Association of Molnupiravir and Nirmatrelvir-Ritonavir with reduced mortality and sepsis in hospitalized omicron patients: a territory-wide study.

This study evaluates the association between antivirals (Molnupiravir and Nirmatrelvir-Ritonavir) and all-cause and respiratory mortality and organ dysfunction among high-risk COVID-19 patients during an Omicron outbreak. Two cohorts, Nirmatrelvir-Ritonavir versus control and Molnupiravir versus control, were constructed with inverse probability treatment weighting to balance baseline characteristics. Cox proportional hazards models evaluated the association of their use with all-cause mortality, respiratory mortality, and all-cause sepsis (a composite of circulatory shock, respiratory failure, acute liver injury, coagulopathy, and acute liver impairment). Patients recruited were hospitalized and diagnosed with the COVID-19 Omicron variant between February 22, 2022 and April 15, 2022, and followed up until May 15, 2022. The study included 17,704 patients. There were 4.67 and 22.7 total mortalities per 1000 person-days in the Nirmatrelvir-Ritonavir and control groups respectively before adjustment (weighted incidence rate ratio, - 18.1 [95% CI - 23.0 to - 13.2]; hazard ratio, 0.18 [95% CI, 0.11-0.29]). There were 6.64 and 25.9 total mortalities per 1000 person-days in the Molnupiravir and control groups respectively before adjustment (weighted incidence rate ratio per 1000 person-days, - 19.3 [95% CI - 22.6 to - 15.9]; hazard ratio, 0.23 [95% CI 0.18-0.30]). In all-cause sepsis, there were 13.7 and 35.4 organ dysfunction events per 1000 person-days in the Nirmatrelvir-Ritonavir and control groups respectively before adjustment (weighted incidence rate ratio per 1000 person-days, - 21.7 [95% CI - 26.3 to - 17.1]; hazard ratio, 0.44 [95% CI 0.38-0.52]). There were 23.7 and 40.8 organ dysfunction events in the Molnupiravir and control groups respectively before adjustment (weighted incidence ratio per 1000 person-days, - 17.1 [95% CI, - 20.6 to - 13.6]; hazard ratio, 0.63 [95% CI 0.58-0.69]). Among COVID-19 hospitalized patients, use of either Nirmatrelvir-Ritonavir or Molnupiravir compared with no antiviral use was associated with a significantly lower incidence of 28-days all-cause and respiratory mortality and sepsis.

Clinical characteristics, risk factors and outcomes of cancer patients with COVID-19: A population-based study.

INTRODUCTION: Cancer patients may be susceptible to poorer outcomes in COVID-19 infection owing to the immunosuppressant effect of chemotherapy/radiotherapy and cancer growth, along with the potential for nosocomial transmission due to frequent hospital admissions. METHODS: This was a population-based retrospective cohort study of COVID-19 patients who presented to Hong Kong public hospitals between 1 January 2020 and 8 December 2020. The primary outcome was a composite endpoint of requirement for intubation, ICU admission and 30-day mortality. RESULTS: The following study consisted of 6089 COVID-19 patients (median age 45.9 [27.8.1-62.7] years; 50% male), of which 142 were cancer subjects. COVID-19 cancer patients were older at baseline and tended to present with a higher frequency of comorbidities, including diabetes mellitus, hypertension, chronic obstructive pulmonary disease, ischemic heart disease, ventricular tachycardia/fibrillation and gastrointestinal bleeding (p < 0.05). These subjects also likewise tended to present with higher serum levels of inflammatory markers, including D-dimer, lactate dehydrogenase, high sensitivity troponin-I and C-reactive protein. Multivariate Cox regression showed that any type of cancer presented with an almost four-fold increased risk of the primary outcome (HR: 3.77; 95% CI: 1.63-8.72; p < 0.002) after adjusting for significant demographics, Charlson comorbidity index, number of comorbidities, past comorbidities and medication history. This association remained significant when assessing those with colorectal (HR: 5.07; 95% CI: 1.50-17.17; p < 0.009) and gastrointestinal malignancies (HR: 3.79; 95% CI: 1.12-12.88; p < 0.03), but not with lung, genitourinary, or breast malignancies, relative to their respective cancer-free COVID-19 counterparts. CONCLUSIONS: COVID-19 cancer patients are associated with a significantly higher risk of intubation, ICU admission and/or mortality.

Incidence of Emergency Department Visits for Sexual Abuse Among Youth in Hong Kong Before and During the COVID-19 Pandemic.

This cohort study assesses the incidence of emergency department (ED) visits in Hong Kong, China, for sexual abuse among youth before and during the COVID-19 pandemic.

Association of Molnupiravir and Nirmatrelvir-Ritonavir with preventable mortality, hospital admissions and related avoidable healthcare system cost among high-risk patients with mild to moderate COVID-19

Background Real-world data is currently limited on the association between oral antiviral therapy and healthcare system burden in patients with mild-to-moderate COVID-19. This study aims to evaluate the clinical and cost effectiveness of Molnupiravir and Nirmatrelvir-ritonavir use in reducing mortality in this population. Methods This is a retrospective cohort study involving 54,355 COVID-19 patients during February 22–March 31,2022 in Hong Kong. Inverse probability of treatment weighting (IPTW) was used to adjust patient characteristics. Our exposure of interest was Molnupiravir/Nirmatrelvir-Ritonavir prescription, with all-cause mortality as the primary outcome. IPTW-adjusted multivariate regressions were used to estimate treatment impact on clinic re-attendance and unplanned admissions. Finally, attributed cost and incremental cost-effectiveness ratios (ICER) were estimated. Findings In the outpatient cohort (N = 33,217, 61.1%), 16.1% used Molnupiravir and 13.4% used Nirmatrelvir-Ritonavir, while in the inpatient cohort (N = 21,138, 38.9%), 3.8% used Molnupiravir and 1.3% used Nirmatrelvir-Ritonavir. IPTW-adjusted Cox model estimated that Molnupiravir (hazard ratio (HR)(95%CI)=0.31 (0.24-0.40), P< 0.0001) and Nirmatrelvir-Ritonavir (HR=0.10 (95%CI 0.05-0.21), P< 0.0001) were significantly associated with a reduced mortality hazard. In the outpatient cohort, both antiviral prescriptions were associated with reduced odds for unplanned hospital admissions (Molnupiravir: odds ratio (OR) =0.72 (0.52-0.98), P=0.039;Nirmatrelvir-Ritonavir: OR=0.37 (0.23-0.60), P<0.0001). Among hospitalised patients, both antiviral prescriptions were associated with significant reductions in the odds ratios for 28-days readmission (Molnupiravir: OR=0.71 (0.52-0.97), P=0.031;Nirmatrelvir-Ritonavir: OR=0.47 (0.24-0.93), P=0.030). ICERs for death averted for Molnupiravir stood at USD493,345.09 in outpatient settings and USD2,629.08 in inpatient settings. In outpatient settings, Nirmatrelvir-ritonavir cost USD331,105.27 to avert one death, but saved USD5,502.53 to avert one death in comparison with standard care. Interpretation In high-risk patients in Hong Kong with mild-to-moderate COVID-19, Molnupiravir and Nirmatrelvir-Ritonavir prescriptions were associated with reduced all-cause mortality and significant cost savings. Funding Centre for Health Systems & Policy Research is funded by The Tung's Foundation;and The Laboratory of Data Discovery for Health Limited(D24H) is funded the AIR@InnoHK platform administered by the Innovation and Technology Commission of Hong Kong. Funders did not have any role in study design, data collection, data analysis, interpretation and writing of this manuscript.

Comparisons of the risk of myopericarditis between COVID-19 patients and individuals receiving COVID-19 vaccines: a population-based study.

BACKGROUND: Both COVID-19 infection and COVID-19 vaccines have been associated with the development of myopericarditis. The objective of this study is to (1) analyse the rates of myopericarditis after COVID-19 infection and COVID-19 vaccination in Hong Kong, (2) compared to the background rates, and (3) compare the rates of myopericarditis after COVID-19 vaccination to those reported in other countries. METHODS: This was a population-based cohort study from Hong Kong, China. Patients with positive RT-PCR test for COVID-19 between 1st January 2020 and 30th June 2021 or individuals who received COVID-19 vaccination until 31st August were included. The main exposures were COVID-19 positivity or COVID-19 vaccination. The primary outcome was myopericarditis. RESULTS: This study included 11,441 COVID-19 patients from Hong Kong, four of whom suffered from myopericarditis (rate per million: 326; 95% confidence interval [CI] 127-838). The rate was higher than the pre-COVID-19 background rate in 2019 (rate per million: 5.5, 95% CI 4.1-7.4) with a rate ratio of 55.0 (95% CI 21.4-141). Compared to the background rate, the rate of myopericarditis among vaccinated subjects in Hong Kong was similar (rate per million: 5.5; 95% CI 4.1-7.4) with a rate ratio of 0.93 (95% CI 0.69-1.26). The rates of myocarditis after vaccination in Hong Kong were comparable to those vaccinated in the United States, Israel, and the United Kingdom. CONCLUSIONS: COVID-19 infection was associated with significantly higher rate of myopericarditis compared to the vaccine-associated myopericarditis.

Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph.

Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 in resource-scarce countries. In this study, we applied machine learning (ML) to the task of detection of SARS-CoV-2 infection using basic laboratory markers. We performed the statistical analysis and trained an ML model on a retrospective cohort of 5148 patients from 24 hospitals in Hong Kong to classify COVID-19 and other aetiology of pneumonia. We validated the model on three temporal validation sets from different waves of infection in Hong Kong. For predicting SARS-CoV-2 infection, the ML model achieved high AUCs and specificity but low sensitivity in all three validation sets (AUC: 89.9-95.8%; Sensitivity: 55.5-77.8%; Specificity: 91.5-98.3%). When used in adjunction with radiologist interpretations of chest radiographs, the sensitivity was over 90% while keeping moderate specificity. Our study showed that machine learning model based on readily available laboratory markers could achieve high accuracy in predicting SARS-CoV-2 infection.

The short version of students' perceptions of interprofessional clinical education-revised (SPICE-R3): a confirmatory factor analysis.

The Students' Perceptions of Physician-Pharmacist Interprofessional Clinical Education and its revision (SPICE, SPICE-R) were designed to understand medicine and pharmacy students' perceptions of interprofessional education and collaborative practice in managing complex health problems. The SPICE-R authors, however, suggested for additional items for subscales "roles and responsibilities for collaborative care" and "patient outcomes from collaborative practice". We added two items and introduced SPICE-R3 to differentiate it from the 10-item SPICE-R2 and to adapt the scale to a wider range of healthcare members. We administered the SPICE-R3 to healthcare students at the height of the COVID-19 outbreak in Hong Kong in February 2020. Using data from 225 students from Chinese medicine, medicine, nursing, and pharmacy, confirmatory factor analysis indicated nine items having acceptable item coefficients. Our data obtained a good fit to the three-factor, nine-item model suggesting construct validity. Results of the between-network analysis suggest that the three subscales of SPICE-R3 correlated systematically with other theoretically relevant variables in the nomological network suggesting convergent validity. The SPICE-R3 is a valid measure to examine Hong Kong healthcare students' interprofessional attitudes in online interprofessional education even during the pandemic. Implications and directions for future research are provided.

Development of a multivariable prediction model for severe COVID-19 disease: a population-based study from Hong Kong.

Recent studies have reported numerous predictors for adverse outcomes in COVID-19 disease. However, there have been few simple clinical risk scores available for prompt risk stratification. The objective is to develop a simple risk score for predicting severe COVID-19 disease using territory-wide data based on simple clinical and laboratory variables. Consecutive patients admitted to Hong Kong's public hospitals between 1 January and 22 August 2020 and diagnosed with COVID-19, as confirmed by RT-PCR, were included. The primary outcome was composite intensive care unit admission, need for intubation or death with follow-up until 8 September 2020. An external independent cohort from Wuhan was used for model validation. COVID-19 testing was performed in 237,493 patients and 4442 patients (median age 44.8 years old, 95% confidence interval (CI): [28.9, 60.8]); 50% males) were tested positive. Of these, 209 patients (4.8%) met the primary outcome. A risk score including the following components was derived from Cox regression: gender, age, diabetes mellitus, hypertension, atrial fibrillation, heart failure, ischemic heart disease, peripheral vascular disease, stroke, dementia, liver diseases, gastrointestinal bleeding, cancer, increases in neutrophil count, potassium, urea, creatinine, aspartate transaminase, alanine transaminase, bilirubin, D-dimer, high sensitive troponin-I, lactate dehydrogenase, activated partial thromboplastin time, prothrombin time, and C-reactive protein, as well as decreases in lymphocyte count, platelet, hematocrit, albumin, sodium, low-density lipoprotein, high-density lipoprotein, cholesterol, glucose, and base excess. The model based on test results taken on the day of admission demonstrated an excellent predictive value. Incorporation of test results on successive time points did not further improve risk prediction. The derived score system was evaluated with out-of-sample five-cross-validation (AUC: 0.86, 95% CI: 0.82-0.91) and external validation (N = 202, AUC: 0.89, 95% CI: 0.85-0.93). A simple clinical score accurately predicted severe COVID-19 disease, even without including symptoms, blood pressure or oxygen status on presentation, or chest radiograph results.

Impact of COVID-19 on Child Maltreatment: Income Instability and Parenting Issues.

Introduction: Children are widely recognized as a vulnerable population during disasters and emergencies. The COVID-19 pandemic, like a natural disaster, brought uncertainties and instability to the economic development of the society and social distancing, which might lead to child maltreatment. This study aims to investigate whether job loss, income reduction and parenting affect child maltreatment. Methods: We conducted a cross-sectional online survey of 600 randomly sampled parents aged 18 years or older who had and lived with a child under 10 years old in Hong Kong between 29 May to 16 June 2020. Participants were recruited from a random list of mobile phone numbers of a panel of parents. Of 779 recruited target parents, 600 parents completed the survey successfully via a web-based system after obtaining their online consent for participating in the survey. Results: Income reduction was found significantly associated with severe (OR = 3.29, 95% CI = 1.06, 10.25) and very severe physical assaults (OR = 7.69, 95% CI = 2.24, 26.41) towards children. Job loss or large income reduction were also significantly associated with severe (OR= 3.68, 95% CI = 1.33, 10.19) and very severe physical assaults (OR = 4.05, 95% CI = 1.17, 14.08) towards children. However, income reduction (OR = 0.29, 95% CI = 0.15, 0.53) and job loss (OR = 0.47, 95% CI = 0.28, 0.76) were significantly associated with less psychological aggression. Exposure to intimate partner violence between parents is a very strong and significant factor associated with all types of child maltreatment. Having higher levels of difficulty in discussing COVID-19 with children was significantly associated with more corporal punishment (OR = 1.19, 95% CI = 1.05, 1.34), whereas having higher level of confidence in managing preventive COVID-19 behaviors with children was negatively associated with corporal punishment (OR = 0.87, 95% CI = 0.76, 0.99) and very severe physical assaults (OR = 0.74, 95% CI = 0.58, 0.93). Conclusions: Income instability such as income reduction and job loss amplified the risk of severe and very severe child physical assaults but protected children from psychological aggression. Also, confidence in teaching COVID-19 and managing preventive COVID-19 behaviors with children was significantly negatively associated with corporal punishment during pandemic.

Spatial analysis of the impact of urban geometry and socio-demographic characteristics on COVID-19, a study in Hong Kong.

The World Health Organization considered the wide spread of COVID-19 over the world as a pandemic. There is still a lack of understanding of its origin, transmission, and treatment methods. Understanding the influencing factors of COVID-19 can help mitigate its spread, but little research on the spatial factors has been conducted. Therefore, this study explores the effects of urban geometry and socio-demographic factors on the COVID-19 cases in Hong Kong. For each patient, the places they visited during the incubation period before going to hospital were identified, and matched with corresponding attributes of urban geometry (i.e., building geometry, road network and greenspace) and socio-demographic factors (i.e., demographic, educational, economic, household and housing characteristics) based on the coordinates. The local cases were then compared with the imported cases using stepwise logistic regression, logistic regression with case-control of time, and least absolute shrinkage and selection operator regression to identify factors influencing local disease transmission. Results show that the building geometry, road network and certain socio-economic characteristics are significantly associated with COVID-19 cases. In addition, the results indicate that urban geometry is playing a more important role than socio-demographic characteristics in affecting COVID-19 incidence. These findings provide a useful reference to the government and the general public as to the spatial vulnerability of COVID-19 transmission and to take appropriate preventive measures in high-risk areas.

Association of Individual Health Literacy with Preventive Behaviours and Family Well-Being during COVID-19 Pandemic: Mediating Role of Family Information Sharing.

Objective: We tested a model of individual health literacy information sharing with family members, personal preventive behaviours and family well-being during the Coronavirus Disease 2019 (COVID-19) pandemic in Hong Kong. Methods: We analysed data of 1501 randomly selected Chinese adults from a cross-sectional survey in Hong Kong from 9 to 23 April, 2020. Individual health literacy about COVID-19 with the items extracted from the questionnaire in World Health Organization Risk Communication and Community Engagement (RCCE) Action Plan Guidance for COVID-19 preparedness and response, COVID-19 information sharing with family members, preventive behaviours against COVID-19 and family well-being were measured. Structural equation modelling analysis tested the proposed model. Findings: COVID-19 information sharing with family members partially mediated the association between individual health literacy and personal preventive behaviours. The direct effect of 0.24 was shown, and the indirect effect through COVID-19 information sharing with family members was small at 0.03 (Z = 3.66, p < 0.001). Family well-being was associated with personal preventive behaviours against COVID-19. The model was adjusted for sex, age, and socioeconomic status factors and had good fit with RMSEA = 0.04, CFI = 0.98, TLI = 0.96, and SRMR = 0.02. Conclusion: COVID-19 information sharing with family members was a partial mediator between individual health literacy and personal preventive behaviours against COVID-19. Strategies for enhancing health literacy and preventive measures against COVID-19 are needed to promote family well-being in the pandemic.

Mental health crisis under COVID-19 pandemic in Hong Kong, China.

OBJECTIVES: To compare the mental health burden before and during the COVID-19 outbreak and identify the vulnerable groups by sociodemographic factors. METHODS: We analyzed repeated cross-sectional data from the Hong Kong Family and Health Information Trend Survey (FHInTS) in 2016 (N = 4036) and 2017 (N = 4051) and the COVID-19 Health Information Survey (CoVHInS) in April 9-23, 2020 (N = 1501) using population-based random samples of general adults by landline telephone and online panel. Stress (Perceived Stress Scale 4), anxiety symptoms (General Anxiety Disorders 2), depression symptoms (Patient Health Questionnaire-2), subjective happiness (4-point Likert item), and sociodemographic factors were collected. RESULTS: Compared with 2016 and 2017, the stress level increased by 28.3%, prevalence of anxiety increased by 42.3%, and the depression symptoms and unhappiness have doubled (all P for trends <0.001) during the COVID-19 outbreak. The increases in stress levels were significantly larger among older and less educated respondents (P for interactions <0.001). CONCLUSION: Hong Kong had a mental health emergency even with no lockdown and well-managed outbreaks. Older and under-privileged people will suffer most. Public mental health interventions are urgently needed particularly for the older adults and individuals with primary or lower education attainment.