Adjunctive corticosteroid treatment for organizing pneumonia in COVID-19 patients with persistent respiratory failure.

Since the beginning of COVID-19 pandemic, clinical, radiological and histopathological features consistent with viral-induced organizing pneumonia (OP) have been reported as hallmark characteristics of the disease. Here, we describe the case of ten patients with severe COVID-19 pneumonia treated with methylprednisolone 1mg/kg for showing clinical and radiological features suggestive of OP at least 20 days after symptom onset and despite standard treatment for COVID-19.

New treatment directions for IPF: current status of ongoing and upcoming clinical trials.

INTRODUCTION: The main objective of this review is to explore the wide and expanding field of new clinical trials in IPF. Recent trials have confirmed the efficacy of the approved drugs pirfenidone and nintedanib; nonetheless, the discovery of new biological pathways has opened new horizons in this field. Areas covered: New strategies against matrix deposition are under study and so is for the role of immunity and autoimmunity. Recent advances in the use of stem cells are opening new possibilities for the recovery of damaged lung tissues. The role of microbioma is under investigation in order to evaluate the use of antibiotics in IPF treatment. Analysing all the new and the upcoming clinical trials, we are trying to offer a comprehensive view of the emerging new frontiers in the treatment of IPF. Expert commentary: The key points for the ongoing and upcoming clinical trials will be to avoid previous mistakes and to choose carefully both study populations and efficacy endpoints. The exciting possibility to enrol patients with progressive lung fibrosis, both idiopathic and not, could be a next step forward. How the existing therapies will fit in a futurist scenario of personalized medicine is still a challenge.

[Definition and validation of a predictive model to identify patients with chronic obstructive pulmonary disease (COPD) from administrative databases]. / Definizione e validazione di un modello predittivo per l'identificazione di pazienti affetti da broncopneumopatia cronica ostruttiva (BPCO) a partire dai sistemi informativi sanitari.

OBJECTIVE: To develop and validate a predictive model for the identification of patients with Chronic Obstructive Pulmonary Disease (COPD) among the resident population of the Lazio region, using information available in the regional administrative systems (SIS) as well as clinical data of a panel of COPD patients. SETTING AND PARTICIPANTS: All residents in the Lazio region over 40 years of age in 2007 (2,625,102 inhabitants) MAIN OUTCOME MEASURES: The predictive model was developed through record linkage of health care related consumption patterns among 428 panel patients with confirmed COPD diagnosis in 2006 and a control group of patients without COPD (selection from outpatients specialized health care registry, 1:4). Hospital admission for COPD was defined a priori to be sufficient to identify a COPD patient. For all other panel patients and controls, specific drug use (minimum 2 prescriptions during 12 months) and hospitalization for respiratory causes during the past 9 years were retrieved and compared between panel and control patients. COPD associated factors were selected through a Bootstrap- Stepwise (BS) procedure. The predictive model was validated through internal (cross-validation-bootstrap) and external validation (comparison with external COPD patients with confirmed diagnosis), and through comparison with other COPD identification approaches. RESULTS: The BS procedure identified the following predictors of COPD: consumption of beta 2 agonists, anticholinergics, corticosteroids, oxygen, and previous hospitalization for respiratory failure. For each patient, the expected probability of being affected by COPD was estimated. Depending on the cut-point of expected probability, sensibility ranged from 74.5% to 99.6% and specificity from 37.8% to 86.2%. Using the 0.30 cut-point, the model succeeded in identifying 67% of patients with diagnosis of COPD confirmed with spirometry. The predictive performance increased with increasing COPD severity. Prevalence of COPD turned out to be 7.8 %. The age-specific estimation was similar to results from other approaches. CONCLUSION: The predictive model shows good performance to identify COPD patients, even if it does not allow to identify those patients who have not been registered in the regional health care service or do not request any public health care service.