Design and rationale of the COVID-19 Critical Care Consortium international, multicentre, observational study.

INTRODUCTION: There is a paucity of data that can be used to guide the management of critically ill patients with COVID-19. In response, a research and data-sharing collaborative-The COVID-19 Critical Care Consortium-has been assembled to harness the cumulative experience of intensive care units (ICUs) worldwide. The resulting observational study provides a platform to rapidly disseminate detailed data and insights crucial to improving outcomes. METHODS AND ANALYSIS: This is an international, multicentre, observational study of patients with confirmed or suspected SARS-CoV-2 infection admitted to ICUs. This is an evolving, open-ended study that commenced on 1 January 2020 and currently includes >350 sites in over 48 countries. The study enrols patients at the time of ICU admission and follows them to the time of death, hospital discharge or 28 days post-ICU admission, whichever occurs last. Key data, collected via an electronic case report form devised in collaboration with the International Severe Acute Respiratory and Emerging Infection Consortium/Short Period Incidence Study of Severe Acute Respiratory Illness networks, include: patient demographic data and risk factors, clinical features, severity of illness and respiratory failure, need for non-invasive and/or mechanical ventilation and/or extracorporeal membrane oxygenation and associated complications, as well as data on adjunctive therapies. ETHICS AND DISSEMINATION: Local principal investigators will ensure that the study adheres to all relevant national regulations, and that the necessary approvals are in place before a site may contribute data. In jurisdictions where a waiver of consent is deemed insufficient, prospective, representative or retrospective consent will be obtained, as appropriate. A web-based dashboard has been developed to provide relevant data and descriptive statistics to international collaborators in real-time. It is anticipated that, following study completion, all de-identified data will be made open access. TRIAL REGISTRATION NUMBER: ACTRN12620000421932 (http://anzctr.org.au/ACTRN12620000421932.aspx).

Examination of CIs in health and medical journals from 1976 to 2019: an observational study.

OBJECTIVES: Previous research has shown clear biases in the distribution of published p values, with an excess below the 0.05 threshold due to a combination of p-hacking and publication bias. We aimed to examine the bias for statistical significance using published confidence intervals. DESIGN: Observational study. SETTING: Papers published in Medline since 1976. PARTICIPANTS: Over 968 000 confidence intervals extracted from abstracts and over 350 000 intervals extracted from the full-text. OUTCOME MEASURES: Cumulative distributions of lower and upper confidence interval limits for ratio estimates. RESULTS: We found an excess of statistically significant results with a glut of lower intervals just above one and upper intervals just below 1. These excesses have not improved in recent years. The excesses did not appear in a set of over 100 000 confidence intervals that were not subject to p-hacking or publication bias. CONCLUSIONS: The huge excesses of published confidence intervals that are just below the statistically significant threshold are not statistically plausible. Large improvements in research practice are needed to provide more results that better reflect the truth.

Cohort study of a specialist social worker intervention on hospital use for patients at risk of long stay.

BACKGROUND: Long-stay patients in acute hospitals commonly present with complex psychosocial needs and use high levels of hospital resources. OBJECTIVE: To determine whether a specialist social worker-led model of care was associated with a reduction in length of stay for medically stable patients with complex psychosocial needs who were at risk of long stay, and to determine the economic value of this model relative to the decision makers' willingness to pay for bed days released. DESIGN: A prospective, matched cohort study with historical controls. SETTING: A large, tertiary teaching and referral hospital in metropolitan Southeast Queensland, Australia. METHODS: Length of hospital stay for a cohort of patients seen under the specialist social worker-led model of care was compared with a matched control group of patients admitted to the hospital prior to the introduction of the new model of care using a multistate model with the social worker model of care as an intermediate event. Costs associated with the model of care were calculated and an estimate of the 'cost per bed day' was produced. RESULTS: The model of care reduced mean length of stay by 33 days. This translated to 9999 bed days released over 12 months. The cost to achieve this was estimated to be $A229 000 over 12 months. The cost per bed day released was $23, which is below estimates of hospital decision makers' willingness to pay for a bed day to be released for an alternate use. CONCLUSIONS: The specialist social worker-led model of care was associated with a reduced length of stay at a relatively low cost. This is likely to represent a cost-effective use of hospital resources. The limitations of our historic control cohort selection mean that results should be interpreted with caution. Further research is needed to confirm these findings.

Using Microsimulation to Estimate the Future Health and Economic Costs of Salmonellosis under Climate Change in Central Queensland, Australia.

BACKGROUND: The incidence of salmonellosis, a costly foodborne disease, is rising in Australia. Salmonellosis increases during high temperatures and rainfall, and future incidence is likely to rise under climate change. Allocating funding to preventative strategies would be best informed by accurate estimates of salmonellosis costs under climate change and by knowing which population subgroups will be most affected. OBJECTIVE: We used microsimulation models to estimate the health and economic costs of salmonellosis in Central Queensland under climate change between 2016 and 2036 to inform preventative strategies. METHODS: We projected the entire population of Central Queensland to 2036 by simulating births, deaths, and migration, and salmonellosis and two resultant conditions, reactive arthritis and postinfectious irritable bowel syndrome. We estimated salmonellosis risks and costs under baseline conditions and under projected climate conditions for Queensland under the A1FI emissions scenario using composite projections from 6 global climate models (warm with reduced rainfall). We estimated the resulting costs based on direct medical expenditures combined with the value of lost quality-adjusted life years (QALYs) based on willingness-to-pay. RESULTS: Estimated costs of salmonellosis between 2016 and 2036 increased from 456.0 QALYs (95% CI: 440.3, 473.1) and AUD29,900,000 million (95% CI: AUD28,900,000, AUD31,600,000), assuming no climate change, to 485.9 QALYs (95% CI: 469.6, 503.5) and AUD31,900,000 (95% CI: AUD30,800,000, AUD33,000,000) under the climate change scenario. CONCLUSION: We applied a microsimulation approach to estimate the costs of salmonellosis and its sequelae in Queensland during 2016-2036 under baseline conditions and according to climate change projections. This novel application of microsimulation models demonstrates the models' potential utility to researchers for examining complex interactions between weather and disease to estimate future costs. https://doi.org/10.1289/EHP1370.

Thermal clothing to reduce heart failure morbidity during winter: a randomised controlled trial.

OBJECTIVE: To examine whether providing thermal clothing improved the health of patients with heart failure during winter. DESIGN: Parallel group randomised controlled trial. SETTING: Large public hospital in Brisbane during winter 2016. PARTICIPANTS: 91 patients with systolic or diastolic heart failure who were over 50 years old. INTERVENTION: 47 patients were randomised to receive thermal clothes (socks, top and hat) and 44 received usual care. Patients could not be blinded to their randomised group. All patients' data were available for the primary outcome which was collected blind to randomised group. MAIN OUTCOME MEASURES: The primary outcome was the mean number of days in hospital during winter. Secondary outcomes included quality of life and sleep, and blood tests were collected for cardiovascular risk factors. Participants completed clothing diaries in midwinter which were used to estimate their overall clothing insulation using the 'clo'. Monitors inside the participants' homes recorded indoor temperatures throughout winter. RESULTS: The mean number of days in hospital during winter was 4.2 in the usual care group and 3.0 in the thermal clothing group (mean difference -1.2 days, 95% CI -4.8 to 2.5 days). Most participants (85%) in the thermal clothing group reported using the thermals. There was an increase in overall clothing insulation at night in the thermal clothing group (mean difference 0.13 clo, 95% CI 0.03 to 0.23). Most participants in both groups did not wear sufficient clothing (defined as a clo below 1) and regularly experienced indoor temperatures below 18°C during midwinter. CONCLUSIONS: There was no clear statistical improvement in health in the thermal clothing group. Efforts to improve health during winter may need to focus on passive interventions such as home insulation rather than interventions that target behaviour change. TRIAL REGISTRATION NUMBER: ACTRN12615001023549; Results.

Effect of temperature and precipitation on salmonellosis cases in South-East Queensland, Australia: an observational study.

OBJECTIVE: Foodborne illnesses in Australia, including salmonellosis, are estimated to cost over $A1.25 billion annually. The weather has been identified as being influential on salmonellosis incidence, as cases increase during summer, however time series modelling of salmonellosis is challenging because outbreaks cause strong autocorrelation. This study assesses whether switching models is an improved method of estimating weather-salmonellosis associations. DESIGN: We analysed weather and salmonellosis in South-East Queensland between 2004 and 2013 using 2 common regression models and a switching model, each with 21-day lags for temperature and precipitation. RESULTS: The switching model best fit the data, as judged by its substantial improvement in deviance information criterion over the regression models, less autocorrelated residuals and control of seasonality. The switching model estimated a 5 °C increase in mean temperature and 10 mm precipitation were associated with increases in salmonellosis cases of 45.4% (95% CrI 40.4%, 50.5%) and 24.1% (95% CrI 17.0%, 31.6%), respectively. CONCLUSIONS: Switching models improve on traditional time series models in quantifying weather-salmonellosis associations. A better understanding of how temperature and precipitation influence salmonellosis may identify where interventions can be made to lower the health and economic costs of salmonellosis.

Seasonal variation in cardiovascular disease risk factors in a subarctic population: the Tromsø Study 1979-2008.

BACKGROUND: Seasonal changes in cardiovascular disease (CVD) risk factors may be due to exposure to seasonal environmental variables like temperature and acute infections or seasonal behavioural patterns in physical activity and diet. Investigating the seasonal pattern of risk factors should help determine the causes of the seasonal pattern in CVD. Few studies have investigated the seasonal variation in risk factors using repeated measurements from the same individual, which is important as individual and population seasonal patterns may differ. METHODS: The authors investigated the seasonal pattern in systolic and diastolic blood pressure, heart rate, body weight, total cholesterol, triglycerides, high-density lipoprotein cholesterol, C reactive protein and fibrinogen. Measurements came from 38 037 participants in the population-based cohort, the Tromsø Study, examined up to eight times from 1979 to 2008. Individual and population seasonal patterns were estimated using a cosinor in a mixed model. RESULTS: All risk factors had a highly statistically significant seasonal pattern with a peak time in winter, except for triglycerides (peak in autumn), C reactive protein and fibrinogen (peak in spring). The sizes of the seasonal variations were clinically modest. CONCLUSIONS: Although the authors found highly statistically significant individual seasonal patterns for all risk factors, the sizes of the changes were modest, probably because this subarctic population is well adapted to a harsh climate. Better protection against seasonal risk factors like cold weather could help reduce the winter excess in CVD observed in milder climates.

The impact of heatwaves on mortality and emergency hospital admissions from non-external causes in Brisbane, Australia.

OBJECTIVES: Heatwaves can have significant health consequences resulting in increased mortality and morbidity. However, their impact on people living in tropical/subtropical regions remains largely unknown. This study assessed the impact of heatwaves on mortality and emergency hospital admissions (EHAs) from non-external causes (NEC) in Brisbane, a subtropical city in Australia. METHODS: We acquired daily data on weather, air pollution and EHAs for patients aged 15 years and over in Brisbane between January 1996 and December 2005, and on mortality between January 1996 and November 2004. A locally derived definition of heatwave (daily maximum ≥37°C for 2 or more consecutive days) was adopted. Case-crossover analyses were used to assess the impact of heatwaves on cause-specific mortality and EHAs. RESULTS: During heatwaves, there was a statistically significant increase in NEC mortality (OR 1.46; 95% CI 1.21 to 1.77), cardiovascular mortality (OR 1.89; 95% CI 1.44 to 2.48), diabetes mortality in those aged 75+ (OR 9.96; 95% CI 1.02 to 96.85), NEC EHAs (OR 1.15; 95% CI 1.07 to 1.23) and EHAs from renal diseases (OR 1.41; 95% CI 1.09 to 1.83). The elderly were found to be particularly vulnerable to heatwaves (eg, for NEC EHAs, OR 1.24 for 65-74-year-olds and 1.39 for those aged 75+). CONCLUSIONS: Significant increases in NEC mortality and EHAs were observed during heatwaves in Brisbane where people are well accustomed to hot summer weather. The most vulnerable were the elderly and people with cardiovascular, renal or diabetic disease.

Projecting future heat-related mortality under climate change scenarios: a systematic review.

BACKGROUND: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality. OBJECTIVES: We conducted a systematic review of research and methods for projecting future heat-related mortality under climate change scenarios. DATA SOURCES AND EXTRACTION: A literature search was conducted in August 2010, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 through July 2010. DATA SYNTHESIS: Fourteen studies fulfilled the inclusion criteria. Most projections showed that climate change would result in a substantial increase in heat-related mortality. Projecting heat-related mortality requires understanding historical temperature-mortality relationships and considering the future changes in climate, population, and acclimatization. Further research is needed to provide a stronger theoretical framework for projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution, and mortality displacement. CONCLUSIONS: Scenario-based projection research will meaningfully contribute to assessing and managing the potential impacts of climate change on heat-related mortality.

Assessment of heat-related health impacts in Brisbane, Australia: comparison of different heatwave definitions.

BACKGROUND: There is no global definition of a heatwave because local acclimatisation and adaptation influence the impact of extreme heat. Even at a local level there can be multiple heatwave definitions, based on varying temperature levels or time periods. We investigated the relationship between heatwaves and health outcomes using ten different heatwave definitions in Brisbane, Australia. METHODOLOGY/PRINCIPAL FINDINGS: We used daily data on climate, air pollution, and emergency hospital admissions in Brisbane between January 1996 and December 2005; and mortality between January 1996 and November 2004. Case-crossover analyses were used to assess the relationship between each of the ten heatwave definitions and health outcomes. During heatwaves there was a statistically significant increase in emergency hospital admissions for all ten definitions, with odds ratios ranging from 1.03 to 1.18. A statistically significant increase in the odds ratios of mortality was also found for eight definitions. The size of the heat-related impact varied between definitions. CONCLUSIONS/SIGNIFICANCE: Even a small change in the heatwave definition had an appreciable effect on the estimated health impact. It is important to identify an appropriate definition of heatwave locally and to understand its health effects in order to develop appropriate public health intervention strategies to prevent and mitigate the impact of heatwaves.

Temperature and cardiovascular deaths in the US elderly: changes over time.

BACKGROUND: Short-term changes in temperature have been associated with cardiovascular deaths. This study examines changes in this association over time among the US elderly. METHODS: Daily cardiovascular mortality counts from 107 cities in the US National Morbidity and Mortality Air Pollution Study were regressed against daily temperature using the case-crossover method. Estimates were averaged by time and season using a meta-analysis. RESULTS: In summer 1987 the average increase in cardiovascular deaths due to a 10 degrees F increase in temperature was 4.7%. By summer 2000, the risk with higher temperature had disappeared (-0.4%). In contrast, an increase in temperature in fall, winter and spring was associated with a decrease in deaths, and this decrease remained constant over time. CONCLUSIONS: Heat-related cardiovascular deaths in the elderly have declined over time, probably due to increased use of air conditioning, while increased risks with cold-related temperature persist.