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.

METHODS: To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10-54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values-a metric assessing gain in forecasting accuracy-by comparing predicted versus observed ASFRs from the past 15 years (2007-21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.

FINDINGS: During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63-5·06) to 2·23 (2·09-2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137-147), declining to 129 million (121-138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1-canonically considered replacement-level fertility-in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7-29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59-2·08) in 2050 and 1·59 (1·25-1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6-43·1) in 2050 and 54·3% (47·1-59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions-decreasing, for example, in south Asia from 24·8% (23·7-25·8) in 2021 to 16·7% (14·3-19·1) in 2050 and 7·1% (4·4-10·1) in 2100-but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40-1·92) in 2050 and 1·62 (1·35-1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.

INTERPRETATION: Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world.

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.

METHODS: Oxy-PICU was a pragmatic, multicentre, open-label, randomised controlled trial in 15 UK paediatric intensive care units (PICUs). Children admitted as an emergency, who were older than 38 weeks corrected gestational age and younger than 16 years receiving invasive ventilation and supplemental oxygen were randomly allocated in a 1:1 ratio via a concealed, central, web-based randomisation system to conservative peripheral oxygen saturations ([SpO2] 88-92%) or liberal (SpO2 >94%) targets. The primary outcome was the duration of organ support at 30 days following random allocation, a rank-based endpoint with death either on or before day 30 as the worst outcome (a score equating to 31 days of organ support), with survivors assigned a score between 1 and 30 depending on the number of calendar days of organ support received. The primary effect estimate was the probabilistic index, a value greater than 0·5 indicating more than 50% probability that conservative oxygenation is superior to liberal oxygenation for a randomly selected patient. All participants in whom consent was available were included in the intention-to-treat analysis. The completed study was registered with the ISRCTN registry (ISRCTN92103439).

FINDINGS: Between Sept 1, 2020, and May 15, 2022, 2040 children were randomly allocated to conservative or liberal oxygenation groups. Consent was available for 1872 (92%) of 2040 children. The conservative oxygenation group comprised 939 children (528 [57%] of 927 were female and 399 [43%] of 927 were male) and the liberal oxygenation group included 933 children (511 [56%] of 920 were female and 409 [45%] of 920 were male). Duration of organ support or death in the first 30 days was significantly lower in the conservative oxygenation group (probabilistic index 0·53, 95% CI 0·50-0·55; p=0·04 Wilcoxon rank-sum test, adjusted odds ratio 0·84 [95% CI 0·72-0·99]). Prespecified adverse events were reported in 24 (3%) of 939 patients in the conservative oxygenation group and 36 (4%) of 933 patients in the liberal oxygenation group.

INTERPRETATION: Among invasively ventilated children who were admitted as an emergency to a PICU receiving supplemental oxygen, a conservative oxygenation target resulted in a small, but significant, greater probability of a better outcome in terms of duration of organ support at 30 days or death when compared with a liberal oxygenation target. Widespread adoption of a conservative oxygenation saturation target (SpO2 88-92%) could help improve outcomes and reduce costs for the sickest children admitted to PICUs.

METHODS: In the global, open-label, phase 3 IMbrave050 study, adult patients with high-risk surgically resected or ablated hepatocellular carcinoma were recruited from 134 hospitals and medical centres in 26 countries in four WHO regions (European region, region of the Americas, South-East Asia region, and Western Pacific region). Patients were randomly assigned in a 1:1 ratio via an interactive voice-web response system using permuted blocks, using a block size of 4, to receive intravenous 1200 mg atezolizumab plus 15 mg/kg bevacizumab every 3 weeks for 17 cycles (12 months) or to active surveillance. The primary endpoint was recurrence-free survival by independent review facility assessment in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT04102098.

FINDINGS: The intention-to-treat population included 668 patients randomly assigned between Dec 31, 2019, and Nov 25, 2021, to either atezolizumab plus bevacizumab (n=334) or to active surveillance (n=334). At the prespecified interim analysis (Oct 21, 2022), median duration of follow-up was 17·4 months (IQR 13·9-22·1). Adjuvant atezolizumab plus bevacizumab was associated with significantly improved recurrence-free survival (median, not evaluable [NE]; [95% CI 22·1-NE]) compared with active surveillance (median, NE [21·4-NE]; hazard ratio, 0·72 [adjusted 95% CI 0·53-0·98]; p=0·012). Grade 3 or 4 adverse events occurred in 136 (41%) of 332 patients who received atezolizumab plus bevacizumab and 44 (13%) of 330 patients in the active surveillance group. Grade 5 adverse events occurred in six patients (2%, two of which were treatment related) in the atezolizumab plus bevacizumab group, and one patient (<1%) in the active surveillance group. Both atezolizumab and bevacizumab were discontinued because of adverse events in 29 patients (9%) who received atezolizumab plus bevacizumab.

INTERPRETATION: Among patients at high risk of hepatocellular carcinoma recurrence following curative-intent resection or ablation, recurrence-free survival was improved in those who received atezolizumab plus bevacizumab versus active surveillance. To our knowledge, IMbrave050 is the first phase 3 study of adjuvant treatment for hepatocellular carcinoma to report positive results. However, longer follow-up for both recurrence-free and overall survival is needed to assess the benefit-risk profile more fully.

METHODS: This multicentre, randomised, placebo-controlled, phase 2b trial was done at 60 hospitals and clinics in 20 countries. Eligible study participants were aged between 12 and 75 years with a documented history of GPP as per the European Rare and Severe Psoriasis Expert Network criteria, with a history of at least two past GPP flares, and a GPP Physician Global Assessment (GPPGA) score of 0 or 1 at screening and random assignment. Patients were randomly assigned (1:1:1:1) to receive subcutaneous placebo, subcutaneous low-dose spesolimab (300 mg loading dose followed by 150 mg every 12 weeks), subcutaneous medium-dose spesolimab (600 mg loading dose followed by 300 mg every 12 weeks), or subcutaneous high-dose spesolimab (600 mg loading dose followed by 300 mg every 4 weeks) over 48 weeks. The primary objective was to demonstrate a non-flat dose-response curve on the primary endpoint, time to first GPP flare.

FINDINGS: From June 8, 2020, to Nov 23, 2022, 157 patients were screened, of whom 123 were randomly assigned. 92 were assigned to receive spesolimab (30 high dose, 31 medium dose, and 31 low dose) and 31 to placebo. All patients were either Asian (79 [64%] of 123) or White (44 [36%]). Patient groups were similar in sex distribution (76 [62%] female and 47 [38%] male), age (mean 40·4 years, SD 15·8), and GPP Physician Global Assessment score. A non-flat dose-response relationship was established on the primary endpoint. By week 48, 35 patients had GPP flares; seven (23%) of 31 patients in the low-dose spesolimab group, nine (29%) of 31 patients in the medium-dose spesolimab group, three (10%) of 30 patients in the high-dose spesolimab group, and 16 (52%) of 31 patients in the placebo group. High-dose spesolimab was significantly superior versus placebo on the primary outcome of time to GPP flare (hazard ratio [HR]=0·16, 95% CI 0·05-0·54; p=0·0005) endpoint. HRs were 0·35 (95% CI 0·14-0·86, nominal p=0·0057) in the low-dose spesolimab group and 0·47 (0·21-1·06, p=0·027) in the medium-dose spesolimab group. We established a non-flat dose-response relationship for spesolimab compared with placebo, with statistically significant p values for each predefined model (linear p=0·0022, emax1 p=0·0024, emax2 p=0·0023, and exponential p=0·0034). Infection rates were similar across treatment arms; there were no deaths and no hypersensitivity reactions leading to discontinuation.

INTERPRETATION: High-dose spesolimab was superior to placebo in GPP flare prevention, significantly reducing the risk of a GPP flare and flare occurrence over 48 weeks. Given the chronic nature of GPP, a treatment for flare prevention is a significant shift in the clinical approach, and could ultimately lead to improvements in patient morbidity and quality of life.