scholarly journals Maternal mortality associated with COVID-19 in Brazil in 2020 and 2021: Comparison with non-pregnant women and men

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261492
Author(s):  
Beatriz Martinelli Menezes Gonçalves ◽  
Rossana Pulcinelli V. Franco ◽  
Agatha S. Rodrigues
Keyword(s):  
Risk Factor ◽  
Intensive Care ◽  
Severe Acute Respiratory Syndrome ◽  
Maternal Mortality ◽  
Mortality Rates ◽  
Postpartum Women ◽  
Risk Of Death ◽  
Pregnancy And Postpartum ◽  
Patient Groups ◽  
Second Period

Objective Mortality rates of pregnant and postpartum women grew in the second COVID-19 pandemic year. Our objective is to understand this phenomenon to avoid further deaths. Methods We collected data from SIVEP-Gripe, a nationwide Brazilian database containing surveillance data on all severe acute respiratory syndrome caused by COVID-19, between the first notified case (February 2020) until the 17th epidemiological week of 2021. We stratified patients into maternal women (which includes pregnant and postpartum women), non-maternal women and men and divided them by time of diagnosis in two periods: first period (February to December 2020) and second period (the first 17 epidemiological weeks of 2021 before pregnant and postpartum women were vaccinated). Results During the second period, all patients had higher risk of presenting severe COVID-19 cases, but the maternal population was at a higher risk of death (OR of 2.60 CI 95%: 2.28–2.97)–almost double the risk of the two other groups. Maternal women also had a higher risk of needing intensive care, intubation and of presenting desaturation in the second period. Importantly, maternal women presented fewer comorbidities than other patient groups, suggesting that pregnancy and postpartum can be an important risk factor associated with severe COVID-19. Conclusion Our results suggest that the Gama variant, which has been related to greater virulence, transmissibility and mortality rates leads to more severe cases of COVID-19 for pregnant and postpartum women.

Severe Acute Respiratory Syndrome by COVID-19 in pregnant and postpartum women

2021 ◽  
Vol 21 (suppl 2) ◽  
pp. 461-469
Author(s):  
Ana Paula Nogueira Godoi ◽  
Gilcelia Correia Santos Bernardes ◽  
Nivea Aparecida de Almeida ◽  
Saulo Nascimento de Melo ◽  
Vinícius Silva Belo ◽  
...  
Keyword(s):  
Heart Disease ◽  
Severe Acute Respiratory Syndrome ◽  
Pregnant Women ◽  
Descriptive Analysis ◽  
Ventilatory Support ◽  
Clinical Manifestations ◽  
Morbidity And Mortality ◽  
Epidemiological Surveillance ◽  
Postpartum Women ◽  
Risk Of Death

Abstract Objectives: to evaluate the morbidity and mortality profile and factors associated with death due to severe acute respiratory syndrome (SARS) by COVID-19 in pregnant and postpartum women. Methods: this is a quantitative and retrospective research that analyzed the SIVEP-gripe Database (Influenza Epidemiological Surveillance Information System), from 01/01/2020 to 04/01/2021. All pregnant women and postpartum women diagnosed with SARS caused by COVID-19 in the State of Minas Gerais were included. After the descriptive analysis of the hospitalizations profile, the association between different exposure variables and the occurrence of death was evaluated. Results: of the 227 records obtained, 94.3% required hospitalization. Among hospitalizations in the Intensive Care Unit, 29.8% used invasive ventilatory support. Fifteen deaths were recorded. The most frequent clinical manifestations were: cough and fever; the predominant comorbidities were cardiovascular disease and diabetes mellitus. The variables “ICU stay”, “use of ventilatory support” and “heart disease” were associated with the occurrence of deaths. Conclusions: hospitalization was necessary for most pregnant women with SARS and the presence of previous heart disease increased the risk of death. Knowing the SARS morbidity and mortality profile is important in the definition of public health strategies aimed at reducing the impacts of COVID-19 during pregnancy and the puerperium.

scholarly journals After-Hours Discharge from Intensive Care Increases the Risk of Readmission and Death

2007 ◽  
Vol 35 (4) ◽  
pp. 477-485 ◽  
Author(s):  
D. V. Pilcher ◽  
G. J. Duke ◽  
C. George ◽  
M. J. Bailey ◽  
G. Hart
Keyword(s):  
Intensive Care ◽  
New Zealand ◽  
Odds Ratio ◽  
Readmission Rate ◽  
Mortality Rates ◽  
Risk Of Death ◽  
Prevalence Trends ◽  
Increased Risk ◽  
Patient Database ◽  
After Hours

Despite reports showing night discharge from an intensive care unit (ICU) is associated with increased mortality, it is unknown if this has resulted in changes in practice in recent years. Our aim was to determine prevalence, trends and effect on patient outcome of discharge timing from ICU throughout Australia and New Zealand. Two datasets from the Australian and New Zealand Intensive Care Society Adult Patient Database (ANZICS APD) were examined: 1. All submissions to the APD from 1.1.2003 to 31.12.2004 to determine contemporary practices. 2. Forty hospitals which had submitted continuous data between 1.1.2000 and 31.12.2004 to determine trends in practice over time. Outcomes investigated were hospital mortality and ICU readmission rate. Between 1.1.2003 and 31.12.2004, the ANZICS APD reported 76,690 patients discharged alive from ICU; 13,968 (18.2%) were discharged after-hours (between 1800 and 0559 hours). After-hours discharges had a higher readmission rate (6.3% vs. 5.1%; P= <0.0001) and higher mortality (8.0% vs. 5.3%; P= <0.0001). Peak readmission (8.6%) and mortality rates (9.7%) were seen in patients discharged between 0300 and 0400 hours. After-hours discharge was a predictor of mortality (odds ratio 1.42, 95% confidence interval 1.32-1.52; P= <0.0001) in multivariate analysis. Between 2000 and 2004, after-hours discharges increased (P=0.0015) with seasonal peaks during winter. The risk of death increased as the proportion of patients discharged after-hours rose. After-hours discharge from ICU is associated with increased risk of death and readmission to ICU. It has become more frequent. The risk of death increases as more after-hours discharges occur.

scholarly journals How important is obesity as a risk factor for respiratory failure, intensive care admission and death in hospitalised COVID-19 patients? Results from a single Italian centre

2020 ◽  
Vol 183 (4) ◽  
pp. 389-397 ◽  
Author(s):  
Matteo Rottoli ◽  
Paolo Bernante ◽  
Angela Belvedere ◽  
Francesca Balsamo ◽  
Silvia Garelli ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Risk Factor ◽  
Intensive Care ◽  
Respiratory Failure ◽  
Logistic Regression Analysis ◽  
Severe Illness ◽  
Intensive Care Admission ◽  
Risk Of Death ◽  
Design And Methods

Objective: Specific comorbidities and old age create a greater vulnerability to severe Coronavirus Disease 19 (COVID-19). While obesity seems to aggravate the course of disease, the actual impact of the BMI and the cutoff which increases illness severity are still under investigation. The aim of the study was to analyze whether the BMI represented a risk factor for respiratory failure, admission to the intensive care unit (ICU) and death. Research design and methods: A retrospective cohort study of 482 consecutive COVID-19 patients hospitalised between March 1 and April 20, 2020. Logistic regression analysis and Cox proportion Hazard models including demographic characteristics and comorbidities were carried out to predict the endpoints within 30 days from the onset of symptoms. Results: Of 482 patients, 104 (21.6%) had a BMI ≥ 30 kg/m2. At logistic regression analysis, a BMI between 30 and 34.9 kg/m2 significantly increased the risk of respiratory failure (OR: 2.32; 95% CI: 1.31–4.09, P = 0.004) and admission to the ICU (OR: 4.96; 95% CI: 2.53–9.74, P < 0.001). A significantly higher risk of death was observed in patients with a BMI ≥ 35 kg/m2 (OR: 12.1; 95% CI: 3.25–45.1, P < 0.001). Conclusions: Obesity is a strong, independent risk factor for respiratory failure, admission to the ICU and death among COVID-19 patients. A BMI ≥ 30 kg/m2 identifies a population of patients at high risk for severe illness, whereas a BMI ≥ 35 kg/m2 dramatically increases the risk of death.

scholarly journals Candidemia in intensive care units over nine years at a large Italian university hospital: Comparison with other wards

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252165
Author(s):  
Sara Mazzanti ◽  
Lucia Brescini ◽  
Gianluca Morroni ◽  
Elena Orsetti ◽  
Antonella Pocognoli ◽  
...  
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Antifungal Therapy ◽  
Cumulative Incidence ◽  
Mortality Rates ◽  
University Hospital ◽  
Icu Patients ◽  
Risk Of Death ◽  
Significant Difference ◽  
Over Time

Purpose Candidemia is an alarming problem in critically ill patients including those admitted in intensive care units (ICUs). We aimed to describe the clinical and microbiological characteristics of bloodstream infections (BSIs) due to Candida spp. in patients admitted to ICUs of an italian tertiary referral university hospital over nine years. Methods A retrospective observational study of all cases of candidemia in adult patients was carried out from January 1, 2010 to December 31, 2018 at a 980-bedded University Hospital in Ancona, Italy, counting five ICUs. The incidence, demographics, clinical and microbiologic characteristics, therapeutic approaches and outcomes of ICU-patients with candidemia were collected. Non-ICU patients with candidemia hospitalized during the same time period were considered for comparison purposes. Early (7 days from the occurrence of the episode of Candida BSI) and late (30 days) mortality rates were calculated. Results During the study period, 188/505 (36%) episodes of candidemia occurred in ICU patients. Cumulative incidence was 9.9/1000 ICU admission and it showed to be stable over time. Candida albicans accounted for 52% of the cases, followed by C. parapsilosis (24%), and C. glabrata (14%). There was not a significant difference in species distribution between ICU and non-ICU patients. With the exception of isolates of C. tropicalis which showed to be fluconazole resistant in 25% of the cases, resistance to antifungals was not of concern in our patients. Early and late mortality rates, were 19% and 41% respectively, the latter being significantly higher than that observed in non-ICU patients. At multivariate analysis, factors associated with increased risk of death were septic shock, acute kidney failure, pulmonary embolism and lack of antifungal therapy. The type of antifungal therapy did not influence the outcome. Mortality did not increased significantly over time. Conclusion Neither cumulative incidence nor crude mortality of candidemia in ICU patients increased over time at our institution. However, mortality rate remained high and significantly associated with specific host-related factors in the majority of cases.

scholarly journals Bacteremic sepsis leads to higher mortality when adjusting for confounders with propensity score matching

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lisa Mellhammar ◽  
Fredrik Kahn ◽  
Caroline Whitlow ◽  
Thomas Kander ◽  
Bertil Christensson ◽  
...  
Keyword(s):  
Intensive Care ◽  
Clinical Review ◽  
Pathogen Detection ◽  
Mortality Rates ◽  
Blood Cultures ◽  
Population Heterogeneity ◽  
Sepsis Diagnosis ◽  
Culture Positive ◽  
Culture Negative ◽  
Microbial Samples

AbstractOne can falsely assume that it is well known that bacteremia is associated with higher mortality in sepsis. Only a handful of studies specifically focus on the comparison of culture-negative and culture-positive sepsis with different conclusions depending on study design. The aim of this study was to describe outcome for critically ill patients with either culture-positive or -negative sepsis in a clinical review. We also aimed to identify subphenotypes of sepsis with culture status included as candidate clinical variables. Out of 784 patients treated in intensive care with a sepsis diagnosis, blood cultures were missing in 140 excluded patients and 95 excluded patients did not fulfill a sepsis diagnosis. Of 549 included patients, 295 (54%) had bacteremia, 90 (16%) were non-bacteremic but with relevant pathogens detected and in 164 (30%) no relevant pathogen was detected. After adjusting for confounders, 90-day mortality was higher in bacteremic patients, 47%, than in non-bacteremic patients, 36%, p = 0.04. We identified 8 subphenotypes, with different mortality rates, where pathogen detection in microbial samples were important for subphenotype distinction and outcome. In conclusion, bacteremic patients had higher mortality than their non-bacteremic counter-parts and bacteremia is more common in sepsis when studied in a clinical review. For reducing population heterogeneity and improve the outcome of trials and treatment for sepsis, distinction of subphenotypes might be useful and pathogen detection an important factor.

scholarly journals Early Prediction of Seven-Day Mortality in Intensive Care Unit Using a Machine Learning Model: Results from the SPIN-UTI Project

2021 ◽  
Vol 10 (5) ◽  
pp. 992
Author(s):  
Martina Barchitta ◽  
Andrea Maugeri ◽  
Giuliana Favara ◽  
Paolo Marco Riela ◽  
Giovanni Gallo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Learning Algorithm ◽  
Area Under The Curve ◽  
Support Vector ◽  
Icu Admission ◽  
Risk Of Death ◽  
Saps Ii ◽  
Svm Algorithm

Patients in intensive care units (ICUs) were at higher risk of worsen prognosis and mortality. Here, we aimed to evaluate the ability of the Simplified Acute Physiology Score (SAPS II) to predict the risk of 7-day mortality, and to test a machine learning algorithm which combines the SAPS II with additional patients’ characteristics at ICU admission. We used data from the “Italian Nosocomial Infections Surveillance in Intensive Care Units” network. Support Vector Machines (SVM) algorithm was used to classify 3782 patients according to sex, patient’s origin, type of ICU admission, non-surgical treatment for acute coronary disease, surgical intervention, SAPS II, presence of invasive devices, trauma, impaired immunity, antibiotic therapy and onset of HAI. The accuracy of SAPS II for predicting patients who died from those who did not was 69.3%, with an Area Under the Curve (AUC) of 0.678. Using the SVM algorithm, instead, we achieved an accuracy of 83.5% and AUC of 0.896. Notably, SAPS II was the variable that weighted more on the model and its removal resulted in an AUC of 0.653 and an accuracy of 68.4%. Overall, these findings suggest the present SVM model as a useful tool to early predict patients at higher risk of death at ICU admission.

scholarly journals A Timely Call to Arms: COVID-19, the Circadian Clock, and Critical Care

2021 ◽  
Vol 36 (1) ◽  
pp. 55-70
Author(s):  
Jeffrey Haspel ◽  
Minjee Kim ◽  
Phyllis Zee ◽  
Tanja Schwarzmeier ◽  
Sara Montagnese ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Human Physiology ◽  
Critical Care ◽  
Intensive Care ◽  
Severe Acute Respiratory Syndrome ◽  
Circadian Clock ◽  
Clinical Course ◽  
Disease Expression ◽  
Severe Manifestation ◽  
Novel Coronavirus

We currently find ourselves in the midst of a global coronavirus disease 2019 (COVID-19) pandemic, caused by the highly infectious novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we discuss aspects of SARS-CoV-2 biology and pathology and how these might interact with the circadian clock of the host. We further focus on the severe manifestation of the illness, leading to hospitalization in an intensive care unit. The most common severe complications of COVID-19 relate to clock-regulated human physiology. We speculate on how the pandemic might be used to gain insights on the circadian clock but, more importantly, on how knowledge of the circadian clock might be used to mitigate the disease expression and the clinical course of COVID-19.

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