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Hospital admissions in the US fell dramatically with the onset of the coronavirus disease 2019 (COVID-19) pandemic. However, little is known about differences in admissions patterns among patient groups or the extent of the rebound. In this study of approximately one million medical admissions from a large, nationally representative hospitalist group, we found that declines in non-COVID-19 admissions from February to April 2020 were generally similar across patient demographic subgroups and exceeded 20 percent for all primary admission diagnoses. By late June/early July 2020, overall non-COVID-19 admissions had rebounded to 16 percent below prepandemic baseline volume (8 percent including COVID-19 admissions). Non-COVID-19 admissions were substantially lower for patients residing in majority-Hispanic neighborhoods (32 percent below baseline) and remained well below baseline for patients with pneumonia (-44 percent), chronic obstructive pulmonary disease/asthma (-40 percent), sepsis (-25 percent), urinary tract infection (-24 percent), and acute ST-elevation myocardial infarction (-22 percent). Health system leaders and public health authorities should focus on efforts to ensure that patients with acute medical illnesses can obtain hospital care as needed during the pandemic to avoid adverse outcomes.

Introduction It is currently admitted that adverse drug reactions (ADRs) account for a great burden of disease. Of particular concern are ADR-induced hospital admissions, particularly in the elderly; they receive most of the medications and they are the most prone to develop ADRs. Therefore, our aim was to carry out a study of ADR-induced hospital admissions focused on the elderly population. Methods For the purpose, a systematic review and meta-analysis was performed of those studies addressing ADR-induced hospital admissions in patients over 60 years of age. A computerized search of the literature was carried out in the main databases. The search spans from 1988 to 2015. A pooled prevalence figure was calculated with 95% CIs; heterogeneity was also explored. Results The final number of selected articles was 42; all of them were published between January 1988 and August 2015. The overall average percentage of hospital admissions was 8.7% (95% CI, 7.6–9.8%). NSAIDs are one of the medication classes more frequently related to these admissions (percentages range from 2.3 to 33.3%). Inappropriate medication as a risk factor was studied in nine studies, four found a statistically significant relationship between those medications and hospital admissions. Conclusions Circa one in ten hospital admissions of older patients are due to ADRs. A great burden of disease is due to a few and identifiable medication classes; in most of the cases, the reactions are well known and probably preventable. A sense of purpose and determination is needed by health authorities to face this problem. Doctors, on their part, should be aware when prescribing some specific identifiable medications to these patients. Key points One in ten hospital admissions in older patients are due to ADRs; NSAIDs are the medications the most related with these admissions, followed by other common medications used in patients of this age, such as beta-blockers. A great burden of disease is due to medications that are intended to cure or alleviate disease; this burden of disease is not only painful for the patients but also costly . Identified risk factors are particular medication classes and polymedication. In most of the cases, reactions are probably preventable .

Azithromycin, an antibiotic with potential antiviral and anti-inflammatory properties, has been used to treat COVID-19, but evidence from community randomised trials is lacking. We aimed to assess the effectiveness of azithromycin to treat suspected COVID-19 among people in the community who had an increased risk of complications. In this UK-based, primary care, open-label, multi-arm, adaptive platform randomised trial of interventions against COVID-19 in people at increased risk of an adverse clinical course (PRINCIPLE), we randomly assigned people aged 65 years and older, or 50 years and older with at least one comorbidity, who had been unwell for 14 days or less with suspected COVID-19, to usual care plus azithromycin 500 mg daily for three days, usual care plus other interventions, or usual care alone. The trial had two coprimary endpoints measured within 28 days from randomisation: time to first self-reported recovery, analysed using a Bayesian piecewise exponential, and hospital admission or death related to COVID-19, analysed using a Bayesian logistic regression model. Eligible participants with outcome data were included in the primary analysis, and those who received the allocated treatment were included in the safety analysis. The trial is registered with ISRCTN, ISRCTN86534580. The first participant was recruited to PRINCIPLE on April 2, 2020. The azithromycin group enrolled participants between May 22 and Nov 30, 2020, by which time 2265 participants had been randomly assigned, 540 to azithromycin plus usual care, 875 to usual care alone, and 850 to other interventions. 2120 (94%) of 2265 participants provided follow-up data and were included in the Bayesian primary analysis, 500 participants in the azithromycin plus usual care group, 823 in the usual care alone group, and 797 in other intervention groups. 402 (80%) of 500 participants in the azithromycin plus usual care group and 631 (77%) of 823 participants in the usual care alone group reported feeling recovered within 28 days. We found little evidence of a meaningful benefit in the azithromycin plus usual care group in time to first reported recovery versus usual care alone (hazard ratio 1·08, 95% Bayesian credibility interval [BCI] 0·95 to 1·23), equating to an estimated benefit in median time to first recovery of 0·94 days (95% BCI −0·56 to 2·43). The probability that there was a clinically meaningful benefit of at least 1·5 days in time to recovery was 0·23. 16 (3%) of 500 participants in the azithromycin plus usual care group and 28 (3%) of 823 participants in the usual care alone group were hospitalised (absolute benefit in percentage 0·3%, 95% BCI −1·7 to 2·2). There were no deaths in either study group. Safety outcomes were similar in both groups. Two (1%) of 455 participants in the azothromycin plus usual care group and four (1%) of 668 participants in the usual care alone group reported admission to hospital during the trial, not related to COVID-19. Our findings do not justify the routine use of azithromycin for reducing time to recovery or risk of hospitalisation for people with suspected COVID-19 in the community. These findings have important antibiotic stewardship implications during this pandemic, as inappropriate use of antibiotics leads to increased antimicrobial resistance, and there is evidence that azithromycin use increased during the pandemic in the UK. UK Research and Innovation and UK Department of Health and Social Care.

England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories. This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions. The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69–83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500–5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700–1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness. Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures. National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.

AbstractObjectiveTo estimate the risks of daily hospital admissions for cause specific major cardiovascular diseases associated with short term exposure to ambient fine particulate matter (aerodynamic diameter ≤2.5 μm; PM2.5) pollution in China.DesignNational time series study.Setting184 major cities in China.Population8 834 533 hospital admissions for cardiovascular causes in 184 Chinese cities recorded by the national database of Urban Employee Basic Medical Insurance from 1 January 2014 to 31 December 2017.Main outcome measuresDaily counts of city specific hospital admissions for primary diagnoses of ischaemic heart disease, heart failure, heart rhythm disturbances, ischaemic stroke, and haemorrhagic stroke among different demographic groups were used to estimate the associations between PM2.5 and morbidity. An overdispersed generalised additive model was used to estimate city specific associations between PM2.5 and cardiovascular admissions, and random effects meta-analysis used to combine the city specific estimates.ResultsOver the study period, a mean of 47 hospital admissions per day (standard deviation 74) occurred for cardiovascular disease, 26 (53) for ischaemic heart disease, one (five) for heart failure, two (four) for heart rhythm disturbances, 14 (28) for ischaemic stroke, and two (four) for haemorrhagic stroke. At the national average level, an increase of 10 μg/m3 in PM2.5 was associated with a 0.26% (95% confidence interval 0.17% to 0.35%) increase in hospital admissions on the same day for cardiovascular disease, 0.31% (0.22% to 0.40%) for ischaemic heart disease, 0.27% (0.04% to 0.51%) for heart failure, 0.29% (0.12% to 0.46%) for heart rhythm disturbances, and 0.29% (0.18% to 0.40%) for ischaemic stroke, but not with haemorrhagic stroke (−0.02% (−0.23% to 0.19%)). The national average association of PM2.5 with cardiovascular disease was slightly non-linear, with a sharp slope at PM2.5 levels below 50 μg/m3, a moderate slope at 50-250 μg/m3, and a plateau at concentrations higher than 250 μg/m3. Compared with days with PM2.5 up to 15 μg/m3, days with PM2.5 of 15-25, 25-35, 35-75, and 75 μg/m3 or more were significantly associated with increases in cardiovascular admissions of 1.1% (0 to 2.2%), 1.9% (0.6% to 3.2%), 2.6% (1.3% to 3.9%), and 3.8% (2.1% to 5.5%), respectively.According to projections, achieving the Chinese grade 2 (35 μg/m3), Chinese grade 1 (15 μg/m3), and World Health Organization (10 μg/m3) regulatory limits for annual mean PM2.5 concentrations would reduce the annual number of admissions for cardiovascular disease in China. Assuming causality, which should be done with caution, this reduction would translate into an estimated 36 448 (95% confidence interval 24 441 to 48 471), 85 270 (57 129 to 113 494), and 97 516 (65 320 to 129 820), respectively.ConclusionsThese data suggest that in China, short term exposure to PM2.5 is associated with increased hospital admissions for all major cardiovascular diseases except for haemorrhagic stroke, even for exposure levels not exceeding the current regulatory limits.

BackgroundAdmission of infants to hospital with bronchiolitis consumes considerable healthcare resources each winter. We report an analysis of hospital admissions in England over five decades.MethodsData were analysed from the Hospital In-Patient Enquiry (HIPE, 1968–1985), Hospital Episode Statistics (HES, 1989–2011), Oxford Record Linkage Study (ORLS, 1963–2011) and Paediatric Intensive Care Audit Network (PICANet, 2003–2012). Cases were identified using International Classification of Diseases (ICD) codes in discharge records. Bronchiolitis was given a separate code in ICD9 (used in England from 1979). Geographical variation was analysed using Local Authority area boundaries. Maternal and perinatal risk factors associated with bronchiolitis and subsequent admissions for asthma were analysed using record-linkage.ResultsAll-England HIPE and HES data recorded 468 138 episodes of admission for bronchiolitis in infants aged <1 year between 1979 and 2011. In 2011 the estimated annual hospital admission rate was 46.1 (95% CI 45.6 to 46.6) per 1000 infants aged <1 year. Between 2004 and 2011 the rates rose by an average of 1.8% per year in the all-England HES data, whereas admission rates to paediatric intensive care changed little (1.3 to 1.6 per 1000 infants aged <1 year). A fivefold geographical variation in hospital admission rates was observed. Young maternal age, low social class, low birth weight and maternal smoking were among factors associated with an increased risk of hospital admission with bronchiolitis.ConclusionsHospital admissions for infants with bronchiolitis have increased substantially in recent years. However, cases requiring intensive care have changed little since 2004.

Emergency Department (ED) visits decreased significantly in the United States during the COVID-19 pandemic. A troubling proportion of this decrease was among patients who typically would have been admitted to the hospital, suggesting substantial deferment of care. We sought to describe and characterize the impact of COVID-19 on hospital admissions through EDs, with a specific focus on diagnosis group, age, gender, and insurance coverage. We conducted a retrospective, observational study of aggregated third-party, anonymized ED patient data. This data included 501,369 patient visits from twelve EDs in Massachusetts from 1/1/2019–9/9/2019, and 1/1/2020–9/8/2020. We analyzed the total arrivals and hospital admissions and calculated confidence intervals for the change in admissions for each characteristic. We then developed a Poisson regression model to estimate the relative contribution of each characteristic to the decrease in admissions after the statewide lockdown, corresponding to weeks 11 through 36 (3/11/2020–9/8/2020). We observed a 32% decrease in admissions during weeks 11 to 36 in 2020, with significant decreases in admissions for chronic respiratory conditions and non-orthopedic needs. Decreases were particularly acute among women and children, as well as patients with Medicare or without insurance. The most common diagnosis during this time was SARS-CoV-2. Our findings demonstrate decreased hospital admissions through EDs during the pandemic and suggest that several patient populations may have deferred necessary care. Further research is needed to determine the clinical and operational consequences of this delay.

Population aging, coupled with improvements in healthcare, may influence ICU admission trends and care practices among critically ill elderly patients (≥80 years), longitudinal data evaluating this remain limited in China. Our aim was to analyze and compare trends in ICU admissions, clinical outcomes, and resource use among critically ill elderly patients (≥80 years), in comparison with older (65-79 years) and younger (16-64 years) cohorts. We retrospectively analyzed ICU patients aged ≥16 years admitted to a tertiary referral hospital in China from January 2014 to December 2021. A total of 31,535 patients were categorized into three age groups: ≥ 80 years (11.5%), 65-79 years (30.7%), and <65 years (57.8%). ICU admission rates for elderly patients declined significantly from 13.2% in 2014 to 9.0% in 2021 (p < 0.001, relative decrease 31.8%), particularly among nonsurgical admissions. Elderly patients had higher comorbidities, greater disease severity scores, but lower daily average TISS-28 scores compared to younger cohorts. They were more likely to receive inotropic/vasopressor support and nutritional interventions, had higher blood loss due to frequent laboratory testing, and required more red blood cell transfusions. However, they were less likely to undergo invasive ventilation. The proportion of elderly patients requiring invasive ventilation decreased significantly over the study period. Despite a higher hospital mortality rate (elderly 14.1%, older 6.1%, younger 3.1%; p < 0.001), elderly patients demonstrated a more significant reduction in risk-adjusted mortality over time compared to younger patients (elderly vs. younger, 12.5% vs. 6.3%, relative reduction per year, p < 0.001). ICU admission rates for elderly patients are declining, particularly in nonsurgical cases. Less invasive life support modalities have been increasingly utilized in their care. While mortality remains higher among elderly patients, they demonstrate a more significant improvement in survival over time compared to younger cohorts.

Background Demographic aging is expected to substantially affect intensive care medicine, with a growing proportion of elderly patients and increasing clinical complexity, while resources remain limited. It is therefore critical for clinicians and health systems to understand, how intensive care unit (ICU) admissions, outcomes, and treatment intensity across patients of differing age have evolved in recent years. Longitudinal data on these parameters are scarce on the population level. Methods We conducted a retrospective population-based analysis of all German inpatient cases from 2011–2022. Hospitalizations with ICU treatment ≥ 24 h were included. Temporal trends in ICU admissions, in-hospital mortality, ICU-related deaths, and use of organ replacement therapies (ORT) were analyzed and stratified by age groups. ORTs comprised mechanical ventilation, renal replacement therapy, and extracorporeal membrane oxygenation. Results Overall, 8.4 million ICU admissions were analyzed. During the observation period, ICU admissions showed an overall decline of 12.6%, driven by reductions in patients aged 65–79 years (− 18.1%) and ≥ 80 years (− 24%), while remaining stable in younger patients. Despite fewer admissions, ICU-related mortality showed an overall increase from 14.4% to 18.9%, mainly in patients < 80 years. Overall, in-hospital deaths declined across all age groups, but the proportion of ICU-related deaths rose among patients < 80 years. ORT use increased across all age groups and was associated with persistently high mortality, particularly with combined ORTs (up to 79%). Patients aged 65–79 years received combined ORTs most frequently. Patients ≥ 80 years had the highest mortality. Conclusions ICU utilization and outcomes in Germany have shifted markedly over the past decade. Declining admissions among older patients, increasing ICU-related mortality in younger patients, and rising treatment intensity underscore age-specific differences in critical care delivery and outcomes, with important implications for ICU admission practices, treatment decisions and future resource planning.