Injury
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Systematic reviews, of level-I primary literature, are the gold standard for the formation of Clinical Practice Guidelines in Orthopaedic Surgery. When systematic reviews have multiple groups of data, meta-analyses can be conducted to analyse the direct comparison of the data points (pairwise meta-analysis). Over recent years, statisticians have created a new statistical model called network meta-analyses that can be applied to systematic reviews. network meta-analyses allow for comparison of different treatment outcomes that may or may not have been directly assessed through level-I primary studies. network meta-analyses are appearing more and more in Orthopaedic Surgery literature; therefore, in this article, we discuss what a Network Meta-analysis is and its application in Orthopaedics.
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The last two decades have seen the reintroduction of tourniquets into guidelines for the management of acute limb trauma requiring hemorrhage control. Evidence supporting tourniquet application has demonstrated low complication rates in modern military settings involving rapid evacuation timeframes. It is unclear how these findings translate to patients who have prolonged transport times from injury in rural settings. This scoping review investigates the relationship between time and distance on metabolic complications, limb salvage and mortality following tourniquet use in civilian and military settings. ⋯ This scoping review presents literature describing comparatively safe tourniquet application when used for less than two hours duration. However, there is limited research describing prolonged tourniquet application or when used for protracted distances, such that the impact of tourniquet release time on metabolic outcomes and complications remains unclear. Prospective studies utilizing the development of an international database to provide this dataset is required.
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Cirrhosis in trauma patients is an indicator of poor prognosis, but current trauma injury grading systems do not take into account liver dysfunction as a risk factor. Our objective was to construct a simple clinical mortality prediction model in cirrhotic trauma patients: Cirrhosis Outcomes Score in Trauma (COST). ⋯ Current trauma injury grading systems do not take into account liver dysfunction as a risk factor. COST is highly predictive of mortality in cirrhotic trauma patients. The simplicity of the score makes it useful in guiding clinical care and in optimizing goals of care discussions. Future studies to validate this prediction model are required prior to clinical use.
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Overweight and obese patients are more prevalent in rural and remote areas and are of major public health concern in Australia. We aimed to evaluate the mortality and morbidity of overweight and obese trauma patients in the rural Australian context. ⋯ The majority of trauma presentations in our regional community are in overweight or obese patients. Overweight and obese patients are more likely to require intubation and have a longer intensive care unit admission than normal weight counterparts. Amongst obese patients, those with BMI > 40 (obesity class 3) are at significantly increased risk of complications.
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Patient registries have grown in size and number along with general computing power and digitization of the healthcare world. In contrast to databases, registries are typically patient data systematically created and collected for the express purpose of answering health-related questions. Registries can be disease-, procedure-, pathology-, or product-based in nature. ⋯ As with any study type, the intended design does not automatically lead to a study of a certain quality. While no specific tool exists for assessing the quality of a registry-based study, some important considerations include ensuring the registry is appropriate for the question being asked, whether the patient population is representative, the presence of an appropriate comparison group, and the validity and generalizability of the registry in question. The future of clinical registries remains to be seen, but the incorporation of big data and machine learning algorithms will certainly play an important role.