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.

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.

The effects of hypertension on the prognosis of coronavirus disease 2019: a systematic review and meta-analysis on the interactions with age and antihypertensive treatment.

BACKGROUND: Hypertension and angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs) have been reported to be associated with the prognosis of COVID-19, but the findings remain controversial. Here, we conducted a systematic review to summarize the current evidence. METHODS: We retrieved all the studies by MEDLINE via PubMed, CENTRAL, and Embase using the MeSH terms until 30 April 2021. A fixed or random effect model was applied to calculate pooled adjusted odds ratio (AOR) with 95% confidence interval (CI). Interactive analysis was performed to identify the interaction effect of hypertension and age on in-hospital mortality. RESULTS: In total, 86 articles with 18 775 387 COVID-19 patients from 18 countries were included in this study. The pooled analysis showed that the COVID-19 patients with hypertension had increased risks of in-hospital mortality and other adverse outcomes, compared with those without hypertension, with an AOR (95% CI) of 1.36 (1.28-1.45) and 1.32 (1.24-1.41), respectively. The results were mostly repeated in countries with more than three independent studies. Furthermore, the effect of hypertension on in-hospital mortality is more evident in younger and older COVID-19 patients than in 60-69-year-old patients. ACEI/ARBs did not significantly affect the mortality and adverse outcomes of COVID-19 patients, compared with those receiving other antihypertensive treatments. CONCLUSION: Hypertension is significantly associated with an increased risk of in-hospital mortality and adverse outcomes in COVID-19. The effect of hypertension on in-hospital mortality among consecutive age groups followed a U-shaped curve. ACEI/ARB treatments do not increase in-hospital mortality and other poor outcomes of COVID-19 patients with hypertension.

Clinical outcomes of COVID-19 patients with rheumatic diseases: a retrospective cohort study and synthesis analysis in Wuhan, China.

BACKGROUND: The clinical outcomes of patients with rheumatic diseases infected with COVID-19 were inconsistent characteristics across regions and time periods. We need to revisit and sort out the clinical characteristics of these patients at the beginning of the global COVID-19 epidemic. METHODS: We collected data from confirmed COVID-19 patients from two military-run field hospitals and classified them into the rheumatic disease group and no rheumatic disease groups, and the latter was further distinguished by ARD and non-ARD. We compared the primary outcome, which we defined as mortality, and the secondary outcome, which we defined as the ICU occupancy rate, the duration of hospitalization and the duration of viral clearance, between the patients with and without rheumatic diseases after PSM. A study-level meta-analysis of four studies was conducted on the mortality of the COVID-19 patients with and without rheumatic diseases. RESULTS: A total of 4353 COVID-19 patients were included in our cohort study; 91 had rheumatic diseases. The mean age of the entire cohort was 59.37, and 2281 (52.40%) patients were female. The mortalities after PSM were 1.11% and 3.46% in the rheumatic diseases and no rheumatic disease groups, respectively. The ICU occupancy rates after PSM were 2.22% and 4.61% in the rheumatic diseases and no rheumatic disease groups. The duration of hospitalization and viral clearance in the rheumatic disease group were 15.97 and 43.69, respectively; moreover, the same parameters in the no rheumatic diseases after PSM were 15.48 and 45.48. No significant differences were found in either the primary or secondary outcomes. After excluding the gout cases, the results were still similar. However, there was a significant difference between the two groups upon meta-analysis (RR = 1.70, 95% CI 1.35-2.13). CONCLUSIONS: Rheumatic diseases seemed to aggravate the course of COVID-19 infection. However, the poor outcomes of COVID-19 seemed to be unassociated with rheumatic diseases undergoing an adequate medical intervention. KEY POINTS: • We compared the outcomes and prognosis of COVID-19 patients in China at the beginning of the outbreak regarding the presence or absence of rheumatic disease patients and made some meaningful conclusions for future outbreaks of similar infectious diseases. • We compared similar recent studies from other countries and explored the changes and differences in patient outcomes associated with COVID-19 as it continued to spread worldwide during the year, providing clinical evidence to further explore the role rheumatic diseases play in COVID-19 patient outcomes. • We provided evidence for the treatment of relevant patients and made rationalized recommendations for treatment strategy.

Calcium channel blockers improve prognosis of patients with coronavirus disease 2019 and hypertension.

BACKGROUND: Hypertension is considered an important risk factor for the coronavirus disease 2019 (COVID-19). The commonly anti-hypertensive drugs are the renin-angiotensin-aldosterone system (RAAS) inhibitors, calcium channel blockers (CCBs), and beta-blockers. The association between commonly used anti-hypertensive medications and the clinical outcome of COVID-19 patients with hypertension has not been well studied. METHODS: We conducted a retrospective cohort study that included all patients admitted with COVID-19 to Huo Shen Shan Hospital and Guanggu District of the Maternal and Child Health Hospital of Hubei Province, Wuhan, China. Clinical and laboratory characteristics were extracted from electronic medical records. Hypertension and anti-hypertensive treatment were confirmed by medical history and clinical records. The primary clinical endpoint was all-cause mortality. Secondary endpoints included the rates of patients in common wards transferred to the intensive care unit and hospital stay duration. Logistic regression was used to explore the risk factors associated with mortality and prognosis. Propensity score matching was used to balance the confounders between different anti-hypertensive treatments. Kaplan-Meier curves were used to compare the cumulative recovery rate. Log-rank tests were performed to test for differences in Kaplan-Meier curves between different groups. RESULTS: Among 4569 hospitalized patients with COVID-19, 31.7% (1449/4569) had a history of hypertension. There were significant differences in mortality rates between hypertensive patients with CCBs (7/359) and those without (21/359) (1.95% vs. 5.85%, risk ratio [RR]: 0.32, 95% confidence interval [CI]: 0.13-0.76, χ2 = 7.61, P = 0.0058). After matching for confounders, the mortality rates were similar between the RAAS inhibitor (4/236) and non-RAAS inhibitor (9/236) cohorts (1.69% vs. 3.81%, RR: 0.43, 95% CI: 0.13-1.43, χ2 = 1.98, P = 0.1596). Hypertensive patients with beta-blockers (13/340) showed no statistical difference in mortality compared with those without (11/340) (3.82% vs. 3.24%, RR: 1.19, 95% CI: 0.53-2.69, χ2 = 0.17, P = 0.6777). CONCLUSIONS: In our study, we did not find any positive or negative effects of RAAS inhibitors or beta-blockers in COVID-19 patients with hypertension, while CCBs could improve prognosis.

Use of proton pump inhibitors are associated with higher mortality in hospitalized patients with COVID-19.

BACKGROUND: The adverse effects of proton pump inhibitors (PPIs) on pneumonia have been well reported. However, the relationship between the use of PPIs and the adverse outcomes of coronavirus disease 2019 (COVID-19) is currently inconclusive. In this study, we aimed to explore the relationship between the use of PPIs and the in-hospital mortality among patients who were laboratory-confirmed SARS-CoV-2. METHODS: Data was derived from 2 hospitals which both were the first batch of SARS-CoV-2 specialist hospitals with four types of sensitivity analyses. This cohort included 4634 patients older than 18 years who were laboratory-confirmed SARS-CoV-2. Endpoints were death in hospital (primary) and the recovery of COVID-19 (secondary: the time of COVID-19 nucleic acid testing turning negative). RESULTS: In the entire cohort, there were 3588 non-users, 399 ≤ 0.5 defined daily dose (DDD) PPIs users, 483 1 DDD users, and 164 ≥ 1.5 DDD users. The multivariate logistic regression analysis (odds ratio (OR) = 3.63, 95% confidence interval (CI) = 1.83-7.23, P = 0.0002) and four types of sensitivity analyses showed higher mortality in patients using PPIs during hospitalization, while the relationship between different PPIs dosages and the hospital mortality remained insignificant. Usage of the PPIs significantly prolongs the time of COVID-19 nucleic acid testing turning negative. CONCLUSIONS: The use of PPIs may increase the risk of in-hospital death of patients who were laboratory-confirmed SARS-CoV-2, which means that physicians may need to re-evaluate the benefit-risk assessment of the use of PPIs during the COVID-19 pandemic.

Prediction of in-hospital clinical outcomes of coronavirus disease 2019 patients based on machine learning algorithms

Objective: To construct prediction models for the clinical outcomes of coronavirus disease 2019 (COVID-19) patients using machine learning algorithms, and explore the outcome-related factors.