Outcomes of Critically Ill Pregnant Women with COVID-19 in the United States.
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ABSTRACT:
SUBMITTER: Easter SR
PROVIDER: S-EPMC7781146 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.
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Project description:Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.
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Project description:BackgroundFew studies have evaluated whether pandemic-related stressors, worries, and social distancing have affected the mental health of pregnant women during the COVID-19 pandemic.MethodsData came from an online survey of United States pregnant women (n = 715), conducted in May 2020. The Edinburgh Postnatal Depression Scale and Generalized Anxiety Disorder Scale were used to assess depressive symptoms, thoughts of self-harm, and moderate or severe anxiety. Multiple logistic regressions were used to examine the associations of COVID-19 experiences with mental health outcomes.ResultsParticipants were racially diverse. The prevalence of adverse mental health outcomes was 36% for probable depression, 20% for thoughts of self-harm, and 22% for anxiety. Women who reported family members dying from COVID-19 had four times higher odds of having thoughts of self-harm than women who did not experience family death. Depression was more prevalent among women who canceled or reduced medical appointments. Women were more likely to have worse mental health outcomes if they expressed worry about getting financial or emotional/social support, about their pregnancy, or about family or friends. Strict social distancing was positively associated with depression. A higher proportion of adults working from home was inversely associated with depression and thoughts of self-harm.ConclusionHigh percentages of pregnant women had symptoms of depression or anxiety, suggesting an urgent need to screen and treat mental health conditions among pregnant women during the pandemic. Pandemic-related risks and protective factors are relevant to developing tailored interventions to address the mental health of pregnant women during pandemic circumstances.
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Project description:BackgroundWe assessed maternal and neonatal outcomes of critically ill pregnant and puerperal patients in the clinical course of coronavirus disease 2019 (COVID-19).MethodsRecords of pregnant and puerperal women with polymerase chain reaction positive COVID-19 virus who were admitted to our intensive care unit (ICU) from March 2020 to August 2021 were investigated. Demographic, clinical and laboratory data, pharmacotherapy, and neonatal outcomes were analyzed. These outcomes were compared between patients that were discharged from ICU and patients who died in ICU.ResultsNineteen women were included in this study. Additional oxygen was required in all cases (100%). Eight patients (42%) were intubated and mechanically ventilated. All patients that were mechanically ventilated have died. Increased levels of C-reactive protein (CRP) was seen in all patients (100%). D-dimer values increased in 15 patients (78.9%); interleukin-6 (IL-6) increased in 16 cases (84.2%). Sixteen patients used antiviral drugs. Eleven patients were discharged from the ICU and eight patients have died due to complications of COVID-19 showing an ICU mortality rate of 42.1%. Mean number of hospitalized days in ICU was significantly lower in patients that were discharged (P = 0.037). Seventeen patients underwent cesarean-section (C/S) (89.4%). Mean birth week was significantly lower in patients who died in ICU (P = 0.024). Eleven preterm (57.8%) and eight term deliveries (42.1%) occurred.ConclusionHigh mortality rate was detected among critically ill pregnant/parturient patients followed in the ICU. Main predictors of mortality were the need of invasive mechanical ventilation and higher number of days hospitalized in ICU. Rate of C/S operations and preterm delivery were high. Pleasingly, the rate of neonatal death was low and no neonatal COVID-19 occurred.
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Project description:Many US states published crisis standards of care (CSC) guidelines for allocating scarce critical care resources during the COVID-19 pandemic. However, the performance of these guidelines in maximizing their population benefit has not been well tested. In 2,272 adults with COVID-19 requiring mechanical ventilation drawn from the Study of the Treatment and Outcomes in Critically Ill Patients with COVID-19 (STOP-COVID) multicenter cohort, we test the following three approaches to CSC algorithms: Sequential Organ Failure Assessment (SOFA) scores grouped into ranges, SOFA score ranges plus comorbidities, and a hypothetical approach using raw SOFA scores not grouped into ranges. We find that area under receiver operating characteristic (AUROC) curves for all three algorithms demonstrate only modest discrimination for 28-day mortality. Adding comorbidity scoring modestly improves algorithm performance over SOFA scores alone. The algorithm incorporating comorbidities has modestly worse predictive performance for Black compared to white patients. CSC algorithms should be empirically examined to refine approaches to the allocation of scarce resources during pandemics and to avoid potential exacerbation of racial inequities.
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