A risk prediction score to identify patients at low risk for COVID-19 infection.

Introduction: Singapore's enhanced surveillance programme for COVID-19 identifies and isolates hospitalised patients with acute respiratory symptoms to prevent nosocomial spread. We developed risk prediction models to identify patients with low risk for COVID-19 from this cohort of hospitalised patients with acute respiratory symptoms. Methods: This was a single-centre retrospective observational study. Patients admitted to our institution's respiratory surveillance wards from 10 February to 30 April 2020 contributed data for analysis. Prediction models for COVID-19 were derived from a training cohort using variables based on demographics, clinical symptoms, exposure risks and blood investigations fitted into logistic regression models. The derived prediction models were subsequently validated on a test cohort. Results: Of the 1,228 patients analysed, 52 (4.2%) were diagnosed with COVID-19. Two prediction models were derived, the first based on age, presence of sore throat, dormitory residence, blood haemoglobin level (Hb), and total white blood cell counts (TW), and the second based on presence of headache, contact with infective patients, Hb and TW. Both models had good diagnostic performance with areas under the receiver operating characteristic curve of 0.934 and 0.866, respectively. Risk score cut-offs of 0.6 for Model 1 and 0.2 for Model 2 had 100% sensitivity, allowing identification of patients with low risk for COVID-19. Limiting COVID-19 screening to only elevated-risk patients reduced the number of isolation days for surveillance patients by up to 41.7% and COVID-19 swab testing by up to 41.0%. Conclusion: Prediction models derived from our study were able to identify patients at low risk for COVID-19 and rationalise resource utilisation.

Efficacy and safety of sofosbuvir/velpatasvir in a real-world chronic hepatitis C genotype 3 cohort.

BACKGROUND AND AIM: Real-world data on sofosbuvir/velpatasvir with and without ribavirin (SOF/VEL ± RBV), particularly among patients with genotype 3 (GT3) decompensated cirrhosis, prior treatment, coinfection, and hepatocellular carcinoma (HCC), are scarce. We aimed to assess the efficacy and safety of SOF/VEL ± RBV in a real-world setting that included both community and incarcerated GT3 hepatitis C virus (HCV) patients. METHODS: We included all GT3 HCV patients treated with SOF/VEL ± RBV in our institution. The primary outcome measure was the overall sustained virological response 12 weeks after treatment (SVR12), reported in both intention-to-treat (ITT) and per-protocol analyses. The secondary outcome measures were SVR12 stratified by the presence of decompensated cirrhosis, prior treatment, HCC, and HIV/hepatitis C virus coinfection and the occurrence rate of serious adverse events requiring treatment cessation or hospitalization. RESULTS: A total of 779 HCV patients were treated with 12 weeks of SOF/VEL ± RBV, of which 85% were treated during incarceration. Among the 530 GT3 HCV patients, 31% had liver cirrhosis, and 6% were treatment-experienced. The overall SVR12 for GT3 was 98.7% (95% confidence interval: 97.3%, 99.5%) and 99.2% (95% confidence interval: 98.1%, 99.8%) in ITT and per-protocol analyses, respectively. High SVR12 was also seen in ITT analysis among GT3 HCV patients with decompensated cirrhosis (88%), prior treatment (100%), HCC (100%), and HIV/hepatitis B virus coinfection (100%). Apart from one patient who developed myositis, no other serious adverse events were observed. CONCLUSION: The SOF/VEL ± RBV is a safe and efficacious treatment option for GT3 HCV patients in a real-world setting. SOF/VEL with RBV may be considered for decompensated GT3 HCV patients.