The machine learning model based on trajectory analysis of ribonucleic acid test results predicts the necessity of quarantine in recurrently positive patients with SARS-CoV-2 infection.

Background: SARS-CoV-2 patients re-experiencing positive nucleic acid test results after recovery is a concerning phenomenon. Current pandemic prevention strategy demands the quarantine of all recurrently positive patients. This study provided evidence on whether quarantine is required in those patients, and predictive algorithms to detect subjects with infectious possibility. Methods: This observational study recruited recurrently positive patients who were admitted to our shelter hospital between May 12 and June 10, 2022. The demographic and epidemiologic data was collected, and nucleic acid tests were performed daily. virus isolation was done in randomly selected cases. The group-based trajectory model was developed based on the cycle threshold (Ct) value variations. Machine learning models were validated for prediction accuracy. Results: Among the 494 subjects, 72.04% were asymptomatic, and 23.08% had a Ct value under 30 at recurrence. Two trajectories were identified with either rapid (92.24%) or delayed (7.76%) recovery of Ct values. The latter had significantly higher incidence of comorbidities; lower Ct value at recurrence; more persistent cough; and more frequently reported close contacts infection compared with those recovered rapidly. However, negative virus isolation was reported in all selected samples. Our predictive model can efficiently discriminate those with delayed Ct value recovery and infectious potentials. Conclusion: Quarantine seems to be unnecessary for the majority of re-positive patients who may have low transmission risks. Our predictive algorithm can screen out the suspiciously infectious individuals for quarantine. These findings may assist the enaction of SARS-CoV-2 pandemic prevention strategies regarding recurrently positive patients in the future.

Can the nucleic acid Ct value of discharged patients infected with SARS-CoV-2 Omicron variant be 35?--A retrospective study on fluctuation of nucleic acid Ct values in SNIEC mobile cabin hospital.

Objective: To explore the meaning of cycle threshold (Ct) value fluctuation and the appropriateness of setting the discharge Ct value to 35, which is the current standard in Chinese guidelines. Method: A retrospective study was conducted on 95 patients with Ct value fluctuation (Ct value below 35 on day 3; group A) and 97 patients with a normal discharge process (control; group B). Their clinical characteristics and follow-up data were collected. Results: (1) There was no significant difference between the groups in age, gender distribution, number of vaccinations, initial ORF-Ct value, and initial N-Ct value. The proportion of patients complicated with chronic internal disorders, respiratory symptoms, and abnormal chest radiology in group A was significantly higher than that in group B. (2) Between the two groups, there was no significant difference in the ORF-Ct or N-Ct value on day 1, but the ORF-Ct and N-Ct values of group B on days 2 to 4 were significantly higher than those of group A. (3) There was no significant difference between the groups in the ORF-Ct value at discharge, but there was a significant difference in the N-Ct value at discharge. Seven days after discharge, almost 100% of the patients had been cured. The mean negative conversion interval of nucleic acid of the patients in group A was 14.5 ± 4.6 days, which was longer than that of the patients in group B (11.8 ± 4 days). (4) Logistic regression analysis showed that the ORF-Ct value on day 2 was the key factor influencing the Ct value fluctuation. Conclusion: The fluctuation of Ct value is only a normal phenomenon in the recovery period of the disease, and there is no need for excessive intervention. It is reasonable to set the Ct value of the discharge standard to 35 and retest the nucleic acid on the 10th day after discharge for patients with underlying diseases or symptoms.

The machine learning model based on trajectory analysis of ribonucleic acid test results predicts the necessity of quarantine in recurrently positive patients with SARS-CoV-2 infection

Background SARS-CoV-2 patients re-experiencing positive nucleic acid test results after recovery is a concerning phenomenon. Current pandemic prevention strategy demands the quarantine of all recurrently positive patients. This study provided evidence on whether quarantine is required in those patients, and predictive algorithms to detect subjects with infectious possibility. Methods This observational study recruited recurrently positive patients who were admitted to our shelter hospital between May 12 and June 10, 2022. The demographic and epidemiologic data was collected, and nucleic acid tests were performed daily. virus isolation was done in randomly selected cases. The group-based trajectory model was developed based on the cycle threshold (Ct) value variations. Machine learning models were validated for prediction accuracy. Results Among the 494 subjects, 72.04% were asymptomatic, and 23.08% had a Ct value under 30 at recurrence. Two trajectories were identified with either rapid (92.24%) or delayed (7.76%) recovery of Ct values. The latter had significantly higher incidence of comorbidities;lower Ct value at recurrence;more persistent cough;and more frequently reported close contacts infection compared with those recovered rapidly. However, negative virus isolation was reported in all selected samples. Our predictive model can efficiently discriminate those with delayed Ct value recovery and infectious potentials. Conclusion Quarantine seems to be unnecessary for the majority of re-positive patients who may have low transmission risks. Our predictive algorithm can screen out the suspiciously infectious individuals for quarantine. These findings may assist the enaction of SARS-CoV-2 pandemic prevention strategies regarding recurrently positive patients in the future.

Vaccination, symptomatic infection and negative conversion of viral RNA by body mass index, diabetes, and age: An observational study.

BACKGROUND: The associations of doses of vaccine received with symptomatic infection with SARS-CoV-2 and negative conversion rate of viral RNA by BMI, diabetes, and age are unclear. METHODS: Included were adult cases of SARS-CoV-2 infection hospitalized at a makeshift hospital in Shanghai (N = 38,592). Each case received a real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test every day until discharge. Symptomatic cases had ≥1 pre-specified symptoms. Negative conversion time (NCT) was the duration between the specimen collection date associated with the first positive RT-PCR test and the first test date of the two consecutive negative tests at least 24 h apart. BMI-, diabetes- and age-stratified multivariable logistic and Poisson regressions were applied. FINDINGS: Coexistence of overweight/obesity and diabetes was associated with a higher risk of symptomatic infection and a longer NCT compared with coexistence of normal weight and without diabetes, but this association was primarily attributed to underlying comorbidities. Compared with absence of vaccination, booster vaccination, but not full vaccination, was consistently associated with a 42 %-56 % lower odds of symptomatic infection and ∼1.6-1.8 days of shorter NCT across different strata separately for weight and diabetes. Age-stratified analyses found that the effectiveness of booster vaccination did not attenuate with age, except for preventing symptomatic infection among adults with diabetes. INTERPRETATION: BMI and diabetes co-determined their associations with symptomatic infection and NCT. Booster vaccination but not full vaccination was associated a lower risk of symptomatic infection, a shorter NCT or both regardless of BMI, diabetes status and age.

Keeping Things Normal During an Uncommon Time: A Lesson from National Taiwan University

The COVID-19 pandemic impacts the learning and teaching experiences of faculty, students, and school staff in all levels of education around the world. While most schools face the challenges of closing down campuses, moving courses online, and relying on technology tools to deliver instructional activities, as one of the few countries with a regular semester schedule, universities in Taiwan have different experiences handling the current situation. This reflective essay aims to share our experiences and learned lessons at National Taiwan University (NTU) about keeping everything going commonly during the uncommon time. This essay will focus on the countermeasures the Center of Teaching and Learning Development (CTLD) and Digital Learning Center (DLC) at NTU had taken on in responding to the change versus unchanged environment. The pandemic impact were discussed from the interrelationships of the university policy, course, and instructor. And our reflections provide five suggestions regarding future precautions to other educational institutions.