Data from cohorts, registries, randomised trials, electronic medical records and administrative claims databases have increasingly been used to inform the use of therapies for neurological diseases. ...While novel sophisticated methods are enabling us to use existing data to guide treatment decisions, the complexity of statistical methodology is making appraisal of clinical evidence increasingly demanding. In this narrative review, we provide a brief overview of the most commonly used methods for evaluation of treatment effectiveness in neurology. This primer discusses complementarity of randomised and non-randomised study designs, sources of observational data, different forms of bias and the appropriate mitigation strategies, statistical significance, Bayesian approaches and provides an overview of multivariable regression models, propensity score-based models, causal inference, mediation analysis and Mendelian randomisation.
Geographical mapping of dengue in resource-limited settings is crucial for targeting control interventions but is challenging due to the problem of zero-inflation because many cases are not reported. ...We developed a negative binomial generalised linear mixed effect model accounting for zero-inflation, spatial, and temporal random effects to investigate the spatial variation in monthly dengue cases in Bangladesh. The model was fitted to the district-level (64 districts) monthly reported dengue cases aggregated over the period 2000 to 2009 and Bayesian inference was performed using the integrated nested Laplace approximation. We found that mean monthly temperature and its interaction with mean monthly diurnal temperature range, lagged by two months were significantly associated with dengue incidence. Mean monthly rainfall at two months lag was positively associated with dengue incidence. Densely populated districts and districts bordering India or Myanmar had higher incidence than others. The model estimated that 92% of the annual dengue cases occurred between August and September. Cases were identified across the country with 94% in the capital Dhaka (located almost in the middle of the country). Less than half of the affected districts reported cases as observed from the surveillance data. The proportion reported varied by month with a higher proportion reported in high-incidence districts, but dropped towards the end of high transmission season.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Local weather influences the transmission of the dengue virus. Most studies analyzing the relationship between dengue and climate are based on relatively coarse aggregate measures such as mean ...temperature. Here, we include both mean temperature and daily fluctuations in temperature in modelling dengue transmission in Dhaka, the capital of Bangladesh. We used a negative binomial generalized linear model, adjusted for rainfall, anomalies in sea surface temperature (an index for El Niño-Southern Oscillation), population density, the number of dengue cases in the previous month, and the long term temporal trend in dengue incidence. In addition to the significant associations of mean temperature and temperature fluctuation with dengue incidence, we found interaction of mean and temperature fluctuation significantly influences disease transmission at a lag of one month. High mean temperature with low fluctuation increases dengue incidence one month later. Besides temperature, dengue incidence was also influenced by sea surface temperature anomalies in the current and previous month, presumably as a consequence of concomitant anomalies in the annual rainfall cycle. Population density exerted a significant positive influence on dengue incidence indicating increasing risk of dengue in over-populated Dhaka. Understanding these complex relationships between climate, population, and dengue incidence will help inform outbreak prediction and control.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Orthostatic hypotension is a potential risk factor for falls in older adults, but existing evidence on this relationship is inconclusive. This study addresses the association between orthostatic ...hypotension and falls.
Systematic review and meta-analysis of the cross-sectional and longitudinal studies assessing the association between orthostatic hypotension and falls, as preregistered in the PROSPERO database (CRD42017060134).
A literature search was performed on February 20, 2017, in MEDLINE (from 1946), PubMed (from 1966), and EMBASE (from 1947) using the terms orthostatic hypotension, postural hypotension, and falls. References of included studies were screened for other eligible studies. Study selection was performed independently by 2 reviewers using the following inclusion criteria: published in English; mean/median age of the population ≥65 years; blood pressure measurement before and after postural change; and assessment of the association of orthostatic hypotension with falls. The following studies were excluded: conference abstracts, case reports, reviews, and editorials. Data extraction was performed independently by 2 reviewers.
Unadjusted odds ratios of the association between orthostatic hypotension and falls were used for pooling using a random effects model. Studies were rated as high, moderate, or low quality using the Newcastle-Ottawa Scale.
Out of 5646 studies, 63 studies (51,800 individuals) were included in the systematic review and 50 studies (49,164 individuals) in the meta-analysis. Out of 63 studies, 39 were cross-sectional and 24 were longitudinal. Orthostatic hypotension was positively associated with falls (odds ratio 1.73, 95% confidence interval 1.50-1.99). The result was independent of study population, study design, study quality, orthostatic hypotension definition, and blood pressure measurement method.
Orthostatic hypotension is significantly positively associated with falls in older adults, underpinning the clinical relevance to test for an orthostatic blood pressure drop and highlighting the need to investigate orthostatic hypotension treatment to potentially reduce falls.
Orthostatic hypotension (OH) is common in older adults with reported prevalence rates of 5–40%. A direct link between OH and cognitive performance has been proposed due to impaired vascular ...autoregulation.
To systematically assess the literature of the association between OH and cognitive performance in older adults.
Literature search of MEDLINE, Embase, Cochrane Central Register of Controlled Trials and PsycINFO from inception to May 2017. Studies were included if OH and cognition were assessed in subjects of mean or median age ≥65 years. Risk of bias was assessed with the Newcastle Ottawa Scale.
Of 3266 studies screened, 32 studies (22 cross-sectional; 10 longitudinal) reporting data of 28,980 individuals were included. OH prevalence ranged from 3.3% to 58%. Of the 32 studies, 18 reported an association between OH and worse cognitive performance and 14 reported no association. Mini Mental State Examination (MMSE) was the most commonly used cognitive assessment tool. Studies using more than one cognitive assessment tool were more likely to find an association between OH and worse cognition. OH was significantly associated with a lower MMSE mean score (mean difference − 0.51 (95% CI: −0.85, −0.17, p = 0.003)) and an increased risk of cognitive impairment (OR 1.19 (95% CI, 1.00–1.42, p = 0.048)).
OH is common in older populations and is associated with worse cognition expressed as lower MMSE scores. Use of MMSE alone as a cognitive assessment tool may underestimate the association. It is yet unclear whether the association between OH and worse cognitive performance is causative.
•Orthostatic hypotension is associated with worse cognition in older adults.•It is not yet clear whether the association is causative.•Orthostatic hypotension is common in older adults and often asymptomatic.
Background:
Multiple sclerosis patients experience 3–6 times more seizures than the general population, but observations vary among studies. Seizure risk in disease-modifying therapy recipients ...remains unknown.
Objective:
The objective of this study was to compare seizure risk in multiple sclerosis patients receiving disease-modifying therapy versus placebo.
Methods:
MEDLINE(OVID), Embase, CINAHL, and ClinicalTrials.gov were searched from database inception until August 2021. Phase 2–3 randomized, placebo-controlled trials reporting efficacy and safety data for disease-modifying therapies were included. Network meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, using Bayesian random effects model for individual and pooled (by drug target) therapies. Main outcome was loge seizure risk ratios 95% credible intervals. Sensitivity analysis included meta-analysis of non-zero-event studies.
Results:
A total of 1993 citations and 331 full-texts were screened. Fifty-six included studies (29,388 patients—disease-modifying therapy = 18,909; placebo = 10,479) reported 60 seizures (therapy = 41; placebo = 19). No individual therapy was associated with altered seizure risk ratio. Exceptions were daclizumab (−17.90 −65.31; −0.65) and rituximab (−24.86 −82.71; −1.37) trending toward lower risk ratio; cladribine (25.78 0.94; 4.65) and pegylated interferon-beta-1a (25.40 0.78; 85.47) trended toward higher risk ratio. Observations had wide credible intervals. Sensitivity analysis of 16 non-zero-event studies revealed no difference in risk ratio for pooled therapies (l0.32 −0.94; 0.29)
Conclusion:
No evidence of association was found between disease-modifying therapy and seizure risk—this informs seizure management in multiple sclerosis patients.
Objectives: Over the lifespan cumulative changes to the brain lead to cognitive decline and eventually to dementia in 20-25% of adults 85 years and older. A commonly used screening tool for cognitive ...function is the Standard 30 point Mini-Mental State Examination (MMSE). Though the MMSE is used to screen for dementia, little is known about the changes in scores over the lifespan in general populations.
Method: A systematic search was conducted using Cochrane, EMBASE, MEDLINE and PsycINFO for articles published from January 1, 2007 to May 25, 2017. Articles were included if they had a longitudinal design reporting at least two MMSE scores. A mixed-effect meta-regression analysis was conducted to examine the influence of age on MMSE score followed by a change-point regression analysis determining the age at which MMSE declines.
Results: 45 articles including 58,939 individuals (age range 18-108 years, 61.2% female) summarized 222 MMSE point estimates from 35 cohorts. The meta-regression demonstrated a significant decrease in MMSE scores with higher age (regression coefficient of age: −0.10 (Confidence Interval (CI) −0.15, −0.05)). The average annual decline in MMSE scores identified by the change-point analysis at the age of 41 years and 84 years were −0.04 (95% CI: −0.05, −0.03) and −0.53 (95% CI: −0.55, −0.50), respectively.
Conclusions: Between the age of 29 and 105 years MMSE scores decline, with the highest decline between age 84 and 105 years.
Clinical Implementations: The use of MMSE should be restricted to higher age categories in aging general populations.
Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and ...incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7–2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.
Whether progression independent of relapse activity (PIRA) heralds earlier onset of secondary progressive multiple sclerosis (SPMS) and more rapid accumulation of disability during SPMS remains to be ...determined. We investigated the association between early PIRA, relapse-associated worsening (RAW) of disability and time to SPMS, subsequent disability progression and their response to therapy.
This observational cohort study included patients with relapsing-remitting multiple sclerosis (RRMS) from the MSBase international registry across 146 centres and 39 countries. Associations between the number of PIRA and RAW during early multiple sclerosis (MS) (the initial 5 years of MS onset) were analysed with respect to: time to SPMS using Cox proportional hazards models adjusted for disease characteristics; and disability progression during SPMS, calculated as the change of Multiple Sclerosis Severity Scores over time, using multivariable linear regression.
10 692 patients met the inclusion criteria: 3125 (29%) were men and the mean MS onset age was 32.2 years. A higher number of early PIRA (HR=1.50, 95% CI 1.28 to 1.76, p<0.001) and RAW (HR=2.53, 95% CI 2.25 to 2.85, p<0.001) signalled a higher risk of SPMS. A higher proportion of early disease-modifying therapy exposure (per 10%) reduced the effect of early RAW (HR=0.94, 95% CI 0.89 to 1.00, p=0.041) but not PIRA (HR=0.97, 95% CI 0.91 to 1.05, p=0.49) on SPMS risk. No association between early PIRA/RAW and disability progression during SPMS was found.
Early disability increase during RRMS is associated with a greater risk of SPMS but not the rate of disability progression during SPMS. The deterioration associated with early relapses represents a potentially treatable risk factor of SPMS.
Australian New Zealand Clinical Trials Registry (ACTRN12605000455662).
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