Neuromyelitis optica in a pregnant woman with systemic lupus erythematous: A case report.

No Abstact##

Sociodemographic and Illness-Related Indicators to Predict the Status of Neuromyelitis Optica Spectrum Disorder (NMOSD) Five Years after Disease Onset

Background: Neuromyelitis Optica Spectrum Disorder (NMOSD) is an autoimmune demyelinating disease of the central nervous system. Currently, no factors have been identified to predict the long-term course of NMOSD. To counter this, we analyzed data of 58 individuals with NMOSD at disease onset and about five years later. Methods: Medical records of 58 individuals with NMOSD (mean age: 31.13 years at disease onset; 86.2% female) were retrospectively analyzed. At baseline, a thorough medical and disease-related examination was performed; the same examination was repeated about five years later at follow-up, including treatment-related information. Mean outcome measure was the difference in EDSS (Expanded Disease Severity Scale) scores between baseline and follow-up. Results: Mean disease duration was 4.67 years. Based on the differences of the EDSS scores between baseline and follow-up, participants were categorized as improving (n = 39; 67.2%), unchanged (n = 13; 22.4%) and deteriorating (n = 6; 10.3%). Deteriorating was related to a higher progression index, and a higher number of attacks, while the annualized relapse rate reflecting the number of attacks per time lapse did not differ between the three groups. Improving was related to a higher intake of rituximab, and to a higher rate of seropositive cases. Unchanged was related to a lower rate of seropositive cases. Factors such as age, gender, somatic and psychiatric comorbidities, symptoms at disease onset, relapse rates, number and location of cervical plaques, or brain plaques and thoracolumbar plaques at baseline did not differ between those improving, deteriorating or remaining unchanged. Conclusions: Among a smaller sample of individuals with NMOSD followed-up about five years later, individuals deteriorating over time reported a higher progression index, while the annualized relapse rate was unrelated to the progress of disease. Overall, it appears that the course of NMOSD over a time lapse of about five years after disease onset is highly individualized. Accordingly, treatment regimen demands a highly individually tailored approach

Comparison of prevalence rates of restless legs syndrome, self-assessed risks of obstructive sleep apnea, and daytime sleepiness among patients with multiple sclerosis (MS), clinically isolated syndrome (CIS) and Neuromyelitis Optica Spectrum Disorder (NMOSD)

Prevalence rates for restless legs syndrome (RLS) and risk of Obstructive Sleep Apnea (OSA) in individuals with Neuromyelitis Optica Spectrum Disorder (NMOSD) and Clinically Isolated Syndrome (CIS) are unknown. The aims of the present study were to assess symptoms of RLS and self-assessed risks of OSA in individuals with NMOSD and CIS, to compare these prevalence rates with those of persons with multiple sclerosis (MS), and to associate RLS and OSA with expanded disability status scale (EDSS) scores, daytime sleepiness, fatigue, paresthesia, and medication.; A total of 495 individuals (mean age = 34.92 years, 84.9% females) were assessed. Of these, 24 had NMOSD, 112 had CIS and 359 had MS. Trained neurologists ascertained individuals' neurological diagnoses, assessed their EDSS scores, and conducted a clinical interview to assess RLS. Additionally, participants completed questionnaires covering sociodemographic information, risks of snoring and OSA, daytime sleepiness, fatigue, paresthesia and medication.; Prevalence rates of RLS were 45.8% in NMOSD, 41.1% in CIS, and 28.7% in MS. Prevalence rates of self-assessed risks of OSA were 8.3% in NMOSD, 7.7% in CIS, and 7.8% in MS; these rates were not significantly different. Across the entire sample and within the diagnostic groups, RLS and OSA scores were unrelated to EDSS, daytime sleepiness, fatigue or medication.; Individuals with NMOSD, CIS and MS have high prevalence rates for RLS and self-assessed risks of obstructive sleep apnea syndrome (OSAS), which are unrelated to EDSS, daytime sleepiness, fatigue, paresthesia, or medication. Sleep issues should be monitored during routine check-ups for individuals with NMOSD and CIS

Clinical Characteristics and Disability Progression of Early- and Late-Onset Multiple Sclerosis Compared to Adult-Onset Multiple Sclerosis

Compared to the adult onset of multiple sclerosis (AOMS), both early-onset (EOMS) and late-onset (LOMS) are much less frequent, but are often under- or misdiagnosed. The aims of the present study were: 1. To compare demographic and clinical features of individuals with EOMS, AOMS and LOMS, and 2. To identify predictors for disability progression from relapsing remitting MS (RRMS) to secondary progressive MS (SPMS).; Data were taken from the Isfahan Hakim MS database. Cases were classified as EOMS (MS onset 18 years), LOMS (MS onset >50 years) and AOMS (MS >18 and 50 years). Patients' demographic and clinical (initial symptoms; course of disease; disease patterns from MRI; disease progress) information were gathered and assessed. Kaplan-Meier and Cox proportional hazard regressions were conducted to determine differences between the three groups in the time lapse in conversion from relapsing remitting MS to secondary progressive MS.; A total of 2627 MS cases were assessed; of these 127 were EOMS, 84 LOMS and 2416 AOMS. The mean age of those with EOMS was 14.5 years; key symptoms were visual impairments, brain stem dysfunction, sensory disturbances and motor dysfunctions. On average, 24.6 years after disease onset, 14.2% with relapsing remitting MS (RRMS) were diagnosed with secondary progressive MS (SPMS). The key predictor variable was a higher Expanded Disability Status Scale (EDSS) score at disease onset. Compared to individuals with AOMS and LOMS, those with EOMS more often had one or two relapses in the first two years, and more often gadolinium-enhancing brain lesions. For individuals with AOMS, mean age was 29.4 years; key symptoms were sensory disturbances, motor dysfunctions and visual impairments. On average, 20.5 years after disease onset, 15.6% with RRMS progressed to SPMS. The key predictors at disease onset were: a higher EDSS score, younger age, a shorter inter-attack interval and spinal lesions. Compared to individuals with EOMS and LOMS, individuals with AOMS more often had either no or three and more relapses in the first two years. For individuals with LOMS, mean age was 53.8 years; key symptoms were motor dysfunctions, sensory disturbances and visual impairments. On average, 14 years after disease onset, 25.3% with RRMS switched to an SPMS. The key predictors at disease onset were: occurrence of spinal lesions and spinal gadolinium-enhancement. Compared to individuals with EOMS and AOMS, individuals with LOMS more often had no relapses in the first two years, and higher EDSS scores at disease onset and at follow-up.; Among a large sample of MS sufferers, cases with early onset and late onset are observable. Individuals with early, adult and late onset MS each display distinct features which should be taken in consideration in their treatment

Decoy Cell Viruria in Kidney Transplant Patients. Does it correlate with Renal Function?

Objective: BK virus (BKV) infection after kidney transplantation has been a topic of great interest in the recent decade. Prospective screening studies have revealed that BKVN is principally an early complication of renal transplantation occurring within the first post-transplant year in most cases. The aim of the present study was to observe the incidence of decoy cell viruria in renal transplant recipients. Furthermore, correlation of decoy cell viruria with graft function was assessed. Methods: This analytic cross-sectional study was conducted in the Transplant Center of Alzahra Hospital, Isfahan, Iran between Jun 2014 and June 2015. Clinical screening for polyomavirus infection was done by means of urine cytological evaluation for decoy cells. Urine samples were analyzed in three steps including 2-4 months after transplantation, three and six months later. Results: Thirty-three patients (22 male and 11 female) received kidney transplant from living donors. The average of patients' age was 41.9 +/- 12.83 (range: 20-63 years). Peritoneal and hemodialysis were used for 15.6% and 84.4% of recipients. The occurrence of decoy cell viruria at the time of enrollment, 3 and 6 months later was found in 18.2%, 10.7% and zero, respectively. Conclusion: As urine cytology is easy to perform and of low cost, it is a useful tool for the investigation of active polyoma virus infection. Moreover, the findings advocate that the presence of decoy cells along with high creatinine is a better indicator of the virus presence

Post-treatment Guillain-Barre Syndrome in a Patient with Brucellosis; A Case Report

Introduction: Guillain-Barre Syndrome is an uncommon complication during acute brucellosis. Case presentation: In this study, we present a case of Guillain-Barre Syndrome in a 22-year old male patient with complaints of weakness in his lower limbs. He had a history of acute Brucella infection for four months and received antimicrobial medication. Conclusion: the patients can be affected by GBS after antimicrobial treatment

Association Between Helicobacter Pylori Infection and Seronegative Neuromyelitis Optica Spectrum Disorder

Background: Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune demyelinating disease in the central nervous system. Association between NMOSD and Helicobacter pylori (H. pylori) infection has been investigated, but few studies have assessed the relationship between H. pylori and seronegative AQP4-Ab NMOSD. Objectives: This study aimed to survey the association between H. pylori infection and NMOSD patients with seronegative AQP4-Ab status, as well as the possible relationship between the presence of H. pylori and clinical characteristics. Materials & Methods: This cross-sectional study was carried out in Kashani Hospital affiliated with the Isfahan University of Medical Sciences, Isfahan, Iran, from October 2017 to May 2019. A total of 35 consecutive seronegative AQP4-Ab NMOSD patients and 37 sex and age-matched healthy controls participated in the study. Demographic and clinical characteristics were obtained from all participants. We assessed participants’ seroprevalence of IgG and IgM antibodies against H. pylori. The Association of H. pylori with NMOSD was determined. Results: The frequency of IgG and IgM Ab H. pylori seropositivity in NMOSD patients was 22.9% and 40.0%, respectively. Among HC, 11(29.7%) and 20(54.1%) were positive for IgG and IgM Ab H. pylori. Although the rate of H. pylori IgG (OR=0.700, 95%, CI=0.243, 2.017, P=0.420) and IgM Ab (OR=0.567, 95%, CI=0.222, 1.444, P=0.233) seropositivity in NMOSD were lower than NMOSD, these differences were not statistically different. No clinical variables associated with H. pylori IgG and IgM seropositivity infection seropositivity. Conclusion: These findings show that possibly there is no relationship between H. pylori infection and seronegative AQP4-Ab NMOSD

Higher Disease and Pain Severity and Fatigue and Lower Balance Skills Are Associated with Higher Prevalence of Falling among Individuals with the Inflammatory Disease of Neuromyelitis Optica Spectrum Disorder (NMOSD)

Neuromyelitis optica spectrum disorder (NMOSD) is a chronic inflammatory and autoimmune disorder that is associated with impaired vision, sensory loss, pain, fatigue, and spasms in the upper and lower limbs. Typically, persons with this disorder are also at higher risks of falls. Given this, the aims of the study were to compare the prevalence rates of falling for NMOSD cases and healthy controls (HCs), and to predict falling in the former group based on sociodemographic, psychological, and illness-related factors.; A total of 95 adults with NMOSD (Mean age = 34.89 years; 70.5% females) and 100 matched HCs took part in the study. All participants completed a series of questionnaires covering sociodemographic information and falling rates. The NMOSD individuals also reported on disease duration, pain, fatigue, and fear of falling, while their balance performance was objectively assessed.; Compared to healthy controls, the NMOSD cases had a 2.5-fold higher risk of falling. In this latter group, higher scores for pain, fatigue, fear of falling, and higher EDSS scores were distinguished between fallers and non-fallers, and objective balance skills had no predictive value.; Compared to healthy controls, NMOSD sufferers had a 2.5-fold higher risk of experiencing falls. In this group, disease impairments (EDSS, fatigue, pain) predicted falling. Specific interventions such as regular resistance training might reduce the risk of falling

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. METHODS: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING: Bill & Melinda Gates Foundation