Use of Intraoperative Ultrasound During Spinal Surgery

Study Design: Review and technical report. Objective: Intraoperative ultrasound has been used by spine surgeons since the early 1980s. Since that time, more advanced modes of intraoperative imaging and navigation have become widely available. Although the use of ultrasound during spine surgery has fallen out of favor, it remains the only true real-time imaging modality that allows surgeons to visualize soft tissue anatomy instantly and continuously while operating. It is our objective to demonstrate that for this reason, ultrasound is a useful adjunctive technique for spine surgeons, especially when approaching intradural lesions or when addressing pathology in the ventral spinal canal via a posterior approach. Methods: Using PubMed, the existing literature regarding the use of intraoperative ultrasound during spinal surgery was evaluated. Also, surgical case logs were reviewed to identify spinal operations during which intraoperative ultrasound was used. Illustrative cases were selected and reviewed in detail. Results: This article provides a brief review of the history of intraoperative ultrasound in spine surgery and describes certain surgical scenarios during which this technique might be useful. Several illustrative cases are provided from our own experience. Conclusions: Surgeons should consider the use of intraoperative ultrasound when approaching intradural lesions or when addressing pathology ventral to the thecal sac via a posterior approach

Validation of an International Classification of Disease, Ninth Revision coding algorithm to identify decompressive craniectomy for stroke

Background: Although International Classification of Disease, Ninth Revision, Clinical Modification (ICD9-CM) coding is the basis of administrative claims data, no study has validated an ICD9-CM algorithm to identify patients undergoing decompressive craniectomy for space-occupying supratentorial infarction. Methods: Patients who underwent decompressive craniectomy for stroke at our institution were retrospectively identified and their associated ICD9-CM codes were extracted from billing data. An ICD9-CM algorithm was generated and its accuracy compared against physician review. Results: A total of 10,925 neurosurgical operations were performed from December 2008 to March 2015, of which 46 (0.4%) were decompressive craniectomy for space-occupying stroke. The ICD9-CM procedure code for craniectomy (01.25) was only encoded in 67.4% of patients, while craniotomy (01.24) was used in 19.6% and lobectomy (01.39, 01.53, 01.59) in 13.1%. The ICD-9-CM algorithm included patients with a diagnosis codes for cerebral infarction (433.11, 434.01, 434.11, and 434.91) and a procedure code for craniotomy, craniectomy, or lobectomy. Patients were excluded with an ICD9-CM diagnosis code for brain tumor, intracranial abscess, subarachnoid hemorrhage, vertebrobasilar infarction, intracranial aneurysm, Moyamoya disease, intracranial venous sinus thrombosis, vertebral artery dissection, congenital cerebrovascular anomaly, head trauma or an ICD9-CM procedure code for laminectomy. This algorithm had a sensitivity of 97.8%, specificity of 99.9%, positive predictive value of 88.2%, and negative predictive value of 99.9%. The majority of false-positive results were patients who underwent evacuation of a primary intracerebral hematoma. Conclusion: An ICD-9-CM algorithm based on diagnosis and procedure codes can effectively identify patients undergoing decompressive craniectomy for supratentorial stroke

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Structural Elements Recognized by Abacavir-Induced T Cells

Adverse drug reactions are one of the leading causes of morbidity and mortality in health care worldwide. Human leukocyte antigen (HLA) alleles have been strongly associated with drug hypersensitivities, and the causative drugs have been shown to stimulate specific T cells at the sites of autoimmune destruction. The structural elements recognized by drug-specific T cell receptors (TCRs) in vivo are poorly defined. Drug-stimulated T cells express TCRs specific for peptide/HLA complexes, but the characteristics of peptides (sequence, or endogenous or exogenous origin) presented in the context of small molecule drugs are not well studied. Using HLA-B*57:01 mediated hypersensitivity to abacavir as a model system, this study examines structural similarities of HLA presented peptides recognized by drug-specific TCRs. Using the crystal structure of HLA-B*57:01 complexed with abacavir and an immunogenic self peptide, VTTDIQVKV SPT5a 976–984, peptide side chains exhibiting flexibility and solvent exposure were identified as potential drug-specific T cell recognition motifs. Viral sequences with structural motifs similar to the immunogenic self peptide were identified. Abacavir-specific T cell clones were used to determine if virus peptides presented in the context of abacavir stimulate T cell responsiveness. An abacavir-specific T cell clone was stimulated by VTQQAQVRL, corresponding to HSV1/2 230–238, in the context of HLA-B*57:01. These data suggest the T cell polyclonal response to abacavir consists of multiple subsets, including T cells that recognize self peptide/HLA-B*57:01 complexes and crossreact with viral peptide/HLA-B*57:01 complexes due to similarity in TCR contact residues

Tuberculose cutânea disseminada com escrofuloderma associado à tuberculose de arco costal

Os autores relatam caso de tuberculose cutânea disseminada com escrofuloderma associado à tuberculose de arco costal. Paciente de 46 anos, do sexo feminino, há um ano com nódulos de um a 6cm em região cervical, dorso, axilas e regiões glúteas, que culminavam com fistulização e eliminação de secreção purulenta, associados a febre vespertina diária, sudorese noturna e emagrecimento de 10kg nos últimos três meses. A radiografia de tórax mostrou lesão lítica na terceira costela esquerda. A cultura de secreção do nódulo foi positiva para Mycobacterium tuberculosis. O tratamento para tuberculose resultou em melhora clínica e resolução das lesões cutâneas da paciente

Impact of paravalvular leak on outcomes after transcatheter aortic valve implantation : meta-analysis of Kaplan-Meier-derived individual patient data

Background Paravalvular leak (PVL) after transcatheter aortic valve implantation (TAVI) is frequent and the impact of mild PVL on outcomes remains uncertain. Our study aimed to evaluate the impact of PVL on TAVI outcomes. Methods To analyze late outcomes of patients after TAVI according to the presence and severity of PVL, PubMed/MEDLINE, EMBASE and Google Scholar were searched for studies that reported rates of all-cause mortality/survival and/or rehospitalization and/or cardiovascular mortality accompanied by at least one Kaplan-Meier curve for any of these outcomes. We adopted a 2-stage approach to reconstruct individual patient data based on the published Kaplan-Meier graphs. Results Thirty-eight studies with Kaplan-Meier curves met our eligibility criteria including over 25,000 patients. Patients with any degree of PVL after TAVI had a significantly higher risk of overall mortality (hazard ratio (HR), 1.52; 95% confidence interval (CI), 1.43-1.61; p < 0.001), rehospitalization (HR, 1.81; 95% CI, 1.54-2.12; p < 0.001), and cardiovascular mortality (HR, 1.52; 95% CI, 1.33-1.75; p < 0.001) over time. These findings remained consistent when we stratified the results for the methods of assessment of PVL (i.e., echocardiography vs. angiography) and PVL severity. Both moderate/severe PVL and mild PVL were associated with increased risk of overall mortality (p < 0.001), rehospitalization (p < 0.001), and cardiovascular mortality (p < 0.001) during follow-up. Conclusions Patients with PVL, even if mild, experience higher risk of all-cause mortality, rehospitalization, and cardiovascular mortality following TAVI. These findings provide support to the implementation of procedural strategies to prevent any degree of PVL at the time of TAVI