ABSTRACT
We investigate the dynamic connectedness among health-tech equity and medicine prices (producer and consumer) and Medicare cost indices for the US market. In doing so, we apply Cross-Quantilogram Dynamic Connectedness based on Time-Varying Parameter Vector Autoregression (TVP-VAR) approaches to analyse historical high-frequency time-series data. TVP-VAR results show that health-tech equity is the highest volatility transmitter while Medicare price is the highest volatility receiver. We also find medicine producer price is the net volatility contributor while the retail price of medicine is the net volatility receiver. The Cross-Quantilogram analysis confirms a strong bivariate quantile dependence between respective markets at a higher quantile of each market. Cross-quantilogram demonstrates a higher level of connectedness among the markets when considering medium and long memory. We observe health-tech equity turned to be a profound volatility contributor, while medicine price (both producer and retail prices) and Medicare appeared to net volatility receiver during the time of COVID19 Pandemic. The financial performance of health-tech equity returns elevates the price volatility of medicine and eventually Medicare cost, which imply that equity return should be incorporated forming medicine prices. © 2022 Elsevier Ltd
ABSTRACT
OBJECTIVE: The first pandemic phase of COVID-19 in Italy was characterized by high in-hospital mortality ranging from 23% to 38%. During the third pandemic phase there has been an improvement in the management and treatment of COVID-19, so mortality and predictors may have changed. A prospective study was planned to identify predictors of mortality during the third pandemic phase. PATIENTS AND METHODS: From 15 December 2020 to 15 May 2021, 208 patients were hospitalized (median age: 64 years; males: 58.6%); 83% had a median of 2 (IQR,1-4) comorbidities; pneumonia was present in 89.8%. Patients were monitored remotely for respiratory function and ECG trace for 24 hours/day. Management and treatment were done following the timing and dosage recommended by international guidelines. RESULTS: 79.2% of patients necessitated O2-therapy. ARDS was present in 46.1% of patients and 45.4% received non-invasive ventilation and 11.1% required ICU treatment. 38% developed arrhythmias which were identified early by telemetry and promptly treated. The in-hospital mortality rate was 10%. At multivariate analysis independent predictors of mortality were: older age (R-R for≥70 years: 5.44), number of comorbidities ≥3 (R-R 2.72), eGFR ≤60 ml/min (RR 2.91), high d-Dimer (R-R for≥1,000 ng/ml:7.53), and low PaO2/FiO2 (R-R for <200: 3.21). CONCLUSIONS: Management and treatment adherence to recommendations, use of telemetry, and no overcrowding appear to reduce mortality. Advanced age, number of comorbidities, severe renal failure, high d-Dimer and low P/F remain predictors of poor outcome. The data help to identify current high-risk COVID-19 patients in whom management has yet to be optimized, who require the greatest therapeutic effort, and subjects in whom vaccination is mandatory.