SAPS-3 performance for hospital mortality prediction in 30,571 patients with COVID-19 admitted to ICUs in Brazil.
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ABSTRACT:
SUBMITTER: Kurtz P
PROVIDER: S-EPMC8270768 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
Publications
SAPS-3 performance for hospital mortality prediction in 30,571 patients with COVID-19 admitted to ICUs in Brazil.
Kurtz Pedro P Bastos Leonardo S L LSL Salluh Jorge I F JIF Bozza Fernando A FA Soares Marcio M
Intensive care medicine 20210710 9
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Project description:As a novel risk factor, COVID-19 has led to an increase in the incidence of candidemia and an elevated mortality rate. Despite being of clinical importance, there is a lack of data regarding COVID-19-associated candidemia (CAC) among Iranian patients. Therefore, in this retrospective study, we assessed CAC epidemiology in the intensive care units (ICUs) of two COVID-19 centers in Mashhad, Iran, from early November 2020 to late January 2021. Yeast isolates from patients' blood were identified by 21-plex polymerase chain reaction (PCR) and sequencing, then subjected to antifungal susceptibility testing according to the CLSI M27-A3 protocol. Among 1988 patients with COVID-19 admitted to ICUs, seven had fungemia (7/1988; 0.03%), among whom six had CAC. The mortality of the limited CAC cases was high and greatly exceeded that of patients with COVID-19 but without candidemia (100% (6/6) vs. 22.7% (452/1988)). In total, nine yeast isolates were collected from patients with fungemia: five Candida albicans, three C. glabrata, and one Rhodotorula mucilaginosa. Half of the patients infected with C. albicans (2/4) were refractory to both azoles and echinocandins. The high mortality of patients with CAC, despite antifungal therapy, reflects the severity of the disease in these patients and underscores the importance of rapid diagnosis and timely initiation of antifungal treatment.
| S-EPMC8068363 | biostudies-literature
Project description:BackgroundIllness predictive scoring systems are significant and meaningful adjuncts of patient management in the Intensive Care Unit (ICU). They assist in predicting patient outcomes, improve clinical decision making and provide insight into the effectiveness of care and management of patients while optimizing the use of hospital resources. We evaluated mortality predictive performance of Simplified Acute Physiology Score (SAPS 3) and Mortality Probability Models (MPM0-III) and compared their performance in predicting outcome as well as identifying disease pattern and factors associated with increased mortality.MethodsThis was a retrospective cohort study of adult patients admitted to the ICU of the Aga Khan Hospital, Dar- es- Salaam, Tanzania between August 2018 and April 2020. Demographics, clinical characteristics, outcomes, source of admission, primary admission category, length of stay and the support provided with the worst physiological data within the first hour of ICU admission were extracted. SAPS 3 and MPM0-III scores were calculated using an online web-based calculator. The performance of each model was assessed by discrimination and calibration. Discrimination between survivors and non-survivors was assessed by the area under the receiver operator characteristic curve (ROC) and calibration was estimated using the Hosmer-Lemeshow goodness-of-fit test.ResultsA total of 331 patients were enrolled in the study with a median age of 58 years (IQR 43-71), most of whom were male (n = 208, 62.8%), of African origin (n = 178, 53.8%) and admitted from the emergency department (n = 306, 92.4%). In- hospital mortality of critically ill patients was 16.1%. Discrimination was very good for all models, the area under the receiver-operating characteristic (ROC) curve for SAPS 3 and MPM0-III was 0.89 (95% CI [0.844-0.935]) and 0.90 (95% CI [0.864-0.944]) respectively. Calibration as calculated by Hosmer-Lemeshow goodness-of-fit test showed good calibration for SAPS 3 and MPM0-III with Chi- square values of 4.61 and 5.08 respectively and P-Value > 0.05.ConclusionBoth SAPS 3 and MPM0-III performed well in predicting mortality and outcome in our cohort of patients admitted to the intensive care unit of a private tertiary hospital. The in-hospital mortality of critically ill patients was lower compared to studies done in other intensive care units in tertiary referral hospitals within Tanzania.
| S-EPMC8603815 | biostudies-literature
Project description:BackgroundThe Simplified Acute Physiology Score (SAPS) 3 is a reliable score to predict mortality. This study aims to investigate the predictive values of SAPS 3 and other clinical parameters for death in critically ill coronavirus disease 2019 (COVID-19) patients.MethodsThis is a prospective study in a tertiary hospital for patients who required intensive care due to COVID-19 infection in northeast Brazil. Two distinct groups were constructed according to the epidemiological data: first wave and second wave. The severity of patients admitted was estimated using the SAPS 3 score.ResultsA total of 767 patients were included: 290 were enrolled in the first wave and 477 in the second wave. Patients in the first wave had more comorbidities, were put on mechanical ventilation and required dialysis and vasopressors more frequently (p<0.05). During the second wave, non-invasive ventilation was more often required (p<0.05). In both periods, older patients and higher SAPS 3 scores on admission were associated with death (p<0.05). Non-invasive ventilation use showed a negative association with death only in the second wave period. In the first wave, the SAPS 3 score was more useful (area under the curve [AUC] 0.897) in predicting death in critically ill COVID-19 patients than in the second wave (AUC 0.810).ConclusionThe SAPS 3 showed very reliable predictive values for death during the waves of the COVID-19 pandemic, mostly together with kidney and pulmonary dysfunction.
| S-EPMC9129229 | biostudies-literature
Project description:BackgroundThe ongoing Coronavirus disease of 2019 (COVID-19) pandemic has hit Brazil hard in period of different dominant variants. Different COIVD-19 variants have swept through the region, resulting that the total number of cases in Brazil is the third highest in the world. This study is aimed at investigating the regional heterogeneity of in-hospital mortality of COVID-19 in Brazil and the effects of vaccination and social inequality.MethodsWe fitted a multivariate mixed-effects Cox model to a national database of inpatient data in Brazil who were admitted for COVID-19 from February 27, 2020 to March 15, 2022. The in-hospital mortality risks of vaccinated and unvaccinated patients were compared, with adjustment for age, state, ethnicity, education and comorbidities. And the effects of variables to in-hospital mortality were also compared. Stratified analysis was conducted across different age groups and vaccine types.ResultsBy fitting the multivariate mixed-effects Cox model, we concluded that age was the most important risk factor for death. With regards to educational level, illiterate patients (hazard ratio: 1.63, 95% CI: 1.56-1.70) had a higher risk than those with a university or college degree. Some common comorbidities were more dangerous for hospitalized patients, such as liver disease (HR: 1.46, 95% CI: 1.34-1.59) and immunosuppression (HR:1.32, 95% CI: 1.26-1.40). In addition, the states involving Sergipe (HR: 1.75, 95% CI: 1.46-2.11), Roraima (HR: 1.65, 95% CI: 1.43-1.92), Maranhão (HR: 1.57, 95% CI: 1.38-1.79), Acre (HR: 1.44, 95% CI: 1.12-1.86), and Rondônia (HR: 1.26, 95% CI: 1.10-1.44) in the north and the northeast region tended to have higher hazard ratios than other area. In terms of vaccine protection, vaccination did not significantly reduce mortality among hospitalized patients. Sinovac and AstraZeneca offered different protection in different regions, and no vaccine provided high protection in all regions.ConclusionThe study revealed the regional heterogeneity of in-hospital mortality of Covid-19 in Brazil and the effects of vaccination and social inequality. We found that ethnic concentrations were consistent with higher proportion of death cases relative to population size. White Brazilians had more frequent international travel opportunities. As race revealed the intersection of social connections, we speculated that uneven interactions with residential communities partially contribute to the spread of the epidemic. Additionally, the vaccine showed different protection in different regions. In the northern and northeastern regions, AstraZeneca was much more protective than Sinovac, while Sinovac was more protective for hospitalized patients with varying numbers of comorbidities in the Central-west, Southeast and South regions.
| S-EPMC9250816 | biostudies-literature
Project description:BackgroundThe ongoing Coronavirus disease of 2019 (COVID-19) pandemic has hit Brazil hard in period of different dominant variants. Different COIVD-19 variants have swept through the region, resulting that the total number of cases in Brazil is the third highest in the world. This study is aimed at investigating the regional heterogeneity of in-hospital mortality of COVID-19 in Brazil and the effects of vaccination and social inequality.MethodsWe fitted a multivariate mixed-effects Cox model to a national database of inpatient data in Brazil who were admitted for COVID-19 from February 27, 2020 to March 15, 2022. The in-hospital mortality risks of vaccinated and unvaccinated patients were compared, with adjustment for age, state, ethnicity, education and comorbidities. And the effects of variables to in-hospital mortality were also compared. Stratified analysis was conducted across different age groups and vaccine types.ResultsBy fitting the multivariate mixed-effects Cox model, we concluded that age was the most important risk factor for death. With regards to educational level, illiterate patients (hazard ratio: 1.63, 95% CI: 1.56-1.70) had a higher risk than those with a university or college degree. Some common comorbidities were more dangerous for hospitalized patients, such as liver disease (HR: 1.46, 95% CI: 1.34-1.59) and immunosuppression (HR:1.32, 95% CI: 1.26-1.40). In addition, the states involving Sergipe (HR: 1.75, 95% CI: 1.46-2.11), Roraima (HR: 1.65, 95% CI: 1.43-1.92), Maranhão (HR: 1.57, 95% CI: 1.38-1.79), Acre (HR: 1.44, 95% CI: 1.12-1.86), and Rondônia (HR: 1.26, 95% CI: 1.10-1.44) in the north and the northeast region tended to have higher hazard ratios than other area. In terms of vaccine protection, vaccination did not significantly reduce mortality among hospitalized patients. Sinovac and AstraZeneca offered different protection in different regions, and no vaccine provided high protection in all regions.ConclusionThe study revealed the regional heterogeneity of in-hospital mortality of Covid-19 in Brazil and the effects of vaccination and social inequality. We found that ethnic concentrations were consistent with higher proportion of death cases relative to population size. White Brazilians had more frequent international travel opportunities. As race revealed the intersection of social connections, we speculated that uneven interactions with residential communities partially contribute to the spread of the epidemic. Additionally, the vaccine showed different protection in different regions. In the northern and northeastern regions, AstraZeneca was much more protective than Sinovac, while Sinovac was more protective for hospitalized patients with varying numbers of comorbidities in the Central-west, Southeast and South regions.
| S-EPMC9250816 | biostudies-literature
Project description:BackgroundThe ongoing Coronavirus disease of 2019 (COVID-19) pandemic has hit Brazil hard in period of different dominant variants. Different COIVD-19 variants have swept through the region, resulting that the total number of cases in Brazil is the third highest in the world. This study is aimed at investigating the regional heterogeneity of in-hospital mortality of COVID-19 in Brazil and the effects of vaccination and social inequality.MethodsWe fitted a multivariate mixed-effects Cox model to a national database of inpatient data in Brazil who were admitted for COVID-19 from February 27, 2020 to March 15, 2022. The in-hospital mortality risks of vaccinated and unvaccinated patients were compared, with adjustment for age, state, ethnicity, education and comorbidities. And the effects of variables to in-hospital mortality were also compared. Stratified analysis was conducted across different age groups and vaccine types.ResultsBy fitting the multivariate mixed-effects Cox model, we concluded that age was the most important risk factor for death. With regards to educational level, illiterate patients (hazard ratio: 1.63, 95% CI: 1.56-1.70) had a higher risk than those with a university or college degree. Some common comorbidities were more dangerous for hospitalized patients, such as liver disease (HR: 1.46, 95% CI: 1.34-1.59) and immunosuppression (HR:1.32, 95% CI: 1.26-1.40). In addition, the states involving Sergipe (HR: 1.75, 95% CI: 1.46-2.11), Roraima (HR: 1.65, 95% CI: 1.43-1.92), Maranhão (HR: 1.57, 95% CI: 1.38-1.79), Acre (HR: 1.44, 95% CI: 1.12-1.86), and Rondônia (HR: 1.26, 95% CI: 1.10-1.44) in the north and the northeast region tended to have higher hazard ratios than other area. In terms of vaccine protection, vaccination did not significantly reduce mortality among hospitalized patients. Sinovac and AstraZeneca offered different protection in different regions, and no vaccine provided high protection in all regions.ConclusionThe study revealed the regional heterogeneity of in-hospital mortality of Covid-19 in Brazil and the effects of vaccination and social inequality. We found that ethnic concentrations were consistent with higher proportion of death cases relative to population size. White Brazilians had more frequent international travel opportunities. As race revealed the intersection of social connections, we speculated that uneven interactions with residential communities partially contribute to the spread of the epidemic. Additionally, the vaccine showed different protection in different regions. In the northern and northeastern regions, AstraZeneca was much more protective than Sinovac, while Sinovac was more protective for hospitalized patients with varying numbers of comorbidities in the Central-west, Southeast and South regions.
| S-EPMC9250816 | biostudies-literature
Project description:ObjectivesThe coronavirus disease 2019 (COVID-19) pandemic has highlighted inequalities in access to healthcare systems, increasing racial disparities and worsening health outcomes in these populations. This study analysed the association between sociodemographic characteristics and COVID-19 in-hospital mortality in Brazil.Study designA retrospective analysis was conducted on quantitative reverse transcription polymerase chain reaction-confirmed hospitalised adult patients with COVID-19 with a defined outcome (i.e. hospital discharge or death) in Brazil. Data were retrieved from the national surveillance system database (SIVEP-Gripe) between February 16 and August 8, 2020.MethodsClinical characteristics, sociodemographic variables, use of hospital resources and outcomes of hospitalised adult patients with COVID-19, stratified by self-reported race, were investigated. The primary outcome was in-hospital mortality. The association between self-reported race and in-hospital mortality, after adjusting for clinical characteristics and comorbidities, was evaluated using a logistic regression model.ResultsDuring the study period, Brazil had 3,018,397 confirmed COVID-19 cases and 100,648 deaths. The study population included 228,196 COVID-19-positive adult in-hospital patients with a defined outcome; the median age was 61 years, 57% were men, 35% (79,914) self-reported as Black/Brown and 35.4% (80,853) self-reported as White. The total in-hospital mortality was 37% (85,171/228,196). Black/Brown patients showed higher in-hospital mortality than White patients (42% vs 37%, respectively), were admitted less frequently to the intensive care unit (ICU) (32% vs 36%, respectively) and used more invasive mechanical ventilation (21% vs 19%, respectively), especially outside the ICU (17% vs 11%, respectively). Black/Brown race was independently associated with high in-hospital mortality after adjusting for sex, age, level of education, region of residence and comorbidities (odds ratio = 1.15; 95% confidence interval = 1.09-1.22).ConclusionsAmong hospitalised Brazilian adults with COVID-19, Black/Brown patients showed higher in-hospital mortality, less frequently used hospital resources and had potentially more severe conditions than White patients. Racial disparities in health outcomes and access to health care highlight the need to actively implement strategies to reduce inequities caused by the wider health determinants, ultimately leading to a sustainable change in the health system.
| S-EPMC7836512 | biostudies-literature
Project description:Whether severe COVID-19 is by itself a significant risk factor for the development of candidemia currently remains an open question as conflicting results have been published. We aim to assess the occurrence of candidemia in patients with severe COVID-19 admitted to the intensive care unit (ICU). We conducted a retrospective study on patients with severe SARS-CoV-2-related pneumonia admitted to 5 ICUs in France who were specifically screened for fungal complications between March 2020 and January 2021. The study population included a total of 264 patients; the median age was 56 years old and most of them were male (n = 186; 70.5%) and immunocompetent (n = 225; 87.5%), and 62.7% (n = 153/244) were on extracorporeal membrane oxygenation support. Microbiological analysis included 4864 blood culture samples and beta-glucan test performed on 975 sera. Candidemia was diagnosed in 13 (4.9%) patients. The species involved were mainly C. albicans (n = 6) and C. parapsilosis (n = 5). Almost all patients (12/13; 92.3%) had a colonization by yeasts. ICU mortality was not significantly impacted by the occurrence of candidemia. Unrelated positive beta-glucan tests were observed in 49 patients (23.4%), including 6 with mold infections and 43 with false positive results. In our series, patients with severe SARS-CoV-2-related pneumonia seemed at low risk of developing invasive candidiasis.
| S-EPMC9320616 | biostudies-literature
Project description:ObjectiveTo develop predictive models for in-hospital mortality and length of stay (LOS) for coronavirus disease 2019 (COVID-19)-positive patients.Patients and methodsWe performed a multicenter retrospective cohort study of hospitalized COVID-19-positive patients. A total of 764 patients admitted to 14 different hospitals within the Cleveland Clinic from March 9, 2020, to May 20, 2020, who had reverse transcriptase-polymerase chain reaction-proven coronavirus infection were included. We used LightGBM, a machine learning algorithm, to predict in-hospital mortality at different time points (after 7, 14, and 30 days of hospitalization) and in-hospital LOS. Our final cohort was composed of 764 patients admitted to 14 different hospitals within our system.ResultsThe median LOS was 5 (range, 1-44) days for patients admitted to the regular nursing floor and 10 (range, 1-38) days for patients admitted to the intensive care unit. Patients who died during hospitalization were older, initially admitted to the intensive care unit, and more likely to be white and have worse organ dysfunction compared with patients who survived their hospitalization. Using the 10 most important variables only, the final model's area under the receiver operating characteristics curve was 0.86 for 7-day, 0.88 for 14-day, and 0.85 for 30-day mortality in the validation cohort.ConclusionWe developed a decision tool that can provide explainable and patient-specific prediction of in-hospital mortality and LOS for COVID-19-positive patients. The model can aid health care systems in bed allocation and distribution of vital resources.
| S-EPMC8114764 | biostudies-literature
Project description: Not available
| S-EPMC8131881 | biostudies-literature