| Literature DB >> 36103083 |
Giulia Russo1,2, Nicola Flor3, Francesco Casella4, Sonia Ippolito3, Federica Leidi4, Giovanni Casazza5, Dejan Radovanovic6, Federico Vezzulli4, Pierachille Santus6, Chiara Cogliati4.
Abstract
While lung ultrasonography (LUS) proved to be a useful diagnostic and prognostic tool in acute phase of COVID 19 pneumonia, its role in detecting long-term pulmonary sequelae has yet to be explored. In our prospective observational study we assessed the potential of LUS in detecting the presence of computed tomography (CT) fibrotic-like changes after 6 months from COVID-19 pneumonia. Patients who were discharged with a diagnosis of severe COVID-19 pneumonia were enrolled. After 6 months from hospital discharge they underwent LUS, chest CT scan and pulmonary function tests. A logistic regression analysis was performed to assess the association between presence of symptoms, LUS score and diffusing capacity for carbon monoxide (DLCO) at 6-month after hospital discharge and CT scan fibrotic-like changes. A second logistic model was performed to assess the value of some predefined baseline factors (age, sex, worst PaO2/FiO2, ventilator support, worst CRP value, worst D-dimer value and worst LUS score during hospitalization) to predict fibrotic-like changes on 6-month CT scan. Seventy-four patients were enrolled in the study. Twenty-four (32%) showed lung abnormalities suitable for fibrotic-like changes. At multivariate logistic regression analysis LUS score after 6 months from acute disease was significantly associated with fibrotic-like pattern on CT scan. The second logistic model showed that D-dimer value was the only baseline predictive variable of fibrotic-like changes at multivariate analysis. LUS performed after 6 months from severe COVID-19 pneumonia may be a promising tool for detection and follow-up of pulmonary fibrotic sequelae.Entities:
Keywords: COVID-19 pneumonia; Computed tomography; Lung ultrasound; Pulmonary fibrosis; Ultrasonography
Year: 2022 PMID: 36103083 PMCID: PMC9472735 DOI: 10.1007/s11739-022-03084-9
Source DB: PubMed Journal: Intern Emerg Med ISSN: 1828-0447 Impact factor: 5.472
Population characteristics
| Overall population (n. 74) | |
|---|---|
| Age–median (IQR)–years | 65.5 (56.25–73) |
| Sex: female–no. (%) | 20 (27) |
| Coexisting conditions–no. (%) | |
| Hypertension | 31 (22.9) |
| CAD | 9 (6.7) |
| Diabetes | 16 (11.8) |
| Obesity BMI > 30 kg/m2 | 6 (4.4) |
| BMI > 25; ≤ 30 30 kg/m2 | 24 (17.8) |
| Charlson Comorbidity index—median (IQR) | 2 (0–4) |
| Laboratory findings during hospital stay–median (IQR) | |
| Worst CRP value (mg/L) | 107 (99–133) |
| Worst D-dimer value (ng/L) | 1157.5 (615.5–2011.5) |
| Worst P/F ratio | 215 (131–271) |
| LUS during hospital stay* | |
| Worst LUS score–median (IQR) | 17 (12–20) |
| Patients with positive LUS–no. (%) | 68 (98.5) |
| Patients with bilateral involvement–no. (%) | 68 (98.5) |
| Patients with consolidations- no. (%) | 33 (47.8) |
| Transfer to ICU | 2 (2.7) |
| Need for CPAP | 35 (47.3) |
IQR interquartile range, CAD coronary artery disease, BMI body mass index, CRP C reactive protein, P/F ratio PaO2/FiO2, LUS lung ultrasound, ICU intensive care unit, CPAP continuous positive airway pressure
*69 patients underwent LUS during hospital stay
LUS findings at six months
| LUS SCORE–median (IQR) | 2 (0–5.25) |
| Patients with positive LUS–no. (%) | 50 (69.4) |
| Patients with bilateral involvement–no. (%) | 31 (41.9) |
| Patients with small subpleural nodules no. (%) | 31 (43.1) |
| Patients with thickened and fragmented pleural line no. (%) | 38 (52.8) |
| Number of involved regions–median (IQR) | 2 (0–4) |
| Negative regions (i.e. score B0)–% | 76.8 |
| Positive regions (i.e. score B1;B2;B3)–% | 23.2 |
| Localization of positive REGIONS–% | |
| Anterior superior | (11.7) |
| Anterior inferior | (8.9) |
| Lateral superior | (9.6) |
| Lateral inferior | (23.5) |
| Posterior superior | (14.5) |
| Posterior inferior | (31.8) |
LUS lung ultrasound
Fig. 1Examples of LUS findings at 6 months after Covid-19 pneumonia. a Interstitial pattern with separated B-lines, LUS score 1. b Interstitial pattern with confluent B-lines, LUS score 2. c Image blow-up for better appreciation of the irregular/fragmented pleural line. d Sub-centimetric pleural nodule, irregular pleural line
Univariate and multivariate analysis
| Univariate | Multivariate | |||
|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | |||
| Six months LUS Score | ||||
| Fatigue and/or dyspnea at six months (presence vs absence) | 0.659 (0.247–1.762) | 0.4063 | − | − |
| Six months DLCO (%)° | 0.998 (0.973–1.024) | 0.9018 | − | − |
Univariate and multivariate logistic regression analysis for the association between 6-month LUS score, symptoms and DLCO and fibrotic-like changes on 6-month CT scan. LUS lung ultrasound, DLCO diffusion lung CO. ° Values are expressed as % of predicted value
Bold values indicate statistical significance at the p < 0.05 level
Fig. 2ROC curve model: LUS score accuracy for detecting patients with 6-month fibrotic-like changes on CT scan
Univariate and multivariate analysis
| Univariate | Multivariate | |||
|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | |||
| Age (years) | – | ns | ||
| Sex (male vs female) | 1.63 (0.51–5.17) | 0.41 | – | – |
| Need for MV or CPAP support | 1.78 (0.66–4.77) | 0.25 | ||
| Worst P/F | 0.99 (0.987–1.00) | 0.05 | – | – |
| Worst CPR value (mg/L) | 1.002 (0.997–1.01) | 0.51 | – | – |
Worst D-Dimer (ng/L) (> 1157,5 vs ≤ 1157,5) | ||||
| Worst LUS score | 1.04 (0.95–1.14) | 0.4 | – | – |
Univariate and multivariate logistic regression for age, sex, ventilator support, respiratory impairment (expressed as P/F), biochemical variables and LUS score during hospitalization as predictors of fibrotic-like changes on 6-month CT scan. MV mechanical ventilation, CPAP continuous positive airway pressure, P/F ratio PaO2/FiO2, CRP C reactive protein, LUS lung ultrasound
Bold values indicate statistical significance at the p < 0.05 level