Ligamentum flavum cyst in the lumbar spine: a case report and review of the literature

Degenerative changes in the lumbar spine can be followed by cystic changes. Most reported intraspinal cysts are ganglion or synovial cysts. Ligamentum flavum pseudocyst, as a cystic lesion in the lumbar spine, is a rare and unusual cause of neurologic signs and symptoms and is usually seen in elderly persons (due to degenerative changes). They are preferentially located in the lower lumbar region, while cervical localization is rare. Complete removal of the cyst leads to excellent results and seems to preclude recurrence. We report the case of a right-sided ligamentum flavum cyst occurring at L3–L4 level in a 70-year-old woman, which was surgically removed with excellent postoperative results and complete resolution of symptoms. In addition, we discuss and review reports in the literature

Optimal Cerebral Perfusion Pressure During Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

OBJECTIVES: The recommendation of induced hypertension for delayed cerebral ischemia treatment after aneurysmal subarachnoid hemorrhage has been challenged recently and ideal pressure targets are missing. A new concept advocates an individual cerebral perfusion pressure where cerebral autoregulation functions best to ensure optimal global perfusion. We characterized optimal cerebral perfusion pressure at time of delayed cerebral ischemia and tested the conformity of induced hypertension with this target value. DESIGN: Retrospective analysis of prospectively collected data. SETTING: University hospital neurocritical care unit. PATIENTS: Thirty-nine aneurysmal subarachnoid hemorrhage patients with invasive neuromonitoring (20 with delayed cerebral ischemia, 19 without delayed cerebral ischemia). INTERVENTIONS: Induced hypertension greater than 180 mm Hg systolic blood pressure. MEASUREMENTS AND MAIN RESULTS: Changepoint analysis was used to calculate significant changes in cerebral perfusion pressure, optimal cerebral perfusion pressure, and the difference of cerebral perfusion pressure and optimal cerebral perfusion pressure 48 hours before delayed cerebral ischemia diagnosis. Optimal cerebral perfusion pressure increased 30 hours before the onset of delayed cerebral ischemia from 82.8 +/- 12.5 to 86.3 +/- 11.4 mm Hg (p < 0.05). Three hours before delayed cerebral ischemia, a changepoint was also found in the difference of cerebral perfusion pressure and optimal cerebral perfusion pressure (decrease from -0.2 +/- 11.2 to -7.7 +/- 7.6 mm Hg; p < 0.05) with a corresponding increase in pressure reactivity index (0.09 +/- 0.33 to 0.19 +/- 0.37; p < 0.05). Cerebral perfusion pressure at time of delayed cerebral ischemia was lower than in patients without delayed cerebral ischemia in a comparable time frame (cerebral perfusion pressure delayed cerebral ischemia 81.4 +/- 8.3 mm Hg, no delayed cerebral ischemia 90.4 +/- 10.5 mm Hg; p < 0.05). Inducing hypertension resulted in a cerebral perfusion pressure above optimal cerebral perfusion pressure (+12.4 +/- 8.3 mm Hg; p < 0.0001). Treatment response (improvement of delayed cerebral ischemia: induced hypertension(+) [n = 15] or progression of delayed cerebral ischemia: induced hypertension(-) [n = 5]) did not correlate to either absolute values of cerebral perfusion pressure or optimal cerebral perfusion pressure, nor the resulting difference (cerebral perfusion pressure [p = 0.69]; optimal cerebral perfusion pressure [p = 0.97]; and the difference of cerebral perfusion pressure and optimal cerebral perfusion pressure [p = 0.51]). CONCLUSIONS: At the time of delayed cerebral ischemia occurrence, there is a significant discrepancy between cerebral perfusion pressure and optimal cerebral perfusion pressure with worsening of autoregulation, implying inadequate but identifiable individual perfusion. Standardized induction of hypertension resulted in cerebral perfusion pressures that exceeded individual optimal cerebral perfusion pressure in delayed cerebral ischemia patients. The potential benefit of individual blood pressure management guided by autoregulation-based optimal cerebral perfusion pressure should be explored in future intervention studies

Enteric dysbiosis and fecal calprotectin expression in premature infants.

BackgroundPremature infants often develop enteric dysbiosis with a preponderance of Gammaproteobacteria, which has been related to adverse clinical outcomes. We investigated the relationship between increasing fecal Gammaproteobacteria and mucosal inflammation, measured by fecal calprotectin (FC).MethodsStool samples were collected from very-low-birth weight (VLBW) infants at ≤2, 3, and 4 weeks' postnatal age. Fecal microbiome was surveyed using polymerase chain reaction amplification of the V4 region of 16S ribosomal RNA, and FC was measured by enzyme immunoassay.ResultsWe enrolled 45 VLBW infants (gestation 27.9 ± 2.2 weeks, birth weight 1126 ± 208 g) and obtained stool samples at 9.9 ± 3, 20.7 ± 4.1, and 29.4 ± 4.9 days. FC was positively correlated with the genus Klebsiella (r = 0.207, p = 0.034) and its dominant amplicon sequence variant (r = 0.290, p = 0.003), but not with the relative abundance of total Gammaproteobacteria. Klebsiella colonized the gut in two distinct patterns: some infants started with low Klebsiella abundance and gained these bacteria over time, whereas others began with very high Klebsiella abundance.ConclusionIn premature infants, FC correlated with relative abundance of a specific pathobiont, Klebsiella, and not with that of the class Gammaproteobacteria. These findings indicate a need to define dysbiosis at genera or higher levels of resolution

A novel approach : the propensity to propagate (PTP) method for controlling for host factors in studying the transmission of Mycobacterium tuberculosis

RATIONALE: Understanding the genetic variations among Mycobacterium tuberculosis (MTB) strains with differential ability to transmit would be a major step forward in preventing transmission. OBJECTIVES: To describe a method to extend conventional proxy measures of transmissibility by adjusting for patient-related factors, thus strengthening the causal association found with bacterial factors. METHODS: Clinical, demographic and molecular fingerprinting data were obtained during routine surveillance of verified MTB cases reported in the Netherlands between 1993 and 2011, and the phylogenetic lineages of the isolates were inferred. Odds ratios for host risk factors for clustering were used to obtain a measure of each patient's and cluster's propensity to propagate (CPP). Mean and median cluster sizes across different categories of CPP were compared amongst four different phylogenetic lineages. RESULTS: Both mean and median cluster size grew with increasing CPP category. On average, CPP values from Euro-American lineage strains were higher than Beijing and EAI strains. There were no significant differences between the mean and median cluster sizes among the four phylogenetic lineages within each CPP category. CONCLUSIONS: Our finding that the distribution of CPP scores was unequal across four different phylogenetic lineages supports the notion that host-related factors should be controlled for to attain comparability in measuring the different phylogenetic lineages' ability to propagate. Although Euro-American strains were more likely to be in clusters in an unadjusted analysis, no significant differences among the four lineages persisted after we controlled for host factors.Portuguese Foundation for Science and Technology (FCT) (SFRH/BD/33902/2009 to HN-G). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts