The PROVENT-C19 registry: A study protocol for international multicenter SIAARTI registry on the use of prone positioning in mechanically ventilated patients with COVID-19 ARDS.

BACKGROUND: The worldwide use of prone position (PP) for invasively ventilated patients with COVID-19 is progressively increasing from the first pandemic wave in everyday clinical practice. Among the suggested treatments for the management of ARDS patients, PP was recommended in the Surviving Sepsis Campaign COVID-19 guidelines as an adjuvant therapy for improving ventilation. In patients with severe classical ARDS, some authors reported that early application of prolonged PP sessions significantly decreases 28-day and 90-day mortality. METHODS AND ANALYSIS: Since January 2021, the COVID19 Veneto ICU Network research group has developed and implemented nationally and internationally the "PROVENT-C19 Registry", endorsed by the Italian Society of Anesthesia Analgesia Resuscitation and Intensive Care…'(SIAARTI). The PROVENT-C19 Registry wishes to describe 1. The real clinical practice on the use of PP in COVID-19 patients during the pandemic at a National and International level; and 2. Potential baseline and clinical characteristics that identify subpopulations of invasively ventilated patients with COVID-19 that may improve daily from PP therapy. This web-based registry will provide relevant information on how the database research tools may improve our daily clinical practice. CONCLUSIONS: This multicenter, prospective registry is the first to identify and characterize the role of PP on clinical outcome in COVID-19 patients. In recent years, data emerging from large registries have been increasingly used to provide real-world evidence on the effectiveness, quality, and safety of a clinical intervention. Indeed observation-based registries could be effective tools aimed at identifying specific clusters of patients within a large study population with widely heterogeneous clinical characteristics. TRIAL REGISTRATION: The registry was registered (ClinicalTrial.Gov Trials Register NCT04905875) on May 28,2021.

Multidimensional 3-Month Follow-Up of Severe COVID-19: Airways beyond the Parenchyma in Symptomatic Patients.

SARS-CoV-2 may lead to a large spectrum of respiratory manifestations, including pulmonary sequelae. We conducted a single-center longitudinal study of survivors from severe COVID-19 cases who underwent a chest CT during hospitalization (CTH). Three months after being discharged, these patients were evaluated by a clinical examination, pulmonary function tests and a chest-CT scan (CTFU). Sixty-two patients were enrolled. At follow-up, 27% complained of exertional dyspnoea and 12% of cough. Dyspnoeic patients had a lower forced expiratory flow (FEF)25-75 (p = 0.015), while a CT scan (p = 0.016 showed that patients with cough had a higher extent of bronchiectasis. Lung volumes and diffusion of carbon monoxide (DLCO) at follow-up were lower in patients who had been invasively ventilated, which correlated inversely with the length of hospitalization and ground-glass extension at CTH. At follow-up, 14.5% of patients had a complete radiological resolution, while 85.5% presented persistence of ground-glass opacities, and 46.7% showed fibrotic-like alterations. Residual ground-glass at CTFU was related to the length of hospitalization (r = 0.48; p = 0.0002) and to the need for mechanical ventilation or high flow oxygen (p = 0.01) during the acute phase. In conclusion, although patients at three months from discharge showed functional impairment and radiological abnormalities, which correlated with a prolonged hospital stay and need for mechanical ventilation, the persistence of respiratory symptoms was related not to parenchymal but rather to airway sequelae.

Differences in early, intermediate, and long-term mortality among elderly patients admitted to the ICU: results of a retrospective observational study.

BACKGROUND: Few studies have investigated both short- and long-term prognostic factors, and the differences between chronic and acute conditions in the very old critically ill patient. Our study aims to shed light in this field and to provide useful prognostic factors that may support clinical decisions in the management of the elderly. METHODS: Six ICUs collected data concerning 80-year-old (or more) patients admitted in 2015 and 2016 and followed-up until May 2018. Three prognostic models were developed: an in-hospital mortality model, a model for patients discharged from the hospital and entering follow-up, and an intermediate model for those alive after three days from ICU admission. RESULTS: Our centers admitted 1189 patients, 1071 (90.1%) had survived after three days from admission, 889 (74.8%) were discharged from the hospital, 701 (59.0%) survived six months after hospital discharge, 539 (45.3%) survived at the end of follow-up. Among survivors the median follow-up time was 810 days. Acute organ failures were the main causes of death in the hospital mortality multivariable model. These factors are modifiable and potentially a target for intervention to improve outcome. The model focused on mortality six months after hospital in patients that survived a three-day time-limited trial, showed a clear shift toward chronic diseases, unmodifiable factors crucial for prognostic assessment. This trend was even more evident at the end of follow-up. CONCLUSIONS: Among very old ICU patients, prognostic factors shift from acute to chronic conditions in passing from in-hospital to posthospital outcomes.

Care and compassion at time of pandemic: an ICU field experience in Italy.

After the COVID-19 pandemic outbreak in March 2020, the majority of hospital policies have followed guidelines aimed to prevent the virus transmission and the families' entry was denied in all hospital wards and intensive care units (ICU). Despite being necessary, such restrictions have been experienced with discomfort and sufferings by the general ICU staff of Treviso Hospital (Italy) and by families of patients. Therefore, from April 2020, a step-by-step project was developed to reactivate contact with COVID-19 patients' families. The several requests and appeals of intensive care communities and organizations, both nationally and internationally, motivated the Treviso hospital initiative, leading to a model that might be potentially useful to other intensive care units worldwide.

Prolonged prone position in pregnant woman with COVID-19 pneumonia.

The manuscript describes a case report of 2 prolonged prone position cycles (72 h each) of a coronavirus disease 2019 pneumonia in an intubated pregnant woman (at 22 weeks of gestational age), being successfully discharged from intensive care unit after 20 days. There were no signs of fetal sufferance at daily obstetric monitoring during prone position, and the fetus was born fully vital and without consequences.At our knowledge, this is the first case of prolonged prone position in a pregnant woman, and we feel that our manuscript could be a valuable contribution to the literature and help intensivists in providing intensive care in these patients, confirming that prone position seems to be a valid therapeutic choice, limiting maternal and fetal hypoxia, and reducing their morbidity, even if the oculate risk/benefit should be performed. Further studies are however necessary to increase the knowledge and the good management of COVID-19 in pregnancy.

Pneumothorax and/or Pneumomediastinum Worsens the Prognosis of COVID-19 Patients with Severe Acute Respiratory Failure: A Multicenter Retrospective Case-Control Study in the North-East of Italy.

Pneumothorax (PNX) and pneumomediastinum (PNM) are potential complications of COVID-19, but their influence on patients' outcomes remains unclear. The aim of the study was to assess incidence, risk factors, and outcomes of severe COVID-19 complicated with PNX/PNM. METHODS: A retrospective multicenter case-control analysis was conducted in COVID-19 patients admitted for respiratory failure in intermediate care units of the Treviso area, Italy, from March 2020 to April 2021. Clinical characteristics and outcomes of patients with and without PNX/PNM were compared. RESULTS: Among 1213 patients, PNX and/or PNM incidence was 4.5%. Among these, 42% had PNX and PNM, 33.5% only PNX, and 24.5% only PNM. COVID-19 patients with PNX/PNM showed higher in-hospital (p = 0.02) and 90-days mortality (p = 0.048), and longer hospitalization length (p = 0.002) than COVID-19 patients without PNX/PNM. At PNX/PNM occurrence, one-third of subjects was not mechanically ventilated, and the respiratory support was similar to the control group. PNX/PNM occurrence was associated with longer symptom length before hospital admission (p = 0.005) and lower levels of blood lymphocytes (p = 0.017). CONCLUSION: PNX/PNM are complications of COVID-19 associated with a worse prognosis in terms of mortality and length of hospitalization. Although they are more frequent in ventilated patients, they can occur in non-ventilated, suggesting that mechanisms other than barotrauma might contribute to their presentation.

COVID-19 ICU mortality prediction: a machine learning approach using SuperLearner algorithm.

BACKGROUND: Since the beginning of coronavirus disease 2019 (COVID-19), the development of predictive models has sparked relevant interest due to the initial lack of knowledge about diagnosis, treatment, and prognosis. The present study aimed at developing a model, through a machine learning approach, to predict intensive care unit (ICU) mortality in COVID-19 patients based on predefined clinical parameters. RESULTS: Observational multicenter cohort study. All COVID-19 adult patients admitted to 25 ICUs belonging to the VENETO ICU network (February 28th 2020-april 4th 2021) were enrolled. Patients admitted to the ICUs before 4th March 2021 were used for model training ("training set"), while patients admitted after the 5th of March 2021 were used for external validation ("test set 1"). A further group of patients ("test set 2"), admitted to the ICU of IRCCS Ca' Granda Ospedale Maggiore Policlinico of Milan, was used for external validation. A SuperLearner machine learning algorithm was applied for model development, and both internal and external validation was performed. Clinical variables available for the model were (i) age, gender, sequential organ failure assessment score, Charlson Comorbidity Index score (not adjusted for age), Palliative Performance Score; (ii) need of invasive mechanical ventilation, non-invasive mechanical ventilation, O2 therapy, vasoactive agents, extracorporeal membrane oxygenation, continuous venous-venous hemofiltration, tracheostomy, re-intubation, prone position during ICU stay; and (iii) re-admission in ICU. One thousand two hundred ninety-three (80%) patients were included in the "training set", while 124 (8%) and 199 (12%) patients were included in the "test set 1" and "test set 2," respectively. Three different predictive models were developed. Each model included different sets of clinical variables. The three models showed similar predictive performances, with a training balanced accuracy that ranged between 0.72 and 0.90, while the cross-validation performance ranged from 0.75 to 0.85. Age was the leading predictor for all the considered models. CONCLUSIONS: Our study provides a useful and reliable tool, through a machine learning approach, for predicting ICU mortality in COVID-19 patients. In all the estimated models, age was the variable showing the most important impact on mortality.

An Observational Veneto Research on Ventilator-Associated Pneumonia (OVeRVAP): attributable mortality and cumulative incidence of ventilator-associated pneumonia.

BACKGROUND: The relationship between ventilator-associated pneumonia (VAP) and mortality varies from study to study, and its entity is uncertain due a considerable variation in the attributable mortality. The aim of this study was to evaluate the relationship between VAP frequency and mortality in a cohort of mechanically ventilated patients. METHODS: A multicenter prospective observational study was conducted in 21 Intensive Care Units (ICUs). The patients were recruited from 2008 to 2010 within randomly selected periods. 842 patients of 2595 admitted, met the eligibility criteria and were enrolled in the study. The study's primary outcome was death by any cause in one of the ICUs. We modelled VAP occurrence as a time-dependent covariate and fitted a competing risk analysis model. We estimated the attributable mortality of VAP as the population-attributable fraction of ICU mortality. RESULTS: A total of 121 patients developed VAP (14.4%), for an incidence rate of 15.7 cases per 1000 ventilator days; of the 175 patients (20.8%) who died during the study period, 31 (25.6%) had VAP. The ICU mortality rate in the patients who developed VAP was 22.6 per 1000 ventilator days (95% CI: 15.9-32.1). We estimated an attributable mortality of 8.4%. CONCLUSIONS: In 8.4% of cases, VAP was the leading cause of death in our study. This indicates that the patients died more frequently with VAP rather than because of it.

Is influenza A(H1N1) pneumonia more severe than other community-acquired pneumonias? Results of the GiViTI survey of 155 Italian ICUs.

PURPOSE: Uncertainty about the severity of the A(H1N1) pandemia persists. Information about disease severity can be obtained by investigating intensive care unit (ICU) admissions, especially when historical comparisons can be made with cases of community-acquired pneumonia (CAP). METHODS: This prospective observational study was conducted in 155 ICUs contributing to the GiViTI national database. To assess the impact on ICU workload, the occupancy rate during the epidemic phase was compared with influenza periods in previous years. A logistic regression model was developed to assess the prognostic importance of A(H1N1) influenza. RESULTS: The characteristics of the 319 A(H1N1) cases were similar to those reported in other studies, confirming the young age of patients (mean 43 years) and the higher prevalence among pregnant women and obese people. At the epidemic's peak (October-December 2009) the occupancy rate did not significantly differ from the same period of the previous year, and was significantly lower than the 2009 seasonal influenza outbreak (January-March 2009). Compared with CAP of other origin (3,678 patients), A(H1N1) pneumonia was associated with a lower risk of death. However, after adjusting for confounding this was no longer the case (OR 0.88; 95% CI 0.59-1.31; p = 0.52). CONCLUSION: This study confirmed the specific features of critically ill A(H1N1) patients (i.e., young age, pregnancy, obesity). The pandemic did not increase ICU workload compared with other periods. A(H1N1) pneumonia did not have a higher risk of death than CAP of different origin among patients admitted to the ICU.

End-of-life decision-making and quality of ICU performance: an observational study in 84 Italian units.

PURPOSE: To appraise the end-of-life decision-making in several intensive care units (ICUs) and to evaluate the association between the average inclination to limit treatment and overall survival at ICU level. DESIGN: Prospective, multicenter, observational study, lasting 12 months. SETTING: Eighty-four Italian, adult ICUs. PATIENTS: Consecutive patients (3,793) who died in ICU or were discharged in terminal condition, in 2005. MEASUREMENTS: Data collection included patient description, treatment limitation and decision-makers, involvement of patients and relatives in the decision, and organ donation. A logistic regression model was used to identify predictors of treatment limitation and develop a measure of the inclination to limit treatment for each ICU. This was compared with the standardized mortality ratio, an index of the overall performance of the unit. RESULTS: Treatment limitation preceded 62% of deaths. In 25% of cases, nurses were involved in the decision. Half the limitations were do-not-resuscitate orders, with the remaining half almost equally split between withholding and withdrawing treatment. Units less inclined to limit treatments (odds ratio <0.77) showed higher overall standardized mortality ratio (1.08; 95% confidence interval: 1.04-1.12). LIMITATIONS: The voluntary nature of participation, with self-selected ICUs from a self-selected independent network. CONCLUSIONS: Treatment limitation is common in ICU and still principally a physician's responsibility. Units with below-average inclination to limit treatments have worse performance in terms of overall mortality, showing that limitation is not against the patient's interests. On the contrary, the inclination to limit treatments at the end of life can be taken as an indication of quality in the unit.