Long-term post-acute sequelae of COVID-19 infection: a retrospective, multi-database cohort study in Hong Kong and the UK.

Background: Evidence on post-acute sequelae of SARS-CoV-2 (PASC) has shown inconsistent findings. This study aimed to generate coherent evidence on the post-acute sequelae of COVID-19 infection using electronic healthcare records across two regions. Methods: In this retrospective, multi-database cohort study, patients with COVID-19 aged 18 or above between April 1st 2020 and May 31st 2022 from the Hong Kong Hospital Authority (HKHA) and March 16th 2020 and May 31st 2021 from the UK Biobank (UKB) databases and their matched controls were followed for up to 28 and 17 months, respectively. Covariates between patients with COVID-19 and non-COVID-19 controls were adjusted using propensity score-based inverse probability treatment weighting. Cox proportional regression was used to estimate the hazard ratio (HR) of clinical sequelae, cardiovascular, and all-cause mortality 21 days after COVID-19 infection. Findings: A total of 535,186 and 16,400 patients were diagnosed with COVID-19 from HKHA and UKB, of whom 253,872 (47.4%) and 7613 (46.4%) were male, with a mean age (±SD) of 53.6 (17.8) years and 65.0 (8.5) years, respectively. Patients with COVID-19 incurred greater risk of heart failure (HR 1.82; 95% CI 1.65, 2.01), atrial fibrillation (1.31; 1.16, 1.48), coronary artery disease (1.32; 1.07, 1.63), deep vein thrombosis (1.74; 1.27, 2.37), chronic pulmonary disease (1.61; 1.40, 1.85), acute respiratory distress syndrome (1.89; 1.04, 3.43), interstitial lung disease (3.91; 2.36, 6.50), seizure (2.32; 1.12, 4.79), anxiety disorder (1.65; 1.29, 2.09), post-traumatic stress disorder (1.52; 1.23, 1.87), end-stage renal disease (1.76; 1.31, 2.38), acute kidney injury (2.14; 1.69, 2.71), pancreatitis (1.42; 1.10, 1.83), cardiovascular (2.86; 1.25, 6.51) and all-cause mortality (4.16; 2.11, 8.21) mortality during their post-acute phase of infection. Interpretation: The consistent greater risk of PASC highlighted the need for sustained multi-disciplinary care for COVID-19 survivors. Funding: Health Bureau, The Government of the Hong Kong Special Administrative Region, Collaborative Research Fund, The Government of the Hong Kong Special Administrative Region and AIR@InnoHK, administered by the Innovation and Technology Commission, The Government of the Hong Kong Special Administrative Region.

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.

Booster vaccination with inactivated whole-virus or mRNA vaccines and COVID-19-related deaths among people with multimorbidity: a cohort study.

BACKGROUND: Multimorbidity is a prevalent risk factor for COVID-19-related complications and death. We sought to evaluate the association of homologous booster vaccination using BNT162b2 (Pfizer-BioNTech) or CoronaVac (Sinovac) with COVID-19-related deaths among people with multimorbidity during the initial Omicron wave of the COVID-19 pandemic. METHODS: Using routine clinical records from public health care facilities in Hong Kong, we conducted a territory-wide retrospective cohort study comparing people aged 18 years or older with 2 or more chronic conditions who received a homologous booster (third) dose with those who received only 2 doses, between Nov. 11, 2021, and Mar. 31, 2022. The primary outcome was death related to COVID-19. RESULTS: We included 120 724 BNT162b2 recipients (including 87 289 who received a booster), followed for a median of 34 (interquartile range [IQR] 20-63) days and 127 318 CoronaVac recipients (including 94 977 who received a booster), followed for a median of 38 (IQR 22-77) days. Among BNT162b2 recipients, booster-vaccinated people had fewer COVID-19-related deaths than those who received 2 doses (5 v. 34, incidence rate 1.3 v. 23.4 per million person-days, weighted incidence rate ratio [IRR] 0.05, 95% confidence interval [CI] 0.02-0.16). We observed similar results among recipients of CoronaVac booster vaccination compared with those who received only 2 doses (26 v. 88, incidence rate 5.3 v. 53.1 per million person-days, weighted IRR 0.08, 95% CI 0.05-0.12). INTERPRETATION: Among people with multimorbidity, booster vaccination with BNT162b2 or CoronaVac was associated with reductions of more than 90% in COVID-19-related mortality rates compared with only 2 doses. These results highlight the crucial role of booster vaccination for protecting vulnerable populations as the COVID-19 pandemic continues to evolve.

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.

Relationship between angiotensin-converting enzyme inhibitors or angiotensin receptor blockers and COVID-19 incidence or severe disease.

BACKGROUND: Angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) may be associated with higher susceptibility of COVID-19 infection and adverse outcomes. We compared ACEI/ARB use and COVID-19 positivity in a case-control design, and severity in COVID-19 positive patients. METHODS: Consecutive patients who attended Hong Kong's public hospitals or outpatient clinics between 1 January and 28 July 2020 for COVID-19 real time-PCR (RT-PCR) tests were included. Baseline demographics, past comorbidities, laboratory tests and use of different medications were compared between COVID-19 positive and negative patients. Severe endpoints for COVID-19 positive patients were 28-day mortality, need for intensive care admission or intubation. RESULTS: This study included 213 788 patients (COVID-19 positive: n = 2774 patients; negative: n = 211 014). In total, 162 COVID-19 positive patients (5.83%) met the severity outcome. The use of ACEI/ARB was significantly higher amongst cases than controls (n = 156/2774, 5.62 vs. n = 6708/211014, 3.17%; P < 0.0001). Significant univariate predictors of COVID-19 positivity and severe COVID-19 disease were older age, higher Charlson score, comorbidities, use of ACEI/ARB, antidiabetic, lipid-lowering, anticoagulant and antiplatelet drugs and laboratory tests (odds ratio >1, P < 0.05). The relationship between the use of ACEI/ARB and COVID-19 positivity or severe disease remained significant after multivariable adjustment. No significant differences in COVID-19 positivity or disease severity between ACEI and ARB use were observed (P > 0.05). CONCLUSION: There was a significant relationship between ACEI/ARB use and COVID-19 positivity and severe disease after adjusting for significant confounders.

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.