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1.
Crit Care ; 26(1): 199, 2022 07 04.
Article in English | MEDLINE | ID: covidwho-1916967

ABSTRACT

BACKGROUND: It remains elusive how the characteristics, the course of disease, the clinical management and the outcomes of critically ill COVID-19 patients admitted to intensive care units (ICU) worldwide have changed over the course of the pandemic. METHODS: Prospective, observational registry constituted by 90 ICUs across 22 countries worldwide including patients with a laboratory-confirmed, critical presentation of COVID-19 requiring advanced organ support. Hierarchical, generalized linear mixed-effect models accounting for hospital and country variability were employed to analyse the continuous evolution of the studied variables over the pandemic. RESULTS: Four thousand forty-one patients were included from March 2020 to September 2021. Over this period, the age of the admitted patients (62 [95% CI 60-63] years vs 64 [62-66] years, p < 0.001) and the severity of organ dysfunction at ICU admission decreased (Sequential Organ Failure Assessment 8.2 [7.6-9.0] vs 5.8 [5.3-6.4], p < 0.001) and increased, while more female patients (26 [23-29]% vs 41 [35-48]%, p < 0.001) were admitted. The time span between symptom onset and hospitalization as well as ICU admission became longer later in the pandemic (6.7 [6.2-7.2| days vs 9.7 [8.9-10.5] days, p < 0.001). The PaO2/FiO2 at admission was lower (132 [123-141] mmHg vs 101 [91-113] mmHg, p < 0.001) but showed faster improvements over the initial 5 days of ICU stay in late 2021 compared to early 2020 (34 [20-48] mmHg vs 70 [41-100] mmHg, p = 0.05). The number of patients treated with steroids and tocilizumab increased, while the use of therapeutic anticoagulation presented an inverse U-shaped behaviour over the course of the pandemic. The proportion of patients treated with high-flow oxygen (5 [4-7]% vs 20 [14-29], p < 0.001) and non-invasive mechanical ventilation (14 [11-18]% vs 24 [17-33]%, p < 0.001) throughout the pandemic increased concomitant to a decrease in invasive mechanical ventilation (82 [76-86]% vs 74 [64-82]%, p < 0.001). The ICU mortality (23 [19-26]% vs 17 [12-25]%, p < 0.001) and length of stay (14 [13-16] days vs 11 [10-13] days, p < 0.001) decreased over 19 months of the pandemic. CONCLUSION: Characteristics and disease course of critically ill COVID-19 patients have continuously evolved, concomitant to the clinical management, throughout the pandemic leading to a younger, less severely ill ICU population with distinctly different clinical, pulmonary and inflammatory presentations than at the onset of the pandemic.


Subject(s)
COVID-19 , Pandemics , COVID-19/therapy , Critical Illness/epidemiology , Critical Illness/therapy , Female , Humans , Intensive Care Units , Middle Aged , Prospective Studies , Registries
2.
Eur J Radiol Open ; 9: 100431, 2022.
Article in English | MEDLINE | ID: covidwho-1906978

ABSTRACT

Purpose: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. Methods: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities. Results: In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19. Conclusions: This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive.

3.
Diagnostics (Basel) ; 12(5)2022 May 11.
Article in English | MEDLINE | ID: covidwho-1869507

ABSTRACT

BACKGROUND: COVID-19 superinfection by Aspergillus (COVID-19-associated aspergillosis, CAPA) is increasingly observed due to increased awareness and use of corticosteroids. The aim of this study is to compare clinical and imaging features between COVID-19 patients with and without associated pulmonary aspergillosis. MATERIAL AND METHODS: In this case-control study, hospitalized patients between March 2020 and March 2021 were evaluated. Two observers independently compared 105 chest CTs of 52 COVID-19 patients without pulmonary aspergillosis to 40 chest CTs of 13 CAPA patients. The following features were evaluated: lung involvement, predominant main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings. Chronological changes in the abnormal extent upon CT and chronological changes in the main patterns were compared with mixed models. Patient-wise comparisons of additional features and demographic and clinical data were performed using Student's t-test, Chi-squared test, Fisher's exact tests and Wilcoxon rank-sum tests. RESULTS: Compared to COVID-19 patients without pulmonary aspergillosis, CAPA patients were older (mean age (±SD): 70.3 (±7.8) versus 63.5 (±9.5) years (p = 0.01). The time-dependent evolution rates for consolidation (p = 0.02) and ground glass (p = 0.006) differed. In early COVID-19 disease, consolidation was associated with CAPA, whereas ground glass was less common. Chronological changes in the abnormal extent upon CT did not differ (p = 0.29). Regardless of the time point, bronchial wall thickening was observed more frequently in CAPA patients (p = 0.03). CONCLUSIONS: CAPA patients showed a tendency for consolidation in early COVID-19 disease. Bronchial wall thickening and higher patient age were associated with CAPA. The overall lung involvement was similar between both groups.

4.
Antimicrob Resist Infect Control ; 11(1): 12, 2022 01 21.
Article in English | MEDLINE | ID: covidwho-1643184

ABSTRACT

BACKGROUND: Despite the adoption of strict infection prevention and control measures, many hospitals have reported outbreaks of multidrug-resistant organisms (MDRO) during the Coronavirus 2019 (COVID-19) pandemic. Following an outbreak of carbapenem-resistant Acinetobacter baumannii (CRAB) in our institution, we sought to systematically analyse characteristics of MDRO outbreaks in times of COVID-19, focussing on contributing factors and specific challenges in controlling these outbreaks. METHODS: We describe results of our own CRAB outbreak investigation and performed a systematic literature review for MDRO (including Candida auris) outbreaks which occurred during the COVID-19 pandemic (between December 2019 and March 2021). Search terms were related to pathogens/resistance mechanisms AND COVID-19. We summarized outbreak characteristics in a narrative synthesis and contrasted contributing factors with implemented control measures. RESULTS: The CRAB outbreak occurred in our intensive care units between September and December 2020 and comprised 10 patients (thereof seven with COVID-19) within two distinct genetic clusters (both ST2 carrying OXA-23). Both clusters presumably originated from COVID-19 patients transferred from the Balkans. Including our outbreak, we identified 17 reports, mostly caused by Candida auris (n = 6) or CRAB (n = 5), with an overall patient mortality of 35% (68/193). All outbreaks involved intensive care settings. Non-adherence to personal protective equipment (PPE) or hand hygiene (n = 11), PPE shortage (n = 8) and high antibiotic use (n = 8) were most commonly reported as contributing factors, followed by environmental contamination (n = 7), prolonged critical illness (n = 7) and lack of trained HCW (n = 7). Implemented measures mainly focussed on PPE/hand hygiene audits (n = 9), environmental cleaning/disinfection (n = 9) and enhanced patient screening (n = 8). Comparing potentially modifiable risk factors and control measures, we found the largest discrepancies in the areas of PPE shortage (risk factor in 8 studies, addressed in 2 studies) and patient overcrowding (risk factor in 5 studies, addressed in 0 studies). CONCLUSIONS: Reported MDRO outbreaks during the COVID-19 pandemic were most often caused by CRAB (including our outbreak) and C. auris. Inadequate PPE/hand hygiene adherence, PPE shortage, and high antibiotic use were the most commonly reported potentially modifiable factors contributing to the outbreaks. These findings should be considered for the prevention of MDRO outbreaks during future COVID-19 waves.


Subject(s)
Acinetobacter Infections/prevention & control , Acinetobacter baumannii , COVID-19/complications , COVID-19/epidemiology , Candidiasis/prevention & control , Pandemics , SARS-CoV-2 , Acinetobacter Infections/complications , Acinetobacter baumannii/drug effects , Aged , Candidiasis/complications , Carbapenems/pharmacology , Cross Infection/prevention & control , Disease Outbreaks/prevention & control , Drug Resistance, Multiple, Bacterial , Female , Humans , Infection Control/methods , Male , Middle Aged , Retrospective Studies , Switzerland/epidemiology
5.
Crit Care ; 25(1): 175, 2021 05 25.
Article in English | MEDLINE | ID: covidwho-1243815

ABSTRACT

BACKGROUND: Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. METHODS: Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups. RESULTS: Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016). CONCLUSION: In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk.


Subject(s)
COVID-19/therapy , Critical Illness/therapy , Respiratory Therapy/methods , Respiratory Therapy/statistics & numerical data , Aged , COVID-19/mortality , Critical Illness/mortality , Disease Progression , Female , Hospital Mortality , Humans , Intensive Care Units , Male , Middle Aged , Prospective Studies , Registries , Retrospective Studies , Time Factors , Treatment Outcome
6.
PLoS One ; 16(2): e0247265, 2021.
Article in English | MEDLINE | ID: covidwho-1090541

ABSTRACT

RATIONALE: The COVID-19 pandemic induces considerable strain on intensive care unit resources. OBJECTIVES: We aim to provide early predictions of individual patients' intensive care unit length of stay, which might improve resource allocation and patient care during the on-going pandemic. METHODS: We developed a new semiparametric distributional index model depending on covariates which are available within 24h after intensive care unit admission. The model was trained on a large cohort of acute respiratory distress syndrome patients out of the Minimal Dataset of the Swiss Society of Intensive Care Medicine. Then, we predict individual length of stay of patients in the RISC-19-ICU registry. MEASUREMENTS: The RISC-19-ICU Investigators for Switzerland collected data of 557 critically ill patients with COVID-19. MAIN RESULTS: The model gives probabilistically and marginally calibrated predictions which are more informative than the empirical length of stay distribution of the training data. However, marginal calibration was worse after approximately 20 days in the whole cohort and in different subgroups. Long staying COVID-19 patients have shorter length of stay than regular acute respiratory distress syndrome patients. We found differences in LoS with respect to age categories and gender but not in regions of Switzerland with different stress of intensive care unit resources. CONCLUSION: A new probabilistic model permits calibrated and informative probabilistic prediction of LoS of individual patients with COVID-19. Long staying patients could be discovered early. The model may be the basis to simulate stochastic models for bed occupation in intensive care units under different casemix scenarios.


Subject(s)
COVID-19/mortality , COVID-19/therapy , Hospital Mortality , Hospitalization , Intensive Care Units , Length of Stay , Models, Biological , SARS-CoV-2 , Aged , Female , Humans , Male , Middle Aged , Switzerland/epidemiology
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