Displaying 1-10 letters out of 531 published
profound benefits for melatonin
We physicians are trained to push Rx medicines but increasingly we find that supplements are efficacious and safer. That melatonin is associated with weight loss is news to me. This paper does an excellent job summarizing the clinical implications and cautions in using melatonin. The dosage information is helpful as well.
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Also patients with dementia need motor examination, but do we need more examination tools?
In an editorial commentary accompanying a recent study on the prevalence of apraxia in dementia patients , Bak emphasizes two facts: 1) research in cognitive neuroscience is contributing to increase the awareness of a close relationship between cognitive and motor functions and, by extension, cognitive and motor disorders in clinical populations; 2) despite so, the examination of motor functions in patients with cognitive disorders is not part of the routine clinical evaluation. Apraxia is a disorder in executing voluntary motor programming, in the absence of deficits in primary motor or sensory processes, comprehension of task instructions, object recognition or frontal inertia. Bak identifies apraxia as the critical disorder to address in routine clinical evaluation of patients with cognitive symptoms, as "it is exactly at the intersection between both [movement and cognition]". In Bak's view, a major obstacle to the improvement of clinical practice in this direction, is the absolute lack of tests for apraxia, practical and fast to use as part of routine evaluation. The Edinburgh Motor Assessment, in preparation by Bak and colleagues, is thus introduced as the first tool to respond to this urge. We could not agree more with the importance of considering apraxia in the routine clinical evaluation of cognitive functions in neurological patients, including those with dementia. Apraxia is indeed a cognitive deficit, affecting the higher-order mechanisms that govern purposeful motor production. However, if poverty or absence of tools is the problem, then we might not have a problem. Researchers have long since recognized apraxia as a cognitive disorder (with consequences on motor production). Moreover, efforts have been made to offer handy, standardized tests of praxis functions (e.g., the test TULIA ), based on models of apraxia, whose anatomo-functional correlates have been extensively studied in brain- damaged patients and in healthy individuals, with neuroimaging research. A problem with most previous tests, evaluating gesture recognition, identification and production in great detail, is the administration time, usually so long as to advise their use in a post-screening phase (i.e., after the patient received a diagnosis of apraxia). Addressing this problem, Tessari et al.  have developed STIMA (short test for ideomotor apraxia), a standardized test for an accurate but quick diagnosis of apraxia. The test, also usable for bedside screening, requires the patient to imitate 36 gestures that form eight subscales. The test and each individual subscale are accompanied by tables to correct raw-scores for age and education, and convert raw-scores into equivalent scores (useful for clinicians to estimate deficit severity) and percentiles (more often used for diagnosis in research). Different subscales test for different praxic impairments. In particular, STIMA emphasizes the distinctions between: 1) imitation errors indicative of cortical damage (e.g., sequence errors or unrecognizable gestures) versus subcortical damage (e.g., postural or timing errors); 2) producing distal (fingers/hand) versus proximal (arm) components of gesture; 3) producing known gestures, which recruits semantic structures in the left temporo-parietal cortex, versus producing novel gestures, which relies on a bilateral cortical network, to transform the visual input (the seen gesture) in a motor act. The evaluation of novel gestures is also crucial to detect praxis deficits in patients who can properly use objects and tools in their domestic context. Evaluation of praxis solely based on execution or reports of daily activities may leave those cases unnoticed. STIMA has been used and proven sensitive to apraxic deficits in patients with stroke , as well as neurodegenerative pathologies . Our short (and non-exhaustive) overview of available standardized tests of apraxia shows a scenario brighter than the total absence of suitable tools depicted by Bak, and does justice to the numerous research teams in cognitive neuropsychology and neuroscience, who have paid more attention than Bak fears, to the clinical scopes of their activity and the constraints of the clinical setting (i.e., time pressure). Since the Edinburgh Motor Assessment by Bak et al. comes after recent and less recent attempts to provide clinicians with a fast and accurate test of apraxia, one may ask: do we really need this new tool? Perhaps, the Edinburgh Motor Assessment introduces features that make it more suitable to dementia patients, than other tests; or it relates to a model of apraxia, not represented in the other tests. Presenting the Edinburgh Motor Assessment as the first step toward an apraxia test for clinical practice precludes the possibility to clarify those or other potentially important aspects of that test. Considering its relation to extant tools rather appears as a good method to provide clear indications about which tool one (e.g., a clinician) should select in which case. This may help reducing the noise in the exchange between researchers and clinical practitioners as well as within our research field.
1. Ahmed S, Baker I, Thompson S et al. Utility of testing for apraxia and associated features in dementia. J Neurol Neurosurg Psychiatry 2016; doi:10.1136/jnnp-2015-312945
2. Vanbellingen T, Kersten B, Van Hemelrijk B et al. Comprehensive assessment of gesture production: a new test of upper limb apraxia (TULIA). Eur J Neurol 2010;17:59-66.
3. Tessari A, Toraldo A, Lunardelli A, et al. STIMA: a short screening test for ideo-motor apraxia, selective for action meaning and bodily district. Neurol Sci 2015;36: 977-984.
4. Mengotti P, Corradi-Dell'Acqua C, Negri GA, et al. Selective imitation impairments differentially interact with language processing. Brain 2013;136:2602-2618
5. Papeo L, Cecchetto C, Mazzon G et al. The processing of actions and action-words in amyotrophic lateral sclerosis patients. Cortex 2015; 64:136-147.
Conflict of Interest:
REPLY TO: "RETINAL NERVE FIBRE LAYER THINNING IS ASSOCIATED WITH DRUG RESISTANCE IN EPILEPSY: PROMISING YET OPEN ENDED"
Sir, We thank Kumar et al. for their interest in our recent article on retinal nerve fibre layer thickness (RNFL) in people with epilepsy. In their letter they raise a few points that we would like to address.
1. Comparison between people with epilepsy and healthy controls. They suggest that a comparison between people with drug-resistant versus non- resistant epilepsy might have been more appropriate. However, as described in the paper itself, in Methods - Statistics, we first compared cases versus controls and then tested for differences in the distribution of average RNFL thickness as a continuous variable according to each demographic and clinical factor, including drug-resistance. The results of this comparison are presented in Results - Average RNFL thickness across all quadrants and exposure to AEDs or non-medical treatments, and showed thinner average RNFL in people with drug-resistant epilepsy compared with non-resistant epilepsy.
2) Kumar et al. state that the aetiological spectrum of epilepsy is not described. We report the epilepsy aetiology in Supplementary material, Table S2, classified according to the "Commission on Classification and Terminology of the International League Against Epilepsy, 1989". We also tested for difference in the distribution of RNFL thickness according to the epilepsy type (see Results - Average RNFL thickness and clinical characteristics--univariate associations). This information was all present in the publication.
3) We agree with the fact that age is a major factor determining the RNFL thickness. We analysed correlation of average RNFL thickness with age in both cases and controls. We included only epilepsy duration in the regression models because of high collinearity with age. We did not consider age group distribution as this would have significantly limited the sample size.
4) We recognise that refractive errors may affect RNFL thickness. For this reason, we excluded people with a distance refractive error of >4.50 dioptres mean sphere/>2.5 dioptres cylinder.
5) We attempted to account for all known factors known to be associated with changes in RNFL (exposure to vigabatrin, diabetes, glaucoma or other known ocular disease, concurrent diagnosis of multiple sclerosis, history of trauma or surgery to the eye or orbit, refractive errors, brain MRI evidence of visual pathway involvement), as stated in Methods, Participants.
The points raised by Kumar et al. were therefore all already addressed in the original paper.
Conflict of Interest:
RETINAL NERVE FIBRE LAYER THINNING IS ASSOCIATED WITH DRUG RESISTANCE IN EPILEPSY: PROMISING YET OPEN ENDED
Sir, The recently published article titled "Retinal nerve fibre layer thinning is associated with drug resistance in epilepsy" by Balestrini S et al has been a refreshing approach into a common menace - refractory epilepsy. 30 to 40% of patients with seizure are classified as persistent seizures under AEDs among which refractory epilepsy is included. (1) Retinal nerve fibre layer (RNFL) thinning is an easy and non invasive analysis which would point towards possible refractory epilepsy leading to shortening of lead time to diagnosis. The present paper opens a whole new arena of thought process for evaluation of refractory epilepsy but leaves the promise open ended. Few points we would like to point out are mentioned below (1) Study groups: This retrospective case control analysis based on hospital records compares two groups including those with epilepsy as the case group and healthy individuals as controls. This comparison has its flaws in comparing two different groups with inherent differences in itself. The case group (epileptics) includes both refractory and non- refractory epileptics, with the control groups being healthy controls. Comparing the case group (patients of refractory epilepsy) with non refractory epileptics might have been more prudent. (2) Etiology of refractory epilepsy and its implications: Effectiveness of AEDs in management of epilepsies is heavily weighted on the underlying etiology. The present study has not mentioned the etiological spectrum of epilepsy which would have further helped in enumerating subgroups adding to strength and validity. Over reliance on the retrospective data for delineating refractory epilepsy takes out the possibility of fixing an appropriate etiology for refractoriness (3) Variation in RNFL among the study population: Age group distribution among the study group has not been mentioned. Literature points the role of age as a major factor in determining the RNFL thickness. (2) Even refractive errors has been noted to have an effect on RNFL thickness. (3) The study excludes only few obvious factors noted to be associated with reduction in RNFL thickness namely multiple sclerosis, Alzheimer's disease, previous optic neuritis and angle closure glaucoma. References 1. Beleza P. Refractory epilepsy: a clinically oriented review. Eur Neurol. 2009;62(2):65-71. 2. Celebi AR, Mirza GE. Age-related change in retinal nerve fiber layer thickness measured with spectral domain optical coherence tomography. Invest Ophthalmol Vis Sci. 2013;54(13):8095-103. 3. Pawar N, Maheshwari D, Ravindran M, Ramakrishnan R. Retinal nerve fiber layer thickness in normal Indian pediatric population measured with optical coherence tomography. Indian J Ophthalmol. 2014;62(4):412-8.
Conflict of Interest:
Short Montreal Cognitive Assessment (s-MOCA): validation study
Roalf et al. describe a short form of the Montreal Cognitive Assessment (s-MOCA) comprising 8 items (score range 0-16) from the original MoCA.
Data from a historical cohort administered the MoCA (n = 150)1 were examined to extract s-MoCA scores. There was high correlation between s- MoCA scores and MoCA and MMSE scores (0.94, 0.80 respectively).
s-MoCA scores differed significantly (null hypothesis rejected) between dementia and mild cognitive impairment (MCI), and between MCI (t = 2.6, p = 0.01) and subjective memory complaint (SMC; t = 6.6, p < 0.001).
Using the specified s-MoCA cutoff of <12/16, the test was very sensitive (0.94) but not specific (0.25) for diagnosis of dementia versus MCI, with a better balance for diagnosis of MCI versus SMC (sensitivity 0.75, specificity 0.66).
Effect sizes (Cohen's d) were medium for diagnosis of dementia versus MCI (0.65) but large (1.19) for diagnosis of MCI versus SMC. All outcome measures were similar to those for the MoCA.
This retrospective study suggests s-MoCA has utility as a cognitive screening instrument for diagnosis of dementia and MCI in a dedicated cognitive disorders clinic. Validation of s-MoCA in a prospective cohort from this clinic (n > 200) is now being examined.
1. Larner AJ. Screening utility of the Montreal Cognitive Assessment (MoCA): in place of - or as well as - the MMSE? Int Psychogeriatr 2012;24:391-6.
Conflict of Interest:
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.
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Leg stereotypy disorder: Not true stereotypyWe 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.
Conflict of Interest:
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.
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:
Re:"Correction to odds ratio"
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.
Sascha K?pke, Eik Vettorazzi, Christoph Heesen
Conflict of Interest:
"Correction to odds ratio"
I enjoyed reading the paper of Sascha Kopke et al.  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:
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