Treatment of International Human Rights Violations in the United States

INTRODUCTION: Health-related quality of life (HRQoL) in patients treated in intensive care has been reported to be lower compared with age- and sex-adjusted control groups. Our aim was to test whether stratifying for coexisting conditions would reduce observed differences in HRQoL between patients treated in the ICU and a control group from the normal population. We also wanted to characterize the ICU patients with the lowest HRQoL within these strata. METHODS: We did a cross-sectional comparison of scores of the short-form health survey (SF-36) questionnaire in a multicenter study of patients treated in the ICU (n = 780) and those from a local public health survey (n = 6,093). Analyses were in both groups adjusted for age and sex, and data stratified for coexisting conditions. Within each stratum, patients with low scores (below -2 SD of the control group) were identified and characterized. RESULTS: After adjustment, there were minor and insignificant differences in mean SF-36 scores between patients and controls. Eight (n = 18) and 22% (n = 51) of the patients had low scores (-2 SD of the control group) in the physical and mental dimensions of SF-36, respectively. Patients with low scores were usually male, single, on sick leave before admission to critical care, and survived a shorter time after being in ICU. CONCLUSIONS: After adjusting for age, sex, and coexisting conditions, mean HRQoL scores were almost equal in patients and controls. Up to 22% (n = 51) of the patients had, however, a poor quality of life as compared with the controls (-2 SD). This group, which more often consisted of single men, individuals who were on sick leave before admission to the ICU, had an increased mortality after ICU. This group should be a target for future support

A descriptive study of the surge response and outcomes of ICU patients with COVID-19 during first wave in Nordic countries

Abstract Background We sought to provide a description of surge response strategies and characteristics, clinical management and outcomes of patients with severe COVID-19 in the intensive care unit (ICU) during the first wave of the pandemic in Denmark, Finland, Iceland, Norway and Sweden. Methods Representatives from the national ICU registries for each of the five countries provided clinical data and a description of the strategies to allocate ICU resources and increase the ICU capacity during the pandemic. All adult patients admitted to the ICU for COVID-19 disease during the first wave of COVID-19 were included. The clinical characteristics, ICU management and outcomes of individual countries were described with descriptive statistics. Results Most countries more than doubled their ICU capacity during the pandemic. For patients positive for SARS-CoV-2, the ratio of requiring ICU admission for COVID-19 varied substantially (1.6-6.7%). Apart from age (proportion of patients aged 65 years or over between 29-62%), baseline characteristics, chronic comorbidity burden and acute presentations of COVID-19 disease were similar among the five countries. While utilization of invasive mechanical ventilation was high (59-85%) in all countries, the proportion of patients receiving renal replacement therapy (7-26%) and various experimental therapies for COVID-19 disease varied substantially (e.g. use of hydroxychloroquine 0-85%). Crude ICU mortality ranged from 11% to 33%. Conclusion There was substantial variability in the critical care response in Nordic ICUs to the first wave of COVID-19 pandemic, including usage of experimental medications. While ICU mortality was low in all countries, the observed variability warrants further attention.Peer reviewe

Consent is a confounding factor in a prospective observational study of critically ill elderly patients.

During analysis of a prospective multinational observation study of critically ill patients ≥80 years of age, the VIP2 study, we also studied the effects of differences in country consent for study inclusion. This is a post hoc analysis where the ICUs were analyzed according to requirement for study consent. Group A: ICUs in countries with no requirement for consent at admission but with deferred consent in survivors. Group B: ICUs where some form of active consent at admission was necessary either from the patient or surrogates. Patients' characteristics, the severity of disease and outcome variables were compared. Totally 3098 patients were included from 21 countries. The median age was 84 years (IQR 81-87). England was not included because of changing criteria for consent during the study period. Group A (7 countries, 1200 patients), and group B (15 countries, 1898 patients) were comparable with age and gender distribution. Cognition was better preserved prior to admission in group B. Group A suffered from more organ dysfunction at admission compared to group B with Sequential Organ Failure Assessment score median 8 and 6 respectively. ICU survival was lower in group A, 66.2% compared to 78.4% in group B (p<0.001). We hence found profound effects on outcomes according to differences in obtaining consent for this study. It seems that the most severely ill elderly patients were less often recruited to the study in group B. Hence the outcome measured as survival was higher in this group. We therefore conclude that consent likely is an important confounding factor for outcome evaluation in international studies focusing on old patients

Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)

Management and outcomes in critically ill nonagenarian versus octogenarian patients.

BACKGROUND: Intensive care unit (ICU) patients age 90 years or older represent a growing subgroup and place a huge financial burden on health care resources despite the benefit being unclear. This leads to ethical problems. The present investigation assessed the differences in outcome between nonagenarian and octogenarian ICU patients. METHODS: We included 7900 acutely admitted older critically ill patients from two large, multinational studies. The primary outcome was 30-day-mortality, and the secondary outcome was ICU-mortality. Baseline characteristics consisted of frailty assessed by the Clinical Frailty Scale (CFS), ICU-management, and outcomes were compared between octogenarian (80-89.9 years) and nonagenarian (> 90 years) patients. We used multilevel logistic regression to evaluate differences between octogenarians and nonagenarians. RESULTS: The nonagenarians were 10% of the entire cohort. They experienced a higher percentage of frailty (58% vs 42%; p < 0.001), but lower SOFA scores at admission (6 + 5 vs. 7 + 6; p < 0.001). ICU-management strategies were different. Octogenarians required higher rates of organ support and nonagenarians received higher rates of life-sustaining treatment limitations (40% vs. 33%; p < 0.001). ICU mortality was comparable (27% vs. 27%; p = 0.973) but a higher 30-day-mortality (45% vs. 40%; p = 0.029) was seen in the nonagenarians. After multivariable adjustment nonagenarians had no significantly increased risk for 30-day-mortality (aOR 1.25 (95% CI 0.90-1.74; p = 0.19)). CONCLUSION: After adjustment for confounders, nonagenarians demonstrated no higher 30-day mortality than octogenarian patients. In this study, being age 90 years or more is no particular risk factor for an adverse outcome. This should be considered- together with illness severity and pre-existing functional capacity - to effectively guide triage decisions. TRIAL REGISTRATION: NCT03134807 and NCT03370692

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

Reply to: intensive care unit-to-unit capacity transfers are associated with increased mortality-no hasty conclusions in the event of a crisis

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Intensive care unit to unit capacity transfers are associated with increased mortality : an observational cohort study on patient transfers in the Swedish Intensive Care Register

Background: Transfers from one intensive care unit (ICU) to another ICU are associated with increased length of intensive care and hospital stay. Inter-hospital ICU transfers are carried out for three main reasons: clinical transfers, capacity transfers and repatriations. The aim of the study was to show that different ICU transfers differ in risk-adjusted mortality rate with repatriations having the least risk. Results: Observational cohort study of adult patients transferred between Swedish ICUs during 3 years (2016-2018) with follow-up ending September 2019. Primary and secondary end-points were survival to 30 days and 180 days after discharge from the first ICU. Data from 75 ICUs in the Swedish Intensive Care Register, a nationwide intensive care register, were used for analysis (89% of all Swedish ICUs), covering local community hospitals, district general hospitals and tertiary care hospitals. We included adult patients (16 years or older) admitted to ICU and subsequently discharged by transfer to another ICU. Only the first admission was used. Exposure was discharge to any other ICU (ICU-to-ICU transfer), whether in the same or in another hospital. Transfers were grouped into three predefined categories: clinical transfer, capacity transfer, and repatriation. We identified 15,588 transfers among 112,860 admissions (14.8%) and analysed 11,176 after excluding 4112 repeat transfer of the same individual and 300 with missing risk adjustment. The majority were clinical transfers (62.7%), followed by repatriations (21.5%) and capacity transfers (15.8%). Unadjusted 30-day mortality was 25.0% among capacity transfers compared to 14.5% and 16.2% for clinical transfers and repatriations, respectively. Adjusted odds ratio (OR) for 30-day mortality were 1.25 (95% CI 1.06-1.49 p = 0.01) for capacity transfers and 1.17 (95% CI 1.02-1.36 p = 0.03) for clinical transfers using repatriation as reference. The differences remained 180 days post-discharge. Conclusions: There was a large proportion of ICU-to-ICU transfers and an increased odds of dying for those transferred due to other reasons than repatriation.Funding Agencies: Linköping University; Centre for Research and Development Region Gävleborg, Sweden; Centre for Research and Development Region Östergotland, Sweden</p