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1.
Research in Diagnostic and Interventional Imaging ; 1:100003-100003, 2022.
Article in English | EuropePMC | ID: covidwho-1755536

ABSTRACT

Objectives 1) To develop a deep learning (DL) pipeline allowing quantification of COVID-19 pulmonary lesions on low-dose computed tomography (LDCT). 2) To assess the prognostic value of DL-driven lesion quantification. Methods This monocentric retrospective study included training and test datasets taken from 144 and 30 patients, respectively. The reference was the manual segmentation of 3 labels: normal lung, ground-glass opacity(GGO) and consolidation(Cons). Model performance was evaluated with technical metrics, disease volume and extent. Intra- and interobserver agreement were recorded. The prognostic value of DL-driven disease extent was assessed in 1621 distinct patients using C-statistics. The end point was a combined outcome defined as death, hospitalization>10 days, intensive care unit hospitalization or oxygen therapy. Results The Dice coefficients for lesion (GGO+Cons) segmentations were 0.75±0.08, exceeding the values for human interobserver (0.70±0.08;0.70±0.10) and intraobserver measures (0.72±0.09). DL-driven lesion quantification had a stronger correlation with the reference than inter- or intraobserver measures. After stepwise selection and adjustment for clinical characteristics, quantification significantly increased the prognostic accuracy of the model (0.82 vs. 0.90;p<0.0001). Conclusions A DL-driven model can provide reproducible and accurate segmentation of COVID-19 lesions on LDCT. Automatic lesion quantification has independent prognostic value for the identification of high-risk patients.

2.
Rev Cardiovasc Med ; 22(3): 1063-1072, 2021 09 24.
Article in English | MEDLINE | ID: covidwho-1439023

ABSTRACT

We evaluated the age-specific mortality of unselected adult outpatients infected with SARS-CoV-2 treated early in a dedicated COVID-19 day hospital and we assessed whether the use of hydroxychloroquine (HCQ) + azithromycin (AZ) was associated with improved survival in this cohort. A retrospective monocentric cohort study was conducted in the day hospital of our center from March to December 2020 in adults with PCR-proven infection who were treated as outpatients with a standardized protocol. The primary endpoint was 6-week mortality, and secondary endpoints were transfer to the intensive care unit and hospitalization rate. Among 10,429 patients (median age, 45 [IQR 32-57] years; 5597 [53.7%] women), 16 died (0.15%). The infection fatality rate was 0.06% among the 8315 patients treated with HCQ+AZ. No deaths occurred among the 8414 patients younger than 60 years. Older age and male sex were associated with a higher risk of death, ICU transfer, and hospitalization. Treatment with HCQ+AZ (0.17 [0.06-0.48]) was associated with a lower risk of death, independently of age, sex and epidemic period. Meta-analysis evidenced consistency with 4 previous outpatient studies (32,124 patients-Odds ratio 0.31 [0.20-0.47], I2 = 0%). Early ambulatory treatment of COVID-19 with HCQ+AZ as a standard of care is associated with very low mortality, and HCQ+AZ improve COVID-19 survival compared to other regimens.


Subject(s)
Ambulatory Care , Antiviral Agents/therapeutic use , Azithromycin/therapeutic use , COVID-19/drug therapy , Early Medical Intervention , Hydroxychloroquine/therapeutic use , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Antiviral Agents/adverse effects , Azithromycin/adverse effects , COVID-19/diagnosis , COVID-19/mortality , Drug Therapy, Combination , Female , France , Hospitalization , Humans , Hydroxychloroquine/adverse effects , Male , Middle Aged , Outpatients , Retrospective Studies , Risk Assessment , Risk Factors , Sex Factors , Time Factors , Treatment Outcome , Young Adult
3.
J Clin Med ; 10(10)2021 May 19.
Article in English | MEDLINE | ID: covidwho-1234758

ABSTRACT

BACKGROUND: The COVID-19 pandemic has provided an opportunity to use low- and non-radiating chest imaging techniques on a large scale in the context of an infectious disease, which has never been done before. Previously, low-dose techniques were rarely used for infectious diseases, despite the recognised danger of ionising radiation. METHOD: To evaluate the role of low-dose computed tomography (LDCT) and lung ultrasound (LUS) in managing COVID-19 pneumonia, we performed a review of the literature including our cases. RESULTS: Chest LDCT is now performed routinely when diagnosing and assessing the severity of COVID-19, allowing patients to be rapidly triaged. The extent of lung involvement assessed by LDCT is accurate in terms of predicting poor clinical outcomes in COVID-19-infected patients. Infectious disease specialists are less familiar with LUS, but this technique is also of great interest for a rapid diagnosis of patients with COVID-19 and is effective at assessing patient prognosis. CONCLUSIONS: COVID-19 is currently accelerating the transition to low-dose and "no-dose" imaging techniques to explore infectious pneumonia and their long-term consequences.

5.
Insights Imaging ; 11(1): 117, 2020 Nov 17.
Article in English | MEDLINE | ID: covidwho-930571

ABSTRACT

BACKGROUND: Low-dose chest CT (LDCT) showed high sensitivity and ability to quantify lung involvement of COVID-19 pneumopathy. The aim of this study was to describe the prevalence and risk factors for lung involvement in 247 patients with a visual score and assess the prevalence of incidental findings. METHODS: For 12 days in March 2020, 250 patients with RT-PCR positive tests and who underwent LDCT were prospectively included. Clinical and imaging findings were recorded. The extent of lung involvement was quantified using a score ranging from 0 to 40. A logistic regression model was used to explore factors associated with a score ≥ 10. RESULTS: A total of 247 patients were analyzed; 138 (54%) showed lung involvement. The mean score was 4.5 ± 6.5, and the mean score for patients with lung involvement was 8.1 ± 6.8 [1-31]. The mean age was 43 ± 15 years, with 121 males (48%) and 17 asymptomatic patients (7%). Multivariate analysis showed that age > 54 years (odds ratio 4.4[2.0-9.6] p < 0.001) and diabetes (4.7[1.0-22.1] p = 0.049) were risk factors for a score ≥ 10. Multivariate analysis including symptoms showed that only age > 54 years (4.1[1.7-10.0] p = 0.002) was a risk factor for a score ≥ 10. Rhinitis (0.3[0.1-0.7] p = 0.005) and anosmia (0.3[0.1-0.9] p = 0.043) were protective against lung involvement. Incidental imaging findings were found in 19% of patients, with a need for follow-up in 0.6%. CONCLUSION: The prevalence of lung involvement was 54% in a predominantly paucisymptomatic population. Age ≥ 55 years and diabetes were risk factors for significant parenchymal lung involvement. Rhinitis and anosmia were protective against LDCT abnormalities.

6.
PLoS One ; 15(11): e0241407, 2020.
Article in English | MEDLINE | ID: covidwho-902052

ABSTRACT

OBJECTIVES: The purpose is to assess the ability of low-dose CT (LDCT) to determine lung involvement in SARS-CoV-2 pneumonia and to describe a COVID19-LDCT severity score. MATERIALS AND METHODS: Patients with SARS-CoV-2 infection confirmed by RT-PCR were retrospectively analysed. Clinical data, the National Early Warning Score (NEWS) and imaging features were recorded. Lung features included ground-glass opacities (GGO), areas of consolidation and crazy paving patterns. The COVID19-LDCT score was calculated by summing the score of each segment from 0 (no involvement) to 10 (severe impairment). Univariate analysis was performed to explore predictive factor of high COVID19-LDCT score. The nonparametric Mann-Whitney test was used to compare groups and a Spearman correlation used with p<0.05 for significance. RESULTS: Eighty patients with positive RT-PCR were analysed. The mean age was 55 years ± 16, with 42 males (53%). The most frequent symptoms were fever (60/80, 75%) and cough (59/80, 74%), the mean NEWS was 1.7±2.3. All LDCT could be analysed and 23/80 (28%) were normal. The major imaging finding was GGOs in 56 cases (67%). The COVID19-LDCT score (mean value = 19±29) was correlated with NEWS (r = 0.48, p<0.0001). No symptoms were risk factor to have pulmonary involvement. Univariate analysis shown that dyspnea, high respiratory rate, hypertension and diabetes are associated to a COVID19-LDCT score superior to 50. CONCLUSIONS: COVID19-LDCT score did correlate with NEWS. It was significantly different in the clinical low-risk and high-risk groups. Further work is needed to validate the COVID19-LDCT score against patient prognosis.


Subject(s)
Coronavirus Infections/diagnosis , Lung/diagnostic imaging , Pneumonia, Viral/diagnosis , Adolescent , Adult , Aged , Aged, 80 and over , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/complications , Coronavirus Infections/virology , Cough/etiology , Female , Fever/etiology , Humans , Lung/physiopathology , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/virology , Respiratory Rate , Retrospective Studies , Risk Factors , SARS-CoV-2 , Severity of Illness Index , Statistics, Nonparametric , Tomography, X-Ray Computed , Young Adult
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