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Recent eLetters

Displaying 1-10 letters out of 526 published

  1. Response to 'The prognosis of acute symptomatic seizures after ischaemic stroke'.

    We read with interest the findings and recommendations by the authors. (1)

    Cerebrovascular disease accounts for the increasing burden of seizures and epilepsy in people over the age of 65 years. The distinction between acute and remote symptomatic seizures is highly relevant with implications both for prognosis and clinical management. Acute symptomatic seizures (ASS) following a cerebrovascular event are defined as seizures that occur within 7 days of the ictus while remote symptomatic seizures (RSS) occur out with this time frame. (2) ASS occur in around 6% of acute cerebrovascular events and are more likely in elderly patients, in those with large strokes, stroke involving the cortex or multiple vascular territories, cardioembolic events, and haemorrhagic stroke. (3) Data from the Rochester Epidemiology Project showed a risk for subsequent seizures at 10 years of 33% for ASS, (4) similar to the 28% at 8 years in the Leung Study. Both fall well below the 2014 ILAE operational definition of epilepsy - an enduring predisposition of the brain to generate seizures, defined as a probability of further seizures of at least 60% over the next 10 years. In contrast, following a RSS the 10year risk of further seizures is 71.5%. (4) Thus a diagnosis of epilepsy is not justified for ASS in the context of stroke.

    A decision to commence treatment with anti-epileptic drugs (AEDs) should not be taken lightly; AEDs are commonly implicated in adverse drug reactions, and those with a new brain insult may be particularly susceptible to the mood and cognitive side effects, potentially interfering with rehabilitation. AEDs have known effects on bone health, together with an increased risk of drug interactions in patients who already take numerous drugs to address their many comorbidities, and economic and psychosocial impact. (5)

    While short-term treatment of frequent seizures and status epilepticus occurring within seven days of an acute stroke is appropriate, the overwhelming evidence is that beyond one month there is no benefit from treatment with AEDs. Data from the Rochester Epidemiology Project showed that patients with ASS have a higher mortality during the first 30 days compared to subjects with RSS. (4) This is obviously related to the severity of the underlying stroke but can justify the treatment of ASS in order to minimize the additional contribution to mortality and morbidity due to seizures. However, any recommendation for long-term treatment with antiepileptic drugs beyond a period of a few weeks is against the available evidence. For this reason treatment for four years, as recommended by Leung et al (2016), risks unnecessary exposure of these patients to medication they may not need for many years.

    References: 1. Leung T, Leung H, Soo YOY, Mok VCT, Wong KS. The prognosis of acute symptomatic seizures after ischaemic stroke. J Neurol Neurosurg Psychiatry. 2016 Jan 27; 2. Beghi E, Carpio A, Forsgren L, Hesdorffer DC, Malmgren K, Sander JW, et al. Recommendation for a definition of acute symptomatic seizure. Epilepsia. 2010 Apr;51(4):671-5. 3. Leone MA, Tonini MC, Bogliun G, Gionco M, Tassinari T, Bottacchi E, et al. Risk factors for a first epileptic seizure after stroke: a case control study. J Neurol Sci. 2009 Feb 15;277(1-2):138-42. 4. Hesdorffer DC, Benn EKT, Cascino GD, Hauser WA. Is a first acute symptomatic seizure epilepsy? Mortality and risk for recurrent seizure. Epilepsia. 2009 May;50(5):1102-8. 5. Mula M, Cock HR. More than seizures: improving the lives of people with refractory epilepsy. Eur J Neurol. 2015 Jan;22(1):24-30.

    Conflict of Interest:

    None declared

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  2. Leg stereotypy disorder: Not true stereotypy

    We read the viewpoint on leg stereotypy1 by Joseph Jankovic with great interest. He has described leg stereotypy as repetitive, 1-4 Hz flexion extension, abduction-adduction movement at hips when the patient is seated and the feet rest on the floor.1 This movement has also been described to manifest as flexion extension at the knee joint or as tapping movement of foot.1 Patients as per this description have also been found to have some anxiety when asked to control these movements and also have an inner need to move their legs due to mounting tension. Additionally this movement has been described to reappear on distracting the patient. Stereotypy has been defined as a non-goal-directed movement pattern that is repeated continuously for a period of time in the same form and on multiple occasions, and which is typically distractible.2,3 The key word discernable from this definition is its distractibility. These movements usually disappear when the patient is distracted with various stimuli especially when observed upon by others. This is in contrast with the above mentioned article where the patient's movements reappeared on distracting the patient. Second, stereotypic movements are not associated with an inner urge to perform the movement or to reduce an inner tension by performing the movement. This feature again contradicts with findings described in the above mentioned article in which patients experience an inner need to make the movement in response to an inner need. Such premonitory urges have however been described in the phenomenology of tics.4 Hence the reappearance of movement on distraction and presence of an inner urge to perform the movement create an uncertainity whether the described leg movement should be termed as stereotypy. References 1. Leg stereotypy disorder. Jankovic J. J Neurol Neurosurg Psychiatry 2015;0:1-2. 2. Stereotypies: A Critical Appraisal and Suggestion of a Clinically Useful Definition. Mark J. Edwards, Anthony E. Lang,Kailash P. Bhatia. Movement Disorders, Vol. 27, No. 2, 2012. 3. Pandey S, Sarma N. Stereotypy After Acute Thalamic Infarct. JAMA Neurol. 2015;72(9):1068. 4. Christos Ganos, Davide Martino. Tics and Tourette Syndrome. Neurol Clin 33 (2015) 115-136.

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    None declared

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  3. Meta-analysis by Xu et al. suffers from critical errors

    The meta-analysis by Xu et al is a valiant effort to map the evidence for modifiable risk factors of Alzheimer's disease (AD) (1). We acknowledge this huge effort, however, we have serious concerns regarding the systematic appraisal and the synthesis of the available data.

    On top of the critique by Drs. Wu and Brayne (e-letter), a comprehensive assessment of the article and its results can reveal critical errors in data collection and the analysis of the available evidence. An experienced methodologist could easily spot from the forest plots in the supplementary material that all risk factors are in the same direction, an observation that cannot be explained by chance.

    Therefore, we tried to re-analyze the meta-analyses using data reported in the supplementary material of this paper and, indeed, the summary effect estimates could not be replicated. We figured out that the authors have inadvertently used the extracted ORs (at least for binary exposures) derived from the individual studies as is, without transforming them into the logarithmic scale as it is required, leading to miscalculations of the summary effect sizes. Thus, most if not all inferences in the paper are based on these false summary estimates resulting in misleading conclusions.

    Besides the aforementioned analytical errors, we are afraid that the extraction of relevant data points from the primary studies may suffer from crucial errors as well. We summarise here potential problems for the association between "ever vs never alcohol use" and AD as it illustrated in supplementary material (page 184). Unfortunately, in 4 out of the 11 eligible studies the extracted estimates were wrong. Specifically, in 2 studies the authors included an estimate for the comparison of "wine drinkers vs no drinkers" even though an estimate for "ever vs never alcohol consumption" was available (2,3). In one study they inadvertently reported the estimate for a comparison of tuberculosis history (4) instead of the alcohol use, whereas in another study they extracted an estimate for an occupational exposure to alcohols and phenols (as organic solvents) (5). Moreover, it seems that the study "Lindsay, 2002" (3) has overlapping populations with the study "CHSA, 1994" (6) and therefore it should not be considered twice. Additionally, in one of the included studies (7) the authors have captured an estimate that is most probably is a typo. In the primary study, an OR of 4.10 (95% CI 0.60-80.50) is reported. Our back calculations (based on the point estimate and the lower confidence interval) have shown that the upper CI most probable was 28.05 and this was not corrected by Xu et al, influencing the weight of this study in the meta-analysis.

    Taking all these discrepancies into account we tried to repeat the meta-analysis for the exposure to alcohol and AD. The summary OR (estimated by our team using correct analytical methods, correct effect estimates and after the exclusion of the study with overlapping sample) was 0.79 (95% CI: 0.63-0.98) for fixed effects and 0.84 (95% CI: 0.57- 1.24) for random effects models with I2=57%. In contrast the authors presented a summary OR of 0.63 (95% CI, 0.48-0.79) under the fixed-effects model with I2=11.3%. We have observed similar discrepancies for several other risk factors. Obviously using these effects to calculate the population attributable fractions led to the false conclusion that 66% of the Alzheimer's disease cases could be prevented. Indeed, a more conservative and thorough estimation of the population attributable risk for modifiable risk factors of AD indicated that known risk factors are responsible for only 28.2% (95% CI, 14.2% to 41.5%) of total AD cases worldwide (8).

    Furthermore, inclusion of studies with overlapping samples was also observed in meta-analyses of key risk factors. For example, in the meta- analysis of type 2 diabetes mellitus, the authors included three studies on Cardiovascular Health Cognition Study (Kuller et al 2003, Becker et al 2009 and Irie et al 2008) and another two studies on Baltimore Longitudinal Study of Aging (Moffat et al 2004, Dal et al 2005). However, only the study with the longest follow-up period should be included in the analysis for each of these cohort studies. The same caveat was observed in the meta-analysis for educational attainment.

    Additionally, for other risk factors (e.g socioeconomic status and educational attainment) the authors have not harmonized the exposure of interest, presenting separate meta-analyses for "high level versus low level" and for "low level versus high level" of exposure.

    Finally, we should express our concerns regarding the search strategy applied from the authors. For example in the case of coffee or caffeine drinking, a previous published meta-analysis in 2015 (9) includes more studies and yields non-significant effect estimates (5 studies in the paper by Kim et al and 4 studies in the paper by Xu et al). The authors report a significant random-effects OR of 0.54 (95% CI: 0.39 to 0.69) compared to 0.78 [95% CI: 0.78 to 1.22) by Kim et al which is clearly non- significant. Several similar examples exist throughout the manuscript (e.g. current vs. never statin use, NSAIDs use, ever vs. never smokers).

    Having all these caveats in mind the editorial team of the journal should thoroughly re-assess all the available evidence presented in this paper.

    References

    1. Xu W, Tan LL, Wang H-F, Jiang T, Tan M-S, Tan LL, et al. Meta- analysis of modifiable risk factors for Alzheimer's disease. J Neurol Neurosurg Psychiatry. 2015;86(12):1299-306.

    2. Tyas SL, Manfreda J, Strain LA, Montgomery PR. Risk factors for Alzheimer's disease: a population-based, longitudinal study in Manitoba, Canada. Int J Epidemiol. 2001 Jun;30(3):590-7.

    3. Lindsay J, Laurin D, Verreault R, H?bert R, Helliwell B, Hill GB, et al. Risk factors for Alzheimer's disease: a prospective analysis from the Canadian Study of Health and Aging. Am J Epidemiol. 2002;156(5):445- 53.

    4. Harmanci H, Emre M, Gurvit H, Bilgic B, Hanagasi H, Gurol E, et al. Risk factors for Alzheimer disease: a population-based case-control study in Istanbul, Turkey. Alzheimer Dis Assoc Disord. 2003;17(3):139-45.

    5. Kukull WA, Larson EB, Bowen JD, McCormick WC, Teri L, Pfanschmidt ML, et al. Solvent exposure as a risk factor for Alzheimer's disease: a case-control study. Am J Epidemiol. 1995;141(11):1059-71.

    6. The Canadian Study of Health and Aging: risk factors for Alzheimer's disease in Canada. Neurology. 1994;44(11):2073-80.

    7. Harwood DG, Barker WW, Loewenstein DA, Ownby RL, St George-Hyslop P, Mullan M, et al. A cross-ethnic analysis of risk factors for AD in white Hispanics and white non-Hispanics. Neurology. 1999;52(3):551-6.

    8. Norton S, Matthews FE, Barnes DE, Yaffe K, Brayne C. Potential for primary prevention of Alzheimer's disease: An analysis of population- based data. Lancet Neurol. 2014;13(8):788-94.

    9. Kim Y-S, Kwak SM, Myung S-K. Caffeine intake from coffee or tea and cognitive disorders: a meta-analysis of observational studies. Neuroepidemiology. 2015;44(1):51-63.

    Conflict of Interest:

    None declared

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  4. Re:"Correction to odds ratio"

    Dear Editor,

    We thank Dr. Solari for pointing out an aspect of possible misunderstanding, but surely not incorrectness. We agree that the reverse odds ratio of 5.63 (95% CI 2.87 to 11.05, p<0.001) would more clearly refer to the odds of achieving informed choice. Still the reported odds ratio of 0.18 (95% CI 0.09 to 0.35, p<0.001) gives exactly the same information and is probably more intuitively understood as an odds ratio below 1 usually represents a positive intervention effect by avoiding an unwanted outcome, i.e. in this study avoiding the "absence of informed choice". Therefore, it needs to be stressed that this is not an instance of "errors as part of science" as implied by Dr. Solari, but simply a matter of reporting.

    Furthermore, the proposed way of calculating the odds ratio is rather unusual, as odds are normally calculated within exposure groups and not within outcome groups. The latter would describe the odds to be in the control or in the intervention group, which clearly does not make sense as we want to describe the odds of achieving the outcome. Of course, the odds ratio will be the same for both approaches.

    Best wishes,

    Sascha K?pke, Eik Vettorazzi, Christoph Heesen

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  5. "Correction to odds ratio"

    I enjoyed reading the paper of Sascha Kopke et al. [1] on the efficacy of an evidence-based information program for people with recently diagnosed multiple sclerosis. I noticed, however that the odds ratio (OR) for the primary endpoint (achieving 'informed choice') is incorrect, both in the Abstract and in the Results.

    Abstract: 'For the primary endpoint, a significant difference was shown with 50 of 85 (59%) participants in the intervention group achieving informed choice after 6 months compared with 18 of 89 (20%) in the control group (OR 0.2 (95% CI 0.1 to 0.4), p<0.001).'

    Results: 'The intervention led to significantly more participants with informed choice during 6 months of follow-up (figure 2A), with 50 participants (58.8%) in the IG compared with 18 (20.2%) in the CG (difference 38.6% (95% CI 24.1% to 53.1%); OR 0.18 (95% CI 0.09 to 0.35), p<0.001)'.

    The OR is should in fact be 5.63 (95% CI 2.87-11.05) meaning that patients who received the evidence-based information program achieved informed choice 5.6 times more often than patients who received the control treatment.

    The correct OR (a ratio of ratios) is easily arrived at from examination of the 2 x 2 table below.

    Informed choice- Intervention group: Control group

    Yes- 50 : 18

    No- 35 : 71

    First ratio (informed choice achieved): 50/18 = 2.78. Second ratio (informed choice not achieved): 35/71 = 0.49.

    Ratio of the two ratios (OR): 2.78/0.49 = 5.67. A simpler but less intuitive formula is: 50 x 71/18 x 35 = 5.67.

    Errors are part of science, and sometimes even obvious ones can pass unnoticed in quality peer-reviewed journals. The OR provides information that both clinicians and patients can use for decision making. I hope this letter contributes to making clearer the main findings of this important paper.

    Conflict of Interest:

    None declared

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  6. Thiamine compounds in humans

    I have some comments concerning the report by S. Jesse, D.R. Thal and A.C. Ludolph, recently published in JNNP September 15 2015, pag. 1166-1168 "Thiamine deficiency in Amyotrophic Lateral Sclerosis". In a research dated 1981 Rindi et al. showed that in 12 CSF samples obtained from different healthy subjects, without any clinical disorder involving thiamin status, the only thiamin compounds detected after electrophoretic separation were constantly free thiamine (T) and thiamine- monophosphate (TMP), their mean percentage being 40.7% and 59.3% of total thiamin content respectively. EXPERIENTIA 37, 975-976 (1981). In a successive study Poloni et al. (Arch. Neurol., 1982,39, 507-509) measured free thiamin and thiamin monophosphate levels in plasma and cerebral spinal fluid of patients with ALS, alcoholics, and controls. In plasma of patients with ALS, as well as in plasma and cerebrospinal fluid (CSF) of alcoholics, both thiamin and thiamin monophosphate concentrations were decreased. In CSF of patients with ALS, however, thiamin monophosphate values decreased much more than thiamin levels. This same finding has been observed, interestingly, only in pigs who showed together with rabbits, the highest levels of thiamine in the CSF. In our opinion the selective impairment of thiamin monophosphate production by nerve cells is likely to result from the reduction of the activity of thiamin pyrophosphatase, an enzyme synthesized and highly concentrated in the Golgi complex, a component of the cell where complex molecules such as proteins are synthesized and packaged for use in the body. Thiamin pyrophosphatase diminish in ALS, as well as in experimental motor neuronal degeneration or axotomy. Thus, the thiamin to thiamin monophosphate ratio could be taken as an index of the impairment of neuronal protein synthesis in ALS (Poloni et al.., Arch. Neurol., 1982, 39, 507-509). In an other study, thiamine and thiamine monophosphate levels were measured in the CSF of patients with typical sporadic ALS (50 cases), in other motor neuron diseases (MND) (14 cases), and in patients with upper and/or lower motor neuron lesions of varying origin (disseminated sclerosis, polyneuropathy, spondylotic myelopathy). The thiamine to thiamine monophosphate ratio was greater than or equal to 1 in a high percentage of patients with typical sporadic ALS (94%), in 35.7% of cases with other MND, while it was below one in all the other patients. The decrease of thiamin monophosphate with the inversion of the thiamin to thiamin monophosphate ratio is a finding highly specific to typical sporadic ALS (Poloni et al. It.J.Neurol: Sci.,1986). Other researchers measured the enzymes involved in thiamin synthesis: thiamin pyrophosphatase (TPPase) and thiamin monophosphatase (TMPase) in brain tissue obtained at autopsy from ALS and Parkinsonism-dementia patients from Guam and from Guamanian patients who died from other diseases (controls). TPPase content, chemically determined at pH 9.0, was found to be significantly reduced in the frontal cortex of ALS and Parkinsonism-dementia patients compared to controls. TMPase content, on the contrary, was unchanged (Laforenza et al., J. Neurol. Sci., 1992). Thiamin deficiency causes dry beriberi, a neurologic al disease characterized by "burning" feet, peripheral neuropathy, and Wernicke- Korsakoff syndrome; on this background, in my opinion the method used in this paper to determinate the level of thiamine is indirect and easily subject to drawbacks; Wernicke encephalopathy, istologically observed in two ALS cases, may be due to undernutrition that may be frequently associated in a disease where severe dysphagia may be present in the terminal stage. The reason of the low TMP CSF levels with inversion of the ratio T/TMP, peculiar of ALS patients and ineterestingly found only in pigs, remains unexplained.

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  7. Cholinesterase inhibitors and falls in Parkinson's disease

    We read with great interest the paper by Pagano et al. who conducted a systematic review of prospective, randomised placebo-controlled trials (RCT), in order to assess the efficacy and safety of cholinesterase inhibitors (ChIs) in patients with Parkinson's disease (PD).[1] They concluded that ChIs are effective in the treatment of cognitive impairment in patients with PD. We concur with the authors' nuanced conclusion in the Discussion that based on this meta-analysis no exclusive position can be assumed regarding the efficacy of ChIs in the treatment of frequent falling in PD patients. As the authors point out, the included RCT study by Chung et al. showed that ChI (donepezil) treatment was most effective in the subgroup of patients with frequent falls.[2] This observation suggests that a possible therapeutic indication for cholinergic augmentation therapy to treat falls in PD may require a more personalised or precision type of medicine approach. Cholinergic treatment for falling will most likely have highest efficacy in those PD patients that have the most profound cholinergic system loss, i.e. frequent falling with comorbid cognitive impairment. This may be readily identified by a simple clinical routine, however, this approach would need further validation.[3] It should be noted that cognitive impairment and frequent falling in PD may be caused not only by cholinergic system loss. We have recently shown that cognitive impairment, freezing of gait, and other axial motor impairments are also associated with the presence of beta-amyloid proteinopathy in PD.[4-6] Therefore, future studies should not only have a more detailed fall status assessment but also identify other extra-nigral pathologies in PD that may preclude optimal cholinergic augmentation therapy in these patients.

    References:

    1. Pagano G, Rengo G, Pasqualetti G, et al. Cholinesterase inhibitors for Parkinson's disease: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry 2015;86:767-73.

    2. Chung KA, Lobb BM, Nutt JG, et al. Effects of a central cholinesterase inhibitor on reducing falls in Parkinson disease. Neurology 2010;75:1263-9.

    3. Muller ML, Bohnen NI, Kotagal V, et al. Clinical markers for identifying cholinergic deficits in Parkinson's disease. Mov Disord 2015;30:269-73.

    4. Petrou M, Bohnen NI, Muller ML, et al. Abeta-amyloid deposition in patients with Parkinson disease at risk for development of dementia. Neurology 2012;79:1161-7.

    5. Muller ML, Frey KA, Petrou M, et al. Beta-amyloid and postural instability and gait difficulty in Parkinson's disease at risk for dementia. Mov Disord 2013;28:296-301.

    6. Bohnen NI, Frey KA, Studenski S, et al. Extra-nigral pathological conditions are common in Parkinson's disease with freezing of gait: an in vivo positron emission tomography study. Mov Disord 2014;29:1118-24.

    Conflict of Interest:

    None declared

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  8. Comments on "Meta-analysis of modifiable risk factors for Alzheimer's disease"

    The meta-analysis by Xu et al., (2015)[1] reviews over 300 papers and identified 93 modifiable risk factors for Alzheimer's disease. Among these risk factors, population attributable risks (PAR) of nine important factors were estimated to contribute to up to 66% of Alzheimer's disease cases globally. We acknowledge the great effort of this massive review but there are some substantial analytical issues which should be highlighted.

    (1) Mixture of odds ratio (OR) and relative risk (RR) in the review Although the authors clearly knew the difference between odds ratio (OR) and relative risk (RR) they still combined these results and generated pooled estimates in the meta-analysis. It is generally considered problematic to combine these two epidemiological measures.[2] Odds ratios tend to provide a stronger effect size than relative risks with the two measures only being very close if the prevalence of a disease/disorder is very low. Dementia and Alzheimer's disease are not rare therefore this approach may have led to overestimation of the effect size of risk factors. Although the authors stratified cohort and case-control studies in the meta-analyses, they still reported overall pooled estimates. Given the large number of papers, it would have been possible to focusing only on studies reporting relative risk.

    (2) Grades of evidence Grades of evidence were based on heterogeneity and pooled population size. Although heterogeneity indicates consistency of the results across individual studies, a non-significant I-squared should not be taken as evidence of no heterogeneity.[3] In particular, observational studies generally depend on their research settings and use a variety of methods with diverse study populations. Apparently, similar results can mask considerable underlying variation.

    In the appendix, the authors further excluded some studies according to concerns about study quality and methods. This is an important methodological point and exclusion of studies requires a systematic approach in order for the reader to understand the decisions reviewers have made. Assessments of study quality should be included in "grades of evidence". This corresponds to the first point that the authors could have focused on studies using prospective designs and proper methodologies to provide robust estimates.

    (3) PAR estimation without taking inter-relationship of risk factors into account The PAR calculation did not take into account the inter-relationship between the nine factors leading to spuriously high PAR estimates (66%). Other studies[4,5] have addressed this recognised limitation and an updated analysis of the paper cited by Xu et al[6] was published precisely to correct this important concern. This reduces PAR to around 30%. This is because risk factors such as obesity/low BMI index, frailty/low BMI index (and indeed education and depression) are known to be highly related. Epidemiologists are well aware of the joke that with such naive analyses we claim to be able to prevent over 100% of disorders.

    Finally, some confusing factors such as "current smoking in Asian population" and "diabetes mellitus-II in Asian population" were included in the analysis. The authors suggest the PAR estimate was applied to global Alzheimer's disease cases, but these factors only focus on Asian populations. It is unclear whether it is appropriate to apply these globally.

    We suggest that the findings of this paper over-estimate the effect size and contribution of risk factors for dementia and Alzheimer's disease and that, unfortunately, this contributes to further confusion in wildly over-interpreted media headlines.

    References

    [1] Xu W, Tan L, Wang H-F, Jiang T, Tan M-S, Tan L, et al. Meta- analysis of modifiable risk factors for Alzheimer's disease. Journal of Neurology, Neurosurgery & Psychiatry. 2015. DOI: 10.1136/jnnp-2015- 310548

    [2] Bonita R, Beaglehole R & Kjellstrom T. WHO Basic Epidemiology. 2006. Available: apps.who.int/iris/bitstream/10665/43541/1/9241547073_eng.pdf

    [3] Higgins J & Green S. Cochrane Handbook for Systematic Reviews of Interventions. 2011. Available: handbook.cochrane.org/chapter_9/9_5_2_identifying_and_measuring_heterogeneity.htm

    [4] Norton S, Matthews FE, Barnes DE, Yaffe K, Brayne C. Potential for primary prevention of Alzheimer's disease: an analysis of population- based data. The Lancet Neurology. 2014;13(8):788-94.

    [5] Di Marco LY, Marzo A, Mu?oz-Ruiz M, Ikram MA, Kivipelto M, Ruefenacht D, et al. Modifiable lifestyle factors in dementia: a systematic review of longitudinal observational cohort studies. Journal of Alzheimer's Disease. 2014;42(1):119-35.

    [6] Barnes DE, Yaffe K. The projected effect of risk factor reduction on Alzheimer's disease prevalence. The Lancet Neurology. 2011;10(9):819- 28.

    Conflict of Interest:

    None declared

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  9. Treatment of neuropsychiatric syndromes in Alzheimer's disease (AD): In search of evidence?

    We read with interest the recent systematic review and meta-analysis, "Pharmacological treat-ment of neuropsychiatric symptoms in Alzheimer's disease"(1). By examining the evidence for treating heterogeneous range of neuropsychiatric syndromes in persons with Alzheimer's disease (AD), this study found favorable results for the use of cholinesterase inhibitors (ChEIs) and atyp-ical antipsychotics albeit with risk of side effects, but not for selective serotonin uptake inhibitors (SSRIs), mood stabilizers, or an N-Methyl-D-Aspartate receptor antagonist. The authors sug-gested that their result is generalizable across the spectrum of AD severity. While these findings are important, the results could be expanded. For example, important points including investiga-tion of the heterogeneity (in assessment scales, results, and severity of AD), and methodological limitations need addressing for better understanding of the relative significance of the findings. The Neuropsychiatric Inventory (NPI) used in these trials varies and captures a range of 10 to 12 syndromes. These variations increase the heterogeneity in the findings. Furthermore, this hetero-geneity is enhanced when different compounds with differing mechanism of action or affinity that are designed primarily for individual syndrome use (e.g., antipsychotics for psychosis or de-lusion, or antidepressant for depression, or apathy) are combined. In other words, total NPI score is not necessarily the best reflection of improvement, rather, looking at subtest of items is per-haps more relevant not only in light of studying mechanism of action for each compound, but also for better treatment planning. Same can be said in light of the NPI that aggregates many dif- ferent symptoms, although all related to Behavioral and psychological symptoms of dementia (BPSD), one cannot reasonably expect each medication to be beneficial to all BPSD - i.e. depres-sion and apathy may require something slightly stimulating, while anxiety and agitation may re-quire something slightly sedating. Combining them all under total NPI score and expecting a medication that can cure all is unreasonable. It would have been more informative if these stud-ies reported the effect of each drug on the specific BPSD syndromes and have proper scales to quantify them. Although well formulated to quantify the benefits and safety profiles of various compounds on overall neuropsychiatric syndromes, this meta- analysis could have benefited from taking into account several methodological points, including 1) whether the goal of the included studies was primary or secondary to investigate neuropsychiatric syndromes; and 2) investigated moderating clinical factors.

    The first concern of this study is the lack of explicit statement about the goal of the included studies, which could have shown experimenter bias. This is important for two reasons, A) if the primary goal of the studies was other than neuropsychiatric syndrome, the weight given to indi-vidual compounds would be different. For example, one would anticipate that the cholinesterase inhibitor trials would not be primarily set to find differences in behavioral issues versus the atyp-ical antipsychotic trials, which would be particularly designed to identify such an effect. B) This could be a power issue in that, if the secondary data come from post-hoc analysis, the result could have been underpowered. The second concern is the absence of moderating factors such as inpatient/outpatient, treatment duration, dosage, or severity of AD investigation. Teasing-apart treatment effect for mild, moderate, or severe AD would have added more strength to their find-ing. It is possible that the lack of effect observed in some of the studies is masked because of se-verity of AD, or that optimal dosage was not applied for the preferred duration of treatment.

    In conclusion, with both favorable and dissenting results, although the meta-analysis is well de-signed and carried out, it could have been more informative about the use of psychotropic medi-cation for treating neuropsychiatric syndromes in AD. It could have informed us about the use of each compound for specific AD severity, and duration and dosage of treatment. Also, it could have added notes as to whether these treatment approaches are optimal when used in combina-tion or alone. Given that this study compares itself to earlier meta-analysis and reviews, thus fu-ture studies further benefit by taking into consideration of the above- mentioned points to opti-mize findings.

    References:

    1. Wang J, Yu JT, Wang HF, et al. Pharmacological treatment of neuropsychiatric symptoms in Alzheimer's disease: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry. 2015;86(1):101-109.

    Conflict of Interest:

    None declared

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  10. Hazards of formaldehyde in the workplace.

    The article by Roberts and colleagues on formaldehyde and ALS, is important for its contribution to job related hazards of formaldehyde exposure. One occupation that would be interesting to examine, is wood working/carpentry using mainly plywood. At the core of its manufacture, is formaldehyde. Plywood for indoor use generally uses urea-formaldehyde glue, which has limited water resistance, while outdoor and marine-grade plywood are designed to withstand moisture, and use a water resistant phenol-formaldehyde glue.. Working with plywood produces significant amounts of fine dust containing formaldehyde as well as wood particles. If adequate protection is not used, and ventilation poor, the results can range from eye irritation to various forms of respiratory compromise. Neurological effects are equally likely, especially after years of working in similar dust/formaldehyde environments.

    Conflict of Interest:

    None declared

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