Background Symptoms after Coronavirus Disease (COVID-19) infection affect the quality of life of its survivor especially to the special senses including olfactory function. It is important to prevent the disability at an earlier stage. Vaccination as key prevention has been proven to be effective in reducing symptomatic disease and severity. However, the effects of vaccination on post COVID symptoms have not been evaluated. This study aimed to evaluate the possible protection of full vaccination and the occurrence of post-COVID olfactory dysfunction, specifically anosmia, and hyposmia in patients who were diagnosed with COVID-19. Method A longitudinal analysis using the retrospective cohort of the Indonesian patient-based Post-COVID-19 survey collected from July 2021 until December 2021, involving COVID-19 Patients confirmed by Real-Time Polymerase Chain Reaction (RT-PCR) and/or Antigen test. Variables including demography, comorbidities, health behavior, type of vaccine, symptoms, and treatment were collected through an online questionnaire based on the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS). Participants were matched (1:1) using propensity matching score into two exposure statuses, infected 1)>14 days of full vaccination and 2)<14 days or incomplete or unvaccinated. The olfactory dysfunction was assessed two weeks and four weeks after negative conversion with PCR using a self-measured olfactory questionnaire (MOQ). The Generalized Estimating Equation (GEE) was performed to assess the effect of full vaccination on post-COVID-19 olfactory dysfunction. The Receiver Operating Characteristic determined the sensitivity and specificity of the cutoff value of the days from fully vaccinated to diagnosis and the olfactory dysfunction. Results A total of 442 participants were extracted from the cohort and inoculated with the inactivated viral vaccine (99.5%). The prevalence of olfactory dysfunction in two weeks was 9.95% and 5.43% after four weeks. Adjusted by other variables, people who were infected >14 days after being fully vaccinated had a 69% (adjusted Odds Ratio / aOR 0.31 95% CI 0.102-0.941) probability of developing olfactory dysfunction. Longer days of fully vaccinated to infection are associated with increased risk (aOR 1.012 95% CI 1.002-1.022 p-value 0.015). A cut-off of 88 days of full vaccination-to-diagnosis duration has Area Under Curve (AUC) of 0.693 (p=0.002), the sensitivity of 73.9%, and specificity of 63.3% in differentiating the olfactory dysfunction event in two weeks after COVID-19 with a crude odds ratio of 4.852 (95% CI 1.831-12.855 p=0.001) Conclusion After 14 days of full vaccination, the protective effect could reduce the chance of post-COVID olfactory dysfunction although a longer full vaccination-to-diagnosis duration increases the risk. It is important to consider a booster shot starting from 89 days after the last dose in those who received the inactivated viral regimen.

Introduction Post-COVID symptoms are the new concern in the COVID-19 pandemic, where recovered patients experience residual symptoms affecting their quality of life. Therefore, it is imperative to evaluate the role of complete vaccination, prescribed medication, and micronutrients during COVID episodes in the occurrence of post-COVID symptoms. Method A longitudinal evaluation of Indonesia’s recovered COVID-19 patients was performed using the data collected from July 2021 and extracted in mid-February 2022. All participants were confirmed with a Real-Time Polymerase Chain Reaction test (PCR) and/or antigen test. This study collected demography and comorbidities information, symptoms and treatment of COVID-19, and collection of self-reported post-COVID symptoms every 30 days within 90 days after diagnosis/onset. Exposures of interest include vaccination status, Favipiravir administration, Vitamin C, Vitamin D, and Zinc. A Generalized Estimating Equation (GEE) was used to evaluate the longitudinal effect of exposures, presented with adjusted odds ratios and its 95% confidence interval. Results A total of 923 participants (18.2% fully-vaccinated) were involved in the study, with 79.7% being non-hospitalized. Only 25.7% did not develop any residual symptoms within 90 days. Fatigue was the most reported post-COVID symptom in each measurement time (39.5%, 16.3%, and 7.3%). Full-vaccination was effective against chronic cough (aOR 0.527, 95% CI 0.286–0.971), chronic headache (aOR 0.317, 95% CI 0.163–0.616), and chronic arthritis (aOR 0.285, 95% CI 0.116–0.703). The combination of micronutrient supplementations and Favipiravir gave no significant effect on all post-COVID symptoms. However, early initiation of Favipiravir and delaying vitamin D administration were associated with arthritis. Conclusion Full vaccination of COVID-19 prevents the disease and the development of residual symptoms when infected with SARS-COV-2. Hence, it is crucial to reconsider the prescription of micronutrient supplementation or adjust the dose of Favipiravir in the current guideline.

PurposeThe Chulalongkorn-Hasanuddin Rifampicin-Resistant Tuberculosis Screening Tool (CUHAS-ROBUST) is an artificial intelligence–based (AI–based) application for rifampicin-resistant tuberculosis (RR-TB) screening. This study aims to elaborate on the drug-resistant TB (DR-TB) problem and the impact of CUHAS-ROBUST implementation on RR-TB screening.Design/methodology/approachA qualitative approach with content analysis was performed from September 2020 to October 2020. Medical staff from the primary care center were invited online for application trials and in-depth video call interviews. Transcripts were derived as a data source. An inductive thematic data saturation technique was conducted. Descriptive data of participants, user experience and the impact on the health service were summarizedFindingsA total of 33 participants were selected from eight major islands in Indonesia. The findings show that DR-TB is a new threat, and its diagnosis faces obstacles particularly prolonged waiting time and inevitable delayed treatment. Despite overcoming the RR-TB screening problems with fast prediction, the dubious screening performance, and the reliability of data collection for input parameters were the main concerns of CUHAS-ROBUST. Nevertheless, this application increases the confidence in decision-making, promotes medical procedure compliance, active surveillance and enhancing a low-cost screening approach.Originality/valueThe CUHAS-ROBUST achieved its purpose as a tool for clinical decision-making in RR-TB screening. Moreover, this study demonstrates AI roles in enhancing health-care quality and boost public health efforts against tuberculosis.