Plos One
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Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of information relating to disease presentation, imaging features, and patient characteristics to determine if a patient will benefit from surgery for DCM. We applied a supervised machine learning approach to develop a classification model to predict individual patient outcome after surgery for DCM. ⋯ Worse pre-operative disease severity, longer duration of DCM symptoms, older age, higher body weight, and current smoking status were associated with worse surgical outcomes. We developed a model that predicted positive surgical outcome for DCM with good accuracy at the individual patient level on an independent testing cohort. Our analysis demonstrates the applicability of machine-learning to predictive modeling in spine surgery.
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Clinical Trial
Double arterial cannulation strategy for acute type A aortic dissection repair: A 10-year single-institution experience.
Repair of acute type A aortic dissection (ATAAD) is a complex and emergent cardiovascular surgery that is associated with high perioperative morbidity and mortality. Each cannulation strategy has different benefits and drawbacks during cardiopulmonary bypass. Using a retrospective study design, we aimed to clarify the safety and efficacy of right axillary artery cannulation in combination with femoral artery cannulation compared to single arterial cannulation for ATAAD repair. ⋯ With acceptable short- and mid-term outcomes, DAC is effective and safe for establishing cardiopulmonary bypass during ATAAD repair.
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Traumatic brain injury (TBI) is common and associated with a marked increased risk of developing epilepsy. Animal studies indicate that treatment with selective serotonin reuptake inhibitors (SSRIs) may increase the risk of epilepsy after TBI. The aim of this study was to investigate whether use of SSRIs modifies the risk of epilepsy after TBI. ⋯ This large population based cohort study showed that people using SSRI at the time of a TBI had higher risk of developing epilepsy compared to people not using SSRI at the time of TBI. The results are in line with those of animal studies and calls for further studies to evaluate whether the association is due to SSRIs or to the underlying disease (e.g. depression or anxiety).
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Floating catchment methods have recently been applied to identify priority regions for Automated External Defibrillator (AED) deployment, to aid in improving Out of Hospital Cardiac Arrest (OHCA) survival. This approach models access as a supply-to-demand ratio for each area, targeting areas with high demand and low supply for AED placement. These methods incorporate spatial covariates on OHCA occurrence, but do not provide precise AED locations, which are critical to the initial intent of such location analysis research. Exact AED locations can be determined using optimisation methods, but they do not incorporate known spatial risk factors for OHCA, such as income and demographics. Combining these two approaches would evaluate AED placement impact, describe drivers of OHCA occurrence, and identify areas that may not be appropriately covered by AED placement strategies. There are two aims in this paper. First, to develop geospatial models of OHCA that account for and display uncertainty. Second, to evaluate the AED placement methods using geospatial models of accessibility. We first identify communities with the greatest gap between demand and supply for allocating AEDs. We then use this information to evaluate models for precise AED location deployment. ⋯ The methods in this paper incorporate OHCA spatial risk factors and OHCA coverage to identify spatial regions most in need of resources. These methods can be used to help understand how AED allocation methods affect OHCA accessibility, which is of significant practical value for communities when deciding AED placements.
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An infectious disease outbreak such as the 2009 influenza pandemic is an unexpected demand shock to hospital emergency departments (EDs). We analysed changes in key performance metrics in (EDs) in Victoria during this pandemic to assess the impact of this demand shock. ⋯ This pandemic event caused excess demand leading to increased waiting times, did-not-wait patients and access block. Increases in admitted patients were more strongly associated with crowding than non-admitted patients during the pandemic period, so policies to divert or mitigate low-complexity non-admitted patients are unlikely to be effective in reducing ED crowding.