Method parameters' impact on mortality and variability in mouse stroke experiments: a meta-analysis.
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ABSTRACT:
SUBMITTER: Ingberg E
PROVIDER: S-EPMC4753409 | biostudies-literature | 2016 Feb
REPOSITORIES: biostudies-literature
Publications
Method parameters' impact on mortality and variability in mouse stroke experiments: a meta-analysis.
Ingberg Edvin E Dock Hua H Theodorsson Elvar E Theodorsson Annette A Ström Jakob O JO
Scientific reports 20160215
Although hundreds of promising substances have been tested in clinical trials, thrombolysis currently remains the only specific pharmacological treatment for ischemic stroke. Poor quality, e.g. low statistical power, in the preclinical studies has been suggested to play an important role in these failures. Therefore, it would be attractive to use animal models optimized to minimize unnecessary mortality and outcome variability, or at least to be able to power studies more exactly by predicting v ...[more]
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Project description:BackgroundThe association between poor social relationships and post-stroke mortality remains uncertain, and the evidence regarding the relationship between poor social relationships and the risk of stroke is inconsistent. In this meta-analysis, we aim to elucidate the evidence concerning the risk of stroke and post-stroke mortality among individuals experiencing a poor social relationships, including social isolation, limited social networks, lack of social support, and loneliness.MethodsA thorough search of PubMed, Embase, and the Cochrane Library databases to systematically identify pertinent studies. Data extraction was independently performed by two researchers. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using either a random-effects or fixed-effects model. Sensitivity analyses were conducted to evaluate the reliability of the results. Random-effects meta-regression was performed to explore the sources of heterogeneity in stroke risk estimates between studies. Assessment for potential publication bias was carried out using Egger's and Begg's tests.ResultsNineteen studies were included, originating from 4 continents and 12 countries worldwide. A total of 1,675,707 participants contributed to this meta-analysis. Pooled analyses under the random effect model revealed a significant association between poor social relationships and the risk of stroke (OR = 1.30; 95%CI: 1.17-1.44), as well as increased risks for post-stroke mortality (OR = 1.36; 95%CI: 1.07-1.73). Subgroup analyses demonstrated associations between limited social network (OR = 1.52; 95%CI = 1.04-2.21), loneliness (OR = 1.31; 95%CI = 1.13-1.51), and lack of social support (OR = 1.66; 95%CI = 1.04-2.63) with stroke risk. The meta-regression explained 75.21% of the differences in reported stroke risk between studies. Random-effect meta-regression results indicate that the heterogeneity in the estimated risk of stroke may originate from the continent and publication year of the included studies.ConclusionSocial isolation, limited social networks, lack of social support, and feelings of loneliness have emerged as distinct risk factors contributing to both the onset and subsequent mortality following a stroke. It is imperative for public health policies to prioritize the multifaceted influence of social relationships and loneliness in stroke prevention and post-stroke care.Trial registrationThe protocol was registered on May 1, 2024, on the Prospero International Prospective System with registration number CRD42024531036.
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Project description:BackgroundThis study determined the reliability of topographic motor cortical maps and MEP characteristics in the extensor digitorum communis (EDC) evoked by single-pulse TMS among patients with chronic stroke.MethodsEach of ten patients was studied on three occasions. Measures included location of the EDC hotspot and center of gravity (COG), threshold of activation and average amplitude of the hotspot, number of active sites, map volume, and recruitment curve (RC) slope.ResultsConsistent intrahemispheric measurements were obtained for the three TMS mapping sessions for all measured variables. No statistically significant difference was observed between hemispheres for the number of active sites, COG distance or the RC slope. The magnitude and range of COG movement between sessions were similar to those reported previously with this muscle in able-bodied individuals. The average COG movement over three sessions in both hemispheres was 0.90 cm. The average COG movement in the affected hemisphere was 1.13 (+/- 0.08) cm, and 0.68 (+/- 0.04) cm) for the less affected hemisphere. However, significant interhemispheric variability was seen for the average MEP amplitude, normalized map volume, and resting motor threshold.ConclusionThe physiologic variability in some TMS measurements of EDC suggest that interpretation of TMS mapping data derived from hemiparetic patients in the chronic stage following stroke should be undertaken cautiously. Irrespective of the muscle, potential causes of variability should be resolved to accurately assess the impact of pharmacological or physical interventions on cortical organization as measured by TMS among patients with stroke.
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Project description:BACKGROUND:Microarray data are subject to multiple sources of variation, of which biological sources are of interest whereas most others are only confounding. Recent work has identified systematic sources of variation that are intensity-dependent and non-linear in nature. Systematic sources of variation are not limited to the differing properties of the cyanine dyes Cy(5) and Cy(3) as observed in cDNA arrays, but are the general case for both oligonucleotide microarray (Affymetrix GeneChips) and cDNA microarray data. Current normalization techniques are most often linear and therefore not capable of fully correcting for these effects. RESULTS:We present here a simple and robust non-linear method for normalization using array signal distribution analysis and cubic splines. These methods compared favorably to normalization using robust local-linear regression (lowess). The application of these methods to oligonucleotide arrays reduced the relative error between replicates by 5-10% compared with a standard global normalization method. Application to cDNA arrays showed improvements over the standard method and over Cy(3)-Cy(5) normalization based on dye-swap replication. In addition, a set of known differentially regulated genes was ranked higher by the t-test. In either cDNA or Affymetrix technology, signal-dependent bias was more than ten times greater than the observed print-tip or spatial effects. CONCLUSIONS:Intensity-dependent normalization is important for both high-density oligonucleotide array and cDNA array data. Both the regression and spline-based methods described here performed better than existing linear methods when assessed on the variability of replicate arrays. Dye-swap normalization was less effective at Cy(3)-Cy(5) normalization than either regression or spline-based methods alone.
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Project description:BackgroundDepression may negatively affect stroke outcomes and the progress of recovery. However, there is a lack of updated comprehensive evidence to inform clinical practice and directions of future studies. In this review, we report the multidimensional impact of depression on stroke outcomes.MethodsData sources. PubMed, PsycINFO, EMBASE, and Global Index Medicus were searched from the date of inception. Eligibility criteria. Prospective studies which investigated the impact of depression on stroke outcomes (cognition, returning to work, quality of life, functioning, and survival) were included. Data extraction. Two authors extracted data independently and solved the difference with a third reviewer using an extraction tool developed prior. The extraction tool included sample size, measurement, duration of follow-up, stroke outcomes, statistical analysis, and predictors outcomes. Risk of bias. We used Effective Public Health Practice Project (EPHPP) to assess the quality of the included studies.ResultsEighty prospective studies were included in the review. These studies investigated the impact of depression on the ability to return to work (n = 4), quality of life (n = 12), cognitive impairment (n = 5), functioning (n = 43), and mortality (n = 24) where a study may report on more than one outcome. Though there were inconsistencies, the evidence reported that depression had negative consequences on returning to work, functioning, quality of life, and mortality rate. However, the impact on cognition was not conclusive. In the meta-analysis, depression was associated with premature mortality (HR: 1.61 (95% CI; 1.33, 1.96)), and worse functioning (OR: 1.64 (95% CI; 1.36, 1.99)).ConclusionDepression affects many aspects of stroke outcomes including survival The evidence is not conclusive on cognition and there was a lack of evidence in low-income settings. The results showed the need for early diagnosis and intervention of depression after stroke. The protocol was pre-registered on the International Prospective Register of Systematic Review (PROSPERO) (CRD42021230579).
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Project description:For the past 150 years, bacteria have been investigated primarily in liquid batch cultures. Contrary to most expectations, these cultures are not homogeneous mixtures of single-cell bacteria, because free-floating bacterial aggregates eventually develop in most liquid batch cultures. These aggregates share characteristics with biofilms, such as increased antibiotic tolerance. We investigated how aggregates develop and what influences this development in liquid batch cultures of Pseudomonas aeruginosa We focused on how the method of inoculation affected aggregation by assessing aggregate frequency and size using confocal laser scanning microscopy. Several traditional methods of initiating an overnight bacterial culture, i.e., inoculation directly from frozen cultures, inoculation using agar-grown cells, or inoculation using cells grown in liquid cultures, were investigated. We discovered a direct link between the inoculation method and the size and frequency of biofilm aggregates in liquid batch cultures, with inoculation directly from a plate resulting in the most numerous and largest aggregates. These large aggregates had an overall impact on the cultures' subsequent tolerance toward tobramycin, indicating that the inoculation method has a profound impact on antibiotic tolerance. We also observed a mechanism whereby preformed aggregates recruited single cells from the surrounding culture in a "snowball effect," building up aggregated biomass in the culture. This recruitment was found to rely heavily on the exopolysaccharide Psl. Additionally, we found that both Escherichia coli and Staphylococcus aureus produced aggregates in liquid batch cultures. Our results stress the importance of inoculation consistency throughout experiments and the substantial impact aggregate development in liquid batch cultures may have on the outcomes of microbiological experiments.IMPORTANCE Pure liquid cultures are fundamental to the field of microbiological research. These cultures are normally thought of as homogeneous mixtures of single-cell bacteria; the present study shows that this is not always true. Bacteria may aggregate in these liquid cultures. The aggregation can be induced by the method chosen for inoculation. The presence of aggregates can significantly change the outcomes of experiments by altering the phenotype of the cultures. The study found a mechanism whereby preformed aggregates are able to recruit surrounding single cells in a form of snowball effect, creating more and larger aggregates in the cultures. Once formed, these aggregates are hard to remove. Aggregates in liquid cultures may be an immense unseen challenge for microbiologists.
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Project description:BackgroundAcute glycemic variability (GV) has been correlated with the severity of sepsis. The aim of the study was to evaluate the potential association between acute GV and mortality risk in patients with sepsis.MethodsCohort studies comparing the risk of death within 3 months between septic patients with higher versus lower acute GV were retrieved by systematic search of Medline, Embase, Web of Science, Wanfang and CNKI databases. We used a random-effect model to pool the data by incorporating the between-study heterogeneity. Sensitivity analyses were performed to evaluate the stability of the findings.ResultsTen studies including 4296 patients were available for the meta-analysis. Pooled results showed that septic patients with higher acute GV had significantly increased mortality risk compared to those with lower acute GV, as evidenced by results using different parameters including standard deviation of blood glucose (SDBG, risk ratio [RR]: 1.74, 95% confidence interval [CI] 1.36-2.24, p < 0.001; I2 = 0%), coefficient of variation of blood glucose (RR: 1.91, 95% CI 1.57-2.31, p < 0.001; I2 = 0%), mean amplitude of glycemic excursion (RR: 1.81. 95% CI 1.36-2.40, p < 0.001; I2 = 0%), and glycemic lability index (RR: 2.52, 95% CI 1.72-3.68, p < 0.001; I2 = 0%). Sensitivity analyses by excluding one study at a time did not significantly affect the results (p all < 0.05).ConclusionsHigher acute GV may be a predictor of mortality risk in patients with sepsis.
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Project description:Background and purposeSeveral risk scores have been developed to predict mortality in intracerebral hemorrhage (ICH). We aimed to systematically determine the performance of published prognostic tools.MethodsWe searched MEDLINE and EMBASE for prognostic models (published between 2004 and April 2014) used in predicting early mortality (<6 months) after ICH. We evaluated the discrimination performance of the tools through a random-effects meta-analysis of the area under the receiver operating characteristic curve (AUC) or c-statistic. We evaluated the following components of the study validity: study design, collection of prognostic variables, treatment pathways, and missing data.ResultsWe identified 11 articles (involving 41,555 patients) reporting on the accuracy of 12 different tools for predicting mortality in ICH. Most studies were either retrospective or post-hoc analyses of prospectively collected data; all but one produced validation data. The Hemphill-ICH score had the largest number of validation cohorts (9 studies involving 3,819 patients) within our systematic review and showed good performance in 4 countries, with a pooled AUC of 0.80 [95% confidence interval (CI)=0.77-0.85]. We identified several modified versions of the Hemphill-ICH score, with the ICH-Grading Scale (GS) score appearing to be the most promising variant, with a pooled AUC across four studies of 0.87 (95% CI=0.84-0.90). Subgroup testing found statistically significant differences between the AUCs obtained in studies involving Hemphill-ICH and ICH-GS scores (p=0.01).ConclusionsOur meta-analysis evaluated the performance of 12 ICH prognostic tools and found greater supporting evidence for 2 models (Hemphill-ICH and ICH-GS), with generally good performance overall.
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