Point-of-care ultrasonography for risk stratification of non-critical suspected COVID-19 patients on admission (POCUSCO): A prospective binational study.

BACKGROUND: Lung point-of-care ultrasonography (L-POCUS) is highly effective in detecting pulmonary peripheral patterns and may allow early identification of patients who are likely to develop an acute respiratory distress syndrome (ARDS). We hypothesized that L-POCUS performed within the first 48 hours of non-critical patients with suspected COVID-19 would identify those with a high-risk of worsening. METHODS: POCUSCO was a prospective, multicenter study. Non-critical adult patients who presented to the emergency department (ED) for suspected or confirmed COVID-19 were included and had L-POCUS performed within 48 hours following ED presentation. The lung damage severity was assessed using a previously developed score reflecting both the extension and the intensity of lung damage. The primary outcome was the rate of patients requiring intubation or who died within 14 days following inclusion. RESULTS: Among 296 patients, 8 (2.7%) met the primary outcome. The area under the curve (AUC) of L-POCUS was 0.80 [95%CI:0.60-0.94]. The score values which achieved a sensibility >95% in defining low-risk patients and a specificity >95% in defining high-risk patients were <1 and ≥16, respectively. The rate of patients with an unfavorable outcome was 0/95 (0%[95%CI:0-3.9]) for low-risk patients (score = 0), 4/184 (2.17%[95%CI:0.8-5.5]) for intermediate-risk patients (score 1-15) and 4/17 (23.5%[95%CI:11.4-42.4]) for high-risk patients (score ≥16). In confirmed COVID-19 patients (n = 58), the AUC of L-POCUS was 0.97 [95%CI:0.92-1.00]. CONCLUSION: L-POCUS performed within the first 48 hours following ED presentation allows risk-stratification of patients with non-severe COVID-19.

Management and Outcome of COVID-19 Positive and Negative Patients in French Emergency Departments During the First COVID-19 Outbreak: A Prospective Controlled Cohort Study.

INTRODUCTION: Few studies have investigated the management of COVID-19 cases from the operational perspective of the emergency department (ED), We sought to compare the management and outcome of COVID-19 positive and negative patients who presented to French EDs. METHODS: We conducted a prospective, multicenter, observational study in four EDs. Included in the study were adult patients (≥18 years) between March 6-May 10, 2020, were hospitalized, and whose presenting symptoms were evocative of COVID-19. We compared the clinical features, management, and prognosis of patients according to their confirmed COVID-19 status. RESULTS: Of the 2,686 patients included in this study, 760 (28.3%) were COVID-19 positive. Among them, 364 (48.0%) had hypertension, 228 (30.0%) had chronic cardiac disease, 186 (24.5%) had diabetes, 126 (16.6%) were obese, and 114 (15.0%) had chronic respiratory disease. The proportion of patients admitted to intensive care units (ICU) was higher among COVID-19 positive patients (185/760, 24.3%) compared to COVID-19 negative patients (206/1,926, 10.7%; P <0.001), and they required mechanical ventilation (89, 11.9% vs 37, 1.9%; P <0.001) and high-flow nasal cannula oxygen therapy (135, 18.1% vs 41, 2.2%; P < 0.001) more frequently. The in-hospital mortality was significantly higher among COVID-19 positive patients (139, 18.3% vs 149, 7.7%; P <0.001). CONCLUSION: Emergency departments were on the frontline during the COVID-19 pandemic and had to manage potential COVID-19 patients. Understanding what happened in the ED during this first outbreak is crucial to underline the importance of flexible organizations that can quickly adapt the bed capacities to the incoming flow of COVID-19 positive patients.

Additional value of chest CT AI-based quantification of lung involvement in predicting death and ICU admission for COVID-19 patients.

Objectives: We evaluated the contribution of lung lesion quantification on chest CT using a clinical Artificial Intelligence (AI) software in predicting death and intensive care units (ICU) admission for COVID-19 patients. Methods: For 349 patients with positive COVID-19-PCR test that underwent a chest CT scan at admittance or during hospitalization, we applied the AI for lung and lung lesion segmentation to obtain lesion volume (LV), and LV/Total Lung Volume (TLV) ratio. ROC analysis was used to extract the best CT criterion in predicting death and ICU admission. Two prognostic models using multivariate logistic regressions were constructed to predict each outcome and were compared using AUC values. The first model ("Clinical") was based on patients' characteristics and clinical symptoms only. The second model ("Clinical+LV/TLV") included also the best CT criterion. Results: LV/TLV ratio demonstrated best performance for both outcomes; AUC of 67.8% (95% CI: 59.5 - 76.1) and 81.1% (95% CI: 75.7 - 86.5) respectively. Regarding death prediction, AUC values were 76.2% (95% CI: 69.9 - 82.6) and 79.9% (95%IC: 74.4 - 85.5) for the "Clinical" and the "Clinical+LV/TLV" models respectively, showing significant performance increase (+ 3.7%; p-value<0.001) when adding LV/TLV ratio. Similarly, for ICU admission prediction, AUC values were 74.9% (IC 95%: 69.2 - 80.6) and 84.8% (IC 95%: 80.4 - 89.2) respectively corresponding to significant performance increase (+ 10%: p-value<0.001). Conclusions: Using a clinical AI software to quantify the COVID-19 lung involvement on chest CT, combined with clinical variables, allows better prediction of death and ICU admission.

Changes over time in anxiety, depression, and stress symptoms among healthcare workers in French emergency departments during the first COVID-19 outbreak.

STUDY OBJECTIVE: Assess the changes in anxiety, depression, and stress levels over time and identify risk factors among healthcare workers in French emergency departments (EDs) during the first COVID-19 outbreak. METHOD: A prospective, multicenter study was conducted in 4 EDs and an emergency medical service (SAMU). During 3 months, participants completed fortnightly questionnaires to assess anxiety, depression, and stress using the Hospital Anxiety and Depression and the Chamoux-Simard scale. The changes in anxiety, depression, and stress levels over time were modelled by a linear mixed model including a period effect and a continuous time effect within periods. RESULTS: A total of 211 respondents (43.5 %) completed the survey at inclusion. There was a decrease in mean anxiety (from 7.33 to 5.05, p < 0.001), mean depression (from 4.16 to 3.05, p = 0.009), mean stress at work (from 41.2 to 30.2, p = 0.008), and mean stress at home (from 33.0 to 26.0, p = 0.031) at the beginning of each period. The mean anxiety level was higher for administrative staff (+0.53) and lower for paramedics (-0.61, p = 0.047) compared to physicians. The anxiety level increased with the number of day and night shifts (0.13/day, p < 0.001, 0.12/night, p = 0.025) as did stress at work (1.6/day, p < 0.001, 1.1/night, p = 0.007). Reassigned healthcare workers were at higher risk of stress particularly compared to SAMU workers (stress at work: p = 0.015, at home: p = 0.021, in life in general: p = 0.018). CONCLUSION: Although anxiety, depression, and stress decreased over time, anxiety was higher among physicians and administrative staff. Reassignment and working hours were identified as potential risk factors for mental health distress in EDs.

Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France.

BACKGROUND: COVID-19 pandemic highlighted the need for real-time monitoring of diseases evolution to rapidly adapt restrictive measures. This prospective multicentric study aimed at investigating radiological markers of COVID-19-related emergency activity as global estimators of pandemic evolution in France. We incorporated two sources of data from March to November 2020: an open-source epidemiological dataset, collecting daily hospitalisations, intensive care unit admissions, hospital deaths and discharges, and a teleradiology dataset corresponding to the weekly number of CT-scans performed in 65 emergency centres and interpreted remotely. CT-scans specifically requested for COVID-19 suspicion were monitored. Teleradiological and epidemiological time series were aligned. Their relationships were estimated through a cross-correlation function, and their extremes and breakpoints were compared. Dynamic linear models were trained to forecast the weekly hospitalisations based on teleradiological activity predictors. RESULTS: A total of 100,018 CT-scans were included over 36 weeks, and 19,133 (19%) performed within the COVID-19 workflow. Concomitantly, 227,677 hospitalisations were reported. Teleradiological and epidemiological time series were almost perfectly superimposed (cross-correlation coefficients at lag 0: 0.90-0.92). Maximal number of COVID-19 CT-scans was reached the week of 2020-03-23 (1 086 CT-scans), 1 week before the highest hospitalisations (23,542 patients). The best valid forecasting model combined the number of COVID-19 CT-scans and the number of hospitalisations during the prior two weeks and provided the lowest mean absolute percentage (5.09%, testing period: 2020-11-02 to 2020-11-29). CONCLUSION: Monitoring COVID-19 CT-scan activity in emergencies accurately and instantly predicts hospitalisations and helps adjust medical resources, paving the way for complementary public health indicators.

[White plan and the organisation of emergency response services in France]. / Plan blanc et organisation des secours en France.

The Eemergency plans for outside hospitals (ORSEC) and inside hospitals (white plan) are often linked and must be well structured in order to respond to the tensions created by exceptional health situations. They must be designed, used and updated like toolboxes. How is the chain of care organised? What is the role of the samu (emergency medical assistance service) in the preparation, activation and coordination of the white plan?

Teleradiology as a relevant indicator of the impact of COVID-19 pandemic management on emergency room activities: a nationwide worrisome survey.

OBJECTIVES: To evaluate the impact of COVID-19's lockdown on radiological examinations in emergency services. METHODS: Retrospective, multicentre analysis of radiological examinations requested, via our teleradiology network, from 2017 to 2020 during two timeframes (calendar weeks 5-8 and then 12-15). We included CT scans or MRIs performed for strokes, multiple traumas (Body-CT), cranial traumas (CTr) and acute non-traumatic abdominal pain (ANTAP). We evaluated the number and percentages of examinations performed, of those with a pathological conclusion, and of examinations involving the chest. RESULTS: Our study included 25 centres in 2017, 29 in 2018, 43 in 2019 and 59 in 2020. From 2017 to 2019, the percentages of examinations were constant, which was also true for chest CTs. Each centre's number of examinations, gender distribution and patient ages were unchanged. In 2020, examinations significantly decreased: suspected strokes decreased by 36% (1052 vs 675, p < 0.001), Body-CT by 62% (349 vs 134, p < 0.001), CTr by 52% (1853 vs 895, p < 0.001) and for ANTAP, appendicitis decreased by 38% (45 vs 90, not statistically significant (NS)) sigmoiditis by 44% (98 vs 55, NS), and renal colic by 23% (376 vs 288, NS). The number of examinations per centre decreased by 13% (185.5 vs 162.5, p < 0.001), whereas the number of examinations of the "chest" region increased by 170% (1205 vs 3766, p < 0.001). CONCLUSION: Teleradiology enabled us to monitor the impact of the COVID-19 pandemic management on emergency activities, showing a global decrease in the population's use of care.

Effect of the COVID-19 pandemic on acute stroke reperfusion therapy: data from the Lyon Stroke Center Network.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic would have particularly affected acute stroke care. However, its impact is clearly inherent to the local stroke network conditions. We aimed to assess the impact of COVID-19 pandemic on acute stroke care in the Lyon comprehensive stroke center during this period. METHODS: We conducted a prospective data collection of patients with acute ischemic stroke (AIS) treated with intravenous thrombolysis (IVT) and/or mechanical thrombectomy (MT) during the COVID-19 period (from 29/02/2020 to 10/05/2020) and a control period (from 29/02/2019 to 10/05/2019). The volume of reperfusion therapies and pre and intra-hospital delays were compared during both periods. RESULTS: A total of 208 patients were included. The volume of IVT significantly decreased during the COVID-period [55 (54.5%) vs 74 (69.2%); p = 0.03]. The volume of MT remains stable over the two periods [72 (71.3%) vs 65 (60.8%); p = 0.14], but the door-to-groin puncture time increased in patients transferred for MT (237 [187-339] vs 210 [163-260]; p < 0.01). The daily number of Emergency Medical Dispatch calls considerably increased (1502 [1133-2238] vs 1023 [960-1410]; p < 0.01). CONCLUSIONS: Our study showed a decrease in the volume of IVT, whereas the volume of MT remained stable although intra-hospital delays increased for transferred patients during the COVID-19 pandemic. These results contrast in part with the national surveys and suggest that the impact of the pandemic may depend on local stroke care networks.