eLetters

988 e-Letters

  • Reply to “Concerns regarding the inference that EDS is not rare"

    We would like to thank Hakim et al for the opportunity to continue the debate around the prevalence and definitions of conditions associated with joint hypermobility. Coming to anything like a true population prevalence for these conditions is still a long way off due to both the huge under-diagnosis (1) and ongoing evolution of the clinically-based criteria (2-4) and terminology for patients who do not have one of the known genetic mutations for classical, vascular or the other so-called rare subtypes of Ehlers-Danlos Syndrome (EDS).

    Hakim et al assert in their letter that diagnosed Joint Hypermobility Syndrome (JHS) is known to be ‘common’. We have searched the literature for reported whole population prevalence rates for JHS and have been unable to find any. Therefore our paper is the first to report a diagnosed prevalence for this condition, although this figure can also be derived for the population of Sweden, as we pointed out in our work. (5)

    We completely agree with the letter’s authors that at this point in time it is not possible to know what proportion of people who met the Brighton Criteria for JHS also meet the 2017 hEDS criteria. We hope further research may reveal this data in the future. What we can say, however, is that for the decade or so prior to 2017, experts in the field considered JHS and EDS-HT to be clinically indistinguishable (1, 6-10), indeed many clinicians used the term JHS/EDS-HT in correspondence in recognition of this. Indeed,...

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  • Response to Levy et al.

    We are grateful to Levy et al for their comments on our paper.

    Much of the response to the paper has been to the media coverage and potential consequences of this. That MDIs have a large carbon footprint is hardly news within technical and academic literature. (1) It’s fair to say we were taken aback by the media response. Any guilt induced by headlines which focussed on individual change is deeply regrettable. Our paper was focussed on modelling at the NHS level. In-line with other previous reports we included an individual level comparison to provide context to our findings. (1-3) The “180-mile car journey” ascribed to us by Levy et al. originates from a story about NICE asthma inhalers decision aid.(4) Clearly we can’t control the media and have tried to correct errors in media reporting where possible. It is our opinion that it would be unethical and paternalistic to withhold significant information about treatment options from patients. As academic authors we are reflecting on how best to communicate information of the environmental impact of healthcare to the public and media, and considering how we might improve this in the future.

    Levy et al. highlight concerns “that all patients can be summarily switched from pMDIs to DPIs” or that patients are “deprived of access to pMDI therapy”. We do not propose this in the paper. In fact we make suggestions on how to reduce the greenhouse gas emissions from MDIs where their continuing use is necessary by prio...

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  • Key Reference unavailable

    Many thanks for bringing this to our attention. Unfortunately that report has been removed from their website and we are unable to add it now as a supplementary file. Here is an alternative reference published more recently which contains the same information:

    Janson C, Henderson R, Löfdahl M, et al. Carbon footprint impact of the choice of inhalers for asthma and COPD Thorax doi: 10.1136/thoraxjnl-2019-213744

    The findings presented here on the carbon footprint of inhalers are entirely concordant with other previous reports.

  • SAS Doctors

    The paper says "...specialty and associate specialist (SAS) doctors (doctors who have completed specialist training but do not have a staff position)...".

    That's not correct. Firstly while SAS doctors may have completed specialist training, they more often have not. Secondly, a permenent SAS doctor does have a "staff position" in ordinary language. If this is a reference to US-specific terminology then I suspect the problem is that there is no direct equivalent.

  • Respond to: Search strategy for this scoping review too limited and missed some JLA Priority Setting Partnerships

    Dear Professor Cullum
    Thank you for your comments regarding the of Cullum et al (2016) and Madden & Morley (2016). These two publications were identified through our search strategy, however, they did not meet our inclusion criteria. The a priory criteria set for inclusion and exclusion of primary studies are listed below:
    Inclusion criteria: All steps from James Lind Alliance, list of Top 10 priorities, adults (aged > 18 years or older)
    Exclusion criteria: Unpublished literature, articles not written in English, priority setting partnership without James Lind Alliance, James Lind Alliance without priority setting partnership, protocols, errata, editorial, thesis, comments, review, guidelines, randomized controlled trials.
    1] Cullum N, Buckley H, Dumville J, Hall J, Lamb K, Madden M, Morley R, O'Meara S, Goncalves PS, Soares M, Stubbs N. Wounds research for patient benefit: a 5 year programme of research. NIHR Journals Library; 2016. This report does not describe prioritized the Top 10 list.
    2] Madden M, Morley R. (2016). Exploring the challenge of health research priority setting in partnership: reflections on the methodology used by the James Lind Alliance Pressure Ulcer Priority Setting Partnership. This article does not describe prioritized the Top 10 list.

  • Vulnerability assessment

    In England I have used the output area classification with success for over 10 years to identify social groups with higher rates of admission. I have found deprivation to be a very crude measure. Alas much of this is not published. but several studies regarding admission to the CCU. Also a couple of studies looking at outbreaks of a mystery disease. See below.

    Hope this helps.

    Beeknoo N, Jones R. Using Social Groups to Locate Areas with High Emergency Department Attendance, Subsequent Inpatient Admission and Need for Critical Care. British Journal of Medicine and Medical Research 2016; 18(6): 1-23. doi: 10.9734/BJMMR/2016/29208

    Beeknoo N, Jones R. Using social groups to locate areas of high utilization of critical care. Brit J Healthcare Manage 2016; 22(11): 551-560.

    Jones R. Year-to-year variation in deaths in English Output Areas (OA), and the interaction between a presumed infectious agent and influenza in 2015. SMU Medical Journal 2017; 4(2): 37-69.
    http://smu.edu.in/content/dam/manipal/smu/smims/Volume4No2July2017/SMU%2...(July%202017)%20-%204.pdf

    Jones R. Role of social group and gender in outbreaks of a novel agent leading to increased deaths, with insights into higher international deaths in 2015. Fractal Geometry and Nonlinear Analysis in Medicine and Biology 2017; 3(1): 1-7. doi: 10.15761/FGNAMB.1000146

    Jones R. Differ...

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  • Inconclusive evidence on self-assessed health in Spain during the Great Recession

    Saez, Vidiella-Martin, and López Casasnovas1 investigate the impact of the Great Recession on self-assessed health in Spain analyzing data from four waves—2005, 2008, 2011 and 2014—of a Survey of Household Finances by the Bank of Spain. The surveys included repeated observations of self-assessed health and other variables measured in the same individuals.
    The statistical model of Saez et al. is a mixed logistic regression in which the log of the odds of poor health (log [P / (1 - P)], where P is the probability of declaring poor health) is computed as a linear combination of a random effect for the year of the survey, random effects for individuals and families, and a large set of control variables at both family level (gross wealth, total debt, family income, savings rate, family size, number of family members who work, and type of family residence—owned or rented) and individual level (sex, age—stratified in six groups—, educational level, occupation, and marital status). Saez et al. computed the model with and without adjustment for the control variables and both for the whole sample and for 12 subsamples stratified by sex and age. The observations were weighted, to compensate for the fact that the original survey oversampled the wealthiest households, and the sample was trimmed to eliminate outliers.
    Saez et al. found a downward change in self-perceived health during the third wave of the survey, i.e., that of 2011, which coincides with the most severe per...

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  • Response to Letter by Pollock et al on “Appropriateness of initial dose of non-vitamin K antagonist oral anticoagulants in patients with non-valvular atrial fibrillation in the UK”

    We thank Dr Pollock and colleagues for their interest in our recent study, which suggested that among patients with non-valvular atrial fibrillation in the UK, inappropriate underdosing was more than twice as common among patients starting on apixaban than those starting on dabigatran or rivaroxaban.

    In our analyses, we assumed that patients with missing data on renal function were likely to have unimpaired renal function. Pollock et al expressed their concern regarding the possibility of significant bias resulting from misclassification of renal function among these patients, which could have resulted in the percentage of patients inappropriately prescribed a reduced dose NOAC being overestimated. Among our study population of 30,467 patients, 3856 (12.7%) had missing data on renal function (eGFR values).

    Pollock and colleagues also queried the absence of bodyweight data in our results. We acknowledge that it may have been useful for the reader to see these data, although we presented data on BMI in Table 1 of our article as a proxy measure. Nevertheless, we can confirm that in our dataset very few patients had missing data on bodyweight (2.6% of patients starting on apixaban, 3.0% of those starting on dabigatran and 2.3% of those starting on rivaroxaban). Among patients with a recorded bodyweight, the mean bodyweight was 81.4 kg for patients starting on apixaban, 82.6 kg for those starting on dabigatran, and 82.0 kg for those starting on rivaroxaban. While...

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  • Vitamin test: on patient or doctor's request?

    Thank you for this critical note about vitamin D and B12 testing. The aim of our study was to explore the barriers and facilitators for reducing the number of unnecessary ordered vitamin D and B12 laboratory tests. We found that GPs experienced difficulty to request laborotory tests only for evidenced based indications; often vitamin testing was performed to satisfy patients' requests. We acknowledge the presence of certain medical indications to test vitamin D or B12 bloodlevels and we also performed a training for participating GPs of our study on vitamin D and B12 deficiency and people at risk of such deficiency. The purpose of our study was not to reduce the number of vitamin D and B12 tests to zero, but to explore the barriers and facilitators related to vitamin D and B12 testing in order to improve properly indicated vitamin testing in general practice.

  • Concerns regarding the inference that EDS is not rare

    Dear Sir or Madam

    Re. Diagnosed prevalence of Ehlers-Danlos syndrome and hypermobility spectrum disorder in Wales, UK: a national electronic cohort study and case-control comparison.
    Demmler J C, Atkinson M D, Reinhold E, Choy E, Lyons R A, Brophy S T
    BMJ Open 2019;9:e031365

    We write concerning the paper by Demmler et al., published in BMJ Open. We wish to raise the following concerns:

    1. With regard to combining the Joint Hypermobility Syndrome (JHS) and Ehlers-Danlos syndromes (EDS) populations for analysis.

    If one combines data from a cohort that is found to be ‘common’ (in this case ‘diagnosed JHS’) with one that is found to be ‘rare’ (in this case ‘diagnosed EDS’), the new combined cohort (i.e. diagnosed JHS/EDS) will be common. To then consider the rare cohort common is a fallacy.

    Also, although individuals in a population with a previous diagnosis of JHS (i.e. prior to the 2017 international classification (1,2)) might have Hypermobile EDS (hEDS) by the current classification, it is not known how JHS segregates into Hypermobility Spectrum Disorder (HSD) and hEDS. A JHS population would need to be reassessed to confirm this, or modelling assumptions of the data would need to be applied.
    In addition, it is not known what proportion of the EDS cohort have hEDS versus the rare Mendelian types of EDS. As such, there is no way of knowing whether or by what proportion the two cohorts represent the same or similar or dif...

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