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Recent eLetters

Displaying 1-9 letters out of 293 published

  1. BCIS in hemiarthroplasty

    We found this to be an interesting and thought-provoking article about a relatively less known condition, bone cement implantation syndrome (BCIS).(1) There are clear advantages and disadvantages to the use of cement in hemiarthroplasty, and this data illustrates the infrequent incidence of BCIS whilst emphasising the ever-present risk of serious harm to the patient. As such, it should be worth mentioning the risk of BCIS during the consenting process, as per GMC guidance,(2) in order to ensure that an informed decision is made. The article provides us with an estimated incidence that can be mentioned in the preoperative consenting process.

    Razuin et al.(3) reported post-mortem findings in BCIS of multi- organ embolisation of material from the procedure, i.e. cement and bone. It would be interesting to find out how many BCIS deaths reported on the NRLS had similar post-mortem findings, as opposed to other causes of peri- and intra-operative mortality. We wonder if a retrospective review of affected patients would help identify a subgroup that should not have a cemented procedure. It may also be worth considering further study into alternatives to cement, or the development of a new monomer.

    Anoop Jose, Medical Student, University of Manchester

    Anup Kumar Shetty, Acting consultant orthopaedic surgeon, Tameside General Hospital

    Raja Swaminathan, Consultant orthopaedic surgeon, Tameside General Hospital

    References

    1) Rutter PD, Panesar SS, Darzi A, & Donaldson LJ. (2014). What is the risk of death or severe harm due to bone cement implantation syndrome among patients undergoing hip hemiarthroplasty for fractured neck of femur? A patient safety surveillance study. BMJ open, 4:e004853 doi:10.1136/bmjopen-2014-004853

    2) General Medical Council. Consent: patients and doctors making decisions together - Guidance for doctors. GMC 2008

    3) Razuin R, Effat O, Shahidan MN et al. (2013). Bone cement implantation syndrome. Malaysian J Pathol, 35(1), 87-90

    Conflict of Interest:

    None declared

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  2. Treatment delay affects clinical severity of tuberculosis: a longitudinal cohort study

    Dear Sir, We read the article titled "Treatment delay affects clinical severity of tuberculosis: a longitudinal cohort study" published in BMJ open. The article was interesting as tuberculosis (TB) treatment delay is one of the important issues in timely case detection and management of TB in developing countries. The article was well written. However we have few comments to share which will further facilitate the understanding of the results.

    We noticed inconsistency in the information provided in abstract and main article. In abstract it was mentioned that patients were included 'at the time of diagnosis' vs 'at the start of treatment in TB treatment facilities' in the methodology section of the main article. Especially, in countries like India, we expect some delay in initiation of treatment from the time of diagnosis.(1) So the information on the stage at which the patients were recruited into the study is very important. Moreover the definition of time delay as per the article is "from start of symptom to initiation of specific anti-TB treatment". Hence the recruitment at time of diagnosis of TB is not valid, unless the program in Guinea-Bissau is such that the treatment is started for the TB patient on the same day of diagnosis. If recruitment was done at TB treatment facilities, whether all TB treatment facilities in Bissau were considered for study or any sampling of facilities was done? Time of registration for the study and place of recruitment will affect the treatment delay and hence internal validity and generalizability of study results.

    The study says all cohorts will be followed for two years duration for assessment of mortality outcome; in that case data of patient recruited on 4th June 2010 has to be followed till 4th June 2012. But it is mentioned data was analyzed during June 2010. It could have been better if authors have stated that any censoring for the above time period and the proportion of study population censored. It may be such that data pertaining to objectives- factors affecting treatment delay and effect of treatment delay on clinical severity at diagnosis may have been analyzed during June 2010, but the way it is mentioned in the article is misleading.

    Also in cohort study it is essential to comment on "lost to follow up" during course of study. In smear negative patients, the lost to follow up at 12 months (6 months after completion of treatment) was mentioned as 31.4%. Therefore we can expect more percentage of loss to follow up by end of 24 months. Similarly the information on lost to follow up among smear positive patients was not mentioned though they were the majority in the study population. The author had mentioned all-cause mortality only among smear negative patients that too over 12 months. It would have been better if the total number of tuberculosis patients died over 24 months was also mentioned in the article, as mortality is one of the outcome measures.

    . In the methodology section authors have stated that they have used multiple linear regression model to adjust for multiple risk factors in the treatment delay analysis. It is expected that the outcome variable for multiple linear regression should be a continuous variable (i.e. number of days of delay) and the association in linear regression is expressed in terms of Beta co-efficient. But in table 2 the strength of association was expressed in terms of relative risk showing risk factors related to delay in treatment, which cannot be obtained from multiple linear regression. In case if the association has to be interpreted in terms of Odds ratio or relative risk, the outcome has to be binary (either treatment was delayed or not delayed). There are studies where they have quoted predictor value of factors in terms of either Beta coefficient (2) or in terms of odds ratio after mentioning cut off for considering patient was delayed or not in his treatment (3-5). If the outcome was considered binary and relative risk was obtained using logistic or cox regression, then there should be some cut-off to define whether patient delayed his treatment or not ( Ex. Patients with more than 30 days delay are considered to be delayed in treatment or median cut off).(3-5)

    The study interpreted the smear negative TB as the risk factor for treatment delay. But as per WHO clinical criteria at least two weeks of follow up with antibiotics was recommended before considering a patient for anti- TB specific treatment. So the observed difference of 2-3 weeks in this could be due to the WHO clinical criteria for diagnosing the case and not necessarily a risk factor for treatment delay.

    References 1. Sai Babu B, Satyanarayana AVV, Venkateshwaralu G, Ramakrishna U, Vikram P, Sahu S, et al. Initial default among diagnosed sputum smear- positive pulmonary tuberculosis patients in Andhra Pradesh, India. Int J Tuberc Lung Dis Off J Int Union Tuberc Lung Dis 2008;12(9):1055-8.

    2. Ukwaja KN, Alobu I, Nweke CO, Onyenwe EC. Healthcare-seeking behavior, treatment delays and its determinants among pulmonary tuberculosis patients in rural Nigeria: a cross-sectional study. BMC Health Serv Res 2013;13:25.

    3. Ngadaya ES, Mfinanga GS, Wandwalo ER, Morkve O. Delay in Tuberculosis case detection in Pwani region, Tanzania. a cross sectional study. BMC Health Serv Res 2009;9:196.

    4. Yimer S, Bjune G, Alene G. Diagnostic and treatment delay among pulmonary tuberculosis patients in Ethiopia: a cross sectional study. BMC Infect Dis 2005;5:112.

    5. Needham DM, Foster SD, Tomlinson G, Godfrey-Faussett P. Socio- economic, gender and health services factors affecting diagnostic delay for tuberculosis patients in urban Zambia. Trop Med Int Health 2001;6(4):256-9.

    Conflict of Interest:

    None declared

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  3. Fruit and vegetables in the diet and mental well-being

    The findings of Stranges, et al (2014) that fruit and vegetable consumption was associated with mental well-being brought to mind some other findings (1). There could be numerous mechanisms to explain these results; however, a few jump readily to mind.

    It has been asserted that oxidative stress may play a role in anxiety (2). A diet containing ample amounts of fruits and vegetables, which are rich in antioxidant and anti-inflammatory agents, might promote brain- health in part by reducing oxidative stress (3).

    There is growing evidence that the gastrointestinal microbiota influence brain function (4). This might be by multiple mechanisms. One intriguing possibility is that the gut ecosystem might influence the human epigenome including that of the brain (5). It should be noted that the epigenome retains some malleability throughout the lifespan and that the epigenome appears to influence brain function (6, 7). Whole plant foods, including fruits and vegetables, are believed to promote a health gut ecosystem (8). In addition, phytochemicals found in fruits and vegetables also affect the epigenome and might plausibly shape mood by modulating gene expression (9, 10).

    About the author: www.CeliaMRoss.com

    1. Stranges S, Samaraweera PC, Taggart F, Kandala NB, Stewart-Brown S. Major health-related behaviours and mental well-being in the general population: the Health Survey for England. BMJ Open. 2014 Sep 19;4(9):e005878. 2. Bouayed J, Rammal H, Soulimani R. Oxidative stress and anxiety: relationship and cellular pathways. Oxid Med Cell Longev. 2009 Apr- Jun;2(2):63-7. 3. Lau FC, Shukitt-Hale B, Joseph JA. Nutritional intervention in brain aging: reducing the effects of inflammation and oxidative stress. Subcell Biochem. 42:299-318. 4. Tillisch K. The effects of gut microbiota on CNS function in humans. Gut Microbes. 2014 May 16;5(3). 5. Stilling RM, Dinan TG, Cryan JF. Microbial genes, brain & behaviour - epigenetic regulation of the gut-brain axis. Genes Brain Behav. 2014 Jan;13(1):69-86. 6. Fraga MF, et al. Epigenetic differences arise during the lifetime of monozygotic twins. Proceeding of the National Academy of Science U S A. 2005 Jul 26;102(30):10604-9. 7. D'Addario C, et al. Selective DNA methylation of BDNF promoter in bipolar disorder: differences among patients with BDI and BDII. Neuropsychopharmacology. 2012 Jun;37(7):1647-55. 8. Tuohy KM, Contemo L, Gasperotti M, Viola R. Up-regulating the human intestinal microbiome using whole plant foods, polyphenols, and/or fiber. J Agric Food Chem. 2012 Sep 12;60(36):8776-82. 9. Blade C, Baselga-Escudero L, Arola-Amal A MicroRNAs as New Targets of Dietary Polyphenols. Curr Pharm Biotechnol. 2014 Jul 11. [Epub ahead of print] 10. Pan MH, Lai CS, Wu JC, Ho CT. Epigenetic and disease targets by polyphenols. Curr Pharm Des. 2013;19(34):6156-85.

    Conflict of Interest:

    I write about health issues.

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  4. Reply to Ole Olsen

    Thanks to Ole Olsen for calling attention to a possible inconsistency between the data included in our paper and official stillbirth statistics.

    We always make our own data retrieval from the raw data in the National registries, including the birth registry rather than relying on the official statistics.

    First the official statistics often and also in this case are inconsistent. According to the official publication from National Health Board covering the years 2009-2011 the number of stillbirths in 2010 and 2011 were 255 and 246 respectively (1) whereas according to the official 2013 publication by Statens Serum Institute, the numbers were 270 and 274 in the same two years(2), and finally Statistics of Denmark reports 269 and 262 respectively (3). So what Ole Olsen considers as the truth actually differs between different official bodies.

    Secondly, for scientific purposes it is mandatory to know exactly which conditions are applied for your data, which data sources you get your information from, restriction periods for repeated non fatal events etc.

    Our focus was on stillbirths from 37 weeks. Some differences between dataset may arise from different basic requirements to the dataset. E.g. we only included women delivering in Denmark with a Danish PIN-code. Thus women in transit from other countries, but delivering in Denmark, are not included in our data. Such conditions may explain small differences in different dataset. But according to the latest official stillbirth data including the online statistics which Ole Olsen refer to, the number of stillbirths from 37 weeks was in 2009-2010 247 and in 2011-2012 152, a decrease of 95 (2). According to our data the number of stillbirths from 37 weeks fell from 198 to 148 or with 50 events from 2009-2010 to 2011-2012. In other words, the official statistics suggest a fall which is almost twice the fall we suggested. So if anything, our data were more conservative than the official statistics.

    The reason of focusing on stillbirths from 37 weeks is that a change in induction practice around and after term is not expected to influence stillbirths before 37 weeks. Contrary, inclusion of stillbirths before 37 weeks may actually hide the impressing and welcome decrease in stillbirths from 37 weeks in Denmark through recent years.

    We have delivered detailed figures on our data and the conditions and anticipations we made. We still think we have valid data, which except for year 2010 are actually very close to the latest official statistics (2). We have checked data for year 2010, and still find the results that we published.

    Thus, we see no reason to doubt our results and even less to withdraw our publication.

    ?jvind Lidegaard

    1) Sundhedsstyrelsen. F?dselsstatistikken 2011. Copenhagen, Sundhedsstyrelsen, 2012.

    2) Sundhedsstyrelsen. F?dselsstatistikken 2012. Copenhagen, Statens Serum Institut, 2013.

    3) http://www.statistikbanken.dk/statbank5a/default.asp?w=1280 Visited September 14, 2014.

    Conflict of Interest:

    See original paper

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  5. Trial protocol must explain how possible adverse effects will be looked for and managed

    Grigg and colleagues have published their design for the first-ever randomised controlled in Plasmodium knowlesi malaria, to be carried out over a 2-year period in Sabah [1]. We are concerned because one arm of the trial involves a fixed combination of mefloquine + artesunate.

    The authors of the study protocol rightly acknowledge that mefloquine is associated with neuropsychiatric adverse events (AEs), but go on to state that these are 'self-limiting'. This claim by Grigg et al is incompatible with published reports of neuropsychiatric AEs from mefloquine that have persisted for months, or years [2] [3] [4]. Last year the US Food and Drug Administration strengthened its warning on the neurological and psychiatric adverse effects of mefloquine to its highest level (i.e. a 'black box' warning); the change was prompted by the recognition that the adverse effects of mefloquine can be prolonged and even, in some patients, permanent [5].

    We recommend that the protocol for this trial should include details of how possible adverse effects of mefloquine will be looked for at and after the end of the study, and how the authors propose to manage neuropsychiatric or other AEs that prove to be prolonged, or permanent.

    Andrew Herxheimer

    Ashley Croft

    UK Cochrane Centre, Summertown Pavilion, 18-24 Middle Way, Oxford OX2 7LG, UK

    Conflict of Interest:

    None declared

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  6. Correction: Ambulatory blood pressure adds little to Framingham Risk Score for the primary prevention of cardiovascular disease in older men: secondary analysis of observational study data

    The correct affiliation for Andrew Hayen is: School of Public Health and Community Medicine, The University of New South Wales, Sydney, New South Wales, Australia

    Conflict of Interest:

    None declared

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  7. Correction for the reference 28

    The 28th reference cited in this article should be corrected as:

    28. Xie Y, Ho SC. Prenotification had no additional effect on the response rate and survey quality: a randomized trial. J Clin Epidemiol 2013;66:1422-6.

    Conflict of Interest:

    None declared

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  8. Stillbirth data seem incorrect

    "The registry is considered complete through the period" Hedegaard et al state in their registry study (1) without a supporting reference. However, there seem to be an issue with the quality of the data as the number of stillbirths deviate from the published official statistics. The authors in their online supplement report 539 stillbirths in 2009-10 decreasing to 489 in 2011-12. But according to the published official statistics the number of stillbirths were 260+255=515 in 2009-10 (2) decreasing to 274+236=510 in 2011-12 (3). Thus the seemingly dramatic decrease between the two time periods is reduced from 50 (=539-489) in the paper to 5 (=515-510) according to the official statistics. Even though we all hope for miracles, all too often they evaporate into thin air on closer inspection. I cannot see any other solutions to this conundrum than either the authors thoroughly document the validity of their data or they retract their paper.

    1) Hedegaard M, Lidegaard O, Skovlund CW, Morch LS, Hedegaard M. Reduction in stillbirths at term after new birth induction paradigm: results of a national intervention. BMJ Open. 2014 Aug 14;4(8)

    2) Sundhedsstyrelsen. Fodselsstatistikken 2011. Copenhagen, Sundhedsstyrelsen, 2012.

    3) Statens Serum Institut. Fodselsstatistikken - tal og analyser, 2012. Available at http://www.ssi.dk/~/media/Indhold/DK%20- %20dansk/Sundhedsdata%20og%20it/NSF/Registre/Fodselsregisteret/f%C3%B8dselsstatistikken2012_vers%204.ashx. Accessed September 8th.

    Conflict of Interest:

    None declared

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  9. Response: Assessing the effect of an interactive decision-aid smartphone smoking cessation application (app) on quit rates: a double-blind automated randomised control trial protocol

    Author have come out with an interesting concept of using smart phone app in medical research. Smart phones are rapidly becoming omnipresent with greater processing power and memory and now are commonly used as first device to access information from or off internet. Thousands of medical apps are available for layman to get information regarding diseases. Also, several apps are available to physicians to quickly asses information from guidelines, algorithms and medical formulas making pocket books redundant. Increasingly new app are being developed to provide diagnostics at nominal cost.

    I think this is the first serious attempt to use phone app in medical research, Authors have meticulously prepared protocol and though some provision like locking the device to one particular group may have got frown from some ethical committee members but I think that was essential to have valid randomization.

    In my personal view this is well planned study on a very important socio-medical problem. I shall be very eagerly waiting for the study results and how this concept per se is taken by medical fraternity.

    Dr. Sandeep Tak

    Conflict of Interest:

    None declared

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