Displaying publications 21 - 39 of 39 in total

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  1. Adam A, Ibrahim Z, Mokhtar N, Shapiai MI, Mubin M, Saad I
    Springerplus, 2016;5(1):1580.
    PMID: 27652153 DOI: 10.1186/s40064-016-3277-z
    In the existing electroencephalogram (EEG) signals peak classification research, the existing models, such as Dumpala, Acir, Liu, and Dingle peak models, employ different set of features. However, all these models may not be able to offer good performance for various applications and it is found to be problem dependent. Therefore, the objective of this study is to combine all the associated features from the existing models before selecting the best combination of features. A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. Also, the neural network random weight method is utilized in the proposed AMSKF technique as a classifier. In the conducted experiment, 11,781 samples of peak candidate are employed in this study for the validation purpose. The samples are collected from three different peak event-related EEG signals of 30 healthy subjects; (1) single eye blink, (2) double eye blink, and (3) eye movement signals. The experimental results have shown that the proposed AMSKF feature selector is able to find the best combination of features and performs at par with the existing related studies of epileptic EEG events classification.
  2. Adam A, Ibrahim Z, Mokhtar N, Shapiai MI, Cumming P, Mubin M
    Springerplus, 2016;5(1):1036.
    PMID: 27462484 DOI: 10.1186/s40064-016-2697-0
    Various peak models have been introduced to detect and analyze peaks in the time domain analysis of electroencephalogram (EEG) signals. In general, peak model in the time domain analysis consists of a set of signal parameters, such as amplitude, width, and slope. Models including those proposed by Dumpala, Acir, Liu, and Dingle are routinely used to detect peaks in EEG signals acquired in clinical studies of epilepsy or eye blink. The optimal peak model is the most reliable peak detection performance in a particular application. A fair measure of performance of different models requires a common and unbiased platform. In this study, we evaluate the performance of the four different peak models using the extreme learning machine (ELM)-based peak detection algorithm. We found that the Dingle model gave the best performance, with 72 % accuracy in the analysis of real EEG data. Statistical analysis conferred that the Dingle model afforded significantly better mean testing accuracy than did the Acir and Liu models, which were in the range 37-52 %. Meanwhile, the Dingle model has no significant difference compared to Dumpala model.
  3. Elgadir MA, Uddin MS, Ferdosh S, Adam A, Chowdhury AJK, Sarker MZI
    J Food Drug Anal, 2015 Dec;23(4):619-629.
    PMID: 28911477 DOI: 10.1016/j.jfda.2014.10.008
    Chitosan is a promising biopolymer for drug delivery systems. Because of its beneficial properties, chitosan is widely used in biomedical and pharmaceutical fields. In this review, we summarize the physicochemical and drug delivery properties of chitosan, selected studies on utilization of chitosan and chitosan-based nanoparticle composites in various drug delivery systems, and selected studies on the application of chitosan films in both drug delivery and wound healing. Chitosan is considered the most important polysaccharide for various drug delivery purposes because of its cationic character and primary amino groups, which are responsible for its many properties such as mucoadhesion, controlled drug release, transfection, in situ gelation, and efflux pump inhibitory properties and permeation enhancement. This review can enhance our understanding of drug delivery systems particularly in cases where chitosan drug-loaded nanoparticles are applied.
  4. Adam A, Ibrahim NA, Tah PC, Liu XY, Dainelli L, Foo CY
    JPEN J Parenter Enteral Nutr, 2023 Nov;47(8):1003-1010.
    PMID: 37497593 DOI: 10.1002/jpen.2554
    BACKGROUND: Prevention of enteral feeding interruption (EFI) improves clinical outcomes of critically ill intensive care unit (ICU) patients. This leads to shorter ICU stays and thereby lowers healthcare costs. This study compared the cost of early use of semi-elemental formula (SEF) in ICU vs standard polymeric formula (SPF) under the Ministry of Health (MOH) system in Malaysia.

    METHODS: A decision tree model was developed based on literature and expert inputs. An epidemiological projection model was then added to the decision tree to calculate the target population size. The budget impact of adapting the different enteral nutrition (EN) formulas was calculated by multiplying the population size with the costs of the formula and ICU length of stay (LOS). A one-way sensitivity analysis (OWSA) was conducted to examine the effect each input parameter has on the calculated output.

    RESULTS: Replacing SPF with SEF would lower ICU cost by MYR 1059 (USD 216) per patient. The additional cost of increased LOS due to EFI was MYR 5460 (USD 1114) per patient. If the MOH replaces SPF with SEF for ICU patients with high EFI risk (estimated 7981 patients in 2022), an annual net cost reduction of MYR 8.4 million (USD 1.7 million) could potentially be realized in the MOH system. The cost-reduction finding of replacing SPF with SEF remained unchanged despite the input uncertainties assessed via OWSA.

    CONCLUSION: Early use of SEF in ICU patients with high EFI risk could potentially lower the cost of ICU care for the MOH system in Malaysia.

  5. John CM, Ramasamy R, Al Naqeeb G, Dhiab Al-Nuaimi AH, Adam A
    Curr Med Chem, 2012 Aug 16.
    PMID: 22934758
    Gestational diabetes mellitus (GDM) is a common complication during pregnancy. Metabolic changes in GDM affect fetal development and fetal glucose homeostasis. Several complications of diabetes are related to increased intracellular oxidative stress where prooxidants exceed antioxidant capacity. The present study was initiated to evaluate the effects of nicotinamide on CD4+CD25+ regulatory T cells (Tregs), proliferation of splenocytes, production of reactive oxygen species (ROS) by neutrophils and serum glucose levels. Changes in mRNA levels of two antioxidant genes in liver, viz, superoxide dismutase (SOD1) and catalase (CAT) were quantified with real-time PCR (QRT-PCR). Nicotinamide (50, 100 and 200 mg/kg) was supplemented p.o. to pregnant diabetic rats from days 6 through 20 of gestation. The highest dose enhanced expression of Tregs and increased splenocytes proliferation in both resting and lipopolysaccharide (LPS)-stimulated cells. Oxidative burst activity of neutrophils in response to phorbol myristate acetate (PMA), N-formyl-methionyl-leucyl-phenylalanine (FMLP) or E. coli activation was reduced. mRNA expressions of superoxide dismutase (SOD) and catalase (CAT) genes were upregulated by nicotinamide. In summary, nicotinamide boosted the immune system through stimulation of adaptive immune cells with enhancement of antioxidant defences and reduced production of ROS. Serum glucose level was normalised by nicotinamide (200 mg/kg). These findings provide evidence for usage of nicotinamide as a supplement or as adjunct to therapeutic agents in gestational diabetes and in pregnant individuals with weakened immune systems.
  6. Mohd-Radzman NH, Wan Ismail WI, Jaapar SS, Adam Z, Adam A
    PMID: 27594889 DOI: 10.1155/2016/2467420
    [This corrects the article DOI: 10.1155/2013/938081.].
  7. Mohd-Radzman NH, Ismail WI, Jaapar SS, Adam Z, Adam A
    PMID: 24391675 DOI: 10.1155/2013/938081
    Stevioside from Stevia rebaudiana has been reported to exert antihyperglycemic effects in both rat and human subjects. There have been few studies on these effects in vitro. In this paper, radioactive glucose uptake assay was implemented in order to assess improvements in insulin sensitivity in 3T3-L1 cells by elevation of glucose uptake following treatment with stevioside. Oil Red-O staining and MTT assay were utilized to confirm adipocyte differentiation and cell viability, respectively. Findings from this research showed a significant increase in absorbance values in mature adipocytes following Oil Red-O staining, confirming the differentiation process. Stevioside was noncytotoxic to 3T3-L1 cells as cell viability was reduced by a maximum of 17%, making it impossible to determine its IC50. Stevioside increased glucose uptake activities by 2.1 times (p < 0.001) in normal conditions and up to 4.4 times (p < 0.001) in insulin-resistant states. At times, this increase was higher than that seen in positive control group treated with rosiglitazone maleate, an antidiabetic agent. Expressions of pY20 and p-IRS1 which were measured via Western blot were improved by stevioside treatment. In conclusion, stevioside has direct effects on 3T3-L1 insulin sensitivity via increase in glucose uptake and enhanced expression of proteins involved in insulin-signalling pathway.
  8. Mohd-Radzman NH, Ismail WI, Adam Z, Jaapar SS, Adam A
    PMID: 24324517 DOI: 10.1155/2013/718049
    Insulin resistance is a key factor in metabolic disorders like hyperglycemia and hyperinsulinemia, which are promoted by obesity and may later lead to Type II diabetes mellitus. In recent years, researchers have identified links between insulin resistance and many noncommunicable illnesses other than diabetes. Hence, studying insulin resistance is of particular importance in unravelling the pathways employed by such diseases. In this review, mechanisms involving free fatty acids, adipocytokines such as TNF α and PPAR γ and serine kinases like JNK and IKK β , asserted to be responsible in the development of insulin resistance, will be discussed. Suggested mechanisms for actions in normal and disrupted states were also visualised in several manually constructed diagrams to capture an overall view of the insulin-signalling pathway and its related components. The underlying constituents of medicinal significance found in the Stevia rebaudiana Bertoni plant (among other plants that potentiate antihyperglycemic activities) were explored in further depth. Understanding these factors and their mechanisms may be essential for comprehending the progression of insulin resistance towards the development of diabetes mellitus.
  9. Abai M, Atkins MP, Hassan A, Holbrey JD, Kuah Y, Nockemann P, et al.
    Dalton Trans, 2015 May 14;44(18):8617-24.
    PMID: 25722100 DOI: 10.1039/c4dt03273j
    Efficient scrubbing of mercury vapour from natural gas streams has been demonstrated both in the laboratory and on an industrial scale, using chlorocuprate(II) ionic liquids impregnated on high surface area porous solid supports, resulting in the effective removal of mercury vapour from natural gas streams. This material has been commercialised for use within the petroleum gas production industry, and has currently been running continuously for three years on a natural gas plant in Malaysia. Here we report on the chemistry underlying this process, and demonstrate the transfer of this technology from gram to ton scale.
  10. Alkadi KAA, Ashraf K, Adam A, Shah SAA, Taha M, Hasan MH, et al.
    J Pharm Bioallied Sci, 2020 12 21;13(1):116-122.
    PMID: 34084057 DOI: 10.4103/jpbs.JPBS_279_19
    Objectives: The aim of the present study was to isolate and evaluate cytotoxicity and anti-inflammatory activities of new novel compounds isolated from Prismatomeris glabra.

    Materials and Methods: Dried root of P. glabra was extracted under reflux with methyl alcohol, fractionated through the vacuum liquid chromatography technique, and evaporated and then purified the compounds using column chromatography and preparative thin-layer chromatography. THP-1 cells were treated with amentoflavone, 5,7,4'-hydroxyflavonoid, and stigmasterol with various concentrations (0-30 µg/mL) and then incubated with MTS reagent for 2h. Treatment was done for 24, 48, and 72h. Then, effects of these compounds were also tested on PGE2, TNF-α, and IL-6 expression in human THP-1-derived macrophage cells for 24h.

    Results: Three new compounds such as amentoflavone, 5,7,4'-hydroxyflavonoid, and stigmasterol were isolated. After 24h of incubation, a significant decrease in cell viability was reported with IC50 values of amentoflavone, 5,7,4'- hydroxyflavonoid, and stigmasterol (21 µg/mL ≡ 38 M), (18 µg/mL ≡ 66 M) and (20 µg/mL ≡ 48.5 M), respectively. Whereas for 48 and 72h treatment showed a less decreased cell viability compared with 24h treatment. These compounds also showed a significant reduction in the production of TNF-α, IL-6, and PGE2 in a dose-dependent manner.

    Conclusions: The isolated new compounds showed significant cytotoxicity and anti-inflammatory effects.

  11. Abdul Aziz SH, John CM, Mohamed Yusof NI, Nordin M, Ramasamy R, Adam A, et al.
    Biomed Res Int, 2016;2016:9704607.
    PMID: 27379252 DOI: 10.1155/2016/9704607
    This study attempts to develop an experimental gestational diabetes mellitus (GDM) animal model in female Sprague-Dawley rats. Rats were fed with high fat sucrose diet, impregnated, and induced with Streptozotocin and Nicotinamide on gestational day 0 (D0). Sleeping patterns of the rats were also manipulated to induce stress, a lifestyle factor that contributes to GDM. Rats were tested for glycemic parameters (glucose, C-peptide, and insulin), lipid profiles (total cholesterol, triglycerides, HDL, and LDL), genes affecting insulin signaling (IRS-2, AKT-1, and PCK-1), glucose transporters (GLUT-2 and GLUT-4), proinflammatory cytokines (IL-6, TNF-α), and antioxidants (SOD, CAT, and GPX) on D6 and D21. GDM rats showed possible insulin resistance as evidenced by high expression of proinflammatory cytokines, PCK-1 and CRP. Furthermore, low levels of IRS-2 and AKT-1 genes and downregulation of GLUT-4 from the initial to final phases indicate possible defect of insulin signaling. GDM rats also showed an impairment of antioxidant status and a hyperlipidemic state. Additionally, GDM rats exhibited significantly higher body weight and blood glucose and lower plasma insulin level and C-peptide than control. Based on the findings outlined, the current GDM animal model closely replicates the disease state in human and can serve as a reference for future investigations.
  12. Mansor NI, Ntimi CM, Abdul-Aziz NM, Ling KH, Adam A, Rosli R, et al.
    Bosn J Basic Med Sci, 2021 Feb 01;21(1):98-110.
    PMID: 32156249 DOI: 10.17305/bjbms.2020.4639
    One of the strategies in the establishment of in vitro oxidative stress models for neurodegenerative diseases, such as Alzheimer's disease (AD), is to induce neurotoxicity by amyloid beta (Aβ) peptides in suitable neural cells. Presently, data on the neurotoxicity of Aβ in neural cells differentiated from stem cells are limited. In this study, we attempted to induce oxidative stress in transgenic 46C mouse embryonic stem cell-derived neurons via treatment with Aβ peptides (Aβ1-42 and Aβ25-35). 46C neural cells were generated by promoting the formation of multicellular aggregates, embryoid bodies in the absence of leukemia inhibitory factor, followed by the addition of all-trans retinoic acid as the neural inducer. Mature neuronal cells were exposed to different concentrations of Aβ1-42 and Aβ25-35 for 24 h. Morphological changes, cell viability, and intracellular reactive oxygen species (ROS) production were assessed. We found that 100 µM Aβ1-42 and 50 µM Aβ25-35 only promoted 40% and 10%, respectively, of cell injury and death in the 46C-derived neuronal cells. Interestingly, treatment with each of the Aβ peptides resulted in a significant increase of intracellular ROS activity, as compared to untreated neurons. These findings indicate the potential of using neurons derived from stem cells and Aβ peptides in generating oxidative stress for the establishment of an in vitro AD model that could be useful for drug screening and natural product studies.
  13. Anouar el H, Raweh S, Bayach I, Taha M, Baharudin MS, Di Meo F, et al.
    J Comput Aided Mol Des, 2013 Nov;27(11):951-64.
    PMID: 24243063 DOI: 10.1007/s10822-013-9692-0
    Phenolic Schiff bases are known for their diverse biological activities and ability to scavenge free radicals. To elucidate (1) the structure-antioxidant activity relationship of a series of thirty synthetic derivatives of 2-methoxybezohydrazide phenolic Schiff bases and (2) to determine the major mechanism involved in free radical scavenging, we used density functional theory calculations (B3P86/6-31+(d,p)) within polarizable continuum model. The results showed the importance of the bond dissociation enthalpies (BDEs) related to the first and second (BDEd) hydrogen atom transfer (intrinsic parameters) for rationalizing the antioxidant activity. In addition to the number of OH groups, the presence of a bromine substituent plays an interesting role in modulating the antioxidant activity. Theoretical thermodynamic and kinetic studies demonstrated that the free radical scavenging by these Schiff bases mainly proceeds through proton-coupled electron transfer rather than sequential proton loss electron transfer, the latter mechanism being only feasible at relatively high pH.
  14. Jagaba AH, Kutty SRM, Lawal IM, Abubakar S, Hassan I, Zubairu I, et al.
    J Environ Manage, 2021 Mar 15;282:111946.
    PMID: 33486234 DOI: 10.1016/j.jenvman.2021.111946
    Landfill has become an underlying source of surface and groundwater pollution if not efficiently managed, due to the risk of leachate infiltration into to land and aquifers. The generated leachate is considered a serious environmental threat for the public health, because of the toxic and recalcitrant nature of its constituents. Thus, it must be collected and appropriately treated before being discharged into the environment. At present, there is no single unit process available for proper leachate treatment as conventional wastewater treatment processes cannot achieve a satisfactory level for degrading toxic substances present. Therefore, there is a growing interest in examination of different leachate treatment processes for maximum operational flexibility. Based on leachate characteristics, discharge requirements, technical possibilities, regulatory requirements and financial considerations, several techniques have been applied for its degradation, presenting varying degrees of efficiency. Therefore, this article presents a comprehensive review of existing research articles on the pros and cons of various leachate degradation methods. In line with environmental sustainability, the article stressed on the application and efficiency of sequencing batch reactor (SBR) system treating landfill leachate due to its operational flexibility, resistance to shock loads and high biomass retention. Contributions of integrated leachate treatment technologies with SBR were also discussed. The article further analyzed the effect of different adopted materials, processes, strategies and configurations on leachate treatment. Environmental and operational parameters that affect SBR system were critically discussed. It is believed that information contained in this review will increase readers fundamental knowledge, guide future researchers and be incorporated into future works on experimentally-based SBR studies for leachate treatment.
  15. Alyasseri ZAA, Al-Betar MA, Doush IA, Awadallah MA, Abasi AK, Makhadmeh SN, et al.
    Expert Syst, 2021 Jul 28.
    PMID: 34511689 DOI: 10.1111/exsy.12759
    COVID-19 is the disease evoked by a new breed of coronavirus called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recently, COVID-19 has become a pandemic by infecting more than 152 million people in over 216 countries and territories. The exponential increase in the number of infections has rendered traditional diagnosis techniques inefficient. Therefore, many researchers have developed several intelligent techniques, such as deep learning (DL) and machine learning (ML), which can assist the healthcare sector in providing quick and precise COVID-19 diagnosis. Therefore, this paper provides a comprehensive review of the most recent DL and ML techniques for COVID-19 diagnosis. The studies are published from December 2019 until April 2021. In general, this paper includes more than 200 studies that have been carefully selected from several publishers, such as IEEE, Springer and Elsevier. We classify the research tracks into two categories: DL and ML and present COVID-19 public datasets established and extracted from different countries. The measures used to evaluate diagnosis methods are comparatively analysed and proper discussion is provided. In conclusion, for COVID-19 diagnosing and outbreak prediction, SVM is the most widely used machine learning mechanism, and CNN is the most widely used deep learning mechanism. Accuracy, sensitivity, and specificity are the most widely used measurements in previous studies. Finally, this review paper will guide the research community on the upcoming development of machine learning for COVID-19 and inspire their works for future development. This review paper will guide the research community on the upcoming development of ML and DL for COVID-19 and inspire their works for future development.
  16. Siaw Paw JK, Kiong TS, Kamarulzaman MK, Adam A, Hisham S, Kadirgama K, et al.
    Heliyon, 2023 Nov;9(11):e22238.
    PMID: 38058613 DOI: 10.1016/j.heliyon.2023.e22238
    In the realm of internal combustion engines, there is a growing utilization of alternative renewable fuels as substitutes for traditional diesel and gasoline. This surge in demand is driven by the imperative to diminish fuel consumption and adhere to stringent regulations concerning engine emissions. Sole reliance on experimental analysis is inadequate to effectively address combustion, performance, and emission issues in engines. Consequently, the integration of engine modelling, grounded in machine learning methodologies and statistical data through the response surface method (RSM), has become increasingly significant for enhanced analytical outcomes. This study aims to explore the contemporary applications of RSM in assessing the feasibility of a wide range of renewable alternative fuels for internal combustion engines. Initially, the study outlines the fundamental principles and procedural steps of RSM, offering readers an introduction to this multifaceted statistical technique. Subsequently, the study delves into a comprehensive examination of the recent applications of alternative renewable fuels, focusing on their impact on combustion, performance, and emissions in the domain of internal combustion engines. Furthermore, the study sheds light on the advantages and limitations of employing RSM, and discusses the potential of combining RSM with other modelling techniques to optimise results. The overarching objective is to provide a thorough insight into the role and efficacy of RSM in the evaluation of renewable alternative fuels, thereby contributing to the ongoing discourse in the field of internal combustion engines.
  17. Salleh MZ, Teh LK, Lee LS, Ismet RI, Patowary A, Joshi K, et al.
    PLoS One, 2013;8(8):e71554.
    PMID: 24009664 DOI: 10.1371/journal.pone.0071554
    BACKGROUND: With a higher throughput and lower cost in sequencing, second generation sequencing technology has immense potential for translation into clinical practice and in the realization of pharmacogenomics based patient care. The systematic analysis of whole genome sequences to assess patient to patient variability in pharmacokinetics and pharmacodynamics responses towards drugs would be the next step in future medicine in line with the vision of personalizing medicine.

    METHODS: Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences.

    PRINCIPAL FINDINGS: Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings.

    CONCLUSIONS: The current study successfully unravels the potential of personal genome sequencing in understanding the functionally relevant variations with potential influence on drug transport, metabolism and differential therapeutic outcomes. These will be essential for realizing personalized medicine through the use of comprehensive computational pipeline for systematic data mining and analysis.

  18. Al-Alimi S, Yusuf NK, Ghaleb AM, Adam A, Lajis MA, Shamsudin S, et al.
    Heliyon, 2024 Jun 30;10(12):e33138.
    PMID: 38984305 DOI: 10.1016/j.heliyon.2024.e33138
    The optimal conditions of applied factors to reuse Aluminium AA6061 scraps are (450, 500, and 550) ⁰C preheating temperature, (1-15) % Boron Carbide (B4C), and Zirconium (ZrO2) hybrid reinforced particles at 120 min forging time via Hot Forging (HF) process. The response surface methodology (RSM) and machine learning (ML) were established for the optimisations and comparisons towards materials strength structure. The Ultimate Tensile Strength (UTS) strength and Microhardness (MH) were significantly increased by increasing the processed temperature and reinforced particles because of the material dispersion strengthening. The high melting point of particles caused impedance movements of aluminium ceramics dislocations which need higher plastic deformation force and hence increased the material's mechanical and physical properties. But, beyond Al/10 % B4C + 10 % ZrO2 the strength and hardness were decreased due to more particle agglomeration distribution. The optimisation tools of both RSM and ML show high agreement between the reported results of applied parameters towards the materials' strength characterisation. The microstructure analysis of Field Emission Scanning Electron Microscopy (FE-SEM) and Atomic Force Microscope (AFM) provides insights mapping behavioural characterisation supports related to strength and hardness properties. The distribution of different volumes of ceramic particle proportion was highlighted. The environmental impacts were also analysed by employing a life cycle assessment (LCA) to identify energy savings because of its fewer processing steps and produce excellent hybrid materials properties.
  19. Nguyen TN, Qureshi MM, Klein P, Yamagami H, Mikulik R, Czlonkowska A, et al.
    Neurology, 2023 Jan 24;100(4):e408-e421.
    PMID: 36257718 DOI: 10.1212/WNL.0000000000201426
    BACKGROUND AND OBJECTIVES: Declines in stroke admission, IV thrombolysis (IVT), and mechanical thrombectomy volumes were reported during the first wave of the COVID-19 pandemic. There is a paucity of data on the longer-term effect of the pandemic on stroke volumes over the course of a year and through the second wave of the pandemic. We sought to measure the effect of the COVID-19 pandemic on the volumes of stroke admissions, intracranial hemorrhage (ICH), IVT, and mechanical thrombectomy over a 1-year period at the onset of the pandemic (March 1, 2020, to February 28, 2021) compared with the immediately preceding year (March 1, 2019, to February 29, 2020).

    METHODS: We conducted a longitudinal retrospective study across 6 continents, 56 countries, and 275 stroke centers. We collected volume data for COVID-19 admissions and 4 stroke metrics: ischemic stroke admissions, ICH admissions, IVT treatments, and mechanical thrombectomy procedures. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases.

    RESULTS: There were 148,895 stroke admissions in the 1 year immediately before compared with 138,453 admissions during the 1-year pandemic, representing a 7% decline (95% CI [95% CI 7.1-6.9]; p < 0.0001). ICH volumes declined from 29,585 to 28,156 (4.8% [5.1-4.6]; p < 0.0001) and IVT volume from 24,584 to 23,077 (6.1% [6.4-5.8]; p < 0.0001). Larger declines were observed at high-volume compared with low-volume centers (all p < 0.0001). There was no significant change in mechanical thrombectomy volumes (0.7% [0.6-0.9]; p = 0.49). Stroke was diagnosed in 1.3% [1.31-1.38] of 406,792 COVID-19 hospitalizations. SARS-CoV-2 infection was present in 2.9% ([2.82-2.97], 5,656/195,539) of all stroke hospitalizations.

    DISCUSSION: There was a global decline and shift to lower-volume centers of stroke admission volumes, ICH volumes, and IVT volumes during the 1st year of the COVID-19 pandemic compared with the prior year. Mechanical thrombectomy volumes were preserved. These results suggest preservation in the stroke care of higher severity of disease through the first pandemic year.

    TRIAL REGISTRATION INFORMATION: This study is registered under NCT04934020.

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