Over the last two years, the variants Alpha, Beta, Delta (named by the World Health Organization after the Greek alphabet), and others have caused increases in cases, and illnesses ranging from mild (with no reported symptoms in some cases) to severe. New variants of the virus have also prompted waves. A loosening of restrictions on mask-wearing and other mitigation efforts can precipitate a wave, as can an event or celebration period such as the winter holidays, when people are more likely to travel and gather indoors. Outbreaks of COVID-19 have come in waves in which a surge of new cases typically is followed by a decline in infections. Scientists and public health officials continue to work as quickly as possible to address key questions such as how COVID-19 affects the body why some people have Long COVID (or continuing symptoms the CDC calls “post-COVID conditions”) and the best ways to improve upon the vaccines, test for COVID-19, and treat people who are infected.īelow is a list of nine things you should know about the coronavirus. A Novavax booster is available for adults who cannot take the Pfizer or Moderna vaccines, but it may not protect against recent Omicron variants. Vaccines are available for infants, children, and adults ages 6 months and older, and almost everyone ages 6 months and older can get a Pfizer or Moderna bivalent booster shot that protects against both the original virus and two Omicron strains. were designed to protect against the original strain of the coronavirus, scientists have designed a booster that has shown to be effective against the Omicron variant and BA.4/BA.5 subvariants, and they continue to work on updating it.įour vaccines are being administered from Pfizer-BioNTech, Moderna, Johnson & Johnson, and Novavax, and the Centers for Disease Control (CDC) endorses a clinical preference for the Pfizer and Moderna shots over J&J, based on evidence of vaccine effectiveness, safety, and rare adverse events. While the vaccines that are available in the U.S. Experts are still learning about this new strain of the virus, which they believe may be the most transmissible one so far. In early 2023, the Omicron variant continued to drive cases with the rise of a new subvariant called XBB.1.5. But COVID-19 is still a threat-no one can predict when a new strain might surface, and many questions remain. In some ways, the virus is under better control since the first cases were identified here in January 2020. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.COVID-19 has been upending daily life in the United States for almost three years as SARS-CoV-2, the virus spreading the disease, has caused surges in infections across the country. This may have important implications for prognostic or predictive enrichment. Patients typically do not remain in the same cluster throughout intensive care treatment. The clinical phenotype half-life was between 5 and 6 days for the mild and severe phenotypes, and about 3 days for the medium severe phenotype. During the 21-day period, only 8.2% and 4.6% of patients in the initial mild and severe clusters remained assigned to the same phenotype respectively. Heterogeneity between phenotypes appears to be driven by inflammation and dead space ventilation. After day 4, the severe phenotype split into an intermediate and a severe phenotype for 11 consecutive days. On admission, both a mild and a severe clinical phenotype were found. Forty-one parameters were chosen for cluster analysis. The final patient cohort consisted of 2438 COVID-19 patients with a ICU mortality outcome. Both evolution of the clinical phenotypes over time and patient allocation to these clusters over time were tracked. Clinical phenotypes in each dataset were identified by performing cluster analyses. Twenty-one datasets were created that each covered 24 h of ICU data for each day of ICU treatment. Parameters including demographics, clinical observations, medications, laboratory values, vital signs, and data from life support devices were selected. We used granular data from 3202 adult COVID patients in the Dutch Data Warehouse that were admitted to one of 25 Dutch ICUs between February 2020 and March 2021. By including the dimension of time, we aim to gain further insights into the heterogeneity of COVID-19. However, previous attempts did not take into account temporal dynamics with high granularity. Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment.
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