![]() As the gravity of this situation increases and the attention on Asians as a target for this virus ebbs, replaced by a general paranoia of one another, the disappointment and disillusionment remain. It may be true that these feelings and attitudes toward Asian-Americans were always there, hidden underneath the surface, but fear has brought them to a head in these perilous times. Fear that a stranger will infect us, that others will take all the supplies we need to survive, and that looking out for someone else will cause us to suffer. It becomes one more pebble in a shoe full of rocks, another sign and symptom contributing to a plaguing imposter syndrome.Īpart from the threat of illness and death, fear is perhaps the most virulent part of COVID-19. But, when patients refuse to be seen by anyone “Asian-looking” and when care and concern is met with bigotry and hate, it is an understatement to say that it hurts. Every moment in the hospital, we put ourselves and the people we love at greater risk of contracting the virus, because this profession is more than work, it is a calling. As physicians and resident physicians, we took an oath to help the sick and suffering, even those who are distrustful or prejudiced against us. These sentiments and experiences have not been lost on the Asian doctor. While these accounts have ranged from derogatory comments (“Get your coronavirus out of my country!”) to battery and assault, less talked about are the subtle moments - the stare of a stranger on the street, the fear of coughing or sneezing in an elevator, and the unshakable, unrelenting feeling that you’re different, that you don’t belong. Over the last few months, there have been countless stories of racism and xenophobia towards individuals of Asian descent. Unfortunately, for Asians, this social sterility has left in its wake a sense of isolation and blame. It is undeniable that the social distancing movement is critical in quelling the exponential spread of this virus. Sterile technique has leaked into the public domain, marked not only by how expensive Purell has become or how frequently we are reminded to wash our hands, but also by the ways we have come to treat one another. However, with the advent of the COVID-19 pandemic, we now find ourselves unable to scrub out at the end of the case. We don gown and gloves and communicate behind mask and shield, all to keep ourselves and our patients safe. We’ve made a home of the aseptic operating room, where “don’t touch your face” is a lesson learned on day one. ― Gabriel García Márquez, Love in the Time of CholeraĪs surgeons, we pride ourselves on our sterility. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.“It was a meditation on life, love, old age, death: ideas that had often fluttered around her head like nocturnal birds but dissolved into a trickle of feathers when she tried to catch hold of them." 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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