Retrospective comparative study of IV+ local tranexamic acid versus IV tranexamic acid only in primary total knee replacement

Background: The study is to compare the immediate post-operative outcomes with use of intravenous (IV) tranexamic acid (TXA) versus IV and local TXA combination in primary unilateral total knee arthroplasty. Study comprised of 72 cases of tricompartmental knee primary osteoarthritis who have undergone unilateral total knee arthroplasty at Manipal Hospital, Goa from January 2016 to December 2018. The observations for each group was analysed and post op blood loss in drain, fall of haemoglobin levels and need of blood transfusion was recorded. The results were statistically compared. The mean blood loss fall in HB levels and need of blood transfusions revealed statistically significant differences.Methods: Total 72 patients diagnosed with primary tricompartmental osteoarthritis were divided into two groups retrospectively. Group 1 (IV only): 1 gm IV Tranexamic acid bolus 10 min before deflating the tourniquet. Group 2 (IV + Local): 1 gm IV Tranexamic acid bolus 10 min before deflating the tourniquet and 1 gm Tranexamic Acid in 50 ml saline locally at the time of closure.Results: It was observed that higher post op blood loss, higher fall in haemoglobin (HB) levels and higher requirement of blood transfusions were associated with group 1 as compared to 2.Conclusions: The study inferred that the combination of local and systemic tranexamic acid was superior than systemic administration alone with lower post op blood loss, lower rates of blood transfusion and lower fall in haemoglobin levels without any added complications

Retrospective immediate post-operative comparative study of sequential bilateral total knee replacement versus unilateral total knee replacement for knee primary osteoarthritis

Background: The study is to compare the immediate post operative outcomes of sequential bilateral versus unilateral total knee replacement (TKR) for the treatment of primary knee osteoarthritis. Study comprised of 96 cases of tricompartmental knee primary osteoarthritis who have undergone unilateral and sequential bilateral total knee arthroplasty at Manipal Hospital, Goa from January 2016 to December 2018. The observations for each group was analysed and duration of hospital stay, post operative mobilisation, fall in haemoglobin level immediate post operative, need for blood transfusion, post operative complications, post operative pain and duration of surgery was recorded. The results were statistically compared. The mean duration of hospital stay, post operative blood loss in terms of fall in HB, post operative pain control, need of transfusions and duration of surgery revealed statistically significant differences.Methods: Total 96 patients diagnosed with primary tricompartmental osteoarthritis were divided into two groups retrospectively. Group 1 operated with sequential bilateral TKR under single anaesthetic procedure and group 2 with unilateral TKR both operated by same surgeon and anaesthetist.Results: It was observed that longer duration of surgery and hospital stay, higher fall in HB levels, increased need of analgesics and higher requirement of blood transfusions were associated with group 1 as compared to 2. Complication rates and post op mobilisation was similar in both groups.Conclusions: Sequential bilateral TKR is a viable option for patient with symptomatic bilateral knees but patient selection and pre op counselling takes the priority.  

Stress-testing development pathways under a changing climate: water-energy-food security in the lake Malawi-Shire river system

Malawi depends on Lake Malawi outflows into the Shire River for its water, energy and food (WEF) security. We explore future WEF security risks under the combined impacts of climate change and ambitious development pathways for water use expansion. We drive a bespoke water resources model developed with stakeholder inputs, with 29 bias-corrected climate model projections, alongside stakeholder elicited development pathways, and examine impacts on stakeholder-elicited WEF sector performance metrics. Using scenario analysis, we stress-test the system, explore uncertainties, assess trade-offs between satisfying WEF metrics, and explore whether planned regulation of outflows could help satisfy metrics. While uncertainty from potential future rainfall change generates a wide range of outcomes (including no lake outflow and higher frequency of major downstream floods), we find that potential irrigation expansion in the Lake Malawi catchments could enhance the risk of very low lake levels and risk to Shire River hydropower and irrigation infrastructure performance. Improved regulation of lake outflows through the upgraded barrage does offer some risk mitigation, but trade-offs emerge between lake level management and downstream WEF sector requirements. These results highlight the need to balance Malawi's socio-economic development ambitions across sectors and within a lake-river system, alongside enhanced climate resilience. This article is part of the theme issue 'Developing resilient energy systems'

Lake Malawi’s threshold behaviour: A stakeholder-informed model to simulate sensitivity to climate change

Over 90% of Malawi’s electricity generation and irrigation depend on Lake Malawi outflows into the Shire River. Recent lake level declines have raised concerns over future climate change impacts, including the risk of no outflows if the Lake Malawi Outflow Threshold (LMOT) is passed. Addressing calls for model co-production, we iteratively engage stakeholders in data collection, and eliciting local system insights and management priorities, to inform the development of a Water Evaluation And Planning (WEAP) model for the Lake Malawi Shire River Basin. We use a simple model setup and manual calibration to allow for data sparsity and limited documentation of historical management decisions. The model satisfactorily captures limited observed streamflow patterns of Lake Malawi tributaries and lake level variations for the period 1960–2009, however, small errors in lake level simulation significantly affect simulation of monthly outflows. The riparian countries, Malawi, Tanzania and Mozambique contribute approximately 55%, 41% and 4% respectively to lake inflows (1960–2009 average). Forced with 29 bias-corrected global climate model projections (2021–2050) and assuming no change in current operating rules of key infrastructure, the WEAP model simulates wide-ranging changes. These include much higher lake levels that would cause downstream floods, and much lower lake levels, including 11 projections that fall below the LMOT. Both outcomes would have major implications for downstream hydropower and irrigation. Future water management plans require identification and evaluation of strategies that can address multi-year shifts in lake levels and the uncertainty inherent in future climate and hydrological model outputs

An integrated climate and water resource climate service prototype for long term water allocation in the Upper Yellow River Region of China

Water Resourcing in China has historically been a complex issue requiring the ability to deal with regular floods, droughts and diverse water needs. Climate change represents another challenge to this sector, albeit one that is not traditionally considered by water managers. In this sector in China water management is predominantly based on historic, seasonal and annual forecast data while multi-annual and (multi-)decadal data are seldom used. In this paper, we present the co-development of a climate service prototype designed to provide water managers with insights into the impacts of climate change on the Upper Yellow River region for the next century. The paper is an outcome from our project that encouraged water resource planners and water resource managers to utilise long-term climate information to understand the uncertainties and the challenges our changing climate is likely to have in the region. Using an interdisciplinary team and adopting a user-centred, co-production approach, a prototype web-based data visualisation tool was developed. The development of the prototype was based on a design specification constructed from the findings of detailed interviews that allowed it to be developed and tested under SARS-CoV-2 pandemic restrictions that prevented the typical development process to be undertaken. The developed prototype presents climate information and communicates uncertainties regarding climate change in the remainder of the century through data sets that are typically used by the water sector in China in a simple, easy to understand style. Models that estimate river levels under different extraction scenarios and results about estimated river level and flow, and flood risk are also presented. The prototype was shown to be successful, as key messages relating to the impact of climate change and the challenges for water resource management could be effectively communicated through the tool interface. Practical implications Understanding the impacts of climate change on water resourcing is complicated and multifaceted. There is a need for better data about what water there is and how it is moving around between and within catchments. Estimates of past, present and future climate variables along with historical measurements of river flow can be used to help visualise some of the uncertainties and changes that may happen in the next 50 years. In addition, there is a need to understand changing water demands and water resource management practices. Current water resource management practices are based on historical conditions and assumptions that are less likely to hold true in a more variable and warmer climate. Communicating how future changes will impact future water resourcing is critical to water resources in a changing climate (Belcher et al. 2018). This research outlines the construction of a tool to visualise the impacts of climate change on water availability in part of China that is typically water scarce, using models developed using the Soil Water Assessment Toolkit (SWAT). A model of the Upper Yellow River (UYR) was developed to demonstrate the impact of climate change on river levels in the catchment based on climate variables. The rainfall-runoff model was based on climate predictions from the CMIP5 assessment HadGEM3-GC3.05 climate model and incorporated information about water resource allocations for different administrative regions of the catchment The general climate trend for the region is that it is expected to become significantly warmer. The total amount of precipitation is likely to be about the same, and yet it is expected that overall, the catchment will become significantly drier over time as winter shortens and summer lengthens. The outputs from the model reflect the changes in climate variables. The uncertainties were communicated via a Web based tool. Water resource managers in China helped to coproduce the tool by participating in workshops and providing feedback on prototypes. The workshops helped scientists and water resource managers to communicate about climate change impacts on water resources and water resource management

A common framework for approaches to extreme event attribution

The extent to which a given extreme weather or climate event is attributable to anthropogenic climate change is a question of considerable public interest. From a scientific perspective, the question can be framed in various ways, and the answer depends very much on the framing. One such framing is a risk-based approach, which answers the question probabilistically, in terms of a change in likelihood of a class of event similar to the one in question, and natural variability is treated as noise. A rather different framing is a storyline approach, which examines the role of the various factors contributing to the event as it unfolded, including the anomalous aspects of natural variability, and answers the question deterministically. It is argued that these two apparently irreconcilable approaches can be viewed within a common framework, where the most useful level of conditioning will depend on the question being asked and the uncertainties involved

Tales of future weather

Society is vulnerable to extreme weather events and, by extension, to human impacts on future events. As climate changes weather patterns will change. The search is on for more effective methodologies to aid decision-makers both in mitigation to avoid climate change and in adaptation to changes. The traditional approach uses ensembles of climate model simulations, statistical bias correction, downscaling to the spatial and temporal scales relevant to decision-makers, and then translation into quantities of interest. The veracity of this approach cannot be tested, and it faces in-principle challenges. Alternatively, numerical weather prediction models in a hypothetical climate setting can provide tailored narratives for high-resolution simulations of high-impact weather in a future climate. This 'tales of future weather' approach will aid in the interpretation of lower-resolution simulations. Arguably, it potentially provides complementary, more realistic and more physically consistent pictures of what future weather might look like

A predictive model relating daily fluctuations in summer temperatures and mortality rates

<p>Abstract</p> <p>Background</p> <p>In the context of climate change, an efficient alert system to prevent the risk associated with summer heat is necessary. The authors' objective was to describe the temperature-mortality relationship in France over a 29-year period and to define and validate a combination of temperature factors enabling optimum prediction of the daily fluctuations in summer mortality.</p> <p>Methods</p> <p>The study addressed the daily mortality rates of subjects aged over 55 years, in France as a whole, from 1975 to 2003. The daily minimum and maximum temperatures consisted in the average values recorded by 97 meteorological stations. For each day, a cumulative variable for the maximum temperature over the preceding 10 days was defined.</p> <p>The mortality rate was modelled using a Poisson regression with over-dispersion and a first-order autoregressive structure and with control for long-term and within-summer seasonal trends. The lag effects of temperature were accounted for by including the preceding 5 days. A "backward" method was used to select the most significant climatic variables. The predictive performance of the model was assessed by comparing the observed and predicted daily mortality rates on a validation period (summer 2003), which was distinct from the calibration period (1975–2002) used to estimate the model.</p> <p>Results</p> <p>The temperature indicators explained 76% of the total over-dispersion. The greater part of the daily fluctuations in mortality was explained by the interaction between minimum and maximum temperatures, for a day <it>t </it>and the day preceding it. The prediction of mortality during extreme events was greatly improved by including the cumulative variables for maximum temperature, in interaction with the maximum temperatures. The correlation between the observed and estimated mortality ratios was 0.88 in the final model.</p> <p>Conclusion</p> <p>Although France is a large country with geographic heterogeneity in both mortality and temperatures, a strong correlation between the daily fluctuations in mortality and the temperatures in summer on a national scale was observed. The model provided a satisfactory quantitative prediction of the daily mortality both for the days with usual temperatures and for the days during intense heat episodes. The results may contribute to enhancing the alert system for intense heat waves.</p

Combining dispersion modelling with synoptic patterns to understand the wind-borne transport into the UK of the bluetongue disease vector

Bluetongue, an economically important animal disease, can be spread over long distances by carriage of insect vectors (Culicoides biting midges) on the wind. The weather conditions which influence the midge’s flight are controlled by synoptic scale atmospheric circulations. A method is proposed that links wind-borne dispersion of the insects to synoptic circulation through the use of a dispersion model in combination with principal component analysis (PCA) and cluster analysis. We illustrate how to identify the main synoptic situations present during times of midge incursions into the UK from the European continent. A PCA was conducted on high-pass-filtered mean sea-level pressure data for a domain centred over north-west Europe from 2005 to 2007. A clustering algorithm applied to the PCA scores indicated the data should be divided into five classes for which averages were calculated, providing a classification of the main synoptic types present. Midge incursion events were found to mainly occur in two synoptic categories; 64.8% were associated with a pattern displaying a pressure gradient over the North Atlantic leading to moderate south-westerly flow over the UK and 17.9% of the events occurred when high pressure dominated the region leading to south-easterly or easterly winds. The winds indicated by the pressure maps generally compared well against observations from a surface station and analysis charts. This technique could be used to assess frequency and timings of incursions of virus into new areas on seasonal and decadal timescales, currently not possible with other dispersion or biological modelling methods

Evidence and perceptions of rainfall change in Malawi: Do maize cultivar choices enhance climate change adaptation in sub-Saharan Africa?

Getting farmers to adopt new cultivars with greater tolerance for coping with climatic extremes and variability is considered as one way of adapting agricultural production to climate change. However, for successful adaptation to occur, an accurate recognition and understanding of the climate signal by key stakeholders (farmers, seed suppliers and agricultural extension services) is an essential precursor. This paper presents evidence based on fieldwork with smallholder maize producers and national seed network stakeholders in Malawi from 2010 to 2011, assessing understandings of rainfall changes and decision-making about maize cultivar choices. Our findings show that preferences for short-season maize cultivars are increasing based on perceptions that season lengths are growing shorter due to climate change and the assumption that growing shorter-season crops represents a good strategy for adapting to drought. However, meteorological records for the two study areas present no evidence for shortening seasons (or any significant change to rainfall characteristics), suggesting that short-season cultivars may not be the most suitable adaptation option for these areas. This demonstrates the dangers of oversimplified climate information in guiding changes in farmer decision-making about cultivar choice