Extravascular Lung Water and Acute Lung Injury

Acute lung injury carries a high burden of morbidity and mortality and is characterised by nonhydrostatic pulmonary oedema. The aim of this paper is to highlight the role of accurate quantification of extravascular lung water in diagnosis, management, and prognosis in “acute lung injury” and “acute respiratory distress syndrome”. Several studies have verified the accuracy of both the single and the double transpulmonary thermal indicator techniques. Both experimental and clinical studies were searched in PUBMED using the term “extravascular lung water” and “acute lung injury”. Extravascular lung water measurement offers information not otherwise available by other methods such as chest radiography, arterial blood gas, and chest auscultation at the bedside. Recent data have highlighted the role of extravascular lung water in response to treatment to guide fluid therapy and ventilator strategies. The quantification of extravascular lung water may predict mortality and multiorgan dysfunction. The limitations of the dilution method are also discussed

Association of annual intensive care unit sepsis caseload with hospital mortality from sepsis in the United Kingdom, 2010-2016

Importance Sepsis is associated with a high burden of inpatient mortality. Treatment in intensive care units (ICUs) that have more experience treating patients with sepsis may be associated with lower mortality. Objective To assess the association between the volume of patients with sepsis receiving care in an ICU and hospital mortality from sepsis in the UK. Design, Setting, and Participants This retrospective cohort study used data from adult patients with sepsis from 231 UK ICUs between 2010 and 2016. Demographic and clinical data were extracted from the Intensive Care National Audit & Research Centre (ICNARC) Case Mix Programme database. Data were analyzed from January 1, 2010, to December 31, 2016. Exposures Annual sepsis case volume in an ICU in the year of a patient’s admission. Main Outcomes and Measures Hospital mortality after ICU admission for sepsis assessed using a mixed-effects logistic model in a 3-level hierarchical structure based on the number of individual patients nested in years nested within ICUs. Results Among 273 001 patients included in the analysis, the median age was 66 years (interquartile range, 53-76 years), 148 149 (54.3%) were male, and 248 275 (91.0%) were White. The mean ICNARC-2018 illness severity score was 21.0 (95% CI, 20.9-21.0). Septic shock accounted for 19.3% of patient admissions, and 54.3% of patients required mechanical ventilation. The median annual sepsis volume per ICU was 242 cases (interquartile range, 177-334 cases). The study identified a significant association between the volume of sepsis cases in the ICU and mortality from sepsis; in the logistic regression model, hospital mortality was significantly lower among patients admitted to ICUs in the highest quartile of sepsis volume compared with the lowest quartile (odds ratio [OR], 0.89; 95% CI, 0.82-0.96; P = .002). With volume modeled as a restricted cubic spline, treatment in a larger ICU was associated with lower hospital mortality. A lower annual volume threshold of 215 patients above which hospital mortality decreased significantly was found; 38.8% of patients were treated in ICUs below this threshold volume. There was no significant interaction between ICU volume and severity of illness as described by the ICNARC-2018 score (β [SE], –0.00014 [0.00024]; P = .57). Conclusions and Relevance The findings suggest that patients with sepsis in the UK have higher odds of survival if they are treated in an ICU with a larger sepsis case volume. The benefit of a high sepsis case volume was not associated with the severity of the sepsis episode

Early and late withdrawal of life-sustaining treatment after out-of-hospital cardiac arrest in the United Kingdom: institutional variation and association with hospital mortality

Aim Frequency and timing of Withdrawal of Life-Sustaining Treatment (WLST) after Out-of-Hospital Cardiac Arrest (OHCA) vary across Intensive Care Units (ICUs) in the United Kingdom (UK) and may be a marker of lower healthcare quality if instituted too frequently or too early. We aimed to describe WLST practice, quantify its variability across UK ICUs, and assess the effect of institutional deviation from average practice on patients’ risk-adjusted hospital mortality. Methods We conducted a retrospective multi-centre cohort study including all adult patients admitted after OHCA to UK ICUs between 2010 and 2017. We identified patient and ICU characteristics associated with early (within 72 h) and late (>72 h) WLST and quantified the between-ICU variation. We used the ICU-level observed-to-expected (O/E) ratios of early and late-WLST frequency as separate metrics of institutional deviation from average practice and calculated their association with patients’ hospital mortality. Results We included 28,438 patients across 204 ICUs. 10,775 (37.9%) had WLST and 6397 (59.4%) of them had early-WLST. Both WLST types were strongly associated with patient-level demographics and pre-existing conditions but weakly with ICU-level characteristics. After adjustment, we found unexplained between-ICU variation for both early-WLST (Median Odds Ratio 1.59, 95%CrI 1.49–1.71) and late-WLST (MOR 1.39, 95%CrI 1.31–1.50). Importantly, patients’ hospital mortality was higher in ICUs with higher O/E ratio of early-WLST (OR 1.29, 95%CI 1.21–1.38, p < 0.001) or late-WLST (OR 1.39, 95%CI 1.31–1.48, p < 0.001). Conclusions Significant variability exists between UK ICUs in WLST frequency and timing. This matters because unexplained higher-than-expected WLST frequency is associated with higher hospital mortality independently of timing, potentially signalling prognostic pessimism and lower healthcare quality

Hospital mortality and resource implications of hospitalisation with COVID-19 in London, UK: a prospective cohort study

Background. Coronavirus disease 2019 (COVID-19) had a significant impact on the National Health Service in the United Kingdom (UK), with over 35 000 cases reported in London by July 30, 2020. Detailed hospital-level information on patient characteristics, outcomes, and capacity strain is currently scarce but would guide clinical decision-making and inform prioritisation and planning. Methods. We aimed to determine factors associated with hospital mortality and describe hospital and ICU strain by conducting a prospective cohort study at a tertiary academic centre in London, UK. We included adult patients admitted to the hospital with laboratory-confirmed COVID-19 and followed them up until hospital discharge or 30 days. Baseline factors that are associated with hospital mortality were identified via semiparametric and parametric survival analyses. Results. Our study included 429 patients: 18% of them were admitted to the ICU, 52% met criteria for ICU outreach team activation, and 61% had treatment limitations placed during their admission. Hospital mortality was 26% and ICU mortality was 34%. Hospital mortality was independently associated with increasing age, male sex, history of chronic kidney disease, increasing baseline C-reactive protein level, and dyspnoea at presentation. COVID-19 resulted in substantial ICU and hospital strain, with up to 9 daily ICU admissions and 41 daily hospital admissions, to a peak census of 80 infected patients admitted in the ICU and 250 in the hospital. Management of such a surge required extensive reorganisation of critical care services with expansion of ICU capacity from 69 to 129 beds, redeployment of staff from other hospital areas, and coordinated hospital-level effort. Conclusions. COVID-19 is associated with a high burden of mortality for patients treated on the ward and the ICU and required substantial reconfiguration of critical care services. This has significant implications for planning and resource utilisation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

The impact of variation in critical care organisation on patient mortality: evidence form the United Kingdom

The changing landscape of aging population, increasing incidence of critical illness and more constrained national budgets mean physicians, policy makes, and hospital administrators must consider more efficient ways to organise critical care services. In general, policymakers have embraced the idea of centralising services and increased specialisation to improve efficiency in health care. This thesis explores these policies in the context of critical care services in the UK. Evidence of the productivity of critical care services and in particular volume-outcome relationship in critical care and the underlying mechanism by which this relationship operates is scarce. I consider several aspects of these issues. In the first study I investigate the volume-outcome relationship for sepsis using data from the Intensive Care National Audit and Research Centre which covers all ICUs in the England, Wales, and Northern Ireland. In this cohort study, sepsis case volume in an ICU was significantly associated with hospital mortality from sepsis, and a volume lower threshold of 215 patients per year was associated with an improvement in mortality. The second study explores the underlying mechanism of the volume-outcome relationship. Two possible mechanisms proposed are dynamic learning-by-doing and static scale economies. If the volume-outcome relationship operates through the learning-by-doing mechanism, then patient outcomes would improve by the volume of patients treated over time, making system-wide centralisation unnecessary. This study supports the idea that the underlying mechanism by which volume leads to improved outcomes is through learning-by-doing. ICUs tend to improve by caring for a large volume patients distributed over time. Patients may, therefore, be better served by ICUs organised to achieve minimum volume 5 standards without centralisation. The third study examines the related role of ICU specialisation in improving mortality. This study found that ICU specialisation do not have significantly lower hospital mortality for critically ill patients in the UK after adjusting for patient characteristics and caseload volume. Across the three studies I argue that a minimum volume threshold may be effective in improving patient outcomes. Centralisation may not fully leverage the benefits of the learning-by-doing mechanism. Lastly, accounting for volume, there is no compelling evidence of any added value from ICUs specialisation

Webpage Analysis of Indian Institute of Management (IIM) and Indian Institute of Technology (IIT) : A Webometric Study

The purpose of this research is to look at the website analysis of the 43 Indian institutions (IIT and IIM). The research focused on webometric analysis, which looked at the domain name, domain age, external and internal linkages, as well as all three types of web effects on all responder websites. The study also looks at how stakeholders from both inside and outside the country use websites. The goal of this study is to look into the webometric elements of India\u27s all IIT and IIM institutions. A ranking of the university websites based on several webometric variables was attempted. The domain age, domain extension, internal link, external link, page speed, web impact factors and Alexa Ranking of the websites were all calculated in the study

Rapid response systems:A systematic review and meta-analysis

INTRODUCTION: Although rapid response system teams have been widely adopted by many health systems, their effectiveness in reducing hospital mortality is uncertain. We conducted a meta-analysis to examine the impact of rapid response teams on hospital mortality and cardiopulmonary arrest. METHOD: We conducted a systematic review of studies published from January 1, 1990, through 31 December 2013, using PubMed, EMBASE, CINAHL (Cumulative Index to Nursing and Allied Health Literature) and the Cochrane Library. We included studies that reported data on the primary outcomes of ICU and in-hospital mortality or cardiopulmonary arrests. RESULTS: Twenty-nine eligible studies were identified. The studies were analysed in groups based on adult and paediatric trials that were further sub-grouped on methodological design. There were 5 studies that were considered either cluster randomized control trial, controlled before after or interrupted time series. The remaining studies were before and after studies without a contemporaneous control. The implementation of RRS has been associated with an overall reduction in hospital mortality in both the adult (RR 0.87, 95 % CI 0.81–0.95, p<0.001) and paediatric (RR=0.82 95 % CI 0.76–0.89) in-patient population. There was substantial heterogeneity in both populations. The rapid response system team was also associated with a reduction in cardiopulmonary arrests in adults (RR 0.65, 95 % CI 0.61–0.70, p<0.001) and paediatric (RR=0.64 95 % CI 0.55–0.74) patients. CONCLUSION: Rapid response systems were associated with a reduction in hospital mortality and cardiopulmonary arrest. Meta-regression did not identify the presence of a physician in the rapid response system to be significantly associated with a mortality reduction. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13054-015-0973-y) contains supplementary material, which is available to authorized users