Survival Analysis Part I: Basic concepts and first analyses

Survival analysis is a collection of statistical procedures for data analysis where the outcome variable of interest is time until an event occurs. Because of censoring - the nonobservation of the event of interest after a period of follow-up - a proportion of the survival times of interest will often be unknown. It is assumed that those patients who are censored have the same survival prospects as those who continue to be followed, that is, the censoring is uninformative. Survival data are generally described and modelled in terms of two related functions, the survivor function and the hazard function. The survivor function represents the probability that an individual survives from the time of origin to some time beyond time t. It directly describes the survival experience of a study cohort, and is usually estimated by the KM method. The logrank test may be used to test for differences between survival curves for groups, such as treatment arms. The hazard function gives the instantaneous potential of having an event at a time, given survival up to that time. It is used primarily as a diagnostic tool or for specifying a mathematical model for survival analysis. In comparing treatments or prognostic groups in terms of survival, it is often necessary to adjust for patient-related factors that could potentially affect the survival time of a patient. Failure to adjust for confounders may result in spurious effects. Multivariate survival analysis, a form of multiple regression, provides a way of doing this adjustment, and is the subject the next paper in this series

What role can unmanned aerial vehicles play in emergency response in the Arctic: A case study from Canada

This paper examines search and rescue and backcountry medical response constraints in the Canadian Arctic and potential for unmanned aerial vehicles (UAV) to aid in response and preparedness. Semi-structured interviews (n = 18) were conducted with search and rescue responders, Elders, and emergency management officials to collect data on current emergency response and potential for UAV use. UAV test flights (n = 17) were undertaken with community members. We analyzed five years of weather data to examine UAV flight suitability. Numerous challenges face Arctic search and rescue and backcountry emergency response. Changing social and environmental conditions were described as increasing vulnerability to backcountry emergencies. Responders desired additional first aid and emergency training. Legal and weather restrictions were found to limit where, when and who could fly UAVs. UAVs were demonstrated to have potential benefits for hazard monitoring but not for SAR or medical response due to legal restrictions, weather margins, and local capacity. We find that communities are ill-prepared for ongoing SAR demands, let alone a larger disaster. There are numerous limitations to the use of consumer UAVs by Arctic communities. Prevention of backcountry medical emergencies, building resilience to disasters, and first responder training should be prioritized over introducing UAVs to the response system

ANDROID: An Inter-disciplinary Academic Network that Promotes Co-operation and Innovation among European Higher Education to Increase Society's Resilience to Disasters

Using knowledge, innovation and education to build a culture of safety and resilience at all levels is one of five priorities for action (PFA) that were identified in the Hyogo Framework for Action (HFA). The responsibility for such capacity building resides largely with educators such as higher education institutes, but the complexity of resilience poses a number of challenges. This paper describes ANDROID, an EU funded international partnership of higher education institutes and key actors in disaster resilience, which has been formed to develop innovative European education. ANDROID is based on an inter-disciplinary consortium of partners that comprises scientists from applied, human, social and natural disciplines. ANDROID set out to achieve this aim through a series of inter-linked projects, identified as work packages and led by a sub-group of international partners. This paper describes these projects and highlights key outputs achieved to date: an inter-disciplinary doctoral school; a survey capturing and sharing innovative approaches to inter-disciplinary working; a survey of European education to map teaching and research programmes in disaster resilience; a survey analysing the capacity of European public administrators to address disaster risk; emerging research and teaching concerns in disaster resilience; and, open educational resources

A systems network approach for climate change vulnerability assessment

Vulnerability to climate change is a product of biophysical and social dynamics. Assessments of community or regional vulnerability, however, often focus on quantitative infrastructure and environmental assessments, or qualitative assessments of a community's social dynamics and livelihood activities. A dearth of integrated quantitative assessments is a major barrier for decision makers who require quantitative outputs and indicators, which can measure where vulnerability is most severe and can be linked to climate projections. Our framework and analysis helps address such gaps by identifying variables to build climate change vulnerability indices, which we pilot here focusing on Inuit communities in the Canadian Arctic. We start with a systematic literature review of community-based vulnerability studies and assess relationships among 58 social and biophysical variables. We then use multiplex network analysis to determine how social and environmental variables interact among and within the key component of vulnerability: exposure, sensitivity, and adaptive capacity. We identify several structurally important variables that interact within and across the three dimensions of vulnerability. This method is transferable as an integrative means of understanding not only the direct causes of vulnerability, but also relations that are less tangible. The approach of multiplex network analysis can be a building block to ongoing development of vulnerability indices within the human dimensions of climate change field

Reporting of loss to follow-up information in randomised controlled trials with time-to-event outcomes: a literature survey

<p>Abstract</p> <p>Background</p> <p>To assess the reporting of loss to follow-up (LTFU) information in articles on randomised controlled trials (RCTs) with time-to-event outcomes, and to assess whether discrepancies affect the validity of study results.</p> <p>Methods</p> <p>Literature survey of all issues of the BMJ, Lancet, JAMA, and New England Journal of Medicine published between 2003 and 2005. Eligible articles were reports of RCTs including at least one Kaplan-Meier plot. Articles were classified as "assessable" if sufficient information was available to assess LTFU. In these articles, LTFU information was derived from Kaplan-Meier plots, extracted from the text, and compared. Articles were then classified as "consistent" or "not consistent". Sensitivity analyses were performed to assess the validity of study results.</p> <p>Results</p> <p>319 eligible articles were identified. 187 (59%) were classified as "assessable", as they included sufficient information for evaluation; 140 of 319 (44%) presented consistent LTFU information between the Kaplan-Meier plot and text. 47 of 319 (15%) were classified as "not consistent". These 47 articles were included in sensitivity analyses. When various imputation methods were used, the results of a chi²-test applied to the corresponding 2 × 2 table changed and hence were not robust in about half of the studies.</p> <p>Conclusions</p> <p>Less than half of the articles on RCTs using Kaplan-Meier plots provide assessable and consistent LTFU information, thus questioning the validity of the results and conclusions of many studies presenting survival analyses. Authors should improve the presentation of both Kaplan-Meier plots and LTFU information, and reviewers of study publications and journal editors should critically appraise the validity of the information provided.</p

Bronchopulmonary dysplasia with focus on early prediction and treatment: a narrative review

Background and Objective: Bronchopulmonary dysplasia (BPD) remains a major cause of morbidity and mortality in very preterm infants though early non-invasive ventilation and surfactant treatment and other neonatal therapies have improved the outcome. Therefore, it is necessary to find effective supplemental methods for prediction of BPD. Better understanding of the etiology and molecular mechanisms involved in the pathogenesis of BPD is necessary for development of new effective early treatments. It is generally accepted that BPD is a multifactorial disease often associated with intrauterine infections and placental perfusion disorders. Methods: Recently a new method to predict BPD at birth using artificial intelligence (AI) has been developed. This new method improves the likelihood of developing effective early treatments for BPD. The method combines information on early surfactant treatment, birth weight and gestational age (GA) with analysis of the mid-infrared spectrum of the molecules in gastric aspirate which are produced in the newborn’s lungs. The described methods for early treatment of BPD in this review among others covers inositol, retinol, super oxide dismutase, Clara cell 10 protein, corticosteroids, azithromycin, macrolide and stem cell therapy besides general treatments as nasal continuous positive airway pressure (NCPAP), surfactant, caffeine, oxygen saturation targeting and nutrition. The literature search was performed systemically online via the databases PubMed and Medline between January 1, 2011 and December 31, 2022. Key Content and Findings: A method to predict BPD immediately after birth is now available allowing possibility to develop effective early treatments of BPD. Conclusions: The present review focuses on early prediction and the existing pharmacologic interventions highlighting the potential to improve the outcome of infants with BPD

Chlorpromazine for schizophrenia: a Cochrane systematic review of 50 years of randomised controlled trials

BACKGROUND: Chlorpromazine (CPZ) remains one of the most common drugs used for people with schizophrenia worldwide, and a benchmark against which other treatments can be evaluated. Quantitative reviews are rare; this one evaluates the effects of chlorpromazine in the treatment of schizophrenia in comparison with placebo. METHODS: We sought all relevant randomised controlled trials (RCT) comparing chlorpromazine to placebo by electronic and reference searching, and by contacting trial authors and the pharmaceutical industry. Data were extracted from selected trials and, where possible, synthesised and random effects relative risk (RR), the number needed to treat (NNT) and their 95% confidence intervals (CI) calculated. RESULTS: Fifty RCTs from 1955–2000 were included with 5276 people randomised to CPZ or placebo. They constitute 2008 person-years spent in trials. Meta-analysis of these trials showed that chlorpromazine promotes a global improvement (n = 1121, 13 RCTs, RR 0.76 CI 0.7 to 0.9, NNT 7 CI 5 to 10), although a considerable placebo response is also seen. People allocated to chlorpromazine tended not to leave trials early in both the short (n = 945, 16 RCTs, RR 0.74 CI 0.5 to 1.1) and medium term (n = 1861, 25 RCTs, RR 0.79 CI 0.6 to 1.1). There were, however, many adverse effects. Chlorpromazine is sedating (n = 1242, 18 RCTs, RR 2.3 CI 1.7 to 3.1, NNH 6 CI 5 to 8), increases a person's chances of experiencing acute movement disorders, Parkinsonism and causes low blood pressure with dizziness and dry mouth. CONCLUSION: It is understandable why the World Health Organization (WHO) have endorsed and included chlorpromazine in their list of essential drugs for use in schizophrenia. Low- and middle-income countries may have more complete evidence upon which to base their practice compared with richer nations using recent innovations

An integrative climate change vulnerability index for Arctic aviation and marine transportation

Climate change vulnerability research methods are often divergent, drawing from siloed biophysical risk approaches or social-contextual frameworks, lacking methods for integrative approaches. This substantial gap has been noted by scientists, policymakers and communities, inhibiting decision-makers’ capacity to implement adaptation policies responsive to both physical risks and social sensitivities. Aiming to contribute to the growing literature on integrated vulnerability approaches, we conceptualize and translate new integrative theoretical insights of vulnerability research to a scalable quantitative method. Piloted through a climate change vulnerability index for aviation and marine sectors in the Canadian Arctic, this study demonstrates an avenue of applying vulnerability concepts to assess both biophysical and social components analyzing future changes with linked RCP climate projections. The iterative process we outline is transferable and adaptable across the circumpolar north, as well as other global regions and shows that transportation vulnerability varies across Inuit regions depending on modeled hazards and transportation infrastructures

Determinants of job satisfaction: a European comparison of self-employed and paid employees

The job satisfaction of self-employed and paid-employed workers is analyzed using the European Community Household Panel for the EU-15 covering the years 1994-2001. We distinguish between two types of job satisfaction: job satisfaction in terms of type of work and job satisfaction in terms of job security. Findings from our generalized ordered logit regressions indicate that self-employed individuals as compared to paid employees are more likely to be satisfied with their present jobs in terms of type of work and less likely to be satisfied in terms of job security. The findings also provide many insights into the determinants of the two types of job satisfaction for both self-employed and paid-employed workers

Maximum thermal limits of coral reef damselfishes are size dependent and resilient to near-future ocean acidification

Theoretical models predict that ocean acidification, caused by increased dissolved CO2, will reduce the maximum thermal limits of fishes, thereby increasing their vulnerability to rising ocean temperatures and transient heatwaves. Here, we test this prediction in three species of damselfishes on the Great Barrier Reef, Australia. Maximum thermal limits were quantified using critical thermal maxima (CTmax) tests following acclimation to either present-day or end-of-century levels of CO2 for coral reef environments (∼500 or ∼1,000 µatm, respectively). While species differed significantly in their thermal limits, whereby Dischistodus perspicillatus exhibited greater CTmax (37.88±0.03oC; N=47) than Dascyllus aruanus (37.68±0.02oC; N=85) and Acanthochromis polyacanthus (36.58±0.02oC; N=63), end-of-century CO2 had no effect (D. aruanus) or a slightly positive effect (increase in CTmax of 0.16oC in D. perspicillatus and 0.21oC in A. polyacanthus) on CTmax. Contrary to expectations, smaller individuals were equally as resilient to CO2 as larger conspecifics, and CTmax was higher at smaller body sizes in two species. These findings suggest that ocean acidification will not impair the maximum thermal limits of reef fishes, and they highlight the critical role of experimental biology in testing predictions of theoretical models forecasting the consequences of environmental change