eLetters

1224 e-Letters

  • Methotrexate in erythema nodosum leprosum (MaPs in ENL)

    We read with interest the MaPs in ENL study protocol (de Barros et al, BMJ open 2020).[1] The availability of an alternative drug for cases of chronic or recurrent type 2 lepra reaction with steroid toxicity or unresponsiveness is the need of the hour and although drugs like thalidomide, cyclosporine etc. are prescribed in such patients but cost, adverse effect or non-availability are the major deterrents in their use. The researchers must be complimented for their bold decision to choose methotrexate based only on case reports or a short series of patients (15 patients in total were given methotrexate for type 2 reactions).[2] This is a well-designed protocol aimed at possibly adding another drug to our therapeutic armamentarium for the crippling erythema nodosum leprosum (ENL) reactions. If found useful, methotrexate has the advantage of being a cheap, easy to administer and readily available drug.

    The study proposes to randomize patients with acute, chronic or recurrent ENL into two groups, receiving 20 weeks of prednisolone with either 48 weeks of methotrexate or placebo. While use of methotrexate is justified in patients with chronic and recurrent ENL, , same might not be applicable to cases of acute ENL. Acute ENL, by definition, is an episode that lasts lesser than 24 weeks,[3] as has been defined in the study protocol as well. Most of these cases with acute episode respond well to corticosteroids, clinical response has been observed as early as in 2 week...

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  • Comparing outcomes between ethnic groups - the limitations of body mass index.

    Dear Editor,
    Apea VJ et al. should be congratulated on elucidating the interplay between overlapping factors that influence patient outcomes from COVID-19. From the first reports about this disease, observers have noted that adipose tissue, perhaps through its association with diabetes and heart disease, has been linked to the severity of presentation and to subsequent clinical course. In studying a cosmopolitan patient population in a single large centre, the authors have cleverly eliminated many confounding factors and allowed the influence of ethnicity, per se, to be assessed.
    In this context though, the use of body mass index as a measure of obesity may be too blunt a discriminator. While a BMI of 30 kg/m2 is conventionally taken to define obesity, this measure has significant limitations.2,3 The most obvious is that it does not actually measure lean versus fatty tissue.3 More particularly, the BMI or Quetelet index threshold of 30 kg/m2 may be insensitive to the presence of obesity in those of Asian origin.4 Other authors have shown that the cut off in Asians may be optimally set at a lower level (e.g. 27 kg/m2 for men, and as low as 25 kg/m2 for women).5 We wonder, were Apea VJ et al.’s observations re-examined using such thresholds, if the poor outcomes seem in Asian patients would be more fully accounted for?
    We would welcome their views on this question. As the world’s most populous countries are in Asia, and the...

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  • Antibiotics save admissions and lives.

    Goodness who would have thought it, antibiotics can save admissions and probably lives. After years of vilifying GP's for high antibiotic prescribing we now know the truth. Appropriate prescribers are probably those more accessible with higher consultation rates and higher prescribing rates. Some times the better GP's aren't always those that do as they are told.

  • Response to comment of Aleksandar Ćirković and rebuttal of the suggestion of additional limitations

    This is a response to a comment on the paper dated 20 January 2021.

    Dear Dr. Ćirković,

    We thank Ćirković for welcoming our study. Before answering the points raised by Ćirković I first mention a currently-under-peer-review scientific communication between myself and the editor of the journal which published the article authored by Ćirković, that he cites in his comment [1]. The full text of this Letter to the Editor has been available as a preprint in the public domain since 18 Dec 2021 [2].

    - I address below the points raised by Ćirković on his comment on our BMJ Open paper in turn:

    1. TRIPOD and PROBAST checklists - searching the clinical literature using PubMed and Google Scholar identifies no studies that have used these checklists in the evaluation of vignettes studies or studies of symptom assessment applications. We reviewed the literature on symptom assessment app in our paper, and I have looked again at each of these papers, and none of them used the TRIPOD or the PROBAST checklist, nor did a recent paper in this domain from an independent academic group [3], nor did Ćirković himself in [1]. The TRIPOD checklist (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) is designed for studies into diagnostic and prognostic models for clinicians, and although an interesting suggestion, the use of such a checklist is not compulsory and not having adopted it is not a study limitation in itself. The P...

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  • Five missing limitations to this evaulation

    The study is a welcome addition to the yet sparse database of evaluations of self-diagnosis tools that, unlike expert systems, are to be put into patients’ hands directly. However, there are some limitations missing in the Discussions section that I’d like to add. Firstly, as these self-diagnosis tools can have a significant impact on public health [1], it will be crucial for regulating authorities and lawmakers to create a framework that correctly distributes the liabilities on the participants in the system and ensures a positive ratio of benefit vs risk; this will only be possible if there is enough robust information available on the respective systems/programs/apps to thoroughly assess them. As this novel field is just unfolding, there are plenty of obstacles on the way to a truly objective assessment of AI-driven software, as Nagendran et al recently demonstrated here in the BMJ. [2] They used, among others, the TRIPOD and PROBAST checklists for evaluating the validities of respective studies. A quick check on this study with both would give a result of a TRIPOD adherence of 18 of 24 relevant checklist items and a high risk of bias when using the PROBAST checklist. The release of an updated TRIPOD checklist with a focus on AI-driven software has also been announced and will then be relevant for the evaluation of this study. [3] Thus, incomplete adherence to the present and unknown adherence to the presumably relevant future TRIPOD statements and a high risk of bias a...

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  • Response to comment of Oscar Garcia-Esquirol and rebuttal of the suggestion of study bias.

    This is a response to a comment on the paper dated 7 January 2021.

    Dear Oscar Garcia-Esquirol, Cofounder and Chief Medical Director at Mediktor, one of the symptom checkers evaluated in the study,

    Thank you for your comment on this paper.

    Your letter addressed strong criticism at the paper [1] with respect to bias. I will answer these points in turn below. Our study included a rigorous design process conducted by experienced clinical researchers, data scientists and health policy experts, with the methodology and analysis peer-reviewed by independent and experienced primary care physicians and medical informatics experts at universities in the UK, and in Brown University in the US. To ensure a fair comparison, our team used a large number of clinical vignettes, which were generated from a mix of real patient experiences gleaned from the UK’s NHS 111 telephone triage service and from those generated from the many years’ combined experience of the research team. The gold-standard triage level used in the study was set independently of vignette creation, vignette review and vignette diagnosis gold-standard setting - this was done by a separate panel of three experienced primary care practitioners using a tie-breaker panel method based on the matching process set out by [2].

    A strength of this paper is that it not only compares a range of symptom assessment apps to each other, but also compares their performances to that of practicing GPs. While the...

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  • Approaches for assessing agreement in continuous measurements in a multi-observer setup, comment on “Retrospective comparison of approaches to evaluating inter-observer variability in CT tumour measurements in an academic health centre”

    We read with interest the article by Woo and colleagues, evaluating sensitivity of statistical methods for detecting different levels of interobserver variability in CT measurements of cancer lesions [1]. It is increasingly recognized that in order to evaluate the efficacy of medical imaging there is a need to conduct multi-observer studies in which proper statistical analysis is a critical component [2]. Thus, the study by Woo et al. is a welcome addition to the literature, and the authors are commended for providing open access to data.
    The authors supplemented an observed dataset based on the diameters of 10 CT lesions measured by 13 observers by generating two additional datasets of increased and decreased measurement variability, respectively.
    These three datasets were used to compare three statistical approaches 1) intraclass correlation coefficient (ICC), and what the authors refer to as 2) outlier counts (score) from standard Bland-Altman plotting with limits of agreement, and 3) outlier score from Bland-Altman plotting with fixed limits of agreement.

    We have a few comments.

    We ardently agree with the authors that although the widely used ICC accommodates a multi-observer setup, it is not an ideal method for evaluating interobserver variability; the ICC reveals little about the degree of discrepancy nor supply information to investigate whether the variability may change with the magnitude of measurements (e.g. to reveal that the diameter...

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  • Lack of scientific rigour

    I read with great interest the article “How accurate are digital symptom assessment apps for suggesting conditions and urgency advice? A clinical vignettes comparison to GPs”
    published by Gilbert S. Mehl A, and Baluch A. et al. It evaluated the effectiveness of eight symptom checkers – including Mediktor, of which I am part.

    While I wholeheartedly agree with the statement the study researchers make, citing Chambers D et al. that “rigorous studies are required to show that these apps provide safe and reliable information,” I believe this article is a far cry from being such a rigorous study. I consider it to be little more than an advertising campaign by ADA, since the study falls prey to multiple biases, which I will describe below. These biases invalidate the article as a scientific publication.

    If we examine the foundations upon which the study rests, we can classify these biases thus:

    1) Biases due to the study variables:

    By creating vignettes that simulate clinical cases, a bias is created in the observational conditions of the study variables (SV). The diagnostic accuracy of symptom checkers (SC), created to assess patients in real conditions, are evaluated under artificial conditions. This further violates the nature of the measurement since they are simulated cases created by staff with a direct relationship to ADA, one of the symptom checkers analysed in the study.
    When comparing the SCs’ capability to perform triage, the re...

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  • Risk of 1-year mortality in hospitalised elderly patients with community-acquired pneumonia

    Luo et al. conducted a cohort study to evaluate the effect of frailty on subsequent mortality in hospitalized elderly patients with community-acquired pneumonia (CAP) (1). The adjusted hazard ratio (HR) (95% confidence interval [CI]) of frail patients with community-acquired pneumonia (CAP) for 1-year mortality was 2.70 (1.69 to 4.39), and the adjusted HR (95% CI) of frail patients with severe CAP for 1-year mortality was 2.87 (1.58 to 4.96). In contrast, there was no significant association between frailty and subsequent 30-day mortality. I have a comment about their study.

    Ma et al. also investigated factors affecting 1-year mortality in older hospitalized patients with CAP (2). The adjusted HRs (95% CIs) of male sex, severe under-nutrition, frailty, and readmission for CAP were 1.57 (1.02 to 2.48), 3.75 (1.66 to 8.46), 2.36 (1.29 to 4.27) and 4.50 (2.82 to 7.17), respectively. Recurrent pneumonia was a major risk factor of 1-year mortality, and they recommended advance care planning to improve prognosis in patients with CAP. I think that recurrent pneumonia might be related to progression of frailty and quality of life might become worse. In the era of COVID-19, caution should also be paid for preventing CAP in older inhabitants with frailty.

    References
    1. Luo J, Tang W, Sun Y, Jiang C. Impact of frailty on 30-day and 1-year mortality in hospitalised elderly patients with community-acquired pneumonia: a prospective observational study. BMJ Open. 2020...

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  • Overweight/Obesity (OW/OB) among Ethiopian women—Associated with what else beyond their use of combination oral contraceptives?

    I appreciate the recent analysis of the 2016 Ethiopia Demographic and Health Survey (Endalifer ML et al.), but the article provokes several questions. The authors expressed concern that OB leads to metabolic disorder, including adverse outcomes for neonates and mothers. Knowing that the prevalence of OW/OB was quite low (8.6%), I am eager to learn what fraction of those OW/OB women might have been actually “OB”, that is, BMI ≥30 kg/m2. And how many of the women were found to be underweight, a condition that may lead to adverse outcomes as well?

    It appears that parity was not considered as a factor contributing to OW/OB. Another report based on the same 2016 survey surprisingly failed to find that parity was an independent determinant of OW/OB among Ethiopian women (Yeshaw Y et al. BMJ Open 2020;10: e034963). However, the international literature has elsewhere reported that mothers’ body weight on average is greater as parity rises (Gunderson EP et al. Int J Obes Relat Disord 2004;28:525-35; Koch E et al. J Epidemiol Community Health 2008;62:461-70; and Huayanay-Espinoza CA et al. Prev Chronic Dis 2017;14:E102).

    The literature also has reported that women’s weight is objectively increased or perceived to be increased in association with the use of progestin-based contraceptives (Dal'Ava N et al. Contraception 2012;86:350-3; Vickery Z et al. Contraception 2013;88:503-08; and Nault AM et al. Am J Obstet Gynecol 2013;208:48 e1-6). The surveyed...

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