title stringlengths 1 1.19k | keywords stringlengths 0 668 | concept stringlengths 0 909 | paragraph stringlengths 0 61.8k | PMID stringlengths 10 11 |
|---|---|---|---|---|
Conclusion | opioid use disorder | In this study, zinc supplementation in patients with opioid use disorder subjected to MMT was investigated. Although the study results showed that zinc intake had the capability to positively influence relapse reduction and mental health in such people, more studies are needed before including this supplement in the treatment plans for this group. | PMC9817328 | |
Acknowledgements | The authors hereby would like to extend their gratitude to all the participants and the staff of the addiction treatment clinic concerned, who cooperated to fulfill this study. They also appreciate the Vice-Chancellor’s Office for Research, affiliated with Isfahan University of Medical Sciences, Isfahan, Iran, for the financial support of this research. | PMC9817328 | ||
Authors’ contributions | Both authors contributed to the study procedures, data collection, and analysis. The authors prepared the first draft and read and approved the final version. | PMC9817328 | ||
Funding | Not applicable. | PMC9817328 | ||
Availability of data and materials | The data used in this study will be made available from the corresponding author upon reasonable request. | PMC9817328 | ||
Declarations | PMC9817328 | |||
Ethics approval and consent to participate | A written informed consent form was obtained from all the participants once the research objectives and methodology were explained. The Ethics Committee of Isfahan University of Medical Sciences, Isfahan, Iran, approved this study with the ethics code no. (IR.MUI.MED.REC. 1399.385). Moreover, the principles of the Declaration of Helsinki were met. | PMC9817328 | ||
Consent for publication | Not applicable. | PMC9817328 | ||
Competing interests | The authors did not declare any conflict of interest. | PMC9817328 | ||
References | PMC9817328 | |||
Background | memory complaints | DV and AS contributed equally to this work.There is evidence that both omega-3 long-chain polyunsaturated fatty acids (PUFAs) (eicosapentaenoic acid [EPA] and docosahexaenoic acid [DHA]) and cocoa flavanols can improve cognitive performance in both healthy individuals and in those with memory complaints. However, their combined effect is unknown. | PMC10447509 | |
Objectives | memory complaints | To investigate the combined effect of EPA/DHA and cocoa flavanols (OM3FLAV) on cognitive performance and brain structures in older adults with memory complaints. | PMC10447509 | |
Methods | cognitive impairment | A randomized placebo-controlled trial of DHA-rich fish oil (providing 1.1 g/d DHA and 0.4 g/d EPA) and a flavanol-rich dark chocolate (providing 500 mg/d flavan-3-ols) was conducted in 259 older adults with either subjective cognitive impairment or mild cognitive impairment. Participants underwent assessment at baseline, 3 mo, and 12 mo. The primary outcome was the number of false-positives on a picture recognition task from the Cognitive Drug Research computerized assessment battery. Secondary outcomes included other cognition and mood outcomes, plasma lipids, brain-derived neurotrophic factor (BDNF), and glucose levels. A subset of 110 participants underwent structural neuroimaging at baseline and at 12 mo. | PMC10447509 | |
Results | TG, alertness | 197 participants completed the study. The combined intervention had no significant effect on any cognitive outcomes, with the exception of reaction time variability (P = 0.007), alertness (P < 0.001), and executive function (P < 0.001), with a decline in function observed in the OM3FLAV group (118.6 [SD 25.3] at baseline versus 113.3 [SD 25.4] at 12 mo for executive function) relative to the control, and an associated decrease in cortical volume (P = 0.039). Compared with the control group, OM3FLAV increased plasma HDL, total cholesterol ratio (P < 0.001), and glucose (P = 0.008) and reduced TG concentrations (P < 0.001) by 3 mo, which were sustained to 12 mo, with no effect on BDNF. Changes in plasma EPA and DHA and urinary flavonoid metabolite concentrations confirmed compliance to the intervention. | PMC10447509 | |
Conclusions | cognitive impairment | These results suggest that cosupplementation with ω-3 PUFAs and cocoa flavanols for 12 mo does not improve cognitive outcomes in those with cognitive impairment.This trial was registered at | PMC10447509 | |
Keywords | PMC10447509 | |||
Abbreviations | Alzheimer’s diseaseblueberry powderbrain-derived neurotrophic factorbasal metabolic rateCognitive AgeingCDREFFLAVFOLPCMCIMoCAPCPPSCISwinburne University of TechnologyUniversity of East Anglia | PMC10447509 | ||
Introduction | dementia | SEPARATION | At a population level, interventions that delay the onset of dementia by 2 y are predicted to reduce the number of dementia patients by 20% [Investigations in model systems add validity to the prospective cohort evidence. Furthermore, they provide insights into the molecular and physiological mechanisms underlying long-chain ω-3 PUFAs and FLAVs which suggest that they could confer additive and potentially synergistic effects. Indeed, DHA supplementation increases its availability for neuronal membrane synthesis, neurite outgrowth, and neurogenesis and promotes synaptic plasticity [However, randomized controlled trials that have intervened with either EPA/DHA or flavonoids are conflicting, with many showing marginal or no meaningful cognitive benefits [The primary efficacy endpoint was hippocampal dentate gyrus-sensitive cognitive function, assessed by the number of false-positives on the Picture Recognition Task of the Cognitive Drug Research (CDR) computerized assessment system. The latter is analogous to the classic pattern separation paradigm, which is highly dependent on hippocampal function [ | PMC10447509 |
Subjects and Methods | The study protocol and methods have been described in detail elsewhere [ | PMC10447509 | ||
Ethics | The conduct, evaluation, and documentation of this study abide by Good Clinical Practice guidelines and the guiding principles of the Declaration of Helsinki. The study was approved by the Bellberry Human Research Ethics Committee (Study ID: 2015-03-227) and Swinburne University Human Research Ethics Committee (SHR Project 2015-208) for the Swinburne University of Technology (SUT) site and the National Research Ethics Service Committee (Study ID: 14/EE/0189) for the University of East Anglia (UEA) site. All participants provided informed signed consent prior to participating. The trial was registered at | PMC10447509 | ||
Study design and participants | MCI | RECRUITMENT | The CANN trial was a 12-mo randomized placebo-controlled parallel study with 2 intervention arms. There were 2 recruitment sites, the UEA (Norwich, UK) and SUT (Melbourne, Australia), with MRI analyzed centrally at the University of Illinois (Urbana Champaign, Urbana, IL, United States). Participants were asked to attend 3 clinical visits, at 0 mo (baseline), 3 mo, and 12 mo, to undergo cognitive assessment and provide clinical measures and biological samples. MRI assessment was conducted at baseline and 12 mo in a subset of Participants recruited were aged ≥55 y, with either SCI or MCI [ | PMC10447509 |
Intervention, assignment to group, and blinding | Participants were asked to consume 3 × 1 g oil capsules and 33 g of chocolate drops of either test or control products daily with the main meal of the day. The test capsules provided 1.1 g DHA and 0.4 g EPA per day in triglyceride form. The control capsules contained a blend of 80% palm oil and 20% corn oil to deliver a fatty acid composition typical of a UK or Australian diet. Both the test and control capsules contained 1% lemon oil, to maintain study blinding, and 1% mixed tocopherols for stability of the study oils. The test chocolate provided 508 mg of total flavan-3-ols ranging from monomers to decamers (ie, degrees of polymerization from 1 to 10) (Assignment to the test or control groups was conducted using a randomization algorithm (Covariate Adaptive Randomization software), with groups stratified for | PMC10447509 | ||
Cognitive outcomes | Bracket | As described previously, cognition was assessed at each clinical visit using the CDR computerized assessment system (Bracket Cognition), the MoCA, the Delis–Kaplan Executive Function System, the Verbal Fluency Test (0 and 12 mo only), and the iPosition task. Paper-and pencil Bond-Lader Visual Analogue Scale of Mood and Alertness along with the Leeds Sleep Evaluation Questionnaire were also employed.The CDR test battery [ | PMC10447509 | |
MRI | APPENDIX | A subset of participants, representative of the full group, at both trial sites completed a neuroimaging session at baseline and 12 mo. Here, we report volumetric measures of brain structure in this neuroimaging subset derived from T1-weighted anatomical scans acquired at both sites. Further imaging modalities acquired in this neuroimaging subset are to be reported elsewhere and are detailed in Appendix F of the trial protocol paper [T1-weighted images were processed following the longitudinal processing pipeline [ | PMC10447509 | |
Biological sample collection and analysis | Participants provided an overnight fasted blood sample and a spot urine sample that was their first void of the day.For FLAV and methylxanthine analyses, the metabolites were purified from 50 μL human urine by 96-well plate solid phase extraction (Strata™-X Polymeric Reversed Phase, microelution 2 mg/well). The solid phase extraction treated samples were chromatographically separated and quantified using Exion high-performance ultrahigh performance LC-tandem MS SCIEX QTRAP 6500+ enhanced ultrahigh performance hybrid triple quadrupole-linear ion trap MS with electrospray IonDrive Turbo-V Source. The samples were injected into a Kinetex PFP UPLC column (1.7 μm particle size, 100 Å pore size, 100 mm length, 2.1 mm internal diameter; Phenomenex) with oven temperature maintained at 37°C. Mobile phase A and mobile phase B consisted of 0.1% v/v formic acid in water (Optima grade, Fisher Scientific) and 0.1% v/v formic acid in LC-MS grade acetonitrile (Honeywell Burdick and Jackson) respectively, with a binary gradient ranging from 2% B to 90% B over 30 min and flow rate gradient from 0.55 mL/min to 0.75 mL/min. MS/MS scanning was accomplished by advanced scheduled multiple reaction monitoring using polarity switching between positive and negative ionization mode in Analyst (v.1.6.3, SCIEX) and with quantitation conducted using MultiQuant (v.3.0.2, SCIEX) software platforms. Internal standards included L-tyrosine-The targeted metabolite analysis protocol was optimized and validated to detect 43 analytes, which were quantified relative to 12 authentic commercial and synthetic standards. Where reference standards for metabolites (including FLAV Phase II conjugates) were not available (31 analytes), identification was based on fragmentation profiling involving the precursor structure and 3 to 5 product transitions and confirmed in pooled samples. These metabolites were then quantified relative to their closest structural reference standard with similar ionization intensities (For the fatty acid analysis, plasma samples were analyzed for AA, EPA, and DHA using free/NEFA and lysophosphatidylcholine (LPC) fractions. NEFA and LPC were chosen because they are quantitatively the most important and efficient respectively at delivering DHA to the brain, across the blood brain barrier [BDNF was quantified using a commercially available ELISA assay in serum samples, according to the manufacturer’s instructions (ab212166 – Human BDNF SimpleStep ELISA Kit, Abcam). | PMC10447509 | ||
Dietary assessment | Cancer | CANCER | Assessment of diet at baseline and 12 mo was conducted using a 130-item The European Prospective Investigation into Cancer and Nutrition FFQ [ | PMC10447509 |
Statistical analyses and sample size estimation | The sample size estimate has been detailed previously [All non-MRI analyses were conducted by ANCOVA using mixed models for repeated measures with SAS PROC MIXED. INTERVENTION was fitted as a fixed between-group factor (2 levels: intervention or control group). For non-MRI data, change from baseline was calculated for all outcome variables (ie, 3 mo – 0 mo and 12 mo – 0 mo), and VISIT was fitted as a fixed repeated factor (2 levels: 3 and 12 mo). For MRI data, the 0-mo and 12-mo absolute data was fitted as a 2-level repeated factor. INTERVENTION×VISIT interaction was fitted to the model. The Kenward-Roger approximation was used to estimate denominator degrees of freedom. The LSMEANS statement was used to perform pairwise comparisons between the 2 intervention groups, both overall and at each individual time point. The LSMeans estimates were calculated together with the BASELINE (predose scores) and study site were fitted as covariates. Additional potential covariates included, MCI/SCI status, For the MRI analysis, estimated total intracranial volume, education attainment, and center were added as covariates to the model. The MRI data was evaluated according to the change from an initial baseline scan, thereby overcoming any heterogeneity introduced into the data due to differences in the instruments used at the study sites. Postprocessing of the MRI measures obtained at both sites was conducted at the Biomedical Imaging Center (University of Illinois) to ensure consistency across sites. The effect of group was determined by a univariate ANOVA on the absolute change from 0 to 12 mo (SPSS Version 28.0.1.0). All participants selected for the main per protocol (PP) analyses had completed the entire study and were free of major protocol violations (including medication violations and an overall intervention product compliance of <80%). As a supportive analysis, an intention-to-treat analysis was conducted including all subjects who received at least 1 dose of the study intervention and had postintervention data available. This analysis included CONSORT flowchart diagram. A total of SAS software (STAT 15.1) was used for all statistical analyses | PMC10447509 | ||
Results | PMC10447509 | |||
n-3 PUFA and FLAV response to intervention | PC 38:5 | As anticipated, OM3FLAV intervention resulted in a significant increase in NEFA EPA and DHA and LPC EPA and DHA, along with PC 38:5, PC 38:6, and PC 40:6 fractions (Plasma n-3 PUFA, and urinary flavonoids at baseline and in response to interventionData are mean (SD); ANCOVA using mixed models for repeated measures, with change from baseline (i.e. 3 mo-0 mo and 12 mo-0 mo) fitted as a fixed repeated factor (2 levels: 3 and 12 mo), and center, age, sex and BMI added as covariates.LPC, lysophosphatidylcholine; PC, phosphatidylcholine, PC.36:5 (16:0/20:5, 16:1/20:4, 18:2/18:3), PC.38:6 (16:0/22:6, 18:1/20:5, 18:2/20:4), PC.40:6 (18:0/22:6, 18:1/22:5, 18:2/22:4, 20:2/20:4); OM3FLAV, omega-3 polyunsaturated fatty acids (EPA+DHA; OM3) + cocoa flavan-3-ols (FLAV).Impact of 3-mo and 12-mo consumption of a DHA-rich fish oil and cocoa flavanol mixture (OM3FLAV; | PMC10447509 | |
Primary outcome measure | No significant impact of intervention on picture recognition performance was evident, with mean (SD) of 85.1 (1.3)% and 85.6 (1.4)% at baseline and 12 mo, respectively (Picture recognition new stimuli accuracy (%) at baseline and following 3 mo or 12 mo of a DHA-rich fish oil and cocoa flavanol mixture (OM3FLAV; | PMC10447509 | ||
Secondary cognitive outcome responses | SECONDARY | There was no significant effect of the intervention on any of the secondary composite or individual cognitive outcomes, with the exception of reaction time variability (Cognitive secondary endpoints and response to intervention as per protocol analysisData are mean (SD); ANCOVA using mixed models for repeated measures. TREATMENT was fitted as a fixed between-group factor (2 levels: intervention or control group). Change from baseline was calculated for all outcome variables (ie, 3 mo-0 mo and 12 mo-0 mo), and VISIT was fitted as a fixed repeated factor (2 levels: 3 and 12 mo). BASELINE (predose scores), study site, BMI, and years of education were added as covariates in the final model.part of the CDR test batterya composite measure; Verbal Fluency C1- condition 1, letter fluency, total correct and scaled for age; Verbal Fluency C3a- condition 3, category switching, total correct responses and scaled for age; # Number of items. CDR, Cognitive Drug Research; OM3FLAV, omega-3 polyunsaturated fatty acids (EPA+DHA; OM3) + cocoa flavan-3-ols (FLAV). | PMC10447509 | |
Brain volumes | white matter volume | The baseline MRI data in the group as a whole (Structural MRI assessment of (A) hippocampal volume; (B) cortical volume; (C) cortical white matter volume; and (D) ventricular volume following 12-mo consumption of a DHA-rich fish oil and cocoa flavanol mixture (OM3FLAV; | PMC10447509 | |
Plasma biochemistry | The intervention decreased plasma triglyceride levels by 22% in the OM3FLAV group by 3 mo, with no change in the control group (Plasma biochemistry at baseline and in response to interventionData are mean (SD); ANCOVA using mixed models for repeated measures, with change from baseline (ie, 3 mo-0 mo and 12 mo-0 mo) fitted as a fixed repeated factor (2 levels: 3 and 12 mo), and center, age, sex, and BMI added as covariates. BDNF, brain-derived neurotrophic factor; HDL, high density lipoprotein; OM3FLAV, omega-3 polyunsaturated fatty acids (EPA+DHA; OM3) + cocoa flavan-3-ols (FLAV). | PMC10447509 | ||
Dietary data | Habitual intakes of oily fish (main dietary source of EPA and DHA), total flavonoids and flavan-3-ol were 0.724 portions per week, 842 mg/d and 193 mg/d respectively, with no baseline difference between groups (Nutrient intake (derived from the Food Frequency Questionnaire) at baseline and 12 moData are mean (SD); Intervention Group × Time (baseline, 12 mo) interaction derived from Repeated Measures ANOVA (Analyses were run for the full sample with complete data (results shown) and repeated excluding those reporting total energy expenditure less than 1.1 times their basal metabolic rate (BMR). When excluding underreporters, results were unchanged apart from the following: Carbohydrate, groups differed at baseline (OM3FLAV, omega-3 polyunsaturated fatty acids (EPA+DHA; OM3) + cocoa flavan-3-ols (FLAV). | PMC10447509 | ||
Discussion | memory deficits, MCI, dementia, atrophy, cognitive impairments, cognitive decline, OM3FLAV | SECONDARY, ATROPHY, INSULIN SENSITIVITY, CORTEX | The current study provides the first long-term data to suggest that supplementation with long-chain ω-3 fatty acids and FLAVs over 1 y does not improve cognitive function or brain volumes in individuals with subjective and objective cognitive impairments. The combined dietary intervention resulted in the expected several-fold increases in plasma EPA, DHA, and urinary flavanol metabolite concentrations.This null finding raises several questions regarding the intervention, methodology, and public health implications, which are considered in the following sections. One possibility is that the cognitive battery employed is not sensitive to changes relating to dietary intervention [A second possibility is that the 1-y intervention period was not long enough for the neurophysiological changes associated with PUFAs and FLAVs to become evident. The prodrome of dementia is 20 to 30 y or longer. In prospective cohort studies, positive associations between EPA+DHA and FLAV intakes and cognitive and brain structure represent the benefit of long-term, often decades of habitual dietary exposure [The inclusion of those with SCI and MCI profiles was chosen to increase the translatability of the findings (allowing an exploratory analysis to be conducted as to the most effective window of intervention opportunity). It may be considered as a study limitation, however, potentially increasing the heterogeneity of the response to intervention and thereby decreasing the likelihood of detecting a significant effect of intervention. Although the study is not powered to formally address this issue, we note that there were group differences, specifically for 3 cognitive tests in SCI (reaction time variability, quality of memory, and executive function score) and 2 in MCI, power of attention and picture recognition new stimuli speed). There may be value in targeting more homogenous cohorts in future studies.The lack of effect of OM3FLAV in CANN is consistent with previous interventions that have supplemented with EPA and/or DHA in isolation, as recently reviewed [The impact of intervention length on neurocognitive benefits is evidenced by comparing the 24-mo and 36-mo findings from the LipiDiDiet study [A lower calorie and protein intake in the control group relative to OM3FLAV at 12 mo may have resulted in lower body weight, which could contribute to improved cognition relative to OM3FLAV [There are a number of considerations regarding the intervention itself. One possibility is that there were changes to the interventions during the trial that reduced their functional efficacy. The shelf life of fish oils (FOs) is dependent on certain storage microenvironment conditions to prevent lipid peroxidation. The FO capsules were enriched with mixed tocopherol (3.8 mg/g oil) to prevent any loss of EPA and DHA content. Intervention product fatty acid and FLAV analysis at 1 y indicated no loss of EPA, DHA or flavan-3-ol levels. The FLAV-rich chocolate chips provided 30 mg of caffeine and 262 mg theobromine daily relative to 5.4 mg and 64 mg daily (Of the 11 broad secondary outcomes, performance on one measure of Executive Function (EF) declined in the OM3FLAV group, which was unexpected. The other widely used measures of EF, Verbal Fluency, and Category Switching (measured at baseline and 12 mo) showed no treatment effects. Additionally, EF is generally accepted to rely on prefrontal cortex activity, and we did not find evidence of differential effects on this area (with the caveat that it was not a specific focus of the study).We can be relatively confident that the interventions were consumed as directed. Compliance checks based on intervention returns were good (>95% in both arms), which were supported by plasma and urine fatty acid and flavonoid metabolite enrichment, respectively. Importantly, changes to these biomarkers did not correlate with changes in cognitive function, suggesting that there were not individual differences in intervention response that were related to detectable cognitive benefits.No effect of intervention was evident for hippocampal volume, which was the preregistered secondary outcome for structural MRI. The 0.8% decline in volume of this region over 12 mo in the group as a whole is in line with or potentially lower than would be expected in a mixed SCI/MCI group [Our lack of benefit of OM3FLAV is consistent with the only other randomized controlled trial (RCT) to cosupplement flavonoids (anthocyanins from blueberry powder [BB] and FO providing 1.6 g EPA and 0.8 g DHA per day) for 24 wk in an SCI population [Another possible factor that may contribute to these findings is that the intervention was associated with higher glucose levels, which are known to contribute to cognitive decline via central insulin sensitivity [In conclusion, 1 y intervention with EPA+DHA and cocoa FLAVs did not improve cognition or protect the brain against atrophy in older adults with evidence of memory deficits. However, based on strong prospective cohort evidence of an association between long-term fish/EPA+DHA and flavonoid intake and status and cognitive well-being, and evidence of subgroup variability of response in the current trial, the findings do not preclude modest benefits of supplementation in responsive subgroups. Given the complexity of neuropathological processes underpinning cognitive decline and dementia risk, it is emerging that, at a population level, multidomain [ | PMC10447509 |
References | PMC10447509 | |||
Author contributions | The authors’ responsibilities were as follows –; AMM, AS, NJC, AC, DV: designed the research; DJW, MI, RG, RK: delivered the clinical trial; AS, NJC, HS: designed the cognitive assessment strategy; CK: designed and managed the flavonoid metabolite analysis of the urine samples; MK: undertook the lipidomic analysis under the guidance of CL-Q; DJW, NJC: were responsible for MRI design and data analysis; JFP: was clinical lead on the project; DV, AS, AMM: wrote the paper, with contributions from DJW and NJC; AC, CDK, KM, CL-Q, JFP: critically reviewed the manuscript; AMM had primary responsibility for the final content; and all authors: read and approved the final version of the manuscript. | PMC10447509 | ||
Conflict of interest | DJW has received research funding from Arla Foods, Bayer Healthcare, and Fonterra and consultancy/speaker honoraria from Neurobrands, Naturex, and Bayer Healthcare. AS has received research funding from: Abbott Nutrition, Arla Foods, Bayer, DuPont, Fonterra, GlaxoSmithKline, Nestlé, Nutricia-Danone, and Sanofi. He has received consultancy/speaker fees/honoraria from Bayer, Coca Cola, Danone, GlaxoSmithKline, Naturex, Nestlé, McCormick, Pfizer, Pharmavite, Sanofi, Sen-Jam Pharmaceutical, and Verdure Sciences. He is on the Scientific Advisory Board of Sen-Jam Pharmaceutical and is Chief Scientific Officer for Ārepa Nootropics. All other authors report no conflicts of interest. | PMC10447509 | ||
Funding | The research was funded in part by | PMC10447509 | ||
Data availability | Data described in the manuscript, code book, and analytic code will be made available upon request pending application and approval. | PMC10447509 | ||
Supplementary data | The following is the Supplementary data to this article: | PMC10447509 | ||
Multimedia component1 | PMC10447509 | |||
Acknowledgments | We acknowledge the large contribution by our colleague and friend Prof Keith Wesnes, who sadly died in 2020. Keith was largely responsible for the statistical analysis planning and execution of the CANN study. We thank our nursing and other support staff at our clinical research facilities at the University of East Anglia and Swinburne University for their central role in the delivery of the CANN intervention. We also extend a large debt of gratitude to our 637 participants who registered initial interest in CANN and for the efforts and commitment of the 246 participants who took part on the CANN intervention and clinical and questionnaire-based assessment phases. We acknowledge the large contribution made by Tapas Das, Steve Demichele, and Matt Kuchan at Abbott Nutrition to the design and delivery of the intervention products.Supplementary data to this article can be found online at | PMC10447509 | ||
Background | Type 2 diabetes, impairments in cognitive function, T2DM | TYPE 2 DIABETES | Type 2 diabetes (T2DM) and poor glucose regulation in the immediate postprandial period are both associated with impairments in cognitive function. There is evidence that foods that generate a better postprandial glycemic response, such as low GI foods (which produce a lower glycemic peak, less variability, and a more sustained decline), are associated with cognitive benefits over the morning. However, the potential impact of consuming multiple meals of this nature over the course of a day on cognition in T2DM has not been explored. | PMC10206291 |
Objectives | noninsulin-dependent T2DM | The primary aim of this research was to investigate whether a multimeal paradigm producing a low glycemic response was associated with cognitive benefits in patients with noninsulin-dependent T2DM relative to a multimeal paradigm producing a high glycemic response. | PMC10206291 | |
Methods | noninsulin-dependent T2DM | Twenty-five adults with noninsulin-dependent T2DM (mean age: 57 y) consumed 2 multimeal profiles consisting of a breakfast, lunch, and afternoon snack on 2 separate test days following a randomized, counterbalanced, crossover design. The 2 conditions were a low GI profile (LGIP) and a high GI profile (HGIP). | PMC10206291 | |
Results | satiety, cognitive and executive functions | Cognitive function, glycemic response, mood, and satiety were assessed over the day from 8:30 to 17:00. Overall, there were limited cognitive effects. However, there was evidence for cognitive benefits in the period before lunch, as demonstrated by better global cognitive and executive functions for the LGIP relative to the HGIP. No clear effects were observed for mood. | PMC10206291 | |
Conclusions | T2DM | This study shows that a multimeal paradigm producing a low glycemic response was associated with some benefits for cognitive function in patients with T2DM. | PMC10206291 | |
Clinical Trail Registry reference | NCT03360604 (clinical | PMC10206291 | ||
Keywords | PMC10206291 | |||
Abbreviations | DIABETES | blood-brain barrierchoice reaction timedynamic cerebral autoregulationdependent variableglobal cognitive performancehigh GIhigh GI profilelow GIlow GI profilerapid visual information processingtype 2 diabetes | PMC10206291 | |
Introduction | cognitive impairments, cognitive effect [Cognitive function, T2DM | SECONDARY, TYPE 2 DIABETES | Given that glucose is the main fuel for the brain, it is perhaps not surprising that conditions that are associated with abnormalities in glucose regulation, such as type 2 diabetes (T2DM), are associated with cognitive impairments [Interestingly, dietary intervention studies that have investigated the link between glycemic response and cognitive performance in T2DM have used a single meal paradigm, typically focusing on breakfast. However, humans consume multiple meals throughout the day, spending most of any day in a postprandial state. Therefore, it is more representative of everyday dietary habits if a multiple meal protocol is used to determine the effects of dietary manipulations to improve glycemic control on postprandial cognitive function. The second meal effect demonstrates that the glycemic response to a previous meal can influence the glycemic response to the next meal. This mechanism has also been demonstrated for cognition whereby the nature of the evening meal can impact cognition the next day following an overnight fast, even after a standardized breakfast; a process known as the second meal cognitive effect [Cognitive function is also impacted by mood state, and in some cases, the mechanism for cognitive benefits can be via changes to mood states such as improved self-reported alertness and higher levels of contentment. Although the primary outcome measure here is cognitive function, mood state is also assessed as a secondary outcome measure. Indeed, there is some evidence that a low GI (LGI) diet and LGI foods are beneficial for mood outcomes relative to high GI (HGI) [ | PMC10206291 |
Method | PMC10206291 | |||
Participants | T2DM | Twenty-five adults with a medical diagnosis of T2DM were recruited through a local advertisement at the University of Reading and the surrounding areas. These included 17 men and 8 women, with a mean age of 56.9 y (SD = 7.8), a mean BMI of 30.6 kg/m | PMC10206291 | |
Design | sleepiness, meal carbohydrate | The study followed a counterbalanced, randomized, crossover design with 2 nutritional interventions that produced 2 different glycemic profiles (2 conditions); (1) a low GI profile (LGIP) and (2) a high GI glycemic profile (HGIP). Both conditions consisted of breakfast, lunch, and an afternoon snack (details below), and there were 9 points of assessment over the day, defined using the variable name time. The initial assessment timepoint was undertaken in a fasted state and was treated as baseline data. Eight subsequent time points took place over the course of 7.5 h (Procedural outline for both conditions. CGM, continuous glucose monitor reading; COG, cognitive performance assessment; HFS, hunger, fullness, sleepiness evaluation; SM, subjective mood evaluation.The 2 novel nutritional conditions (Macronutrient composition, GI, and glycemic load (GL) calculations for the low GI profile (LGIP) and high GI profile (HGIP) (TMC, total meal carbohydrate; PCF, proportion of carbohydrate from each food. PCF = CHO/TMC × 100. GI values are taken from Atkinson et al. [ | PMC10206291 | |
Procedure | Diabetes | BLOOD, DIABETES | All exclusion criteria were checked with a self-report questionnaire which participants completed and returned by e-mail prior to a screening session. A 1-h screening session was arranged for the morning at the Hugh Sinclair Unit of Human Nutrition, University of Reading, when height and weight were measured with a Tanita BC-418MA body composition monitor (TANITA Corporation). A venous blood sample was collected in a fasting state, and serum glucose was determined using an Accu-Chek Aviva Blood Glucose Meter System (Roche Diagnostics). A practice run of the cognitive task battery was completed (data not collected) as recommended by Bell et al. [For each test day, upon arrival at 08:00, participants had a continuous glucose sensor (FreeStyle Libre Abbott Diabetes Care Inc) attached to the back of their upper left arm. While the sensor self-calibrated, the participant waited in a quiet room where they were able to watch television or read materials provided within the High Sinclair Research Unit. As shown in | PMC10206291 |
Cognitive function | alertness | The cognitive task battery was administered with E-Prime 2.0 (Psychology Software Tool, Inc). There were 4 separate cognitive tasks: CRT, Rapid Visual Information Processing (RVIP), a merged CRT-RVIP task, and Letter Memory. The CRT task was a measure of general alertness and psychomotor speed. For each trial, a fixation “x” appeared in the center of the screen, which was replaced by a target X either to the left or right of the fixation x. Participants were required to indicate whether the target appeared to the left or right of the fixation point by pressing the relevant key (z or m, respectively) as quickly as possible. The interstimulus interval that separated each trial ranged from 250 ms to 1500 ms in a random fashion (matched across versions). This task lasted for ∼3 min with a total of 60 targets presented. The DVs were accuracy score (maximum 60) and mean reaction time (ms) for correct responses.The RVIP was a measure of sustained attention and working memory. During this task, participants were presented with a continuous string of single numerical digits ranging from 1 to 9 in the center of the screen. The string of numbers was presented at a rate of 75 digits/min, with each trial fixed at 800 ms. Participants continuously monitored the digits for 2 specific target strings, which were “1, 3, and 5” and “6, 4, and 2”. When a target string was observed, the participant would press the space bar as quickly as possible. This task lasted ∼4 min, with a total of 270 single digits being presented, including 20 target strings. The DVs for the task were accuracy score (maximum 20) and mean reaction time (ms) for correct responses.The merged task was a novel concept designed to increase cognitive effort by combining the testing parameters of the CRT and RVIP tasks. Thus, this task is a measure of sustained attention, working memory, and psychomotor speed. The rationale for this task is that it combines 2 already standardized tasks; therefore, the level of demand can be evaluated by comparing the performance of the merged task with the performance of the individual tasks. By combining 2 simpler tests into a more difficult task, the effect of increasing task difficulty can be explored, as previous studies have shown that more difficult demanding tasks are more sensitive to the effects of glucose regulation [The Letter Memory task was a measure of executive function. During this task, participants were presented with a series of letters (consonants only) that appeared individually in the center of the screen. The number of letters presented was either 5 or 7 (8 of each), which randomly varied. When a sequence of letters had ended, participants were presented with a screen that displayed 4 options. Participants had to press the relevant button (1, 2, 3, or 4) to indicate which option contained the last 4 letters that had appeared. Once the participant had indicated their choice, the next sequence of letters would begin. The series of letters were presented at a rate of 30 letters/min, with each letter appearing for 2000 ms. At the end of each sequence, the participant had a maximum of 8000 ms to indicate their choice of the 4 options presented. If they made no choice during the 8000 ms, the next sequence would begin, and no selection was recorded. This task lasted for ∼5 min, with a total of 96 letters being presented across 16 separate sequences. The dependent variables for the task were accuracy score (maximum 16) and mean reaction time (ms) for correct responses.Alternate forms of all cognitive tests were counterbalanced across the test days and time points. | PMC10206291 | |
Glycemic response | Diabetes | DIABETES | Glucose concentrations were measured using a FreeStyle Libre continuous glucose monitoring system (Abbott Diabetes Care Inc). The sensor automatically measured interstitial glucose concentrations every minute and stored readings at 15-min intervals for 8 h. The data was wirelessly transmitted to the reader held by the experimenter upon scanning. During each test day, a total of 23 interstitial glucose readings were taken; immediately before each meal (0 min) and 15, 30, 45, 60, 90, 120, and 150 min post meal consumption ( | PMC10206291 |
Subjective mood and satiety | The Bond-Lader mood questionnaire [ | PMC10206291 | ||
Analysis | Linear mixed models were used for all analyses. For glycemic response, the independent variables condition (LGIP and HGIP) and time (22-time points) were included as fixed factors, with the following covariates included as fixed factors; sex, age, BMI, baseline glucose, and baseline DV score. Baseline glucose was the fasted baseline reading on the test day, and baseline DV score was a performance for the dependent variable being analyzed at the first session of the day. For the glycemic response analysis, baseline glucose and baseline DV represented the same data point, so this was only included once in the model. Additionally, time was specified as a repeated variable to control the covariance structure for each participant. The interaction condition∗time was specified in the model. Pairwise comparisons with Bonferroni corrections were embedded within the model. Participant identification (ID) was included as a random factor to control for the nonindependence of data within participants. The main effects of time are not reported here as these do not inform the research questions. Data from participants ( | PMC10206291 | ||
Results | Background characteristics according to the randomization sequence for this crossover trial are shown in Baseline characteristics of participants by randomization sequence (either LGIP first and HGIP second or HGIP first and LGIP second) data are means and SELGIP, low GI profile; HGIP, high GI profile. | PMC10206291 | ||
Glycemic response | BLOOD | As shown in Blood glucose concentrations (mmol/L) for the low GI profile (LGIP) and the high GI meal profile (HGIP) for the test day following breakfast ( | PMC10206291 | |
Mood and satiety | sleepiness | As shown in Subjective ratings of hunger (A) and sleepiness (B) for the low GI profile (LGIP) and the high GI meal profile (HGIP) ( | PMC10206291 | |
Discussion | cognitive and executive functions, cognitive impairment, noninsulin-dependent T2DM, prediabetes, cognitive or mood effects of the meal profiles, sleepiness, cognitive and mood benefits, satiety, T2DM | EFFECTS LATE, PREDIABETES, OTHER METABOLIC DISORDERS | The aim of this study was to explore the cognitive effects of a multimeal paradigm that produced an LGI response over the course of the day relative to meals which produced an HGI response in patients with noninsulin-dependent T2DM. Overall, there were no cognitive effects for 7 of the 9 cognitive performance measures. However, there were modest cognitive benefits in the period before lunch (2.5–3 h after breakfast), as demonstrated by better global cognitive function for the LGIP relative to the HGIP and specifically, better accuracy for the RVIP task, a measure of executive function. As a combination of all the cognitive tests, the global outcome offers insight into the general direction of effects across the board. Therefore, these results indicate that there is some acute cognitive benefit for patients with T2DM when following meal patterns that are associated with a steadier glycemic response, such as lower peaks and a tapered decline over the postprandial period. This is one of the first studies to assess cognition in patients with T2DM utilizing a multimeal paradigm. The present findings are consistent with studies showing an LGI breakfast is associated with cognitive benefits in prediabetes and T2DM relative to an HGI breakfast [Interestingly, the period before lunch when cognitive benefits were observed did not coincide with glycemic differences between the conditions. Indeed, this asynchrony between cognitive and glycemic effects has been observed previously in healthy young adults [Differences in mood state may also have played a role in the cognitive effects in the morning. For example, the interactions indicated that hunger and sleepiness were higher for the HGIP prior to lunch; however, the pairwise comparisons were NS. This is partially consistent with evidence that lower GI meals are associated with reduced feelings of hunger and increased satiety relative to high GI meals [It was evident in the present study that there were no cognitive or mood effects of the meal profiles in the afternoon, either during the postprandial response to lunch or following an afternoon snack. The simplest conclusion is that there are limited effects of glycemic response and associated physiological processes on cognition during this phase of the day. It is possible that the systematic application of type 1 error correction using the Bonferroni method to the analysis models could lead to type 2 error. It is also possible that our study was underpowered, given that the power calculation was based on a cognitive performance measure that was not assessed in this study. Variation in cognitive measures between studies in this field significantly limits the ability to use the exact same task when calculating a-priori effect size. The absence of other studies exploring the late afternoon phase following glycemic nutritional interventions means further work is required. However, null effects in the GI cognitive field are not unusual in studies with healthy adults [There are a number of limitations to this research. The absence of blood samples renders mechanistic explanations relating to insulin, FFAs, or other plasma characteristics speculative. It would be useful to compare the cognitive performance and glycemic responses of the T2DM sample to a healthy age-matched control group. This would serve 2 purposes; it would enable characterization of the degree of cognitive impairment in this T2DM sample, and it would indicate the relative effectiveness of the LGIP for producing a glycemic response akin to a healthy adult. Nutritional effects on cognitive function are most likely in those with greater capacity for improvement, such as those with more severe T2DM, or in cases where the intervention is particularly effective at benefiting a physiological response, in this case, the glycemic response. Assessing these parameters is not directly possible without a healthy control group. It is noteworthy, though, that the glycemic response to the breakfasts did not differ in the period up to lunch. This indicates that the initial breakfast meal was not effective in producing a differential response between the 2 conditions, which could explain the absence of effects later in the day, that is, a null second meal cognitive effect. Perhaps the breakfast meal is critical for determining cognitive function throughout the remainder of the day. Future studies with a multimeal paradigm would benefit from the inclusion of a breakfast that produces a clear physiological difference between the comparator conditions. Previous research also shows that nutritional interventions in T2DM are most effective when the cognitive demand is high, and the task is verbal memory based [In summary, this study shows that a multimeal paradigm using low GI foods over breakfast, lunch, and an afternoon snack broadly producing a lower glycemic response is associated with modest benefits for cognitive function in patients with noninsulin-dependent T2DM, relative to a meal profile with HGI foods producing a higher glycemic response. For most cognitive outcomes and measures of mood and satiety, there were no differences between the conditions. Interestingly, the benefits for global cognitive and executive functions were only observed ∼2.5–3 h after breakfast, immediately prior to lunch, at a point when the glycemic response was not different between the 2 conditions. Further research is required to explore possible mechanisms and explore the utility of a longer multimeal paradigm for cognitive and mood benefits in patients with T2DM and other metabolic disorders. | PMC10206291 |
Author contribution | The authors’ responsibilities were as follows–MG, DL, and JL: designed the research; MG and DL: wrote the manuscript; JL: edited the manuscript; MG: collected and analyzed the data; and all authors: read and approved the final manuscript. | PMC10206291 | ||
Conflict of intrest | The authors report no conflicts of interest. | PMC10206291 | ||
Data Availability | Data described in the manuscript will be made available upon request to the corresponding author | PMC10206291 | ||
Funding | The authors reported no funding was received for this study. | PMC10206291 | ||
References | PMC10206291 | |||
Background | hemorrhagic transformation, reperfusion injury, acute ischemic stroke, HT | Cerebrolysin could mitigate reperfusion injury and hemorrhagic transformation (HT) in animal models of acute ischemic stroke. | PMC10041692 | |
Methods | Stroke, HT | SECONDARY, STROKE | This was a prospective, randomized, open-label, parallel-group with active control, multicenter pilot study. Cerebrolysin (30 mL/day over 14 days) was administered concurrently with alteplase (0.9 mg/kg) in 126 patients, whereas 215 control patients received alteplase alone. The primary outcomes were the rate of any and symptomatic HT assessed from day 0 to 14. The secondary endpoints were drug safety and functional outcome measured with the National Institutes of Health Stroke Scale (NIHSS) on day 1 and 14, and the modified Rankin scale (mRS) on day 90. Advanced brain imaging analysis was applied on day 1 and 14 as a marker for in vivo pharmacology of Cerebrolysin. | PMC10041692 |
Results | Cerebrolysin treatment resulted in a substantial decrease of the symptomatic HT rate with an odds ratio (OR) of 0.248 (95% CI: 0.072–0.851; | PMC10041692 | ||
Conclusions | neurological deficit, HT | Early add-on of Cerebrolysin to reperfusion therapy was safe and significantly decreased the rate of symptomatic HT as well as early neurological deficit. No effect on day 90 functional outcome was detected. Improvements in the imaging metrics support the neuroprotective and blood–brain barrier stabilizing activity of Cerebrolysin. | PMC10041692 | |
Trial registration | Name of Registry: ISRCTN.Trial Registration Number: Trial Registration Date: 16/02/2021. | PMC10041692 | ||
Keywords | PMC10041692 | |||
Introduction | neuroinflammation, stroke, AIS, HT, excitotoxicity, rtPA, acute ischemic stroke | STROKE, SECONDARY | Intravenous thrombolysis (IVT) within 4.5 h after acute ischemic stroke (AIS) substantially improves functional outcome [A plethora of experimental stroke models have demonstrated neuroprotective effects of Cerebrolysin and its ability to attenuate blood–brain barrier (BBB) permeability [In our current study, we looked at the effects of Cerebrolysin with IVT versus IVT alone in AIS patients. The rationale behind our research comes from two aspects. First, recombinant tissue plasminogen activator (rtPA) increases the HT rate by degrading the BBB integrity, and promoting neuroinflammation and excitotoxicity [Our primary goal was the assessment of the HT rate. The secondary objectives included the evaluation of treatment safety and functional outcome. In addition, advanced brain imaging analysis was applied in an attempt to demonstrate in vivo the neuroprotective and BBB stabilizing activity of Cerebrolysin. | PMC10041692 |
Methods | EMERGENCY | CEREHETIS was a prospective, randomized, open-label, active control, multicenter, parallel-group phase IIIb pilot study. The patients were enrolled across 8 centers in Russia – the Interregional Clinical Diagnostic Center (Kazan), Municipal Clinical Hospital #7 (Kazan), Kazan Federal University Hospital (Kazan), Perm Territorial Clinical Hospital (Perm), Emergency Medical Center (Naberezhnye Chelny), Leninogorsk District Hospital (Leninogorsk), Nizhnekamsk District Hospital (Nizhnekamsk), and Arsk District Hospital (Arsk) – from April 2018 to August 2020. | PMC10041692 | |
Inclusion and exclusion criteria | arteriovenous malformation, bleeding, Gastrointestinal or genitourinary bleeding, Stroke, stroke, Seizure, intracranial aneurism, brain abscess, liver and kidney failure)• Known, neoplasm, HT, rtPA, head trauma, allergic reactions, trauma | BLEEDING, STROKE, ACUTE MYOCARDIAL INFARCTION, INTRACRANIAL HEMORRHAGE, STROKE, INFECTIVE ENDOCARDITIS, BRAIN TUMOR, ALLERGIC REACTION, BRAIN ABSCESS, ISCHEMIC STROKE, DISORDERS, SUBARACHNOID HEMORRHAGE, PERICARDITIS, NEOPLASM, ACUTE PANCREATITIS, BLOOD, DUODENAL ULCER, BLEEDING DIATHESIS | Main inclusion and exclusion criteria are outlined in Table Inclusion and exclusion criteria
• Confirmed diagnosis of acute ischemic stroke• Age ≥ 18 years• Onset of stroke symptoms within 4.5 h before initiation of rtPA administration
• Current or previous intracranial hemorrhage• Symptoms suggestive of subarachnoid hemorrhage, even if CT scan was normal• Imaging data on admission suggestive of a brain tumor, arteriovenous malformation, brain abscess or intracerebral aneurism• Previous history of brain tumor, intracranial aneurism or arteriovenous malformation• Previous history of brain or spine surgery• Acute myocardial infarction within the previous 3 months• Major bleeding, current or within the previous 6 months• Gastrointestinal or genitourinary bleeding within the previous 3 months• Confirmed relapse of gastric or duodenal ulcer• Unknown time of symptom onset• Minor (NIHSS score < 4) or severe stroke (NIHSS score > 25) on admission• Seizure at stroke onset• Stroke or serious head trauma within the previous 3 months• Administration of heparin within the 48 h preceding the stroke onset, with an activated partial thromboplastin time at presentation exceeding the upper limit of the normal range• Platelet count < 100 × 10• Systolic blood pressure > 185 mm Hg or diastolic blood pressure > 110 mm Hg• Blood glucose < 50 mg/dL (2.8 mmol/L) or > 400 mg/dL (22.2 mmol/L)• Oral anticoagulant treatment• Major surgery or severe trauma within the previous 3 months• Other major disorders associated with an increased risk of bleeding (neoplasm, bleeding diathesis, acute pancreatitis, infective endocarditis, pericarditis, severe liver and kidney failure)• Known allergic reactions to rtPA, Cerebrolysin and its components• Pregnancy and lactation• Endovascular treatmentAll recruited patients admitted to the Interregional Clinical Diagnostic Center (Kazan, Russia) who met additional inclusion criteria were consecutively subjected to advanced brain imaging. The criteria were as following: no contraindications to magnetic resonance imaging (MRI) and computed tomography (CT) perfusion (CTP) study, AIS in the middle cerebral artery territory with a minimum diffusion-weighted imaging (DWI) lesion diameter of 20 mm on admission. Patients with any HT on a follow-up CT scan were excluded from the analysis due to paramagnetic distortions caused by blood on the diffusion-tensor imaging (DTI).The center was selected for advanced brain imaging because it was the only one with MRI being available 24/7. | PMC10041692 |
Randomization and blinding | SECONDARY, RECRUITMENT | Each eligible patient was randomly assigned into either the Cerebrolysin or control group by simple randomization procedure. One randomization list for all centers was issued by generating Bernoulli variates with the probability parameter of 0.333. The Mersenne twister was used as an active generator and the starting point was set at random.Allocation instructions were sealed in opaque envelopes, mixed and distributed between the centers by an independent statistician. Each envelop was randomly picked by the investigators and was opened after the subject’s recruitment.Investigators enrolled participants, assigned them to the intervention, and assessed clinically the primary and secondary endpoints. Imaging data were evaluated locally by radiologists who were blinded to the intervention. However, investigators and participants were not blinded to the treatment assignment because Cerebrolysin had its particular yellowish color and we were not able to conceal it properly. | PMC10041692 | |
Study treatment | stroke, death | STROKE | Both groups received a standard dose of 0.9 mg/kg rtPA (alteplase) administered intravenously within 4.5 h after symptom onset (maximal dosage 90 mg, 10% of the drug given in bolus and the rest in 60 min via intravenous infusion). In addition, measures of standard care for AIS patients were applied for both groups. Patients in the Cerebrolysin group additionally received 30 mL of Cerebrolysin diluted in 100 mL of normal saline administered intravenously through a separate line over 20 min. Cerebrolysin treatment was initiated simultaneously with IVT and continued once daily for 14 consecutive days. Acceptable and prohibited co-medications are listed in Table List of Acceptable and Prohibited Co-Medications
• Baseline stroke therapy• Medications for compensation of electrolyte and acid–base abnormalities• Symptomatic medications (antihypertensive, antidiabetic agents, drugs to normalize sleep (excluding benzodiazepines), antibiotics, and antipyretics)
• Neuroprotective or nootropic agents (citicoline, memantine, amantadine, erythropoietin, diazepam, investigational neuroprotective drugs, piracetam, pramiracetam, pyritinol, meclosulfonate, glycine, etc.)• Medications with vasodilatory effect (naftidrofuryl, cinnarizine, flunarizine, nimodipine, nicergoline, pentoxifylline, ergoloid, vinpocetine, vincamine, ginkgo biloba, etc.)• Antioxidant agents (lipoic acid, ethylmethylhydroxypyridine succinate, etc.)• Levodopa and dopamine agonists• Statins within the first 7 days from the stroke onsetAll participants were treated in the hospital settings since inpatient length of stay was at least 14 days according to the national insurance standard for patients with AIS.Patients were withdrawn from further intervention in case neurosurgery was performed or a life-threatening medical (non-neurological) condition occurred. The patient’s participation was discontinued in case of death. The subjects had the opportunity to exit the study at any time.The intention-to-treat (ITT) population comprised all recruited patients, subjects completed the study were included in the per-protocol (PP) analysis. The study ended once the required number of patients was reached and the protocol was accomplished by the participants. | PMC10041692 |
Study procedures | stroke, Stroke | STROKE, STROKE | At the time of admission (day 0), the screening and baseline assessment was performed. Routine clinical, laboratory, and imaging data were collected. Follow-up visits were scheduled in 24 h (day 1, visit 1), on day 7 (visit 2), 14 (visit 3) and 90 (visit 4).The National Institutes of Health Stroke Scale (NIHSS) score was recorded at baseline, in 24 h and on day 14. The modified Rankin scale (mRS) score was assessed on day 90. Vital signs and laboratory tests were evaluated on day 0 and 14.The Alberta stroke program early CT score (ASPECTS) was assessed at admission. A follow-up CT scan was obtained on day 1, 7 and 14 or at any time if required by a clinician.The investigators had special training in the NIHSS, mRS, and ASPECTS rating to improve the inter-rater agreement. | PMC10041692 |
Outcome measures | neurologic deterioration, death, liver and kidney function, HT | ADVERSE EVENTS | The study primary endpoints were any and symptomatic HT verified on a follow-up CT scan from day 0 to day 14. Symptomatic HT was defined according to the ECASS III trial: any apparently extravascular blood in the brain or within the cranium that was associated with clinical deterioration, as defined by an increase of 4 points or more in the score on the NIHSS, or that led to death and that was identified as the predominant cause of the neurologic deterioration [Secondary endpoints were the functional outcome measured with the NIHSS and mRS as well as drug safety. Favorable functional outcome was defined as the mRS score of ≤ 2 on day 90. The NIHSS score on day 14 was considered as a marker of short-term neurological recovery [From day 0 to 14, patients in both arms were monitored for any adverse events (AE), including changes in vital signs, general and neurological condition, electrocardiogram, and routine laboratory tests (liver and kidney function tests, complete blood count). In case an AE occurred, the decision to withdraw participants from the study was bestowed upon investigators. | PMC10041692 |
Advanced brain imaging procedures | infarct | INFARCT | On day 1 and 14, a routine brain MRI was acquired followed by an axial DTI scan. The MRI exam was performed on a GE Signa HDx 1.5 T scanner (GE Healthcare, USA). The DTI sequence parameters were as follows: spin-echo echo-planar imaging, repetition time = 6000 ms, echo time = 102.9 ms, field of view = 260 mm, b-value = 0 and 1000 s/mmThe maps of fractional anisotropy (FA), axial (AD), radial (RD) and mean (MD) diffusivity were derived from the raw DTI scans using the DTIMap plugin for Horos (v.1.6) [On day 14, a brain CTP scan was obtained using the Dankbaar’s approach [The CTP data were processed on a GE Advanced Workstation 4.7 (GE Healthcare, USA) using the CT Perfusion 4D program. As a result, a series of the permeability–surface area product (PS) maps were obtained.The most representative slice was chosen for analysis in each set of images. On that slice, the infarcted area was outlined and mirrored to the contralateral hemisphere. The values of FA, AD, RD, MD, and PS were assessed within each region of interest (Fig. Advanced brain imaging. The most representative slice was selected from a set of diffusion-tensor imaging and CT perfusion scans. The region of interest is outlined on the affected side (*) and is mirrored to the contralateral hemisphere. To cope with the heterogeneity of the ischemic lesions due to different locations, we calculated absolute values of the laterality index for each parameter using the formula [The infarct volume was calculated on DWI (on day 1) and CT (on day 14) scans according to the ABC/2 method [ | PMC10041692 |
Statistical analysis | REGRESSION | Sample size calculation was performed by means of power analysis for matched case–control studies [The estimated number of subjects needed for the advanced brain imaging analysis, computed by power analysis for a two-sample means test [Once the desired sample size of 264 participants had been achieved, it became clear that the number of patients included in the advanced brain imaging analysis was insufficient – only 26 patients were recruited. This was due to the additional, more stringent inclusion criteria for the imaging cohort. Thus, we decided to increase the total sample size by issuing additional envelops in the described above manner until that number reached 34.The descriptive statistics included median (M) with the interquartile range (IQR) for non-normally distributed continuous data and percentage for categorical data.Groups were compared with the Mann–Whitney U test and Pearson’s χOdds ratio (OR) was calculated with binary logistic regression followed byThe STATA v.14.2 (StataCorp, USA) and IBM SPSS Statistics v.26 (IBM Corporation, USA) software packages were used for statistical analysis. | PMC10041692 | |
Results | stroke, hypertension, HT | INTRACRANIAL HEMORRHAGE, STROKE, ATRIAL FIBRILLATION, DIABETES MELLITUS, REGRESSION, HYPERTENSION | Of 1,117 assessed patients with AIS who were eligible for IVT, 341 subjects were recruited and constituted the ITT population. Twenty-three participants (6.7%) did not complete the study with the dropout rate being equal between the groups. Thus, 318 patients formed the dataset for PP analysis (Fig. CONSORT flow chartAlthough the majority of clinical, laboratory and imaging data were not different between the arms at baseline, the participants occurred to be imbalance in a few variables: the patients in the Cerebrolysin group were slightly younger and, as a result, had fewer cases of hypertension and previous stroke (Table Baseline CharacteristicsMoreover, the univariate logistic regression analysis revealed a specific set of HT predictors in the recruited patients on admission. Thus, the patients with a higher NIHSS score and serum levels of creatinine and urea were more likely to develop symptomatic HT. In contrast, participants with higher diastolic blood pressure and values of albumin and hemoglobin were less likely to encounter symptomatic intracranial hemorrhage. Interestingly, the well-established risk factors like age, atrial fibrillation, hypertension, diabetes mellitus, previous stroke, and ASPECTS score were not identified as HT predictors in our patients (Table Risk factors of symptomatic HT on admission, ITT population, univariate logistic regression, | PMC10041692 |
Primary endpoints | stroke, hypertension, HT | REGRESSION, STROKE, HYPERTENSION | In both arms, HT occurred mostly within 24 h after IVT. In the ITT population, Cerebrolysin set a favorable trend to lower any HT with a rate of 15.9% versus 23.3% in the control group and a corresponding OR of 0.543 (95% CI: 0.281–1.05; Study endpointsLikewise, Cerebrolysin treatment resulted in a substantial decrease of symptomatic HT (ITT population: 3.2% compared to 9.3%; PP population: 2.6% compared to 9.0%) with an OR of 0.248 (95% CI: 0.072–0.851; In the ITT population, the NNT (benefit) to reduce any and symptomatic HT with Cerebrolysin was 13.545 (95% CI, 68.282 (harm) to 6.161 (benefit)) and 16.319 (95% CI, 8.536 (benefit) to 184.973 (benefit)), respectively.Similarly, in the PP cohort, the NNT (benefit) was 10.86 (95% CI, 5.50 (benefit) to 420.68 (benefit)) and 15.65 (95% CI, 8.33 (benefit) to 129.10 (benefit)), respectively.Although the arms were imbalanced in age, history of hypertension and previous stroke, the differences had no effect on the primary endpoints after adjustment in a multivariate logistic regression model. In fact, the NIHSS and ASPECTS were determined as significant confounders for any HT, while symptomatic HT was confounded by the NIHSS (Fig. Primary endpoints. Univariate and multivariate logistic regression. Crude and adjusted OR with CI are reported. Solid markers – intention-to-treat population ( | PMC10041692 |
Secondary endpoints | agitation, HT | SIDE EFFECT | The percentage of patients with a favorable functional outcome was approximately the same in both groups. Early neurological recovery on day 14 was more noticeable in the Cerebrolysin group. However, the difference disappeared in patients with HT (Table Secondary endpoint. Modified Rankin Scale score on day 90. No serious AE related to Cerebrolysin were observed. Several mild-to-moderate AE occurred in both groups within 48 h after treatment initiation and lasted up to a few hours without any consequences. The study investigators had unanimously agreed that none of them were attributed to the studied medication, except mild agitation, a well-known side effect of Cerebrolysin (Table Safety analysisFrom day 0 to 14, there were no clinically significant abnormalities in the vital signs and laboratory tests in both groups. Overall, no safety concerns were noted for the concomitant use of IVT and Cerebrolysin. | PMC10041692 |
Advanced brain imaging | infarct | INFARCT | A total number of patients included in the advanced brain imaging analysis was 33 (Fig. Baseline characteristics (No differences in the DTI metrics and DWI infarct volume between the groups were observed on day 1 (Table DTI data, day 1However, patients treated with Cerebrolysin showed a significant improvement of their DTI data on day 14 (Table BBB permeability and DTI data, day 14Advanced brain imaging analysis: diffusion-tensor imaging data (Moreover, the two-week treatment course with Cerebrolysin reduced the BBB permeability and CT infarct volume by more than 1.5-fold (Fig. Advanced brain imaging analysis: permeability–surface area product, infarct volume, and laterality index ( | PMC10041692 |
Discussion | post-stroke, axonal and myelin damage, stroke, AIS, neurological deficit, HT, rtPA, intracranial hemorrhagic | DRUG-DRUG INTERACTION, STROKE, SECONDARY, EVENTS | The results of this randomized, open-label, multicenter pilot trial in stroke patients demonstrate beneficial effects of Cerebrolysin as an early add-on to IVT on the primary (the rate of symptomatic HT) and secondary (early neurological recovery) endpoints. Although we found a significant improvement in the DTI and PS values of the infarcted area, this treatment approach did not affect the long-term functional outcome.A variety of composite scores to predict HT in AIS patients have been published [The risk of HT is established to be the highest on day 1 after stroke onset, and it keeps being significant for the next 14 days [Cerebrolysin treatment was started simultaneously with IVT and continued for 2 weeks. This approach seems to be safe and could alleviate symptomatic intracranial hemorrhagic events and early neurological deficit. Moreover, the beneficial effects correlated with the positive changes in the imaging metrics, supporting the neuroprotective and BBB stabilizing activity of Cerebrolysin. Thus, our findings are strongly coherent with the initial rationale.However, the rate of symptomatic HT observed in our study was higher than it was reported in other IVT clinical trials [In a prospective open-label study of AIS patients with futile recanalization after rtPA, Poljakovic et al. have demonstrated a clear trend towards HT rate reduction in patients treated with Cerebrolysin [In a previous trial by Lang et al. (CERE-LYSE-1), the authors looked at the safety of Cerebrolysin administered 1 h after rtPA infusion for 10 consecutive days as well as at short- and long-term functional outcomes in AIS patients, but not at HT [While our data on short-term neurological recovery confirms the results of previous trials [The ESCAPE-NA1 trial, a large-scale study of the neuroprotective agent nerinetide, failed to demonstrate an improvement in the long-term post-stroke functional outcome due to a possible drug-drug interaction with alteplase [AD and RD could serve as in vivo surrogate markers of axonal and myelin damage, respectively [PS is a known imaging marker of BBB permeability. The more PS rises following AIS, the higher the risk of HT [The strength of the study came in simultaneous use of Cerebrolysin and rtPA followed by a combined assessment of clinical and advance brain imaging data in AIS patients, which has demonstrated multimodal effects of Cerebrolysin on brain recovery and HT prevention in the clinical settings.However, our research had several limitations. It was not blinded, and standard medical care was applied to both groups.Moreover, the sample size was relatively small. As a consequence, the imbalance in some covariates did occur which could be expected since exact balance is a large-sample property [The study was also limited in terms of ethnic and racial diversity. The majority of the participants were of Russian, Tatar, and Jewish ethnic groups with no patients of African, Asian or Hispanic origin.The analysis of DTI and CTP data was confined to a single slice. As a result, our assessment of the infarcted area was restricted. Moreover, our selection criteria for the advanced brain imaging could be a source of potential bias.Therefore, additional large-scale clinical trials are warranted to confirm our findings. | PMC10041692 |
Conclusions | neurological deficit, HT | Early add-on of Cerebrolysin to reperfusion therapy was safe and significantly decreased the rate of symptomatic HT as well as early neurological deficit. However, no significant effect on day 90 functional outcome was detected. Improvements in the imaging metrics of the infarcted area support the neuroprotective and BBB stabilizing activity of Cerebrolysin. | PMC10041692 | |
Acknowledgements | EMERGENCY | This study would not have been possible without the CEREHETIS investigators: Chauzov E.I., Nizhnekamsk District Hospital, Nizhnekamsk, Russia; Faskhutdinova A.T., Kazan Federal University Hospital, Kazan, Russia; Khastiev R.M., Arsk District Hospital, Arsk, Russia; Kulesh A.A., Perm Territorial Clinical Hospital, Perm, Russia; Laishevskaya R.R., Leninogorsk District Hospital, Leninogorsk, Russia; Musin Sh.G., Emergency Medical Center, Naberezhnye Chelny, Russia; Saikhunov M.V., Interregional Clinical Diagnostic Center, Kazan, Russia; Sultanova I.V., Municipal Clinical Hospital #7, Kazan, Russia; Prokofeva Iu.V., Interregional Clinical Diagnostic Center, Kazan, Russia. The authors would like to thank them all for their valuable support in the project execution and data acquisition.Furthermore, the authors would like to express their sincere gratitude to Professor Natan M. Bornstein, Shaare-Zedek Medical Center, Jerusalem, Israel, for his thorough review of the manuscript and his precious comments. | PMC10041692 | |
Authors’ contributors | DRK: project design and execution, analysis, interpretation, manuscript review. MNK: project design and execution, manuscript preparation and review, data acquisition, analysis, interpretation. All authors have read and approved the manuscript. | PMC10041692 | ||
Funding | This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. | PMC10041692 | ||
Availability of data and materials | The datasets acquired and analyzed for this study are available from the corresponding author upon reasonable request. | PMC10041692 | ||
Declarations | PMC10041692 | |||
Ethics approval and consent to participate | This study was approved by the Local Ethics Committee of the Interregional Clinical Diagnostic Center, Kazan, Russia (Protocol #81 of 04/24/2018). However, there was a change in the list of the study centers after that approval, and the final version of the study protocol was issued on 04/30/2018. The amendment did not deter the enrollment of the patients. All recruited subjects or their legal representatives signed written informed consent. The study methods were performed in accordance with the Declarations of Helsinki. | PMC10041692 | ||
Consent for publication | Not applicable. | PMC10041692 | ||
Competing interests | The authors declare that there is no conflict of interest. | PMC10041692 | ||
References | PMC10041692 | |||
2. Patients and Methods | PMC10055796 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.