"Brain fog" is a symptom of long COVID. Brain fog is suspected to be a neurocognitive dysfunction; however, the underlying pathology remains to be elucidated. To provide better medical care for patients with "brain fog", we collaborated with a hospital outpatient department that specializes in the assessment and treatment of cognitive impairment. For the establishment of the collaborative system, we devised a questionnaire for "brain fog" based on medical reports, internet resources, and clinical experiments to be used as a screening tool. The questionnaire was used to calculate a "brain fog score" (BFS). A BFS of more than 5 points was established as the criterion for patient referral. The present retrospective evaluation suggests that BFS is useful for predicting prognosis and prioritizing patients within limited outpatient appointment slots.

Fatigue is a common symptom of long COVID. Fatigue can majorly disrupt daily life and be challenging to treat. Herein, we describe the effect of saikokeishito, a Kampo medicine, on fatigue in patients with long COVID.Between October 2020 and March 2023, we prescribed saikokeishito to 22 patients with long COVID in the general medicine outpatient department of our hospital. Among them, seven patients (age: 15-58 years, two females) had fatigue, a previously confirmed diagnosis of COVID-19, and no concomitant use of other Kampo formulas. We compared their condition at the start of saikokeishito administration to that 3 months later. Five patients had a slight fever, and four had inflammatory findings on blood tests. Within 3 months, all patients had a 20% or greater reduction in fatigue on a visual analogue scale. Six patients had a 20% or greater increase in health-related QOL and were able to return to society. On the other hand, one patient required a transition to an alternative medication, and one patient's follow-up was prematurely discontinued. Fatigue after COVID-19 may be improved by saikokeishito, especially for the treatment of patients with slight fever or inflammatory findings.

Prolonged cough in coronavirus disease 2019 (COVID-19) is not only uncomfortable for patients, but also prolongs the length of stay in an isolation facility. This results in delays in patients' return to their daily life. Therefore, the prompt treatment of cough is important. In this report, we used Japanese traditional (Kampo) medicine, chikujountanto for the treatment of cases with residual cough, airway secretions, slight fever, anxiety, and insomnia, several days after the onset of coronavirus. From October 2020 to September 2021, we prescribed chikujountanto for thirty-three COVID-19 patients with prolonged cough in an isolation facility. Seven patients (6 women and 1 man with ages ranging 37-70 years) were treated with no other medication. Comorbid symptoms included slight fever, sputum, sore throat, nasal discharge, headache, anxiety/insomnia, and taste/olfactory disorders. The start date of treatment ranged from 9 to 21 days after the onset of COVID-19, and the time until cough and comorbid symptoms improved to values less than NRS 2 or less, was 2 to 6 days after treatment. Three patients had persistent cough and needed to switch to other medication. In COVID-19, chikujountanto may be useful for coughing during the period when the peak of the viral proliferative phase has passed but airway inflammation is still present.

Some simulation-based education tools have been introduced in Kampo medicine. However, there are only a few brief simulation tools to learn qi-blood-fluid (QBF) patterns of traditional Chinese medicine (TCM). In this study, we developed a self-diagnostic questionnaire that allows students learn TCM interviews and QBF patterns by answering the questionnaire and evaluated its reliability and validity. We extracted questionnaire items to classify six QBF patterns (qi deficiency, blood deficiency, yin deficiency, qi stagnation, blood stasis, and phlegm-fluid retention) based on some textbooks of TCM and Kampo medicine. Then we developed an initial questionnaire comprising 35 items. Fifth year medical students at Tohoku University School of Medicine answered the questionnaire of small group teaching during 2017-2020. We evaluated the accuracy of the questionnaire if compared with the diagnosis of academic supervisors. To improve the accuracy, we adjusted the questionnaire’s thresholds and created a predictive model of the patterns using logistic regression analysis. The questionnaire’s sensitivity improved by adjusting the thresholds. Logistic regression analysis resulted in a predictive model that could determine QBF patterns with the same level of accuracy as the original for 20 items overall. The results suggest that the use of a simple questionnaire with ensured accuracy may contribute to better pre-graduate education by making it easier for students to understand their own Kampo medicine patterns.