ABSTRACT
BACKGROUND: The risk of barotrauma associated with different types of ventilatory support is unclear in COVID-19 patients. The primary aim of this study was to evaluate the effect of the different respiratory support strategies on barotrauma occurrence; we also sought to determine the frequency of barotrauma and the clinical characteristics of the patients who experienced this complication. METHODS: This multicentre retrospective case-control study from 1 March 2020 to 28 February 2021 included COVID-19 patients who experienced barotrauma during hospital stay. They were matched with controls in a 1:1 ratio for the same admission period in the same ward of treatment. Univariable and multivariable logistic regression (OR) were performed to explore which factors were associated with barotrauma and in-hospital death. RESULTS: We included 200 cases and 200 controls. Invasive mechanical ventilation was used in 39.3% of patients in the barotrauma group, and in 20.1% of controls (p<0.001). Receiving non-invasive ventilation (C-PAP/PSV) instead of conventional oxygen therapy (COT) increased the risk of barotrauma (OR 5.04, 95% CI 2.30 - 11.08, p<0.001), similarly for invasive mechanical ventilation (OR 6.24, 95% CI 2.86-13.60, p<0.001). High Flow Nasal Oxygen (HFNO), compared with COT, did not significantly increase the risk of barotrauma. Barotrauma frequency occurred in 1.00% [95% CI 0.88-1.16] of patients; these were older (p=0.022) and more frequently immunosuppressed (p=0.013). Barotrauma was shown to be an independent risk for death (OR 5.32, 95% CI 2.82-10.03, p<0.001). CONCLUSIONS: C-PAP/PSV compared with COT or HFNO increased the risk of barotrauma; otherwise HFNO did not. Barotrauma was recorded in 1.00% of patients, affecting mainly patients with more severe COVID-19 disease. Barotrauma was independently associated with mortality. TRIAL REGISTRATION: this case-control study was prospectively registered in clinicaltrial.gov as NCT04897152 (on 21 May 2021).
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BACKGROUND: A major limitation of current predictive prognostic models in patients with COVID-19 is the heterogeneity of population in terms of disease stage and duration. This study aims at identifying a panel of clinical and laboratory parameters that at day-5 of symptoms onset could predict disease progression in hospitalized patients with COVID-19. METHODS: Prospective cohort study on hospitalized adult patients with COVID-19. Patient-level epidemiological, clinical, and laboratory data were collected at fixed time-points: day 5, 10, and 15 from symptoms onset. COVID-19 progression was defined as in-hospital death and/or transfer to ICU and/or respiratory failure (PaO2/FiO2 ratio < 200) within day-11 of symptoms onset. Multivariate regression was performed to identify predictors of COVID-19 progression. A model assessed at day-5 of symptoms onset including male sex, age > 65 years, dyspnoea, cardiovascular disease, and at least three abnormal laboratory parameters among CRP (> 80 U/L), ALT (> 40 U/L), NLR (> 4.5), LDH (> 250 U/L), and CK (> 80 U/L) was proposed. Discrimination power was assessed by computing area under the receiver operating characteristic (AUC) values. RESULTS: A total of 235 patients with COVID-19 were prospectively included in a 3-month period. The majority of patients were male (148, 63%) and the mean age was 71 (SD 15.9). One hundred and ninety patients (81%) suffered from at least one underlying illness, most frequently cardiovascular disease (47%), neurological/psychiatric disorders (35%), and diabetes (21%). Among them 88 (37%) experienced COVID-19 progression. The proposed model showed an AUC of 0.73 (95% CI 0.66-0.81) for predicting disease progression by day-11. CONCLUSION: An easy-to-use panel of laboratory/clinical parameters computed at day-5 of symptoms onset predicts, with fair discrimination ability, COVID-19 progression. Assessment of these features at day-5 of symptoms onset could facilitate clinicians' decision making. The model can also play a role as a tool to increase homogeneity of population in clinical trials on COVID-19 treatment in hospitalized patients.
Subject(s)
COVID-19 Drug Treatment , Aged , Female , Hospital Mortality , Humans , Male , Prospective Studies , Retrospective Studies , SARS-CoV-2 , Treatment OutcomeABSTRACT
INTRODUCTION: To better define COVID-19 long-term impact we prospectively analysed patient-centred outcomes, including general health and symptom duration. METHODS: Barthel index (BI), St. George's Respiratory Questionnaire adapted to patients with COVID-19 (aSGRQ) and WHO Clinical Progression Scale (CPS) were measured at enrolment and at 6 weeks from the onset of symptoms. Persistence of most frequently reported symptoms was assessed at 6 weeks and, among symptomatic patients, at 12 weeks from the onset of symptoms. Predictors of impaired general health over time were identified using an ordinal multilevel multivariate model. RESULTS: A total of 448 patients (55% men, median age 56 years) were enrolled. WHO-CPS showed mild, moderate and severe disease in 48%, 42% and 10% of patients at admission and mild disease in all patients at follow-up, respectively. BI and aSGRQ were normal in 96% and 93% patients before COVID-19 but only in 47% and 16% at COVID-19 diagnosis and in 87% and 65% at 6-week follow-up. Male gender was identified by all three assessments as a predictor of impaired general health (BI, OR 2.14, p < 0.0001; aSGRQ, OR 0.53, p = 0.003; WHO-CPS, OR 1.56, p = 0.01). Other predictors included age, ICU admission and comorbidities (e.g. cardiovascular disease and cancer) for BI, hospital admission for aSGRQ, age and presence of comorbidities for WHO-CPS. At 6- and 12-week follow-up, 39% and 20% of patients, respectively, were still reporting symptoms. Fatigue and breathlessness were the most frequently reported symptoms. CONCLUSIONS: Long-term follow-up facilitates the monitoring of health impairment and symptom persistence and can contribute to plan tailored interventions.
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Aim To study ground-glass opacities (GGO) not only from the coronavirus 2019 (COVID-19) pneumonia" perspective but also as a radiological presentation of other pathologies with comparable features. Methods We enrolled 33 patients admitted to Policlinico Universitario G. B. Rossi who underwent non-contrast-enhanced (NCE) or contrast-enhanced (CE) chest computed tomography (CT) between March 12 and April 12. All patients with CT-detected ground-glass opacity (GGO) were included. All patients resulted as COVID-19 negative at the reverse transcription-polymerase chain reaction (RT-PCR) assay. We studied the different pathologies underlying GGO features: neoplastic diseases and non-neoplastic diseases (viral pneumonias, interstitial pneumonias, and cardiopulmonary diseases) in order to avoid pitfalls and to reach the correct diagnosis. Results All CT scans detected GGOs. Symptomatic patients were 25/33 (75.7%). At the clinical presentation, they reported fever and dry cough; in six out of 25 cases, dyspnea was also reported (24%). Thirty-three (33; 100%) showed GGO at CT: 15/33 (45.45%) presented pure GGO, and 18/33 (54.54%) showed GGO with consolidation. The RT-PCR assay was negative in 100%. We investigated other potential underlying diseases to explain imaging features: neoplastic causes (8/33, 24.24%) and non-neoplastic causes, in particular, infectious pneumonias (16/33, 48,48 %, viral and fungal), interstitial pneumonias (4/33, 12,12%), and cardio-pulmonary disease (5/33, 15,15%). Conclusions GGO remains a diagnostic challenge. Although CT represents a fundamental diagnostic tool because of its sensitivity, it still needs to be integrated with clinical data to achieve the best clinical management. In the presence of typical imaging features (e.g. GGO and consolidation), the radiologist should focus on the pandemic and manage a suspect patient as COVID-19 positive until proven to be negative.