Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

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

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Prestorage inline leukodepletion of buffy coat-depleted packed red blood cells: Comparative analysis of white blood cell count and interleukin-8 between leukodepleted and nonleukodepleted packed red blood cells

Background and Objectives: We aimed to analyze the impact of prestorage Inline leukodepletion and storage time on interleukin 8 (IL-8) levels in stored buffy coat-depleted packed red blood cell (PRBC) units in the Kashmiri population setting. Methods: A total of 50 donors of Kashmiri origin from North India equally and randomly distributed between Leukodepleted (LD) and non-LD (NLD) arms were recruited in this study. Leukodepletion of PRBCs units was performed using 3rd Generation integrated LD filters and the residual white blood cell (WBC) count was enumerated by FACS using fluorochrome-tagged CD45+ antibodies and IL-8 levels measured by ELISA. Results: In contrast to NLD arm, leukodepletion in the LD arm significantly reduced total leukocyte count (TLC) from pre-LD TLC of 2.25 ± 0.47 × 109/PRBC unit to post LD cell count of 2.40 ± 0.65 × 106/PRBC unit, P = 0.001, i.e., 3 log reduction, P = 0.0001. Contrary to the LD arm, a significant difference in IL-8 levels in NLD arm was observed with 27.15 ± 30.32 pg/mL on day 0, 45.15 ± 36.15 pg/mL on day 14, and on day 28, 37.98 ± 33.05 pg/mL. Furthermore, significant variance (LD vs. NLD) in IL-8 levels was observed at day 0, 14th, and 28th day of storage, with maximum variance observed on day 14th Fstat = 21.46, P = 0.00, depicting prestorage LD have a significant role in suppressing the IL-8 levels in LD stored PRBC units while as in NLD PRBC units with time IL-8 accumulated as its cell source (WBCs) was intact. Conclusion: Inline prestorage leukodepletion by 3rd generation LD filters was uniformly effective in reducing the residual WBC count to desired levels of <5 × 106/unit of PRBC. The significant decrease in TLC and resultant far less accumulation of cytokine (IL-8) in prestorage LD PRBC units of Kashmiri origin, as observed in this study, would be translated into clinical benefits associated with transfusion of LD-PRBC units

CSF Neurofilament-H Levels as a Potential Section Prognostic Marker in Patients of GuillainBarré Syndrome- A Cohort Study

Introduction: The prognosis of Guillain-Barré Syndrome (GBS) at an early stage with explicit biomarkers is critical to distinguish patients with possibility of poor recovery. Cerebrospinal Fluid (CSF) serves as an impending source for biomarkers that portrays the exact biochemical changes. Aim: To find out if there is any prognostic value of high CSF phosphorylated Neurofilament Heavy subunit (pNf-H) levels, measured during first two weeks of onset of GBS, as assessed by the level of disability at six months after the onset of GBS. Materials and Methods: The cohort study was conducted in the Department of Neurology and Department of Immunology and Molecular Medicine, at the Sher-I-Kashmir Institute of Medical Sciences, Soura, Srinagar, Jammu and Kashmir, India, over a period of two years from August 2015 to August 2017. Sixty two patients who satisfied the required diagnostic standards for GBS (study group) and 35 patients with tension-type headache (control group) were selected for the study. After clinical and electrophysiological assessment, CSF samples were collected. A commercially available sandwich enzyme immunoassay kit, manufactured by BioVendor-Laboratorní medicína (Czech Republic), was used for measuring human pNf-H quantitatively. Results: Mean CSF pNf-H level in patients with good outcome was 325.3 pg/mL whereas, in patients with poor outcome it was 3655.2 pg/mL. CSF pNf-H levels were found to be suggestively higher in GBS patients with poor outcome as compared to those with good outcome. Only eight patients in good outcome group had pathologically high CSF Nf-H levels whereas 10 patients in poor outcome group had CSF Nf-H levels ≤730 pg/mL. The odds ratio was 17.1 (95% Confidence Interval (CI) 3.83-76.29). Thus, high CSF Nf-H levels on admission predicted poor outcome in GBS (p-value <0.001). Moderate degree of positive correlation was found between CSF Nf-H levels and outcome (F score) at six months (R=0.684; p-value <0.001). Conclusion: It can be determined that higher values of CSF pNf-H in GBS (acute stage), could serve as a predictive marker indicative of poor prognosis

Effect of Vitamin D supplementation on glycemic parameters and progression of prediabetes to diabetes: A 1-year, open-label randomized study

Background: Whether Vitamin D supplementation in prediabetes subjects prevents the development of diabetes is a matter of debate, and the results are inconsistent. This open-label, randomized study in subjects with prediabetes evaluated the effect of 12 months of Vitamin D supplementation on glycemic parameters and progression of prediabetes to diabetes in an ethnically homogeneous Kashmiri population. Materials and Methods: A total of 147 subjects were diagnosed as prediabetes out of which 137 subjects were randomized to receive in addition to standard lifestyle measures, either Vitamin D 60,000 IU weekly for 4 weeks and then 60,000 IU monthly (n = 69) or no Vitamin D (n = 68). Fasting plasma glucose (FPG), 2-h plasma glucose and A1C levels were estimated at 0, 6 and 12 months. Changes in FPG, 2-h plasma glucose, A1C level and the proportion of subjects developing diabetes were assessed among 129 subjects. Results: At 12 months, A1C levels were significantly lesser (5.7% ± 0.4%) in the Vitamin D supplemented group when compared with non-Vitamin D supplemented (6.0% ± 0.3%). Similarly, FPG (97 ± 7) and 2-h plasma glucose (132 ± 16) were significantly less in Vitamin D supplemented group as compared with non-Vitamin D supplemented group (FPG = 116 ± 6 and 2-h plasma glucose = 157 ± 25) at 12 months. Nine out of 65 in non-Vitamin D supplemented and seven out of 64 in the Vitamin D supplemented group developed diabetes. Conclusions: Vitamin D supplementation in prediabetes subjects significantly lowered FPG, 2-h plasma glucose and A1C levels

Profile of leptin, adiponectin, and body fat in patients with hyperprolactinemia: Response to treatment with cabergoline

Introduction: Though hypoadiponectinemia and leptin resistance have been proposed as potential factors for weight gain in patients with hyperprolactinemia (HPL), the effects of HPL and cabergoline on these adipocyte-derived hormones are not clear. Aims of this study were (i) to assess the alterations of body fat, leptin, and adiponectin in patients with HPL (ii) effect of cabergoline treatment on these parameters. Methods: Nineteen consecutive patients with prolactinoma (median prolactin [PRL] 118.6 (interquartile range: 105.3) μg/L) and 20 controls were studied in a nonrandomized matched prospective design. The controls were age, gender, and body mass index (BMI) matched. Anthropometric data, metabolic variables, leptin, and adiponectin were studied at baseline and 3 and 6 months after cabergoline treatment. Results: Patients with prolactinoma had increased level of fasting plasma glucose (P < 0.001) as compared to age-, gender-, and BMI-matched healthy controls. Estradiol concentration of controls was higher than that of patients (P = 0.018). Patients with prolactinoma had higher levels of leptin (P = 0.027) as compared to healthy controls without a significant difference in adiponectin levels. There was a significant decrease of body weight at 3 months (P = 0.029), with a further decline at 6 months (P < 0.001) of cabergoline therapy. Furthermore, there was a significant decrement of BMI (P < 0.001), waist circumference (P = 0.003), waist-hip ratio (P = 0.03), total body fat (P = 0.003), plasma glucose (P < 0.001), leptin levels (P = 0.013), and an increase in estradiol concentration (P = 0.03) at 6 months of cabergoline treatment. Conclusion: Patients with prolactinoma have adverse metabolic profile compared to matched controls. Normalization of PRL with cabergoline corrects all the metabolic abnormalities

Effect of six-month use of oral contraceptive pills on plasminogen activator inhibitor-1 & factor VIII among women with polycystic ovary syndrome: An observational pilot study

Background & objectives: Polycystic ovary syndrome (PCOS) is an endocrinopathy warranting lifelong individualized management by lifestyle and pharmacological agents mainly oral contraceptive pills (OCPs). This study was aimed to report the impact of six-month OCP use on plasminogen activator inhibitor-1 (PAI-1) and factor VIII (FVIII) in women with PCOS. Methods: PCOS women diagnosed on the basis of Rotterdam 2003 criteria, either treated with OCPs (ethinyl estradiol-0.03 mg, levonorgestrel-0.15 mg) for a period of six months (n=40) or drug-naïve (n=42), were enrolled in this study. Blood was drawn to estimate glucose, insulin levels and lipid profile. Chemiluminescence immunoassays were used to measure hormones (LH, FSH, PRL, T4). Plasma levels of PAI-I and FVIII were measured by commercially available kits. Results: Menstrual regularity, Ferriman-Gallwey score and serum total testosterone significantly improved in the OCP group compared to drug-naïve group (P<0.01). No significant difference was observed in PAI-1 levels of the two groups; however, significant decrease in FVIII levels was observed in OCP group as compared to drug-naïve group. PAI-1 levels of OCP group correlated positively with blood glucose two hours, triglycerides and insulin two hours, while FVIII levels of OCP group correlated negatively with fasting insulin and homoeostatic model assessment-insulin resistance. Interpretation & conclusions: OCPs use has differential effect on pro-coagulant markers among women with PCOS. Well-designed, long-term, prospective, large-scale studies are prerequisite to elucidate the efficacy and safety of OCP in the treatment of PCOS

Universal salt iodization is successful in Kashmiri population as iodine deficiency no longer exists in pregnant mothers and their neonates: Data from a tertiary care hospital in North India

Introduction: Normal pregnancy results in a number of important physiological and hormonal changes that alter thyroid function. In pregnancy, the thyroid gland being subjected to physiological stress undergoes several adaptations to maintain sufficient output of thyroid hormones for both mother and fetus. Consequently, pregnant women have been found to be particularly vulnerable to iodine deficiency disorders (IDD), and compromised iodine status during pregnancy has been found to affect the thyroid function and cognition in the neonates. Objectives: Two decades after successful universal salt iodization (USI) in the country, there is scarce data on the iodine status of the pregnant women and their neonates. This is more relevant in areas like Kashmir valley part of sub-Himalayan belt, an endemic region for IDD in the past.The objective was to estimate Urinary Iodine status in pregnant women, the most vulnerable population. Materials and Methods: We studied thyroid function [free T3 (FT3), T3, free T4 (FT4), T4, thyroid stimulating hormone (TSH)] and urinary iodine excretion (UIE) in the 1 st , 2 nd , and 3 rd trimesters and at early neonatal period in neonates in 81 mother-infant pairs (hypothyroid women on replacement) and compared them with 51 control mother-infant pairs (euthyroid). Results: Mean age of cases (29.42 + 3.56 years) was comparable to that of controls (29.87 + 3.37 years). The thyroid function evaluation done at baseline revealed the following: FT3 2.92 ± 0.76 versus 3.71 ± 0.54 pg/ml, T3 1.38 ± 0.37 versus 1.70 ± 0.35 ng/dl, FT4 1.22 ± 0.33 versus 1.52 ± 0.21 ng/dl, T4 9.54 ± 2.34 versus 13.55 ± 2.16 μg/dl, and TSH 7.92 ± 2.88 versus 4.14 ± 1.06 μIU/ml in cases versus controls ( P < 0.01), respectively. The 2 nd to 6 th day thyroid function of neonates born to case and control mothers revealed T3 of 1.46 ± 0.44 versus 1.48 ± 0.36 ng/dl, T4 of 12.92 ± 2.57 versus 11.76 ± 1.78 μg/dl, and TSH of 3.64 ± 1.92 versus 3.82 ± 1.45 μIU/ml, respectively. Discussion: UIE was similar (139.12 ± 20.75 vs. 143.78 ± 17.65 μg/l; P = 0.8), but TSH values were higher in cases (7.92 ± 2.88) as compared to controls (4.14 ± 1.06). Although UIE gradually declined from 1 st trimester to term, it remained in the sufficient range in both cases and controls. Thyroid function and UIE was similar in both case and control neonates. Conclusion: We conclude that pregnant Kashmiri women and their neonates are iodine sufficient, indicating successful salt iodization in the community. Large community-based studies on thyroid function, autoimmunity, malignancies, etc., are needed to see the long-term impact of iodization