[Characteristics of Adverse events of Dietary Supplements Provided byMedical Professionals and their Application in Causality Evaluation Algorithm]

Shokuhin Eiseigaku Zasshi. 2023;64(1):13-20. doi: 10.3358/shokueishi.64.13.
[Article in Japanese]

Abstract

This study aimed to characterize the adverse events of dietary supplements provided by medical professionals and to examine whether there are challenges when applying each case to the causality evaluation algorithm. Data from 290 individual cases collected by the Tokyo Metropolitan Government in cooperation with the Tokyo Medical Association and Tokyo Pharmaceutical Association were analyzed. The causality evaluation algorithm that was used in this study was reported previously. Female patients accounted for 73% of those who experienced adverse events. Both male and female patients who had adverse events were in their 60s and 70s. Many of the participants had underlying diseases and aimed to improve their medical conditions. Furthermore, skin symptoms were the most common. Many of the supplements were made from natural substances, with an average of 7.7 ingredients in each product. More than half of the products were used for less than one month. In most cases, symptoms improved after discontinuation of the products or after the administration of medications. When each event was applied to the causality assessment algorithm, it was necessary to understand the information as follows: in cases of product discontinuation with simultaneous medications recovery was not concluding the product discontinuation, and the physician's judgement should be place as objective evidence. The algorithm was successfully applicable to cases provided by medical professionals and the evaluated results for all cases were 30% possible and 62% highly possible. The evaluated results indicate the relationship between products/ingredients and the symptom, and by adding information on the symptom and its severity, it is possible to clarify the phenomenon to be noted.

Keywords: adverse events; causality evaluation algorithm; dietary supplements;; health foods; medical professionals.

Publication types

  • English Abstract

MeSH terms

  • Algorithms*
  • Dietary Supplements*
  • Female
  • Humans
  • Male
  • Tokyo