Better COVID-19 Intensive Care Unit survival in females, independent of age, disease severity, comorbidities, and treatment

Although male Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) patients have higher Intensive Care Unit (ICU) admission rates and a worse disease course, a comprehensive analysis of female and male ICU survival and underlying factors such as comorbidities, risk factors, and/or anti-infection/inflammatory therapy administration is currently lacking. Therefore, we investigated the association between sex and ICU survival, adjusting for these and other variables. In this multicenter observational cohort study, all patients with SARS-CoV-2 pneumonia admitted to seven ICUs in one region across Belgium, The Netherlands, and Germany, and requiring vital organ support during the first pandemic wave were included. With a random intercept for a center, mixed-effects logistic regression was used to investigate the association between sex and ICU survival. Models were adjusted for age, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, comorbidities, and anti-infection/inflammatory therapy. Interaction terms were added to investigate effect modifications by sex with country and sex with obesity. A total of 551 patients (29% were females) were included. Mean age was 65.4 ± 11.2 years. Females were more often obese and smoked less frequently than males (p-value 0.001 and 0.042, respectively). APACHE II scores of females and males were comparable. Overall, ICU mortality was 12% lower in females than males (27% vs 39% respectively, p-value < 0.01) with an odds ratio (OR) of 0.62 (95%CI 0.39–0.96, p-value 0.032) after adjustment for age and APACHE II score, 0.63 (95%CI 0.40–0.99, p-value 0.044) after additional adjustment for comorbidities, and 0.63 (95%CI 0.39–0.99, p-value 0.047) after adjustment for anti-infection/inflammatory therapy. No effect modifications by sex with country and sex with obesity were found (p-values for interaction > 0.23 and 0.84, respectively). ICU survival in female SARS-CoV-2 patients was higher than in male patients, independent of age, disease severity, smoking, obesity, comorbidities, anti-infection/inflammatory therapy, and country. Sex-specific biological mechanisms may play a role, emphasizing the need to address diversity, such as more sex-specific prediction, prognostic, and therapeutic approach strategies.

The Most Dangerous Game: A Review of Head and Neck Injuries in American Football and Rugby

Study Design The investigators designed and implemented a 20-year cross-sectional study using the National Electronic Injury Surveillance System database. Objective The purpose of this study is to estimate and compare hospital admission (danger) rates between rugby and football of those who presented to the emergency department with head and neck injuries after playing these sports. Methods The primary predictor variable was sport played. The primary outcome variable was danger, measured by hospital admission rates. Results Over the past 20 years, there has been a trend of decreasing incidence of injuries presenting to the emergency department in both sports. There was no difference in the rate of hospital admission when comparing football and rugby (OR, 1.2; P = .1). Male gender was associated with an increased risk of admission. Other variables associated with hospital admission included white racial group, injury taking place in the fall, being either young (15–24 years old) or senior (65 years of age and over), and being injured at school or at a sport/recreational facility. Conclusions There is no difference in danger as measured by admission rates between American football and rugby. There exists, however, several variables that are associated with admission when sustaining injury to the head and neck, when playing these two sports.

Indirect effects of the covid-19 pandemic on childhood infection in England: population based observational study

ObjectiveTo assess the impact of the covid-19 pandemic on hospital admission rates and mortality outcomes for childhood respiratory infections, severe invasive infections, and vaccine preventable disease in England.DesignPopulation based observational study of 19 common childhood respiratory, severe invasive, and vaccine preventable infections, comparing hospital admission rates and mortality outcomes before and after the onset of the pandemic in England.SettingHospital admission data from every NHS hospital in England from 1 March 2017 to 30 June 2021 with record linkage to national mortality data.PopulationChildren aged 0-14 years admitted to an NHS hospital with a selected childhood infection from 1 March 2017 to 30 June 2021.Main outcome measuresFor each infection, numbers of hospital admissions every month from 1 March 2017 to 30 June 2021, percentage changes in the number of hospital admissions before and after 1 March 2020, and adjusted odds ratios to compare 60 day case fatality outcomes before and after 1 March 2020.ResultsAfter 1 March 2020, substantial and sustained reductions in hospital admissions were found for all but one of the 19 infective conditions studied. Among the respiratory infections, the greatest percentage reductions were for influenza (mean annual number admitted between 1 March 2017 and 29 February 2020 was 5379 and number of children admitted from 1 March 2020 to 28 February 2021 was 304, 94% reduction, 95% confidence interval 89% to 97%), and bronchiolitis (from 51 655 to 9423, 82% reduction, 95% confidence interval 79% to 84%). Among the severe invasive infections, the greatest reduction was for meningitis (50% reduction, 47% to 52%). For the vaccine preventable infections, reductions ranged from 53% (32% to 68%) for mumps to 90% (80% to 95%) for measles. Reductions were seen across all demographic subgroups and in children with underlying comorbidities. Corresponding decreases were also found for the absolute numbers of 60 day case fatalities, although the proportion of children admitted for pneumonia who died within 60 days increased (age-sex adjusted odds ratio 1.71, 95% confidence interval 1.43 to 2.05). More recent data indicate that some respiratory infections increased to higher levels than usual after May 2021.ConclusionsDuring the covid-19 pandemic, a range of behavioural changes (adoption of non-pharmacological interventions) and societal strategies (school closures, lockdowns, and restricted travel) were used to reduce transmission of SARS-CoV-2, which also reduced admissions for common and severe childhood infections. Continued monitoring of these infections is required as social restrictions evolve.

Expert Arguments for Trends of Psychiatric Bed Numbers: A Systematic Review of Qualitative Data

Introduction: Mental health policies have encouraged removals of psychiatric beds in many countries. It is under debate whether to continue those trends. We conducted a systematic review of expert arguments for trends of psychiatric bed numbers.Methods: We searched seven electronic databases and screened 15,479 papers to identify expert opinions, arguments and recommendations for trends of psychiatric bed numbers, published until December 2020. Data were synthesized using thematic analysis and classified into arguments to maintain or increase numbers and to reduce numbers.Results: One hundred six publications from 25 countries were included. The most common themes arguing for reductions of psychiatric bed numbers were inadequate use of inpatient care, better integration of care and better use of community care. Arguments to maintain or increase bed numbers included high demand of psychiatric beds, high occupancy rates, increasing admission rates, criminalization of mentally ill, lack of community care and inadequately short length of stay. Cost effectiveness and quality of care were used as arguments for increase or decrease.Conclusions: The expert arguments presented here may guide and focus future debate on the required psychiatric bed numbers. The recommendations may help policymakers to define targets for psychiatric bed numbers. Arguments need careful local evaluation, especially when supporting opposite directions of trends in different contexts.

Trends in inpatient care for psychiatric disorders in NHS hospitals across England, 1998/99–2019/20: an observational time series analysis

Purpose It is unclear how hospitals are responding to the mental health needs of the population in England, against a backdrop of diminishing resources. We aimed to document patterns in hospital activity by psychiatric disorder and how these have changed over the last 22 years. Methods In this observational time series analysis, we used routinely collected data on all NHS hospitals in England from 1998/99 to 2019/20. Trends in hospital admissions and bed days for psychiatric disorders were smoothed using negative binomial regression models with year as the exposure and rates (per 1000 person-years) as the outcome. When linear trends were not appropriate, we fitted segmented negative binomial regression models with one change-point. We stratified by gender and age group [children (0–14 years); adults (15 years +)]. Results Hospital admission rates and bed days for all psychiatric disorders decreased by 28.4 and 38.3%, respectively. Trends were not uniform across psychiatric disorders or age groups. Admission rates mainly decreased over time, except for anxiety and eating disorders which doubled over the 22-year period, significantly increasing by 2.9% (AAPC = 2.88; 95% CI: 2.61–3.16; p < 0.001) and 3.4% (AAPC = 3.44; 95% CI: 3.04–3.85; p < 0.001) each year. Inpatient hospital activity among children showed more increasing and pronounced trends than adults, including an increase of 212.9% for depression, despite a 63.8% reduction for adults with depression during the same period. Conclusion In the last 22 years, there have been overall reductions in hospital activity for psychiatric disorders. However, some disorders showed pronounced increases, pointing to areas of growing need for inpatient psychiatric care, especially among children.

PREDICTION OF DIABETES SCREENING BY USING DATA MINING ALGORITHMS

Diabetes is one of the most common non-communicable diseases in the world. Diabetes affects the ability to produce the hormone insulin. Thus, complications may occur if diabetes remains untreated and unidentified. That features a significant contribution to increased morbidity, mortality, and admission rates of patients in both developed and developing countries. When disease is not detected early, it leads to complications. Medical records of the cases were retrospective. Anthropometric and biochemical information was collected. From this data, four ML classification algorithms, including Decision Tree (J48), Naive-Bayes, PART rule induction, and JRIP, were used to prognosticate diabetes. Precision, recall, F-Measure, Receiver Operating Characteristics (ROC) scores, and the confusion matrix were calculated to determine the performance of the various algorithms. The performance was also measured by sensitivity and specificity. They have high classification accuracy and are generally comparable in predicting diabetes and free diabetes patients. Among the selected algorithms tested, the Decision Tree Classifier (J48) algorithm scored the highest accuracy and was the best predictor, with a classification accuracy of 92.74%.

Molecular and clinical signatures in Acute Kidney Injury define distinct subphenotypes that associate with death, kidney, and cardiovascular events

Introduction: AKI is a heterogeneous syndrome defined via serum creatinine and urine output criteria. However, these markers are insufficient to capture the biological complexity of AKI and not necessarily inform on future risk of kidney and clinical events. Methods: Data from ASSESS-AKI was obtained and analyzed to uncover different clinical and biological signatures within AKI. We utilized a set of unsupervised machine learning algorithms incorporating a comprehensive panel of systemic and organ-specific biomarkers of inflammation, injury, and repair/health integrated into electronic data. Furthermore, the association of these novel biomarker-enriched subphenotypes with kidney and cardiovascular events and death was determined. Clinical and biomarker concentration differences among subphenotypes were evaluated via classic statistics. Kaplan-Meier and cumulative incidence curves were obtained to evaluate longitudinal outcomes. Results: Among 1538 patients from ASSESS-AKI, we included 748 AKI patients in the analysis. The median follow-up time was 4.8 years. We discovered 4 subphenotypes via unsupervised learning. Patients with AKI subphenotype 1 (injury cluster) were older (mean age +/- SD): 71.2 +/- 9.4 (p<0.001), with high ICU admission rates (93.9%, p<0.001) and highly prevalent cardiovascular disease (71.8%, p<0.001). They were characterized by the highest levels of KIM-1, troponin T, and ST2 compared to other clusters (P<0.001). AKI subphenotype 2 (benign cluster) is comprised of relatively young individuals with the lowest prevalence of comorbidities and highest levels of systemic anti-inflammatory makers (IL-13). AKI Subphenotype 3 (chronic inflammation and low injury) comprised patients with markedly high pro-BNP, TNFR1, and TNFR2 concentrations while presenting low concentrations of KIM-1 and NGAL. Patients with AKI subphenotype 4 (inflammation-injury) were predominantly critically ill individuals with the highest prevalence of sepsis and stage 3 AKI. They had the highest systemic (IL-1B, CRP, IL-8) and kidney inflammatory biomarker activity (YKL-40, MCP-1) as well as high kidney injury levels (NGAL, KIM-1). AKI subphenotype 3 and 4 were independently associated with a higher risk of death compared to subphenotype 2. Moreover, subphenotype 3 was independently associated with CKD outcomes and CVD events. Conclusion: We discovered four clinically meaningful AKI subphenotypes with statistical differences in biomarker composites that associate with longitudinal risks of adverse clinical events. Our approach is a novel look at the potential mechanisms underlying AKI and the putative role of biomarkers investigation.

First and Second Wave Dynamics of Emergency Department Utilization during the COVID-19 Pandemic: a retrospective study

Background: Since the COVID-19 pandemic, there has been a decrease in emergency department(ED) utilization. Although this has been thoroughly characterized for the first wave(FW), studies during the second wave(SW) are limited. We examined the changes in ED utilization between the FW and SW, compared to 2019 reference periods. Methods: We performed a retrospective analysis of ED utilization in 3 Dutch hospitals in 2020. The FW and SW (March until June and September until December, respectively) were compared to the reference periods in 2019. ED visits were labeled as (non)COVID suspected. Findings: During the FW and SW ED visits decreased by 20.3% and 15.3%, respectively, when compared to reference periods in 2019. During both waves high urgency visits significantly increased with 3.1% and 2.1%, and admission rates (ARs) increased with 5.0% and 10.4%. Trauma related visits decreased by 5.2% and 3.4%. During the SW we observed less COVID-related visits compared to the FW (4,407 vs 3,102 patients). COVID related visits were significantly more often in higher need of urgent care and ARs where at least 24.0% higher compared to non COVID visits. Interpretation: During both COVID-19 waves ED visits were significantly reduced, with the most distinct decline during the FW. ED patients were more often triaged as high urgent and the ARs were increased compared to the reference period in 2019, reflecting a high burden on ED resources. These findings indicate the need to gain more insight into motives of patients to delay or avoid emergency care during pandemics and prepare EDs for future pandemics.

Contemporary pregnancy outcomes for women with moderate and severe congenital heart disease

Background Women with congenital heart disease (CHD) are surviving into adulthood, with more undergoing pregnancy. Methods Retrospective review of the Vizient database from 2017–2019 for women 15–44 years old with moderate, severe or no CHD and vaginal delivery or caesarean section. Demographics, hospital outcomes and costs were compared. Results There were 2,469,117 admissions: 2,467,589 with no CHD, 1277 with moderate and 251 with severe CHD. Both CHD groups were younger than no CHD, there were fewer white race/ethnicity in the no CHD group and more women with Medicare in both CHD groups compared to no CHD. With increasing CHD severity there was an increase in length of stay, ICU admission rates and costs. There were also higher rates of complications, mortality and caesarean section in the CHD groups. Conclusion Pregnant women with CHD have more problematic pregnancies and understanding this impact is important to improve management and decrease healthcare utilization.

Hospitalization Trends for Acute Appendicitis in Spain, 1998 to 2017

The incidence of acute appendicitis decreased in Western countries from 1930 to at least the early 1990s, when epidemiological data started becoming scarcer. This study aimed to assess the trend in annual hospitalizations for acute appendicitis in all people Spain for a 20-year period between 1998 and 2017. This observational study analyzing direct age-standardized hospital admission rates by gender and age group (0–14 years, 15–34 years, 35–44 years, 45–64 years, and ≥65 years). Joinpoint regression models were fitted to evaluate changes in trends. There were 789,533 emergency hospital admissions for acute appendicitis between 1998 and 2017: 58.9% in boys and men and 41.1% in girls and women. Overall, there was a significant increase in admissions for this cause from 1998 to 2009, with an annual percent change (APC) of 0.6%. Following the peak in 2009, admission rates decreased by around 1.0% annually until 2017. The length of hospital stay gradually decreased from 4.5 days in 1998 to 3.4 days in 2017. The trends in hospital admissions for acute appendicitis in Spain changed over the study period, decreasing from 2009, especially in people younger than 35 years.