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Social media platforms are used for support and as resources by people from the endometriosis community who are seeking advice about diagnosis, education, and disease management. However, little is known about the scientific accuracy of information circulated on Instagram about the disease. To fill this gap, this study analysed the evidence-based nature of content on Instagram about endometriosis. A total of 515 Instagram posts published between February 2022 and April 2022 were gathered and analysed using a content analysis method, resulting in sixteen main content categories, including "educational", which comprised eleven subcategories. Claims within educational posts were further analysed for their evidence-based accuracy, guided by a process which included fact-checking all claims against the current scientific evidence and research. Of the eleven educational subcategories, only four categories (cure, scientific article, symptoms, and fertility) comprised claims that were at least 50% or greater evidence-based. More commonly, claims comprised varying degrees of evidence-based, mixed, and non-evidence-based information, and some categories, such as surgery, were dominated by non-evidence-based information about the disease. This is concerning as social media can impact real-life decision-making and management for individuals with endometriosis. Therefore, this study suggests that health communicators, clinicians, scientists, educators, and community groups trying to engage with the endometriosis online community need to be aware of social media discourses about endometriosis, while also ensuring that accurate and translatable information is provided.
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Introduction Coronavirus disease 2019 (COVID-19) has emerged as a global pandemic that has placed an unprecedented burden on intensive care services worldwide. Identification of a reliable risk-stratification tool for COVID-19 patients is necessary for appropriate resource allocation, selection of clinical management pathways, and guidance of goals of care conversations with families and caregivers in the critical care setting. The Acute Physiologic Assessment and Chronic Health Evaluation (APACHE) II scoring system is one of several predictive models used to classify illness severity and estimate mortality risk on admission to the intensive care unit (ICU). Our retrospective study sought to evaluate the prognostic ability of the APACHE II score in COVID-19 patients according to endpoints of mortality and length of stay (LOS) as well as unfavorable clinical outcomes, including development of acute renal failure (ARF) requiring renal replacement therapy (RRT) and acute venous thromboembolic events (VTE). Methods This multicenter retrospective cohort study evaluated a randomized sample of 3,102 patients with confirmed COVID-19 disease admitted to the ICU from January 2020 to May 2020. A total of 395 patients with complete data points for appropriate APACHE II score calculation, absence of the preexisting comorbidities end-stage renal disease, and history of VTE were included. Linear and logistic regression models were employed to evaluate primary outcomes of mortality and LOS as well as secondary outcomes of VTE and ARF requiring continuous renal replacement therapy (CRRT) or hemodialysis (HD). Key results Among the 395 patients enrolled, total percent mortality and mean LOS were 37.0% and 12.92 days, respectively. Primary outcome analysis revealed a statistically significant increase in odds of mortality as well as in mean LOS with every additional point increase in APACHE II score from a baseline of zero. Specifically, for every point increase in the APACHE II score, odds of mortality increased by 12% (p value < 0.001), and average LOS increased by 0.2 days (p value < 0.001). In our secondary outcome analysis, 14.43% and 62.2% of the total sample population developed ARF requiring RRT and VTE, respectively. For every additional point increase in APACHE II score from a baseline of zero, odds of requiring CRRT or HD increased by 10% on average (95% CI (1.06, 1.15); p value < 0.001). Similarly, for every additional point increase in the APACHE II score from a baseline of zero, there was a corresponding increase in odds of VTE by 19% (95% CI (1.14, 1.24); p value < 0.001). Conclusions The APACHE II score is an effective predictive model of in-hospital mortality and unfavorable clinical outcomes, including prolonged LOS, ARF requiring CRRT or HD, and development of VTE. As therapeutic interventions for COVID-19 evolve, application of this risk-stratification tool may guide clinical management decisions in the critical care setting.
RESUMEN
Central nervous system (CNS) involvement occurs in about 1% of all tuberculosis (TB) cases, classically presenting as a meningitis. Intracerebral tuberculomas are a much rarer manifestation. We describe the case of a young black male who presented with new-onset seizure. Cerebral computerized tomography from an outside hospital reportedly showed findings concerning for septic emboli. Brain magnetic resonance imaging at our institution confirmed the presence of multiple, peripherally enhancing lesions in the right frontal and temporal lobes, cerebellum, and pons. Thoracentesis was performed for a concomitant pleural effusion, which contained elevated levels of adenosine deaminase and ultimately grew Mycobacterium tuberculosis. After ruling out other causes, we reached a diagnosis of CNS TB manifesting as cerebral tuberculomas. The patient was initiated on a course of rifampin, isoniazid, pyrazinamide, and ethambutol for two months, followed by rifampin and isoniazid to complete at least twelve months of antimicrobial therapy. We present this case to highlight this unusual manifestation of CNS TB and review the challenges in diagnosis.
