Key Points Question What respiratory, functional, and psychological sequalae are associated with recovery from coronavirus disease 2019 (COVID-19)? Findings In this cohort study of 238 patients with COVID-19 hospitalized in an academic hospital in Northern Italy, more than half of participants had a significant reduction of diffusing lung capacity for carbon monoxide or measurable functional impairment and approximately one-fifth of patients had symptoms of posttraumatic stress 4 months after discharge. Meaning These findings suggest that despite virological recovery, a sizable proportion of patients with COVID-19 experienced respiratory, functional, or psychological sequelae months after hospital discharge.
The SARS-CoV-2 pandemic significantly affected oncology practice across the globe. There is uncertainty as to the contribution of patients' demographics and oncologic features to severity and mortality from COVID-19 and little guidance as to the role of anticancer and anti-COVID-19 therapy in this population. In a multicenter study of 890 patients with cancer with confirmed COVID-19, we demonstrated a worsening gradient of mortality from breast cancer to hematologic malignancies and showed that male gender, older age, and number of comorbidities identify a subset of patients with significantly worse mortality rates from COVID-19. Provision of chemotherapy, targeted therapy, or immunotherapy did not worsen mortality. Exposure to antimalarials was associated with improved mortality rates independent of baseline prognostic factors. This study highlights the clinical utility of demographic factors for individualized risk stratification of patients and supports further research into emerging anti-COVID-19 therapeutics in SARS-CoV-2-infected patients with cancer. SIGNIFICANCE: In this observational study of 890 patients with cancer diagnosed with SARS-CoV-2, mortality was 33.6% and predicted by male gender, age ≥65, and comorbidity burden. Delivery of cancer therapy was not detrimental to severity or mortality from COVID-19. These patients should be the focus of shielding efforts during the SARS-CoV-2 pandemic. Research.
Many coronavirus disease 2019 (Covid-19) survivors show symptoms months after acute illness. The aim of this work is to describe the clinical evolution of Covid-19, one year after discharge. We performed a prospective cohort study on 238 patients previously hospitalized for Covid-19 pneumonia in 2020 who already underwent clinical follow-up 4 months post-Covid-19. 200 consented to participate to a 12-months clinical assessment, including: pulmonary function tests with diffusing lung capacity for carbon monoxide (DLCO); post-traumatic stress (PTS) symptoms evaluation by the Impact of Event Scale (IES); motor function evaluation (by Short Physical Performance Battery and 2 min walking test); chest Computed Tomography (CT). After 366 [363–369] days, 79 patients (39.5%) reported at least one symptom. A DLCO < 80% was observed in 96 patients (49.0%). Severe DLCO impairment (< 60%) was reported in 20 patients (10.2%), related to extent of CT scan abnormalities. Some degree of motor impairment was observed in 25.8% of subjects. 37/200 patients (18.5%) showed moderate-to-severe PTS symptoms. In the time elapsed from 4 to 12 months after hospital discharge, motor function improves, while respiratory function does not, being accompanied by evidence of lung structural damage. Symptoms remain highly prevalent one year after acute illness.
Patients with rheumatoid arthritis (RA) receive highly targeted biologic therapies without previous knowledge of target expression levels in the diseased tissue. Approximately 40% of patients do not respond to individual biologic therapies and 5–20% are refractory to all. In a biopsy-based, precision-medicine, randomized clinical trial in RA (R4RA; n = 164), patients with low/absent synovial B cell molecular signature had a lower response to rituximab (anti-CD20 monoclonal antibody) compared with that to tocilizumab (anti-IL6R monoclonal antibody) although the exact mechanisms of response/nonresponse remain to be established. Here, in-depth histological/molecular analyses of R4RA synovial biopsies identify humoral immune response gene signatures associated with response to rituximab and tocilizumab, and a stromal/fibroblast signature in patients refractory to all medications. Post-treatment changes in synovial gene expression and cell infiltration highlighted divergent effects of rituximab and tocilizumab relating to differing response/nonresponse mechanisms. Using ten-by-tenfold nested cross-validation, we developed machine learning algorithms predictive of response to rituximab (area under the curve (AUC) = 0.74), tocilizumab (AUC = 0.68) and, notably, multidrug resistance (AUC = 0.69). This study supports the notion that disease endotypes, driven by diverse molecular pathology pathways in the diseased tissue, determine diverse clinical and treatment–response phenotypes. It also highlights the importance of integration of molecular pathology signatures into clinical algorithms to optimize the future use of existing medications and inform the development of new drugs for refractory patients.
Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.
Background Tocilizumab blocks pro-inflammatory activity of interleukin-6 (IL-6), involved in pathogenesis of pneumonia the most frequent cause of death in COVID-19 patients. Methods A multicenter, single-arm, hypothesis-driven trial was planned, according to a phase 2 design, to study the effect of tocilizumab on lethality rates at 14 and 30 days (co-primary endpoints, a priori expected rates being 20 and 35%, respectively). A further prospective cohort of patients, consecutively enrolled after the first cohort was accomplished, was used as a secondary validation dataset. The two cohorts were evaluated jointly in an exploratory multivariable logistic regression model to assess prognostic variables on survival. Results In the primary intention-to-treat (ITT) phase 2 population, 180/301 (59.8%) subjects received tocilizumab, and 67 deaths were observed overall. Lethality rates were equal to 18.4% (97.5% CI: 13.6–24.0, P = 0.52) and 22.4% (97.5% CI: 17.2–28.3, P < 0.001) at 14 and 30 days, respectively. Lethality rates were lower in the validation dataset, that included 920 patients. No signal of specific drug toxicity was reported. In the exploratory multivariable logistic regression analysis, older age and lower PaO2/FiO2 ratio negatively affected survival, while the concurrent use of steroids was associated with greater survival. A statistically significant interaction was found between tocilizumab and respiratory support, suggesting that tocilizumab might be more effective in patients not requiring mechanical respiratory support at baseline. Conclusions Tocilizumab reduced lethality rate at 30 days compared with null hypothesis, without significant toxicity. Possibly, this effect could be limited to patients not requiring mechanical respiratory support at baseline. Registration EudraCT (2020-001110-38); clinicaltrials.gov (NCT04317092).
<b><i>Background:</i></b> Bronchoscopy with bronchoalveolar lavage (BAL) during the SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) pandemic should be reserved to a limited number of clinical indications. The yield of BAL for the diagnosis of suspected or confirmed pulmonary SARS-CoV-2 infection is still unknown. <b><i>Objectives:</i></b> We aimed to evaluate the diagnostic ratio of BAL in detecting SARS-CoV-2 pulmonary infection in patients undergoing bronchoscopy for different indications as well as describe the clinical, radiological, and endoscopic characteristics of patients with SARS-CoV-2 on BAL. <b><i>Method:</i></b> We conducted a multicenter retrospective study including all patients who underwent bronchoscopy for the detection of SARS-CoV-2 on BAL. Clinical, computed tomography (CT), endoscopic, and microbiologic data were gathered from March 16th to May 27th, 2020. <b><i>Results:</i></b> 131 patients were included. Bronchoscopy was performed for suspected SARS-CoV-2 infection (65.5%), alternative diagnosis (12.9%), suspected superinfections (19.8%), and lung atelectasis (1.5%). SARS-CoV-2 was isolated on BAL 43 times (32.8%) and the highest isolation rate was in patients with suspected SARS-CoV-2 infection (74.4%); 76% of positive patients had a double-negative nasopharyngeal swab. Peripheral, posterior and multilobar CT opacities were more frequent in SARS-CoV-2 patients, and the number of CT findings was higher in positive patients, particularly those with suspected SARS-CoV-2 infection. We recorded a progressive reduction of SARS-CoV-2 isolation during the observation period. <b><i>Conclusions:</i></b> In our centers, the rate of detection of SARS-CoV-2 on BAL in patients with suspected infection was 37.2%. The agreement of BAL with nasopharyngeal swabs was high; CT alterations could predict the pretest probability of SARS-CoV-2 infection, but suspicion of viral infection should be always considered.
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