Background Understanding the temporal trend of the disease burden of stroke and its attributable risk factors in China, especially at provincial levels, is important for effective prevention strategies and improvement. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is to investigate the disease burden of stroke and its risk factors at national and provincial levels in China from 1990 to 2019. MethodsFollowing the methodology in the GBD 2019, the incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) of stroke cases in the Chinese population were estimated by sex, age, year, stroke subtypes (ischaemic stroke, intracerebral haemorrhage, and subarachnoid haemorrhage), and across 33 provincial administrative units in China from 1990 to 2019. Attributable mortality and DALYs of underlying risk factors were calculated by a comparative risk assessment. Findings In 2019, there were 3•94 million (95% uncertainty interval 3•43-4•58) new stroke cases in China. The incidence rate of stroke increased by 86•0% (73•2-99•0) from 1990, reaching 276•7 (241•3-322•0) per 100 000 population in 2019. The age-standardised incidence rate declined by 9•3% (3•3-15•5) from 1990 to 2019. Among 28•76 million (25•60-32•21) prevalent cases of stroke in 2019, 24•18 million (20•80-27•87) were ischaemic stroke, 4•36 million (3•69-5•05) were intracerebral haemorrhage, and 1•58 million (1•32-1•91) were subarachnoid haemorrhage. The prevalence rate increased by 106•0% (93•7-118•8) and age-standardised prevalence rate increased by 13•2% (7•7-19•1) from 1990 to 2019. In 2019, there were 2•19 million (1•89-2•51) deaths and 45•9 million (39•8-52•3) DALYs due to stroke. The mortality rate increased by 32•3% (8•6-59•0) from 1990 to 2019. Over the same period, the age-standardised mortality rate decreased by 39•8% (28•6-50•7) and the DALY rate decreased by 41•6% (30•7-50•9). High systolic blood pressure, ambient particulate matter pollution exposure, smoking, and diet high in sodium were four major risk factors for stroke burden in 2019. Moreover, we found marked differences of stroke burden and attributable risk factors across provinces in China from 1990 to 2019.Interpretation The disease burden of stroke is still severe in China, although the age-standardised incidence and mortality rates have decreased since 1990. The stroke burden in China might be reduced through blood pressure management, lifestyle interventions, and air pollution control. Moreover, because substantial heterogeneity of stroke burden existed in different provinces, improved health care is needed in provinces with heavy stroke burden.

Background: Multidelay arterial spin labeling (ASL) is a novel perfusion method of ASL, with arterial transit time (ATT) calculated by multiple postlabeling delays to correct cerebral blood flow (CBF). We verify the accuracy of multidelay ASL in evaluating the ischemic penumbra and perfusion levels in patients with acute ischemic stroke, compared with computed tomography perfusion (CTP). Methods: Patients with acute ischemic stroke with anterior circulation large vessel occlusion received baseline CTP, multidelay ASL, and diffusion-weighted imaging (DWI) in succession. Multidelay ASL image was processed to reconstruct ATT, CBF without ATT correction, and CBF corrected by ATT. The consistency of hypoperfusion and ischemic penumbra volume calculated by CTP and multidelay ASL were quantified by intraclass correlation coefficient (ICC) in 2-way mixed effects, absolute agreement, and single measure. Wilcoxon signed-rank test was used to compare the difference in penumbra volume between CTP, corrected ASL, and uncorrected ASL. Results: Thirty patients were included. Hypoperfusion volume based on multidelay ASL with different thresholds were 117.95 (87.77–151.49) mL for corrected relative CBF<40%, 130.29 (85.99–249.37) mL for CBF corrected by ATT<20 mL·100g -1 ·min -1 , no statistical difference ( P >0.05) compared with the volume of CTP, and consistency was almost excellent (ICC, 0.91) and substantial consistent (ICC, 0.727). The volumes of ischemic penumbra were 91.00 (42.68–125.27) mL for corrected relative CBF<40%-DWI, 108.94 (62.03–150.86) mL for CBF corrected by ATT<20 mL·100 g -1 ·min -1 -DWI, which showed no statistical difference compared with the penumbra volume of CTP ( P >0.05). The consistency was excellent (ICC, 0.822) and moderate (ICC, 0.501), respectively. The volume of uncorrected relative CBF <40%-DWI was 209.57 (123.21–292.45) mL, statistically larger than corrected relative CBF <40%-DWI ( P <0.001) and CTP ( P <0.001). The volume of uncorrected CBF<20 mL·100g -1 ·min -1 -DWI was 186.23 (86.56–298.22) mL, statistically larger than CBF corrected by ATT<20 mL·100g -1 ·min -1 -DWI ( P <0.001) and CTP( P <0.001). Conclusions: The volume of ischemic penumbra determined by CBF/DWI mismatch based on multidelay ASL is consistent with CTP. The penumbra volume calculated by CBF adjusted by ATT is more accurate.

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Background Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. However, the underlying mechanisms of PSD remain ambiguous, and no objective diagnosis tool is available to diagnose PSD. Previous metabolomic studies on PSD included patients with ischemic and hemorrhagic stroke indiscriminately, which is not conducive to elucidating and predicting the occurrence of PSD. The aim of this study is to elucidate the pathogenesis of PSD and provide potential diagnostic markers for PSD in ischemic stroke patients. Methods In total, 51 ischemic stroke patients at 2 weeks were included in this study. Those with depressive symptoms were assigned to the PSD group, while the others were assigned to the non-PSD group. Plasma metabolomics based on liquid chromatography–mass spectrometry (LC-MS) was performed to explore the differential plasma metabolites between the PSD and non-PSD groups. Results Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) showed significant metabolic alterations between PSD patients and non-PSD patients. In total, 41 differential metabolites were screened out, mainly including phosphatidylcholines (PCs), L-carnitine and acyl carnitines, succinic acid, pyruvic acid and L-lactic acid. Metabolite-related pathway analysis revealed that alanine, aspartate and glutamate metabolism, glycerophospholipid metabolism and the citrate cycle (TCA cycle) may contribute to the pathogenesis of PSD. A panel of three signature metabolites [PC(22:5(7Z,10Z,13Z,16Z,19Z)/15:0), LysoPA(18:1(9Z)/0:0) and 1,5-anhydrosorbitol] was determined as potential biomarkers for PSD in ischemic stroke patients. Conclusion These findings are conducive to providing new insights into the pathogenesis of PSD and developing objective diagnostic tools for PSD in ischemic stroke patients.