Short-term and medium-term survival of critically ill patients with solid tumours admitted to the intensive care unit:A retrospective analysis

OBJECTIVES: Patients with cancer frequently require unplanned admission to the intensive care unit (ICU). Our objectives were to assess hospital and 180-day mortality in patients with a non-haematological malignancy and unplanned ICU admission and to identify which factors present on admission were the best predictors of mortality. DESIGN: Retrospective review of all patients with a diagnosis of solid tumours following unplanned admission to the ICU between 1 August 2008 and 31 July 2012. SETTING: Single centre tertiary care hospital in London (UK). PARTICIPANTS: 300 adult patients with non-haematological solid tumours requiring unplanned admission to the ICU. INTERVENTIONS: None. PRIMARY AND SECONDARY OUTCOMES: Hospital and 180-day survival. RESULTS: 300 patients were admitted to the ICU (median age 66.5 years; 61.7% men). Survival to hospital discharge and 180 days were 69% and 47.8%, respectively. Greater number of failed organ systems on admission was associated with significantly worse hospital survival (p<0.001) but not with 180-day survival (p=0.24). In multivariate analysis, predictors of hospital mortality were the presence of metastases (OR 1.97, 95% CI 1.08 to 3.59), Acute Physiology and Chronic Health Evaluation II (APACHE II) Score (OR 1.07, 95% CI 1.01 to 1.13) and a Glasgow Coma Scale Score <7 on admission to ICU (OR 5.21, 95% CI 1.65 to 16.43). Predictors of worse 180-day survival were the presence of metastases (OR 2.82, 95% CI 1.57 to 5.06), APACHE II Score (OR 1.07, 95% CI 1.01 to 1.13) and sepsis (OR 1.92, 95% CI 1.09 to 3.38). CONCLUSIONS: Short-term and medium-term survival in patients with solid tumours admitted to ICU is better than previously reported, suggesting that the presence of cancer alone should not be a barrier to ICU admission

Fifth metatarsal stress fracture in elite male football players:An on-field analysis of plantar loading

ObjectiveEvaluate plantar loading during ‘on-field’ common football movements in players after fifth metatarsal (MT-5) stress fracture and compare with matched healthy players.MethodsFourteen elite male soccer players participated in the study conducted on a natural grass playing surface using firm ground football boots. Seven players who had suffered a primary stress fracture (MT-5 group) and seven matched healthy players (controls, CON) performed three common football movements while in-shoe plantar loading data were collected.ResultsLarge between-group differences exist for maximal vertical force normalised to bodyweight (Fmax) at the lateral toes (2-5) of the stance leg during a set-piece kick (MT-5: 0.2±0.06 bodyweight (BW), CON: 0.1±0.05 BW, effect size (ES) 1.4) and the curved run where the MT-5 group showed higher Fmaxwith very large effect size at the lateral forefoot of the injured (closest to curve) limb when running a curve to receive a pass (MT-5 injured−CON=0.01 BW, ES 1.5). Small between-group differences were evident during straight-line running. However, between-limb analysis of MT-5 group showed significant unloading of the lateral forefoot region of the involved foot.ConclusionsElite male football players who have returned to play after MT-5 stress fracture display significantly higher maximum plantar force at the lateral forefoot and lateral toes (2-5) compared with healthy matched control players during two football movements (kick and curved run) with the magnitude of these differences being very large. These findings may have important implications for manipulating regional load during rehabilitation or should a player report lateral forefoot prodromal symptoms.</jats:sec

A systematic review of natural language processing applied to radiology reports

NLP has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to radiology is of significance but recent reviews on this are limited. This study systematically assesses recent literature in NLP applied to radiology reports. Our automated literature search yields 4,799 results using automated filtering, metadata enriching steps and citation search combined with manual review. Our analysis is based on 21 variables including radiology characteristics, NLP methodology, performance, study, and clinical application characteristics. We present a comprehensive analysis of the 164 publications retrieved with each categorised into one of 6 clinical application categories. Deep learning use increases but conventional machine learning approaches are still prevalent. Deep learning remains challenged when data is scarce and there is little evidence of adoption into clinical practice. Despite 17% of studies reporting greater than 0.85 F1 scores, it is hard to comparatively evaluate these approaches given that most of them use different datasets. Only 14 studies made their data and 15 their code available with 10 externally validating results. Automated understanding of clinical narratives of the radiology reports has the potential to enhance the healthcare process but reproducibility and explainability of models are important if the domain is to move applications into clinical use. More could be done to share code enabling validation of methods on different institutional data and to reduce heterogeneity in reporting of study properties allowing inter-study comparisons. Our results have significance for researchers providing a systematic synthesis of existing work to build on, identify gaps, opportunities for collaboration and avoid duplication

Advances in restoration ecology: rising to the challenges of the coming decades

Simultaneous environmental changes challenge biodiversity persistence and human wellbeing. The science and practice of restoration ecology, in collaboration with other disciplines, can contribute to overcoming these challenges. This endeavor requires a solid conceptual foundation based in empirical research which confronts, tests and influences theoretical developments. We review conceptual developments in restoration ecology over the last 30 years. We frame our review in the context of changing restoration goals which reflect increased societal awareness of the scale of environmental degradation and the recognition that inter-disciplinary approaches are needed to tackle environmental problems. Restoration ecology now encompasses facilitative interactions and network dynamics, trophic cascades, and above- and below ground linkages. It operates in a non-equilibrium, alternative states framework, at the landscape scale, and in response to changing environmental, economic and social conditions. Progress has been marked by conceptual advances in the fields of trait-environment relationships, community assembly, and understanding the links between biodiversity and ecosystem functioning. Conceptual and practical advances have been enhanced by applying evolving technologies, including treatments to increase seed germination and overcome recruitment bottlenecks, high throughput DNA sequencing to elucidate soil community structure and function, and advances in satellite technology and GPS tracking to monitor habitat use. The synthesis of these technologies with systematic reviews of context dependencies in restoration success, model based analyses and consideration of complex socio-ecological systems will allow generalizations to inform evidence based interventions. Ongoing challenges include setting realistic, socially acceptable goals for restoration under changing environmental conditions, and prioritizing actions in an increasingly space-competitive world. Ethical questions also surround the use of genetically modified material, translocations, taxon substitutions, and de-extinction, in restoration ecology. Addressing these issues, as the Ecological Society of America looks to its next century, will require current and future generations of researchers and practitioners, including economists, engineers, philosophers, landscape architects, social scientists and restoration ecologists, to work together with communities and governments to rise to the environmental challenges of the coming decades