Prioritising deteriorating patients using time-to-event analysis: prediction model development and internal-external validation.

BACKGROUND: Binary classification models are frequently used to predict clinical deterioration, however they ignore information on the timing of events. An alternative is to apply time-to-event models, augmenting clinical workflows by ranking patients by predicted risks. This study examines how and why time-to-event modelling of vital signs data can help prioritise deterioration assessments using lift curves, and develops a prediction model to stratify acute care inpatients by risk of clinical deterioration. METHODS: We developed and validated a Cox regression for time to in-hospital mortality. The model used time-varying covariates to estimate the risk of clinical deterioration. Adult inpatient medical records from 5 Australian hospitals between 1 January 2019 and 31 December 2020 were used for model development and validation. Model discrimination and calibration were assessed using internal-external cross validation. A discrete-time logistic regression model predicting death within 24 h with the same covariates was used as a comparator to the Cox regression model to estimate differences in predictive performance between the binary and time-to-event outcome modelling approaches. RESULTS: Our data contained 150,342 admissions and 1016 deaths. Model discrimination was higher for Cox regression than for discrete-time logistic regression, with cross-validated AUCs of 0.96 and 0.93, respectively, for mortality predictions within 24 h, declining to 0.93 and 0.88, respectively, for mortality predictions within 1 week. Calibration plots showed that calibration varied by hospital, but this can be mitigated by ranking patients by predicted risks. CONCLUSION: Time-varying covariate Cox models can be powerful tools for triaging patients, which may lead to more efficient and effective care in time-poor environments when the times between observations are highly variable.

Impact of a prospective feedback loop aimed at reducing non-beneficial treatments in older people admitted to hospital and potentially nearing the end of life. A cluster stepped-wedge randomised controlled trial.

OBJECTIVES: To investigate if a prospective feedback loop that flags older patients at risk of death can reduce non-beneficial treatment at end of life. DESIGN: Prospective stepped-wedge cluster randomised trial with usual care and intervention phases. SETTING: Three large tertiary public hospitals in south-east Queensland, Australia. PARTICIPANTS: 14 clinical teams were recruited across the three hospitals. Teams were recruited based on a consistent history of admitting patients aged 75+ years, and needed a nominated lead specialist consultant. Under the care of these teams, there were 4,268 patients (median age 84 years) who were potentially near the end of life and flagged at risk of non-beneficial treatment. INTERVENTION: The intervention notified clinicians of patients under their care determined as at-risk of non-beneficial treatment. There were two notification flags: a real-time notification and an email sent to clinicians about the at-risk patients at the end of each screening day. The nudge intervention ran for 16-35 weeks across the three hospitals. MAIN OUTCOME MEASURES: The primary outcome was the proportion of patients with one or more intensive care unit (ICU) admissions. The secondary outcomes examined times from patients being flagged at-risk. RESULTS: There was no improvement in the primary outcome of reduced ICU admissions (mean probability difference [intervention minus usual care] = -0.01, 95% confidence interval -0.08 to 0.01). There were no differences for the times to death, discharge, or medical emergency call. There was a reduction in the probability of re-admission to hospital during the intervention phase (mean probability difference -0.08, 95% confidence interval -0.13 to -0.03). CONCLUSIONS: This nudge intervention was not sufficient to reduce the trial's non-beneficial treatment outcomes in older hospital patients. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry, ACTRN12619000675123 (registered 6 May 2019).

Meta-analysis prediction intervals are under reported in sport and exercise medicine.

AIM: Prediction intervals are a useful measure of uncertainty for meta-analyses that capture the likely effect size of a new (similar) study based on the included studies. In comparison, confidence intervals reflect the uncertainty around the point estimate but provide an incomplete summary of the underlying heterogeneity in the meta-analysis. This study aimed to estimate (i) the proportion of meta-analysis studies that report a prediction interval in sports medicine; and (ii) the proportion of studies with a discrepancy between the reported confidence interval and a calculated prediction interval. METHODS: We screened, at random, 1500 meta-analysis studies published between 2012 and 2022 in highly ranked sports medicine and medical journals. Articles that used a random effect meta-analysis model were included in the study. We randomly selected one meta-analysis from each article to extract data from, which included the number of estimates, the pooled effect, and the confidence and prediction interval. RESULTS: Of the 1500 articles screened, 866 (514 from sports medicine) used a random effect model. The probability of a prediction interval being reported in sports medicine was 1.7% (95% CI = 0.9%, 3.3%). In medicine the probability was 3.9% (95% CI = 2.4%, 6.6%). A prediction interval was able to be calculated for 220 sports medicine studies. For 60% of these studies, there was a discrepancy in study findings between the reported confidence interval and the calculated prediction interval. Prediction intervals were 3.4 times wider than confidence intervals. CONCLUSION: Very few meta-analyses report prediction intervals and hence are prone to missing the impact of between-study heterogeneity on the overall conclusions. The widespread misinterpretation of random effect meta-analyses could mean that potentially harmful treatments, or those lacking a sufficient evidence base, are being used in practice. Authors, reviewers, and editors should be aware of the importance of prediction intervals.

Process evaluation of a tailored nudge intervention to promote appropriate care and treatment of older patients at the end-of-life.

BACKGROUND: Non-beneficial treatment affects a considerable proportion of older people in hospital, and some will choose to decline invasive treatments when they are approaching the end of their life. The Intervention for Appropriate Care and Treatment (InterACT) intervention was a 12-month stepped wedge randomised controlled trial with an embedded process evaluation in three hospitals in Brisbane, Australia. The aim was to increase appropriate care and treatment decisions for older people at the end-of-life, through implementing a nudge intervention in the form of a prospective feedback loop. However, the trial results indicated that the expected practice change did not occur. The process evaluation aimed to assess implementation using the Consolidated Framework for Implementation Research, identify barriers and enablers to implementation and provide insights into the lack of effect of the InterACT intervention. METHODS: Qualitative data collection involved 38 semi-structured interviews with participating clinicians, members of the executive advisory groups overseeing the intervention at a site level, clinical auditors, and project leads. Online interviews were conducted at two times: implementation onset and completion. Data were coded to the Consolidated Framework for Implementation Research and deductively analysed. RESULTS: Overall, clinicians felt the premise and clinical reasoning behind InterACT were strong and could improve patient management. However, several prominent barriers affected implementation. These related to the potency of the nudge intervention and its integration into routine clinical practice, clinician beliefs and perceived self-efficacy, and wider contextual factors at the health system level. CONCLUSIONS: An intervention designed to change clinical practice for patients at or near to end-of-life did not have the intended effect. Future interventions targeting this area of care should consider using multi-component strategies that address the identified barriers to implementation and clinician change of practice. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry (ANZCTR), ACTRN12619000675123p (approved 06/05/2019).

Gestational diabetes mellitus screening and diagnosis criteria before and during the COVID-19 pandemic: a retrospective pre-post study.

OBJECTIVE: To determine whether perinatal outcomes after excluding gestational diabetes mellitus (GDM) on the basis of fasting venous plasma glucose (FVPG) assessment during the coronavirus disease 2019 (COVID-19) pandemic in 2020 were similar to those during the preceding year after excluding GDM using the standard oral glucose tolerance test (OGTT) procedure. DESIGN: Retrospective pre-post study. SETTING, PARTICIPANTS: All women who gave birth in Queensland during 1 July - 31 December 2019 and 1 July - 31 December 2020. MAIN OUTCOME MEASURES: Perinatal (maternal and neonatal) outcomes for pregnant women assessed for GDM, by assessment method (2019: OGTT/glycated haemoglobin [HbA1c ] assessment; 2020: GDM could be excluded by an FVPG value below 4.7 mmol/L). RESULTS: 3968 of 29 113 pregnant women in Queensland during 1 July - 31 December 2019 (13.6%) were diagnosed with GDM, and 4029 of 28 778 during 1 July - 31 December 2020 (14.0%). In 2020, FVPG assessments established GDM in 216 women (1.1%) and excluded it in 1660 (5.8%). The frequencies of most perinatal outcomes were similar for women without GDM in 2019 and those for whom it was excluded in 2020 on the basis of FVPG values; the exception was caesarean delivery, for which the estimated probability increase in 2020 was 3.9 percentage points (95% credibility interval, 2.2-5.6 percentage points), corresponding to an extra 6.5 caesarean deliveries per 1000 births. The probabilities of several outcomes - respiratory distress, neonatal intensive care or special nursery admission, large for gestational age babies - were about one percentage point higher for women without GDM in 2020 (excluding those diagnosed on the basis of FVPG assessment alone) than for women without GDM in 2019. CONCLUSIONS: Identifying women at low absolute risk of gestational diabetes-related pregnancy complications on the basis of FVPG assessment as an initial step in GDM screening could reduce the burden for pregnant women and save the health system substantial costs.

Morbid obesity's impact on COVID-19 patients requiring venovenous extracorporeal membrane oxygenation: The covid-19 critical care consortium database review.

Introduction: Obesity is associated with a worse prognosis in COVID-19 patients with acute respiratory distress syndrome (ARDS). Veno-venous (V-V) Extracorporeal Membrane Oxygenation (ECMO) can be a rescue option, however, the direct impact of morbid obesity in this select group of patients remains unclear.Methods: This is an observational study of critically ill adults with COVID-19 and ARDS supported by V-V ECMO. Data are from 82 institutions participating in the COVID-19 Critical Care Consortium international registry. Patients were admitted between 12 January 2020 to 27 April 2021. They were stratified based on Body Mass Index (BMI) at 40 kg/m2. The endpoint was survival to hospital discharge.Results: Complete data available on 354 of 401 patients supported on V-V ECMO. The characteristics of the high BMI (>40 kg/m2) and lower BMI (≤40 kg/m2) groups were statistically similar. However, the 'high BMI' group were comparatively younger and had a lower APACHE II score. Using survival analysis, older age (Hazard Ratio, HR 1.49 per-10-years, CI 1.25-1.79) and higher BMI (HR 1.15 per-5 kg/m2 increase, CI 1.03-1.28) were associated with a decreased patient survival. A safe BMI threshold above which V-V ECMO would be prohibitive was not apparent and instead, the risk of an adverse outcome increased linearly with BMI.Conclusion: In COVID-19 patients with severe ARDS who require V-V ECMO, there is an increased risk of death associated with age and BMI. The risk is linear and there is no BMI threshold beyond which the risk for death greatly increases.

Beneficial Effect of Prone Positioning During Venovenous Extracorporeal Membrane Oxygenation for Coronavirus Disease 2019.

OBJECTIVES: The study investigated the impact of prone positioning during venovenous extracorporeal membrane oxygenation support for coronavirus disease 2019 acute respiratory failure on the patient outcome. DESIGN: An observational study of venovenous extracorporeal membrane oxygenation patients. We used a multistate survival model to compare the outcomes of patients treated with or without prone positioning during extracorporeal membrane oxygenation, which incorporates the dynamic nature of prone positioning and adjusts for potential confounders. SETTING: Seventy-two international institutions participating in the Coronavirus Disease 2019 Critical Care Consortium international registry. PATIENTS: Coronavirus disease 2019 patients who were supported by venovenous extracorporeal membrane oxygenation during the study period. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: There were 232 coronavirus disease 2019 patients at 72 participating institutions who were supported with venovenous extracorporeal membrane oxygenation during the study period from February 16, 2020, to October 31, 2020. Proning was used in 176 patients (76%) before initiation of extracorporeal membrane oxygenation and in 67 patients (29%) during extracorporeal membrane oxygenation. Survival to hospital discharge was 33% in the extracorporeal membrane oxygenation prone group versus 22% in the extracorporeal membrane oxygenation supine group. Prone positioning during extracorporeal membrane oxygenation support was associated with reduced mortality (hazard ratio, 0.31; 95% CI, 0.14-0.68). CONCLUSIONS: Our study highlights that prone positioning during venovenous extracorporeal membrane oxygenation support for refractory coronavirus disease 2019-related acute respiratory distress syndrome is associated with reduced mortality. Given the observational nature of the study, a randomized controlled trial of prone positioning on venovenous extracorporeal membrane oxygenation is needed to confirm these findings.

The comparative mortality of an elite group in the long run of history: an observational analysis of politicians from 11 countries.

This study aims to compare the mortality rate and life expectancy of politicians with those of the age and gender-matched general populations. This was an observational analysis of mortality rates of politicians (i.e. members of national parliaments with available data on dates of birth, death and election, gender, and life tables) in 11 developed countries. Politicians were followed from date of first election until either death or the last available year with life table data. Relative mortality differences were estimated using standardised mortality ratios (SMRs). Absolute inequalities were quantified as the difference in survival by deducting a population's remaining life expectancy from politicians' remaining life expectancy at age 45, estimated using Gompertz parametric proportional hazards models. We included 57,561 politicians (with follow-up ranging from 1816-2016 for France to 1949-2017 for Germany). In almost all countries politicians had similar rates of mortality to the general population in the early part of the twentieth century. Relative mortality and survival differences (favouring politicians) increased considerably over the course of the twentieth century, with recent SMRs ranging from 0.45 (95%CI 0.41-0.50) in Italy to 0.82 (95%CI 0.69-0.95) in New Zealand. The peak life expectancy gaps ranged from 4.4 (95% CI, 3.5-5.4) years in the Netherlands to 7.8 (95% CI, 7.2-8.4) years in the US. Our results show large relative and absolute inequalities favouring politicians in every country. In some countries, such as the US, relative inequalities are at the greatest level in over 150 years.

Impact of a prospective feedback loop on care review activities in older patients at the end of life. A stepped-wedge randomised trial.

BACKGROUND: Hospitalisation rates for older people are increasing, with end-of-life care becoming a more medicalised experience. Innovative approaches are warranted to support early identification of the end-of-life phase, communicate prognosis, provide care consistent with people's preferences, and improve the use of healthcare resources. The Intervention for Appropriate Care and Treatment (InterACT) trial aimed to increase appropriate care and treatment decisions for older people at the end of life, through implementation of a prospective feedback loop. This paper reports on the care review outcomes. METHODS: A stepped-wedge randomised controlled trial was conducted in three large acute hospitals in Queensland, Australia between May 2020 and June 2021. The trial identified older people nearing the end of life using two validated tools for detecting deterioration and short-term death. Admitting clinical teams were provided with details of patients identified as at-risk with the goal of increasing awareness that end of life was approaching to facilitate appropriate patient centred care and avoid non-beneficial treatment. We examined the time between when the patient was identified as 'at-risk' and three outcomes: clinician-led care review discussions, review of care directive measures and palliative care referrals. These were considered useful indicators of appropriate care at the end of life. RESULTS: In two hospitals there was a reduction in the review of care directive measures during the intervention compared with usual care at 21 days (reduced probability of - 0.08; 95% CI: - 0.12 to - 0.04 and - 0.14; 95% CI: - 0.21 to - 0.06). In one hospital there was a large reduction in clinician-led care review discussions at 21 days during the intervention (reduced probability of - 0.20; 95% CI: - 0.28 to - 0.13). There was little change in palliative care referrals in any hospital, with average probability differences at 21 days of - 0.01, 0.02 and 0.04. DISCUSSION: The results are disappointing as an intervention designed to improve care of hospitalised older people appeared to have the opposite effect on care review outcomes. The reasons for this may be a combination of the intervention design and health system challenges due to the pandemic that highlight the complexity of providing more appropriate care at the end of life. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry, ACTRN12619000675123 (registered 6 May 2019).

Cost-effectiveness of an Environmental Cleaning Bundle for Reducing Healthcare-associated Infections.

BACKGROUND: Healthcare-associated infections (HAIs) remain a significant patient safety issue, with point prevalence estimates being ~5% in high-income countries. In 2016-2017, the Researching Effective Approaches to Cleaning in Hospitals (REACH) study implemented an environmental cleaning bundle targeting communication, staff training, improved cleaning technique, product use, and audit of frequent touch-point cleaning. This study evaluates the cost-effectiveness of the environmental cleaning bundle for reducing the incidence of HAIs. METHODS: A stepped-wedge, cluster-randomized trial was conducted in 11 hospitals recruited from 6 Australian states and territories. Bundle effectiveness was measured by the numbers of Staphylococcus aureus bacteremia, Clostridium difficile infection, and vancomycin-resistant enterococci infections prevented in the intervention phase based on estimated reductions in the relative risk of infection. Changes to costs were defined as the cost of implementing the bundle minus cost savings from fewer infections. Health benefits gained from fewer infections were measured in quality-adjusted life-years (QALYs). Cost-effectiveness was evaluated using the incremental cost-effectiveness ratio and net monetary benefit of adopting the cleaning bundle over existing hospital cleaning practices. RESULTS: Implementing the cleaning bundle cost $349 000 Australian dollars (AUD) and generated AUD$147 500 in cost savings. Infections prevented under the cleaning bundle returned a net monetary benefit of AUD$1.02 million and an incremental cost-effectiveness ratio of $4684 per QALY gained. There was an 86% chance that the bundle was cost-effective compared with existing hospital cleaning practices. CONCLUSIONS: A bundled, evidence-based approach to improving hospital cleaning is a cost-effective intervention for reducing the incidence of HAIs.

Performance of variable and function selection methods for estimating the nonlinear health effects of correlated chemical mixtures: A simulation study.

Statistical methods for identifying harmful chemicals in a correlated mixture often assume linearity in exposure-response relationships. Nonmonotonic relationships are increasingly recognized (eg, for endocrine-disrupting chemicals); however, the impact of nonmonotonicity on exposure selection has not been evaluated. In a simulation study, we assessed the performance of Bayesian kernel machine regression (BKMR), Bayesian additive regression trees (BART), Bayesian structured additive regression with spike-slab priors (BSTARSS), generalized additive models with double penalty (GAMDP) and thin plate shrinkage smoothers (GAMTS), multivariate adaptive regression splines (MARS), and lasso penalized regression. We simulated realistic exposure data based on pregnancy exposure to 17 phthalates and phenols in the US National Health and Nutrition Examination Survey using a multivariate copula. We simulated data sets of size N = 250 and compared methods across 32 scenarios, varying by model size and sparsity, signal-to-noise ratio, correlation structure, and exposure-response relationship shapes. We compared methods in terms of their sensitivity, specificity, and estimation accuracy. In most scenarios, BKMR, BSTARSS, GAMDP, and GAMTS achieved moderate to high sensitivity (0.52-0.98) and specificity (0.21-0.99). BART and MARS achieved high specificity (≥0.90), but low sensitivity in low signal-to-noise ratio scenarios (0.20-0.51). Lasso was highly sensitive (0.71-0.99), except for quadratic relationships (≤0.27). Penalized regression methods that assume linearity, such as lasso, may not be suitable for studies of environmental chemicals hypothesized to have nonmonotonic relationships with outcomes. Instead, BKMR, BSTARSS, GAMDP, and GAMTS are attractive methods for flexibly estimating the shapes of exposure-response relationships and selecting among correlated exposures.

A stepped-wedge randomised-controlled trial assessing the implementation, impact and costs of a prospective feedback loop to promote appropriate care and treatment for older patients in acute hospitals at the end of life: study protocol.

BACKGROUND: Hospitalisation rates for the older population have been increasing with end-of-life care becoming a more medicalised and costly experience. There is evidence that some of these patients received non-beneficial treatment during their final hospitalisation with a third of the non-beneficial treatment duration spent in intensive care units. This study aims to increase appropriate care and treatment decisions and pathways for older patients at the end of life in Australia. This study will implement and evaluate a prospective feedback loop and tailored clinical response intervention at three hospitals in Queensland, Australia. METHODS: A stepped-wedge cluster randomised trial will be conducted with up to 21 clinical teams in three acute hospitals over 70 weeks. The study involves clinical teams providing care to patients aged 75 years or older, who are prospectively identified to be at risk of non-beneficial treatment using two validated tools for detecting death and deterioration risks. The intervention's feedback loop will provide the teams with a summary of these patients' risk profiles as a stimulus for a tailored clinical response in the intervention phase. The Consolidated Framework for Implementation Research will be used to inform the intervention's implementation and process evaluation. The study will determine the impact of the intervention on patient outcomes related to appropriate care and treatment at the end of life in hospitals, as well as the associated healthcare resource use and costs. The primary outcome is the proportion of patients who are admitted to intensive care units. A process evaluation will be carried out to assess the implementation, mechanisms of impact, and contextual barriers and enablers of the intervention. DISCUSSION: This intervention is expected to have a positive impact on the care of older patients near the end of life, specifically to improve clinical decision-making about treatment pathways and what constitutes appropriate care for these patients. These will reduce the incidence of non-beneficial treatment, and improve the efficiency of hospital resources and quality of care. The process evaluation results will be useful to inform subsequent intervention implementation at other hospitals. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry (ANZCTR), ACTRN12619000675123p (approved 6 May 2019).

Acceptability, safety, and feasibility of in-bed cycling with critically ill patients.

BACKGROUND: In-bed cycling is a promising intervention that may assist critically ill patients to maintain muscle mass and improve their trajectory of recovery. The acceptability of in-bed cycling from the different perspectives of patients, clinicians, and families are unknown. In addition, the safety and feasibility of in-bed cycling in an Australian tertiary intensive care unit (ICU) is relatively unknown. OBJECTIVES: The objective of this study was to examine the acceptability, safety, and feasibility of in-bed cycling in an Australian tertiary, adult, mixed medical, surgical, trauma ICU. METHODS: An observational process evaluation was embedded in one arm of a two-arm parallel phase II randomised controlled trial that was conducted in an Australian tertiary ICU. The process evaluation was of the acceptability, safety, and feasibility of passive and active in-bed cycling for participants allocated to the trial intervention group. In-bed cycling acceptability questionnaires were designed through a three-step Delphi process. Questionnaire responses from patients, family members, and clinicians who participated in or observed the intervention during the Critical Care Cycling Study (CYCLIST) were evaluated to determine the acceptability of in-bed cycling. The congruence of responses between respondents was also compared. Safety and feasibility of the in-bed cycling intervention were assessed against predetermined criteria. RESULTS: Acceptability questionnaire responses demonstrated that in-bed cycling was an acceptable intervention from the perspectives of patients, family members, and clinicians. Questionnaire responses were congruent across the respondent groups. Safety was demonstrated with two minor transient adverse events occurring during 276 in-bed cycling sessions (adverse event rate: 0.7%). In-bed cycling sessions were feasible with 276 of 304 (90%) planned sessions conducted. CONCLUSIONS: Acceptability questionnaire responses found that in-bed cycling was regarded as an acceptable intervention to patients, family members, and clinicians. The implementation of in-bed cycling was safe and feasible to complete with critically ill patients during the early stages of their critical illness in an Australian tertiary ICU setting.

Earlier tracheostomy is associated with an earlier return to walking, talking, and eating.

BACKGROUND: Conjecture remains regarding the optimal timing for tracheostomy. Most studies examine patient mortality, ventilation duration, intensive care unit (ICU) length of stay, and medical complications. Few studies examine patient-centric outcomes. The aim of this study was to determine whether timing of tracheostomy had an impact on length of stay, morbidity, mortality, and patient-centric outcomes towards their functional recovery. METHODS: This prospective observational study included data for all tracheostomised patients over 4 y in a tertiary ICU. The study time period commenced with the insertion of an endotracheal tube. Data collected included patient and disease specifics; mortality up to 4 y; mobility scores; and time to oral intake, talking, and out-of-bed exercises. To assess differences between timing of tracheostomy, a survival analysis was conducted to dynamically compare patients on days before and after tracheostomy tube (TT) placement during their ICU admission. RESULTS: TT was placed in 276 patients. After tracheostomy, the patients were able to (on average) verbally communicate 7.4 d earlier (confidence interval [CI] = -9.1 to -4.9), return to oral intake 7.0 d earlier (CI = -10 to -4.6), and perform out-of-bed exercises 6.2 d earlier (CI = -8.4 to -4) than those who did not yet have a TT. In patients with an endotracheal tube, none were able to talk or have oral intake, and the majority (99%) did not participate in out-of-bed exercises/active rehabilitation. After tracheostomy, patients subsequently received significantly less analgesic and sedative drugs and more antipsychotics. No clear differences in ICU and long-term mortality were associated with tracheostomy timing. CONCLUSIONS: Earlier tracheostomy is associated with earlier achievement of patient-centric outcomes - patients returning to usual daily activities such as talking, out-of-bed mobility, and eating/drinking significantly earlier, whilst also receiving less sedatives and analgesics.

The effects of ambient temperatures on the risk of work-related injuries and illnesses: Evidence from Adelaide, Australia 2003-2013.

BACKGROUND: The thermal environment can directly affect workers' occupational health and safety, and act as a contributing factor to injury or illness. However, the literature addressing risks posed by varying temperatures on work-related injuries and illnesses is limited. OBJECTIVES: To examine the occupational injury and illness risk profiles for hot and cold conditions. METHODS: Daily numbers of workers' compensation claims in Adelaide, South Australia from 2003 to 2013 (n = 224,631) were sourced together with daily weather data. The impacts of maximum daily temperature on the risk of work-related injuries and illnesses was assessed using a time-stratified case-crossover study design combined with a distributed lag non-linear model. RESULTS: The minimum number of workers' compensation claims occurred when the maximum daily temperature was 25 °C. Compared with this optimal temperature, extremely hot temperatures (99th percentile) were associated with an increase in overall claims (RR: 1.30, 95%CI: 1.18-1.44) whereas a non-significant increase was observed with extremely cold temperatures (1st percentile, RR: 1.10 (95%CI: 0.99-1.21). Heat exposure had an acute effect on workers' injuries whereas cold conditions resulted in delayed effects. Moderate temperatures were associated with a greater injury burden than extreme temperatures. CONCLUSION: Days of very high temperatures were associated with the greatest risks of occupational injuries; whereas moderate temperatures, which occur more commonly, have the greatest burden. These findings suggest that the broader range of thermal conditions should be considered in workplace injury and illness prevention strategies.

Topographical distribution of perioperative cerebral infarction associated with transcatheter aortic valve implantation.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) is associated with a high incidence of cerebrovascular injury. As these injuries are thought to be primarily embolic, neuroprotection strategies have focused on embolic protection devices. However, the topographical distribution of cerebral emboli and how this impacts on the effectiveness of these devices have not been thoroughly assessed. Here, we evaluated the anatomical characteristics of magnetic resonance imaging (MRI)-defined cerebral ischemic lesions occurring secondary to TAVI to enhance our understanding of the distribution of cardioembolic phenomena. METHODS: Forty patients undergoing transfemoral TAVI with an Edwards SAPIEN-XT valve under general anesthesia were enrolled prospectively in this observational study. Participants underwent brain MRI preprocedure, and 3 ± 1 days and 6 ± 1 months postprocedure. RESULTS: Mean ± SD participant age was 82 ± 7 years. Patients had an intermediate to high surgical risk, with a mean Society of Thoracic Surgeons score of 6.3 ± 3.5 and EuroSCORE of 18.1 ± 10.6. Post-TAVI, there were no clinically apparent cerebrovascular events, but MRI assessments identified 83 new lesions across 19 of 31 (61%) participants, with a median ± interquartile range number and volume of 1 ± 2.8 lesions and 20 ± 190 µL per patient. By volume, 80% of the infarcts were cortical, 90% in the posterior circulation and 81% in the right hemisphere. CONCLUSIONS: The distribution of lesions that we detected suggests that cortical gray matter, the posterior circulation, and the right hemisphere are all particularly vulnerable to perioperative cerebrovascular injury. This finding has implications for the use of intraoperative cerebral embolic protection devices, particularly those that leave the left subclavian and, therefore, left vertebral artery unprotected.

Satellite-Based Land-Use Regression for Continental-Scale Long-Term Ambient PM2.5 Exposure Assessment in Australia.

Australia has relatively diverse sources and low concentrations of ambient fine particulate matter (<2.5 µm, PM2.5). Few comparable regions are available to evaluate the utility of continental-scale land-use regression (LUR) models including global geophysical estimates of PM2.5, derived by relating satellite-observed aerosol optical depth to ground-level PM2.5 ("SAT-PM2.5"). We aimed to determine the validity of such satellite-based LUR models for PM2.5 in Australia. We used global SAT-PM2.5 estimates (∼10 km grid) and local land-use predictors to develop four LUR models for year-2015 (two satellite-based, two nonsatellite-based). We evaluated model performance at 51 independent monitoring sites not used for model development. An LUR model that included the SAT-PM2.5 predictor variable (and six others) explained the most spatial variability in PM2.5 (adjusted R2 = 0.63, RMSE (µg/m3 [%]): 0.96 [14%]). Performance decreased modestly when evaluated (evaluation R2 = 0.52, RMSE: 1.15 [16%]). The evaluation R2 of the SAT-PM2.5 estimate alone was 0.26 (RMSE: 3.97 [56%]). SAT-PM2.5 estimates improved LUR model performance, while local land-use predictors increased the utility of global SAT-PM2.5 estimates, including enhanced characterization of within-city gradients. Our findings support the validity of continental-scale satellite-based LUR modeling for PM2.5 exposure assessment in Australia.

Long-term nitrogen dioxide exposure assessment using back-extrapolation of satellite-based land-use regression models for Australia.

Assessing historical exposure to air pollution in epidemiological studies is often problematic because of limited spatial and temporal measurement coverage. Several methods for modelling historical exposures have been described, including land-use regression (LUR). Satellite-based LUR is a recent technique that seeks to improve predictive ability and spatial coverage of traditional LUR models by using satellite observations of pollutants as inputs to LUR. Few studies have explored its validity for assessing historical exposures, reflecting the absence of historical observations from popular satellite platforms like Aura (launched mid-2004). We investigated whether contemporary satellite-based LUR models for Australia, developed longitudinally for 2006-2011, could capture nitrogen dioxide (NO2) concentrations during 1990-2005 at 89 sites around the country. We assessed three methods to back-extrapolate year-2006 NO2 predictions: (1) 'do nothing' (i.e., use the year-2006 estimates directly, for prior years); (2) change the independent variable 'year' in our LUR models to match the years of interest (i.e., assume a linear trend prior to year-2006, following national average patterns in 2006-2011), and; (3) adjust year-2006 predictions using selected historical measurements. We evaluated prediction error and bias, and the correlation and absolute agreement of measurements and predictions using R2 and mean-square error R2 (MSE-R2), respectively. We found that changing the year variable led to best performance; predictions captured between 41% (1991; MSE-R2 = 31%) and 80% (2003; MSE-R2 = 78%) of spatial variability in NO2 in a given year, and 76% (MSE-R2 = 72%) averaged over 1990-2005. We conclude that simple methods for back-extrapolating prior to year-2006 yield valid historical NO2 estimates for Australia during 1990-2005. These results suggest that for the time scales considered here, satellite-based LUR has a potential role to play in long-term exposure assessment, even in the absence of historical predictor data.