The Hindi Version of International Consensus Criteria: A Cross-cultural Adaptation and Validation Study for... 2023 Shah et al

Full title: The Hindi Version of International Consensus Criteria: A Cross-cultural Adaptation and Validation Study for Myalgic Encephalomyelitis in Post-COVID Patients

Abstract

Context: Fatigue is the most prominent feature of long COVID. With the increasing burden of long COVID cases post-acute phase of illness after recurrent waves of the pandemic, understanding its pathophysiology is of paramount importance. Such fatigue and post-viral illness could be associated with features of neuroimmune exhaustion and thus be a part of a larger syndrome such as myalgic encephalomyelitis (ME). Identifying the proportion of patients having ME from those experiencing fatigue would bring us one step closer to understanding the pathophysiology. International consensus criteria (ICC) originally published in English (ICC-E) is a valid and reliable tool for identifying cases of ME. However, a validated Hindi version of ICC-E is not available. : To develop and validate an equivalent version of ICC-E in the native Hindi language (ICC-H) to suit Indian patients and health care workers even at peripheries and to make conducting large scales surveys more feasible.

Subjects and methods: Once permission from the ethics board was granted, guidelines given by MAPI Research Trust were followed and ICC-H was developed from ICC-E, in the following steps: (a) translation to Hindi, (b) back translation, (c) comparison between the translated and back-translated version performed by experts, and (d) pre-pilot test in the intended population. The ICC-H was applied to 53 bilingual individuals knowing both Hindi and English.

Statistical analysis used: The distribution of Hindi and English questionnaires was analyzed using the Chi-square test and Spearman's correlation coefficient was used for correlation between answers of each question.

Results: The score of individual items and its global score was highly correlated with each other (p<0.001). The scores of individual components and global scores of ICC-H at baseline and original ICC-E after 4 weeks did not differ significantly.

Conclusion: This study shows that the ICC-H is a valid and reliable instrument for the assessment of ME. ICC-H can be used for Hindi speaking population for identifying cases of ME. Key Messages There is a significant overlap in symptoms of long COVID and ME, with fatigue being a major component in both. Understanding the prevalence of ME in the post-acute phase of COVID illness can bring us a step closer to understanding its pathophysiology. In a multilingual country like ours, regionally translated criteria are a must for conducting large-scale surveys.

Pubmed abstract, https://pubmed.ncbi.nlm.nih.gov/37355868/
PDF open access, https://japi.org/article/files/JAPI0090_p59-63_compressed.pdf

 

I don't consider the ICC all that great. It might be better than earlier criteria, but it is still flawed. Translating "unrefreshing sleep" in any language still gives the impression that it's a sleep disorder, rather than a symptom on its own that feels something like lack of sleep, but might be completely unrelated to sleep. English doesn't even have a clear medical definition for "fatigue", so how accurate will a translation be? I don't remember the precise definition of PEM, but I expect it's vague, since we don't really understand PEM, and it varies so much between individuals, so any translation is going to be vague too.

Link to a thread to discuss the ICC Diagnostic criteria here:
Is the International Consensus Criteria (ICC) "valid and reliable"?


The authors of this paper might have been better off to use the ICC as a starting point for discussion among Indian practitioners and researchers to come up with their own criteria in their own language (or multiple languages and dialects). Maybe a different language would provide better words for describing ME symptoms. A project for describing ME symptoms in different languages (and traditions?) might be quite useful. This might be a good application for AI: let the AI question PWME in their own language, and then maybe ask the questions again translated from different languages, and let the people rate which wording they feel best describes the symptoms. Surely there's something less misleading than "unrefreshing sleep".

 

Right, they set out to directly translate a weak/flawed criteria while claiming that it's "valid and reliable". I agree that it's better than nothing, but it misses an opportunity to improve it by asking for input from different perspectives (language, culture, experience). Hindi might have better words to describe the symptoms. While I personally don't believe in the validity of the basis of Ayurvedic medicine, its practitioners may have different perceptions about signs of symptoms, including different words to describe them. Maybe they have multiple different words describing different types of "fatigue". Language affects perceptions of concepts. Imagine a questionnaire that asks you to rate your fatigue. Change that word to "tiredness" and you might get different responses. If instead of one word, you had a list including lethargy, lack of energy, listlessness, sleepy, and other such words, you'd get a quite different dataset. Switch that into words or terms in different languages and the datasets would again be different. By forcing only one word, such as "fatigue", you're losing a lot of potentially useful data, and forcing an outcome. I don't even consider "fatigue" to apply to ME; I think ME has a "fatigue-like symptom", and all the knowledge about "fatigue" doesn't necessarily apply. Does caffeine reduce ME's "fatigue"? Does fitness improving exercise reduce that "fatigue"? No? Then maybe it's a bad choice of word, and translating it as accurately as possible doesn't make it any better.

Cohort selection does need consistency. I think the ICC is too vague or loose to provide adequate consistency. Claiming that it's "valid and reliable" gives false impressions about how consistent the study results will be.

I just think it's a missed opportunity. The I(ndian)CC, based on their own language and culture, might have been superior.

 

They weren't asked to come up with a hopefully better criteria based on their perspective; they were asked to accurately translate the ICC, with its English based limitations and biases. I just feel that it was a missed opportunity for improvement. Oh well, it's looking like it might not be that many years before AI will take over creating criteria for cohort selection, and doing a better job of it.

 

I think my main complaint is that the ICC is being presented as more "valid and reliable" than it is. I think if there was a statement along the lines of "We're doing this for consistency with the rest of the world, even though it is quite flawed and doesn't result in consistent study results.", I wouldn't have objections.