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1.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-307237

ABSTRACT

Background: The rapid spread of coronavirus disease COVID 19 calls for early screening and monitoring of these patients to distinguish those that are likely to worsen from stable patients that may be directed to intermediate care facilities. We designed a score for COVID-19 patients severity assessment, dynamic intubation and prolonged stay prediction using the Breathing Frequency (BF) and oxygen saturation (SPO2) signals. Methods: We recorded BF, and SPO2 signals of confirmed COVID-19 patients admitted during the first and second outbreak of the pandemic in France (March to May 2020 and September 2020 to February 2021) in an ICU of a teaching hospital. We extracted four features from the signals that represent the four last hours before intubation for intubated patients and the mean of the four hours before the median intubation time for non-intubated patients. These data were used to train AI algorithms for intubation recognition. Algorithm robustness was checked on a validation set of patients. We selected the best algorithm that was applied every hour to predict intubation, thus a severity evaluation. We performed a 24h moving average of these predictions giving a S 24 severity score that represent the patient's severity during the last 24 h. MS 24 , the maximum of S 24 was confronted with the risk of intubation and prolonged ICU stay (>5 days). Results: We included 177 patients. Among the tested algorithms, the Logistic regression classifier had the best performance. The model had an accuracy of 88.9 % for intubation recognition (AUC=0.92). The accuracy on the validation set was 92.6 %. The S 24 score of intubated patients was significantly higher than non-intubated patients 48h before intubation and increased 24 hours before intubation. MS 24 score allows distinguishing three severity situations with an increased risk of intubation: green (3%), orange (30%) and red (76%). A MS 24 score superior to 20 was highly predictive of an ICU stay greater than 5 day with an accuracy of 88.8% (AUC=0.95). Conclusions: The score we designed uses simple signals and seems to be efficient to visualize the patient's respiratory situation and may help in decision-making. Real-time computation is easy to implement.

2.
SSRN;
Preprint in English | SSRN | ID: ppcovidwho-325830

ABSTRACT

Background: Severe COVID-19 is associated with exaggerated complement activation. We assessed the efficacy and safety of avdoralimab (an anti-C5aR1 mAb) in severe COVID-19. Methods: FORCE was a double-blind, placebo-controlled study. Patients receiving oxygen support ≥5 L/min to maintain SpO2 > 93% (WHO scale ≥ 5) were randomly assigned, in a 1:1 ratio to the avdoralimab and placebo arms. Avdoralimab (500 mg loading dose followed by a 200 mg maintenance dose) or placebo (normal saline) was administered intravenously every 48 h until oxygen therapy was no longer needed, and for a maximum of 14 days. Patients received conventional oxygen therapy or high-flow oxygen (HFO)/non-invasive ventilation (NIV) in cohort 1;HFO, NIV or invasive mechanical ventilation (IMV) in cohort 2 and IMV in cohort 3. The primary outcome was clinical status on the WHO ordinal scale at days 14 and 28 for cohorts 1 and 3, and the number of ventilator-free days at day 28 (VFD28) for cohort 2. Findings: Between May 2020 and January 2021, we randomized 207 patients: 99 in cohort 1, 49 in cohort 2 and 59 in cohort 3. Glucocorticoids were administered to 95% of patients during hospitalization. Avdoralimab did not improve WHO clinical scale score on days 14 and 28 (between-group difference on day 28 of -0.26 (95% CI, -1.2 to 0.7, p =0.7) in cohort 1 and -0.28 (95% CI, -1.8 to 1.2, p =0.6) in cohort 3). Avdoralimab did not improve VFD28 in cohort 2 (between-group difference of -6.3 (95% CI, -13.2 to 0.7, p =0.96), or secondary outcomes in any cohort. No subgroup of interest was identified. Interpretation: In this randomized trial in hospitalized patients with severe COVID-19 pneumonia, avdoralimab did not significantly improve clinical status at days 14 or 28.

3.
Comput Biol Med ; 142: 105192, 2022 03.
Article in English | MEDLINE | ID: covidwho-1588022

ABSTRACT

BACKGROUND: We designed an algorithm to assess COVID-19 patients severity and dynamic intubation needs and predict their length of stay using the breathing frequency (BF) and oxygen saturation (SpO2) signals. METHODS: We recorded the BF and SpO2 signals for confirmed COVID-19 patients admitted to the ICU of a teaching hospital during both the first and subsequent outbreaks of the pandemic in France. An unsupervised machine-learning algorithm (the Gaussian mixture model) was applied to the patients' data for clustering. The algorithm's robustness was ensured by comparing its results against actual intubation rates. We predicted intubation rates using the algorithm every hour, thus conducting a severity evaluation. We designed a S24 severity score that represented the patient's severity over the previous 24 h; the validity of MS24, the maximum S24 score, was checked against rates of intubation risk and prolonged ICU stay. RESULTS: Our sample included 279 patients. . The unsupervised clustering had an accuracy rate of 87.8% for intubation recognition (AUC = 0.94, True Positive Rate 86.5%, true Negative Rate 90.9%). The S24 score of intubated patients was significantly higher than that of non-intubated patients at 48 h before intubation. The MS24 score allowed for the distinguishing between three severity levels with an increased risk of intubation: green (3.4%), orange (37%), and red (77%). A MS24 score over 40 was highly predictive of an ICU stay greater than 5 days at an accuracy rate of 81.0% (AUC = 0.87). CONCLUSIONS: Our algorithm uses simple signals and seems to efficiently visualize the patients' respiratory situations, meaning that it has the potential to assist staffs' in decision-making. Additionally, real-time computation is easy to implement.


Subject(s)
COVID-19 , Triage , Critical Care , Humans , Retrospective Studies , SARS-CoV-2 , Unsupervised Machine Learning
4.
Anaesth Crit Care Pain Med ; 40(4): 100931, 2021 08.
Article in English | MEDLINE | ID: covidwho-1306763

ABSTRACT

AIM: Describing acute respiratory distress syndrome patterns, therapeutics management, and outcomes of ICU COVID-19 patients and indentifying risk factors of 28-day mortality. METHODS: Prospective multicentre, cohort study conducted in 29 French ICUs. Baseline characteristics, comorbidities, adjunctive therapies, ventilatory support at ICU admission and survival data were collected. RESULTS: From March to July 2020, 966 patients were enrolled with a median age of 66 (interquartile range 58-73) years and a median SAPS II of 37 (29-48). During the first 24 h of ICU admission, COVID-19 patients received one of the following respiratory supports: mechanical ventilation for 559 (58%), standard oxygen therapy for 228 (24%) and high-flow nasal cannula (HFNC) for 179 (19%) patients. Overall, 721 (75%) patients were mechanically ventilated during their ICU stay. Prone positioning and neuromuscular blocking agents were used in 494 (51%) and 460 (48%) patients, respectively. Bacterial co-infections and ventilator-associated pneumonia were diagnosed in 79 (3%) and 411 (43%) patients, respectively. The overall 28-day mortality was 18%. Age, pre-existing comorbidities, severity of respiratory failure and the absence of antiviral therapy on admission were identified as independent predictors of 28-day outcome. CONCLUSION: Severity of hypoxaemia on admission, older age (> 70 years), cardiovascular and renal comorbidities were associated with worse outcome in COVID-19 patients. Antiviral treatment on admission was identified as a protective factor for 28-day mortality. Ascertaining the outcomes of critically ill COVID-19 patients is crucial to optimise hospital and ICU resources and provide the appropriate intensity level of care.


Subject(s)
COVID-19 , SARS-CoV-2 , Aged , Cohort Studies , Critical Care , Humans , Intensive Care Units , Middle Aged , Prospective Studies , Respiration, Artificial
6.
Aust Crit Care ; 34(2): 160-166, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1053209

ABSTRACT

BACKGROUND: A high number of thrombotic complications have been reported in critically ill patients with coronavirus disease 2019 (COVID-19) and appear to be related to a hypercoagulable state. Evidence regarding detection, management, and monitoring of COVID-19-associated coagulopathy is still missing. We propose to describe the thrombus viscoelastic properties to investigate the mechanisms of hypercoagulability in patients with COVID-19. METHODS: Thromboelastography (TEG) was performed in 24 consecutive patients admitted to a single intensive care unit for COVID-19 pneumonia, and 10 had a second TEG before being discharged alive from the intensive care unit. RESULTS: Compared with a group of 20 healthy participants, patients with COVID-19 had significantly decreased values of reaction time, coagulation time, and lysis index and increased values of α angle, maximum amplitude, clot strength, and coagulation index. Velocity curves were consistent with increased generation of thrombin. These values persisted in surviving patients despite their good clinical course. DISCUSSION: In patients with COVID-19, TEG demonstrates a complex and prolonged hypercoagulable state including fast initiation of coagulation and clot reinforcement, low fibrinolysis, high potential of thrombin generation, and high fibrinogen and platelet contribution. The antithrombotic strategy in patients with COVID-19 during intensive care hospitalisation and after discharge should be investigated in further studies.


Subject(s)
COVID-19/blood , Pneumonia, Viral/blood , Thrombelastography , Thrombophilia/diagnosis , Thrombophilia/virology , Aged , Female , Humans , Intensive Care Units , Male , Middle Aged , Pneumonia, Viral/virology , SARS-CoV-2
7.
Nature ; 588(7836): 146-150, 2020 12.
Article in English | MEDLINE | ID: covidwho-690324

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has resulted in a pandemic1. The C5a complement factor and its receptor C5aR1 (also known as CD88) have a key role in the initiation and maintenance of several inflammatory responses by recruiting and activating neutrophils and monocytes1. Here we provide a longitudinal analysis of immune responses, including phenotypic analyses of immune cells and assessments of the soluble factors that are present in the blood and bronchoalveolar lavage fluid of patients at various stages of COVID-19 severity, including those who were paucisymptomatic or had pneumonia or acute respiratory distress syndrome. The levels of soluble C5a were increased in proportion to the severity of COVID-19 and high expression levels of C5aR1 receptors were found in blood and pulmonary myeloid cells, which supports a role for the C5a-C5aR1 axis in the pathophysiology of acute respiratory distress syndrome. Anti-C5aR1 therapeutic monoclonal antibodies prevented the C5a-mediated recruitment and activation of human myeloid cells, and inhibited acute lung injury in human C5aR1 knock-in mice. These results suggest that blockade of the C5a-C5aR1 axis could be used to limit the infiltration of myeloid cells in damaged organs and prevent the excessive lung inflammation and endothelialitis that are associated with acute respiratory distress syndrome in patients with COVID-19.


Subject(s)
COVID-19/complications , COVID-19/immunology , Complement C5a/immunology , Inflammation/complications , Inflammation/immunology , Receptor, Anaphylatoxin C5a/immunology , Acute Lung Injury/drug therapy , Acute Lung Injury/immunology , Acute Lung Injury/prevention & control , Animals , Bronchoalveolar Lavage Fluid/chemistry , Bronchoalveolar Lavage Fluid/immunology , CD11b Antigen/immunology , CD11b Antigen/metabolism , COVID-19/blood , COVID-19/pathology , Complement C5a/antagonists & inhibitors , Complement C5a/biosynthesis , Cytokine Release Syndrome/drug therapy , Cytokine Release Syndrome/immunology , Cytokine Release Syndrome/prevention & control , Disease Models, Animal , Female , Humans , Inflammation/drug therapy , Inflammation/pathology , Lung/drug effects , Lung/immunology , Lung/pathology , Mice , Mice, Inbred C57BL , Myeloid Cells/drug effects , Myeloid Cells/immunology , Myeloid Cells/pathology , Receptor, Anaphylatoxin C5a/antagonists & inhibitors , Receptor, Anaphylatoxin C5a/blood , Respiratory Distress Syndrome/drug therapy , Respiratory Distress Syndrome/immunology , Respiratory Distress Syndrome/prevention & control , SARS-CoV-2/drug effects , SARS-CoV-2/immunology , SARS-CoV-2/pathogenicity
8.
Head Neck ; 42(7): 1361-1362, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-141533

ABSTRACT

As an aerosol and droplets generating procedure, tracheostomy increases contamination risks for health workers in the coronavirus disease context. To preserve the health care system capacity and to limit virus cross-transmission, protecting caregivers against coronavirus infection is of critical importance. We report the use of external fixator equipment to set up a physical interface between the patient's neck and the caregiver performing a tracheostomy in COVID-19 patients. Once the metal frame set in place, it is wrapped with a single-use clear and sterile cover for surgical C-arm. This installation is simple, easy, and fast to achieve and can be carried out with inexpensive material available in every hospital. This physical interface is an additional safety measure that prevents the direct projection of secretions or droplets. It should, of course, only be considered as a complement to strict compliance with barrier precautions and personal protective equipment.


Subject(s)
Coronavirus Infections/prevention & control , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Occupational Health , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Protective Devices/statistics & numerical data , Tracheostomy/methods , COVID-19 , China , Coronavirus Infections/epidemiology , Equipment Design , Female , Health Personnel/statistics & numerical data , Humans , Infection Control/methods , Male , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Tracheostomy/instrumentation
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