uses Service repository, we extracted all emergency hospital admissions in England coded with DKA from March 1 to June 30, 2020 (first wave of the pandemic), July 1 to Oct 31, 2020 (post-first wave), and Nov 1, 2020, to Feb 28, 2021 (second wave), and compared these with DKA admissions in the equivalent periods in 2017-20. We also examined baseline characteristics, mortality, and trends in patients who were admitted with DKA. FINDINGS: There were 8553 admissions coded with DKA during the first wave, 8729 during the post-first wave, and 10 235 during the second wave. Compared with preceding years, DKA admissions were 6% (95% CI 4-9; p<0·0001) higher in the first wave of the pandemic (from n=8048), 6% (3-8; p<0·0001) higher in the post-first wave (from n=8260), and 7% (4-9; p<0·0001) higher in the second wave (from n=9610). In the first wave, DKA admissions reduced by 19% (95% CI 16-21) in those with pre-existing type 1 diabetes (from n=4965 to n=4041), increased by 41% (35-47) in those with pre-existing type 2 diabetes (from n=2010 to n=2831), and increased by 57% (48-66) in those with newly diagnosed diabetes (from n=1072 to n=1681). Compared with prepandemic, type 2 diabetes DKA admissions were similarly common in older individuals and men but were higher in those of non-White ethnicities during the first wave. The increase in newly diagnosed DKA admissions occurred across all age groups and these were significantly increased in men and people of non-White ethnicities. In the post-first wave, DKA admissions did not return to the baseline level of previous years; DKA admissions were 14% (11-17) lower in patients with type 1 diabetes (from n=5208 prepandemic to n=4491), 30% (24-36) higher in patients with type 2 diabetes (from n=2011 to n=2613), and 56% (47-66) higher in patients with newly diagnosed diabetes (from n=1041 to n=1625). During the second wave, DKA admissions were 25% (22-27) lower in patients with type 1 diabetes (from n=5769 prepandemic to n=4337), 50% (44-56) higher in patients with type 2 diabetes (from n=2608 to n=3912), and 61% (52-70) higher in patients with newly diagnosed diabetes (from n=1234 to n=1986). INTERPRETATION: Our results provide evidence for differences in the numbers and characteristics of people presenting with DKA during the COVID-19 pandemic compared with in the preceding 3 years. Greater awareness of risk factors for DKA in type 2 diabetes and vigilance for newly diagnosed diabetes presenting with DKA during the COVID-19 pandemic might help mitigate the increased impact of DKA. FUNDING: None.

Rates of Influenza-Associated Hospitalization, Intensive Care Unit Admission, and In-Hospital Death by Race and Ethnicity in the United States From 2009 to 2019.

Importance: Racial and ethnic minority groups, such as Black, Hispanic, American Indian or Alaska Native, and Asian or Pacific Islander persons, often experience higher rates of severe influenza disease. Objective: To describe rates of influenza-associated hospitalization, intensive care unit (ICU) admission, and in-hospital death by race and ethnicity over 10 influenza seasons. Design, Setting, and Participants: This cross-sectional study used data from the Influenza-Associated Hospitalization Surveillance Network (FluSurv-NET), which conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in selected counties, representing approximately 9% of the US population. Influenza hospitalizations from the 2009 to 2010 season to the 2018 to 2019 season were analyzed. Data were analyzed from October 2020 to July 2021. Main Outcomes and Measures: The main outcomes were age-adjusted and age-stratified rates of influenza-associated hospitalization, ICU admission, and in-hospital death by race and ethnicity overall and by influenza season. Results: Among 113 352 persons with an influenza-associated hospitalization (34 436 persons [32.0%] aged ≥75 years; 61 009 [53.8%] women), 70 225 persons (62.3%) were non-Hispanic White (White), 24 850 persons (21.6%) were non-Hispanic Black (Black), 11 903 persons (10.3%) were Hispanic, 5517 persons (5.1%) were non-Hispanic Asian or Pacific Islander, and 857 persons (0.7%) were non-Hispanic American Indian or Alaska Native. Among persons aged younger than 75 years and compared with White persons of the same ages, Black persons were more likely to be hospitalized (eg, age 50-64 years: rate ratio [RR], 2.50 95% CI, 2.43-2.57) and to be admitted to an ICU (eg, age 50-64 years: RR, 2.09; 95% CI, 1.96-2.23). Among persons aged younger than 50 years and compared with White persons of the same ages, American Indian or Alaska Native persons were more likely to be hospitalized (eg, age 18-49 years: RR, 1.72; 95% CI, 1.51-1.96) and to be admitted to an ICU (eg, age 18-49 years: RR, 1.84; 95% CI, 1.40-2.42). Among children aged 4 years or younger and compared with White children, hospitalization rates were higher in Black children (RR, 2.21; 95% CI, 2.10-2.33), Hispanic children (RR, 1.87; 95% CI, 1.77-1.97), American Indian or Alaska Native children (RR, 3.00; 95% CI, 2.55-3.53), and Asian or Pacific Islander children (RR, 1.26; 95% CI, 1.16-1.38), as were rates of ICU admission (Black children: RR, 2.74; 95% CI, 2.43-3.09; Hispanic children: RR, 1.96; 95% CI, 1.73-2.23; American Indian and Alaska Native children: RR, 3.51; 95% CI, 2.45-5.05). In this age group and compared with White children, in-hospital death rates were higher among Hispanic children (RR, 2.98; 95% CI, 1.23-7.19), Black children (RR, 3.39; 95% CI, 1.40-8.18), and Asian or Pacific Islander children (RR, 4.35; 95% CI, 1.55-12.22). Few differences were observed in rates of severe influenza-associated outcomes by race and ethnicity among adults aged 75 years or older. For example, in this age group, compared with White adults, hospitalization rates were slightly higher only among Black adults (RR, 1.05; 95% CI 1.02-1.09). Overall, Black persons had the highest age-adjusted hospitalization rate (68.8 [95% CI, 68.0-69.7] hospitalizations per 100 000 population) and ICU admission rate (11.6 [95% CI, 11.2-11.9] admissions per 100 000 population). Conclusions and Relevance: This cross-sectional study found racial and ethnic disparities in rates of severe influenza-associated disease. These data identified subgroups for whom improvements in influenza prevention efforts could be targeted.

Impact of the SARS-COV-2 Pandemic on the Endovascular Treatment of Acute Stroke - an Italian Single-Center Experience.

OBJECTIVES: The SARS-CoV-2 pandemic greatly influenced the overall quality of healthcare. The purpose of this study was to compare the time variables for acute stroke treatment and evaluate differences in the pre-hospital and in-hospital care before and during the SARS-CoV-2 pandemic, as well as between the first and second waves. MATERIALS AND METHODS: Observational and retrospective study from an Italian hospital, including patients who underwent thrombectomy between January 1st 2019 and December 31st 2020. RESULTS: Out of a total of 594 patients, 301 were treated in 2019 and 293 in 2020. The majority observed in 2019 came from spoke centers (67,1%), while in 2020 more than half (52%, p < 0.01) were evaluated at the hospital's emergency room directly (ER-NCGH). When compared to 2019, time metrics were globally increased in 2020, particularly in the ER-NCGH groups during the period of the first wave (N = 24 and N = 56, respectively): "Onset-to-door":50,5 vs 88,5, p < 0,01; "Arrival in Neuroradiology - groin":13 vs 25, p < 0,01; "Door-to-groin":118 vs 143,5, p = 0,02; "Onset-to-groin":180 vs 244,5, p < 0,01; "Groin-to-recanalization": 41 vs 49,5, p = 0,03. When comparing ER-NCGH groups between the first (N = 56) and second (N = 49) waves, there was an overall improvement in times, namely in the "Door-to-CT" (47,5 vs 37, p < 0,01), "Arrival in Neuroradiology - groin" (25 vs 20, p = 0,03) and "Onset-to-groin" (244,5 vs 227,5, p = 0,02). CONCLUSIONS: During the SARS-CoV-2 pandemic, treatment for stroke patients was delayed, particularly during the first wave. Reallocation of resources and the shutting down of spoke centers may have played a determinant role.

Risk of contracting SARS-CoV-2 (COVID-19) from hospital admission and the impact of protection efforts on acute stroke treatment.

BACKGROUND: It is unclear how interventions designed to restrict community and in-hospital exposure to the SARS-CoV-2 (COVID-19) virus influenced stroke care for patients seeking acute treatment. Therefore, we aimed to determine how these COVID-19 interventions impacted acute stroke treatment times and to assess the risk of contracting COVID-19 due to their stay in our medical center. METHODS: Retrospective, single center, two-phase study evaluating hospital and community trends from 12/2019 - 04/2020 compared to the previous year and pre/post (n = 156/93) intervention implementation. Phase I assessed stroke treatment times, delay to hospital arrival, and witnessed stroke volume. Phase II, a post-implementation telephone survey, assessed risk of developing symptoms or testing positive for COVID-19. RESULTS: Stroke volume declined by 29% (p < .05) from April to March compared to the previous year. However, no significant delays in seeking medical care (pre Mdn=112, post Mdn=95, p = .34) was observed. Witnessed stroke volume decreased 11% (p < .001) compared to the pre-implementation group, but no significant delay in IV alteplase (pre Mdn=22 mins; post Mdn=26 mins, p = .08) nor endovascular treatment (pre Mdn=60 mins; post Mdn=80 mins, p = .45) was observed. In Phase II, 63 patients participated, two tested (3%) COVID-19 positive during admission and four (6%) within two weeks of discharge. COVID-19 contraction risk during and after hospitalization remained similar to the general population (RR=1.75, 95%CI: 0.79-3.63). Overall results indicated a marked decrease in stroke volume, no significant delays to either seek or provide acute stroke care were evident, and COVID-19 contraction risk was low. CONCLUSIONS: Seeking acute stroke medical care outweighs the risk of COVID-19 exposure.

COVID-19 Lockdown Effects on Acute Stroke Care in Latin America.

OBJECTIVES: COVID-19 pandemic has forced important changes in health care worldwide. Stroke care networks have been affected, especially during peak periods. We assessed the impact of the pandemic and lockdowns in stroke admissions and care in Latin America. MATERIALS AND METHODS: A multinational study (7 countries, 18 centers) of patients admitted during the pandemic outbreak (March-June 2020). Comparisons were made with the same period in 2019. Numbers of cases, stroke etiology and severity, acute care and hospitalization outcomes were assessed. RESULTS: Most countries reported mild decreases in stroke admissions compared to the same period of 2019 (1187 vs. 1166, p = 0.03). Among stroke subtypes, there was a reduction in ischemic strokes (IS) admissions (78.3% vs. 73.9%, p = 0.01) compared with 2019, especially in IS with NIHSS 0-5 (50.1% vs. 44.9%, p = 0.03). A substantial increase in the proportion of stroke admissions beyond 48 h from symptoms onset was observed (13.8% vs. 20.5%, p < 0.001). Nevertheless, no differences in total reperfusion treatment rates were observed, with similar door-to-needle, door-to-CT, and door-to-groin times in both periods. Other stroke outcomes, as all-type mortality during hospitalization (4.9% vs. 9.7%, p < 0.001), length of stay (IQR 1-5 days vs. 0-9 days, p < 0.001), and likelihood to be discharged home (91.6% vs. 83.0%, p < 0.001), were compromised during COVID-19 lockdown period. CONCLUSIONS: In this Latin America survey, there was a mild decrease in admissions of IS during the COVID-19 lockdown period, with a significant delay in time to consultations and worse hospitalization outcomes.

Hospital admission for type 2 diabetes mellitus under the Universal Coverage Scheme in Thailand: A time- and geographical-trend analysis, 2009-2016.

BACKGROUND: Descriptive analyses of 2009-2016 were performed using the data of the Universal Coverage Scheme (UCS) which covers nearly 70 percent of the Thai population. The analyses described the time and geographical trends of nationwide admission rates of type 2 diabetes mellitus (T2DM) and its complications, including chronic kidney disease (CKD), myocardial infarction, cerebrovascular diseases, retinopathy, cataract, and diabetic foot amputation. METHODS AND FINDINGS: The database of T2DM patients aged 15-100 years who were admitted between 2009 and 2016 under the UCS and that of the UCS population were retrieved for the analyses. The admitted cases of T2DM were extracted from the database using disease codes of principal and secondary diagnoses defined by the International Classification of Diseases 9th and 10th Revisions. The T2DM admission rates in 2009-2016 were the number of admissions divided by the number of the UCS population. The standardized admission rates (SARs)were further estimated in contrast to the expected number of admissions considering age and sex composition of the UCS population in each region. A linearly increased trend was found in T2DM admission rates from 2009 to 2016. Female admission rates were persistently higher than that of males. In 2016, an increase in the T2DM admission rates was observed among the older ages relative to that in 2009. Although the SARs of T2DM were generally higher in Bangkok and central regions in 2009, except that with CKD and foot amputation which had higher trends in northeastern regions, the geographical inequalities were fairly reduced by 2016. CONCLUSION: Admission rates of T2DM and its major complications increased in Thailand from 2009 to 2016. Although the overall geographical inequalities in the SARs of T2DM were reduced in the country, further efforts are required to improve the health system and policies focusing on risk factors and regions to manage the increasing T2DM.