Social impact of brain fog and analysis of risk factors: Long COVID in Japanese population.

OBJECTIVE: To reveal the clinical features and assess risk factors linked to brain fog and its societal implications, including labor productivity, providing valuable insights for the future care of individuals who have experienced coronavirus disease 2019 (COVID-19). METHODS: We analyzed a comprehensive cohort dataset comprising 1,009 patients with COVID-19 admitted to Japanese hospitals. To assess brain fog, we analyzed patients who responded to a questionnaire indicating symptoms such as memory impairment and poor concentration. RESULTS: The prevalence of brain fog symptoms decreased 3 months posthospitalization but remained stable up to 12 months. Neurological symptoms such as taste and smell disorders and numbness at hospitalization correlated with a higher frequency of identifying brain fog as a long COVID manifestation. Our findings indicated that advanced age, female sex, a high body mass index, oxygen required during hospitalization, chronic obstructive pulmonary disease, asthma, and elevated C-reactive protein and elevated D-dimer levels were risk factors in patients exhibiting brain fog. Additionally, we demonstrated the negative impact of brain fog on labor productivity by presenteeism scores. INTERPRETATIONS: This study clarified the clinical characteristics of patients experiencing brain fog as a long COVID manifestation, specifically emphasizing neurological symptoms during hospitalization and their correlation with brain fog. Additionally, the study identified associated risk factors for its onset and revealed that the emergence of brain fog was linked to a decline in labor productivity.

Clinical utility of the Oncomine Dx Target Test multi-CDx system and the possibility of utilizing those original sequence data.

BACKGROUND: Companion diagnostic tests play a crucial role in guiding treatment decisions for patients with non-small cell lung cancer (NSCLC). The Oncomine Dx Target Test (ODxTT) Multi-CDx System has emerged as a prominent companion diagnostic method. However, its efficacy in detecting driver gene mutations, particularly rare mutations, warrants investigation. AIMS: This study aimed to assess the performance of the ODxTT in detecting driver gene mutations in NSCLC patients. Specifically, we aimed to evaluate its sensitivity in detecting epidermal growth factor receptor (EGFR) mutations, a key determinant of treatment selection in NSCLC. MATERIALS AND METHODS: We conducted a retrospective analysis of NSCLC patients who underwent testing with the ODxTT at Keio University Hospital between May 2020 and March 2022. Patient samples were subjected to both DNA and RNA tests. Driver gene mutation status was assessed, and instances of missed mutations were meticulously examined. RESULTS: Of the 90 patients, five had nucleic acid quality problems, while 85 underwent both DNA and RNA tests. Driver gene mutations were detected in 56/90 (62.2%) patients. Of the 34 patient specimens, driver mutations were not detected using the ODxTT; however, epidermal growth factor receptor (EGFR) mutations were detected using polymerase chain reaction-based testing in two patients, and a KRAS mutation was detected by careful examination of the sequence data obtained using the ODxTT in one patient. For the above three cases, carefully examining the gene sequence information obtained using the ODxTT could identify driver mutations that were not mentioned in the returned test results. Additionally, we confirmed comparable instances of overlook results for EGFR mutations in the dataset from South Korea, implying that this type of oversight could occur in other countries using the ODxTT. EGFR mutation was missed in ODxTT in Japan (6.3%, 2/32), South Korea (2.0%, 1/49), and overall (3.7%, 3/81). CONCLUSION: Even if sufficient tumor samples are obtained, rare EGFR mutations (which are excluded from the ODxTT's genetic mutation list) might not be detected using the current ODxTT system due to the program used for sequence analysis. However, such rare EGFR mutations can still be accurately detected on ODxTT's sequence data using next-generation sequencing.