COVID-19 in Liver Transplant Candidates: Pre- and Post-Transplant Outcome (preprint)

Background: The impact of COVID-19 on patients on the waiting list for liver transplantation (LT) and on their post-LT course is presently unknown. Methods: Data from consecutive adult LT candidates with COVID-19 were collected across Europe in a dedicated registry and analyzed.Findings: From February 21st to November 20th, 2020, 136 adult cases with laboratory confirmed SARS-CoV-2 infection from 33 centers in 11 European countries were collected, with 113 having COVID-19. Thirty-seven (37/113, 32·7%) patients died after a median of 18 (10-30) days, respiratory failure being the major cause (33/37, 89·2%). The 60-day mortality risk did not significantly change between first (35·3%, 95% CI 23·9-50·0) and second wave (26·0%, 95% CI 16·2-40·2). Multivariable Cox regression analysis showed lab-MELD score ≥15 (MELD 15-19 HR 6·09, 95% CI 2·01-18·45; MELD ≥20 HR 5·21, 95% CI 1·76-15·45) and dyspnea on presentation (HR 4·10, 95% CI 2·09-8·06) being the two negative independent factors for mortality. The mortality risk reached 49·2% (31/63) in patients with decompensated cirrhosis and lab-MELD score ≥15. Twenty-six patient received a LT after a median time of 78.5 (IQR 44-102) days and 25 (96%) are alive after median follow-up of 118 days (IQR 31-170).Interpretation: Increased mortality in LT candidates with COVID-19 (32·7%), reaching 49·2% in those with decompensated cirrhosis and lab-MELD score ≥15, with no significant difference between first and second wave of the pandemic. Respiratory failure was the major cause of death. The dismal prognosis of patients with decompensated cirrhosis supports the adoption of strict preventative measures and the urgent testing of vaccination efficacy in this population. Prior SARS-CoV-2 symptomatic infection did not affect early post-transplant survival (96%).Funding: No funding source.Declaration of Interests: None to declare. Ethics Approval Statement: Data was collected in accordance with General Data Protection Regulation (GDPR), the European Union legislation and the ELTR privacy policy. Reg. HCB/2020/0479 released by CLINICAL RESEARCH ETHICS COMMITTEE from Hospital Clinic Barcelona

The repurposed use of anesthesia machines to ventilate critically ill patients with Coronavirus Disease 2019 (COVID-19) (preprint)

Background: The surge of critically ill patients due to the coronavirus disease-2019 (COVID-19) overwhelmed critical care capacity in areas of northern Italy. Anesthesia machines have been used as alternatives to traditional ICU mechanical ventilators. However, the outcomes for patients with COVID-19 respiratory failure cared for with Anesthesia Machines is currently unknow. We hypothesized that COVID-19 patients receiving care with Anesthesia Machines would have worse outcomes compared to standard practice.MethodsWe designed a retrospective study of patients admitted with a confirmed COVID-19 diagnosis at a large tertiary urban hospital in northern Italy. Two care units were included: a 27-bed standard ICU and a 15-bed temporary unit emergently opened in an operating room setting. Intubated patients assigned to Anesthesia Machines (AM group) were compared to a control cohort treated with standard mechanical ventilators (ICU-VENT group). Outcomes were assessed at 60-day follow-up. A multivariable Cox regression analysis of risk factors between survivors and non-survivors was conducted to determine the adjusted risk of death for patients assigned to AM group.ResultsComplete daily data from 89 mechanically ventilated patients consecutively admitted to the two units were analyzed. Seventeen patients were included in the AM group, whereas 72 were in the ICU-VENT group. Disease severity and intensity of treatment were comparable between the two groups. The 60-day mortality was significantly higher in the AM group compared to the ICU-vent group (12/17 vs. 27/72, 70.6% vs. 37.5%, respectively, p = 0.016). Allocation to AM group was associated with a significantly increased risk of death after adjusting for covariates (HR 4.05, 95% CI: 1.75–9.33, p = 0.001). Several incidents and complications were reported with Anesthesia Machine care, raising safety concerns.ConclusionsOur results support the hypothesis that care associated with the use of Anesthesia Machines is inadequate to provide long-term critical care to patients with COVID-19. Added safety risks must be considered if no other option is available to treat severely ill patients during the ongoing pandemic.Clinical Trial NumberNot applicable

Prone Position in Intubated, Mechanically Ventilated Patients with Coronavirus Disease-19. (preprint)

Background: Limited data are available on the use of prone position in intubated, invasively ventilated patients with Coronavirus disease-19 (COVID-19). Aim of this study is to investigate the use and effect of prone position in this population during the first 2020 pandemic wave.Methods: Retrospective, multicentre, national cohort study conducted between February 24 and June 14, 2020 in 24 Italian Intensive Care Units (ICU) on adult patients needing invasive mechanical ventilation for respiratory failure caused by COVID-19.Clinical data were collected on the day of ICU admission. Information regarding the use of prone position were collected daily. Follow-up for patient outcomes was performed on July 15, 2020. The respiratory effects of the first prone position were studied in a subset of 78 patients. Patients were classified as Responders if the PaO2/FiO2 ratio increased ≥ 20 mmHg during prone position. Results:  Of 1057 included patients, mild, moderate and severe ARDS was present in 15, 50 and 35% of patients, respectively and had a resulting mortality of 25, 33 and 41%. Prone position was applied in 61% of the patients. Patients placed prone had a more severe disease and died significantly more (45% vs 33%, p<0.001). Overall, prone position induced a significant increase in PaO2/FiO2 ratio, while no change in respiratory system compliance was observed. Seventy-eight % of patients were Responders to prone position. Non-Responders had a more severe respiratory failure and died more often in the ICU (65% vs. 38%, p=0.047).Conclusions: During the COVID-19 pandemic, prone position has been widely adopted to treat mechanically ventilated patients with respiratory failure. The majority of patients improved their oxygenation during prone position, most likely due to a better ventilation perfusion matching.Trial registration: clinicaltrials.gov  number: NCT04388670

Tracheostomy Practice in Mechanically Ventilated Patients With SARS-CoV-2 Induced Acute Respiratory Distress Syndrome: a Single-center Retrospective Study With Focus on Tracheomalacia (preprint)

Background: The SARS-CoV-2 pandemic increased the number of patients needing invasive mechanical ventilation, either through an endotracheal tube or through a tracheostomy. Tracheomalacia is a rare, but potentially severe complication of mechanical ventilation, which can significantly complicate the weaning process. Aim of this study was to describe the strategies of airway management in mechanically ventilated patients with respiratory failure due to SARS-CoV-2, the incidence of severe tracheomalacia, and investigate the factors associated with its occurrence.Methods. Retrospective, single-center study performed in an Italian teaching hospital. All adult patients admitted to the Intensive Care Unit (ICU) between February 24 and June 30, 2020, treated with invasive mechanical ventilation for respiratory failure caused by SARS-CoV-2 were included. Clinical data were collected on the day of ICU admission, while information regarding airway management was collected daily.Results. A total of 151 patients were included in the study. On admission, ARDS severity was mild in 21%, moderate in 62%, and severe in 17% of the cases, with an overall mortality of 39.7%. A tracheostomy was performed in 73 (48.3%) patients: open surgical technique in 54 patients (74%) and percutaneous Ciaglia technique in 19 patients (26%). Patients in whom a tracheostomy was performed had, compared to the other patients, a longer duration of mechanical ventilation and longer ICU and hospital length of stay. Tracheomalacia was diagnosed in 8 (5%) patients. The factors associated with tracheomalacia were female sex, obesity, and tracheostomy.Conclusions. In our population, approximately 50% of patients with ARDS due to SARS-CoV-2 were tracheostomized. Tracheostomized patients had a longer ICU and hospital length of stay. Five percent of our population was diagnosed with tracheomalacia. This percentage is 10 times higher than what is reported in available literature and the underlying mechanisms are not fully understood.

Neurological Manifestations in Patients Hospitalized with COVID-19: A Retrospective Analysis from a Large Cohort in Northern Italy (preprint)

Background: SARS-CoV2 infection is a systemic disease that may involve multiple organs, including the nervous system. Aims of our study are to describe prevalence and clinical features of neurological manifestations, mortality and hospital discharge in subjects hospitalized with COVID-19.Methods: All individuals admitted for COVID-19 were retrospectively included. Patients were classified according to the symptoms at hospital entry in 1) isolated respiratory, 2) combined respiratory and neurologic, 3) isolated neurologic and 4) stroke manifestations. Descriptive statistics and non-parametric tests to compare the groups were applied. Kaplan Meier probability curves and multivariable Cox regression models for survival and hospital discharge were applied.Results: The analysis included 901 patients, 42.6% showed a severe or critical disease with an overall mortality of 21.2%. At least one neurological symptom or disease was observed in 30.2% of subjects ranging from dysgeusia/anosmia (9.1%) to post-infective diseases (0.8%). Patients with respiratory symptoms experienced a more severe disease and a higher in-hospital mortality compared to those who showed only neurologic symptoms. Kaplan Meier estimates displayed a statistically significant different survival among groups (p=0.003): subjects with stroke had the worst. After adjusting for risk factors such as age, sex and comorbidity, individuals with isolated neurologic manifestations exhibited a better survival (aHR 0.398, 95% CI 0.206-0.769, p=0.006).Discussion: Neurologic manifestations in COVID-19 are common but heterogeneous. Subjects with isolated neurologic manifestations, experienced a lower mortality than those with respiratory symptoms, suggesting that neurologic disease may have a different course than when the virus involves respiratory system.Funding Statement: None.Declaration of Interests: The authors declare that they have no conflicts of interest for this work.Ethics Approval Statement: The local Ethics Committee approved the protocol under the special conditions indicated by the Italian 648/96 law. All subjects provided written informed consent.

Development of Machine Learning models to predict RT-PCR results for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data. (preprint)

Background: Reverse Transcription-Polymerase Chain Reaction (RT-PCR) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) diagnosis currently requires quite a long time span. A quicker and more efficient diagnostic tool in emergency departments could improve management during this global crisis. Our main goal was assessing the accuracy of artificial intelligence in predicting the results of RT-PCR for SARS-COV-2, using basic information at hand in all emergency departments. Methods: : This is a retrospective study carried out between February 22, 2020 and March 16, 2020 in one of the main hospitals in Milan, Italy. We screened for eligibility all patients admitted with influenza-like symptoms tested for SARS-COV-2. Patients under 12 years old and patients in whom the leukocyte formula was not performed in the ED were excluded. Input data through artificial intelligence were made up of a combination of clinical, radiological and routine laboratory data upon hospital admission. Different Machine Learning algorithms available on WEKA data mining software and on Semeion Research Centre depository were trained using both the Training and Testing and the K-fold cross-validation protocol. Results: : Among 199 patients subject to study (median [interquartile range] age 65 [46-78] years; 127 [63.8%] men), 124 [62.3%] resulted positive to SARS-COV-2. The best Machine Learning System reached an accuracy of 91.4% with 94.1% sensitivity and 88.7% specificity. Conclusion: Our study suggests that properly trained artificial intelligence algorithms may be able to predict correct results in RT-PCR for SARS-COV-2, using basic clinical data. If confirmed, on a larger-scale study, this approach could have important clinical and organizational implications.

Genomic epidemiology of SARS-CoV-2 reveals multiple lineages and early spread of SARS-CoV-2 infections in Lombardy, Italy (preprint)

From February to April, 2020, Lombardy (Italy) was the area who worldwide registered the highest numbers of SARS-CoV-2 infection. By extensively analyzing 346 whole SARS-CoV-2 genomes, we demonstrated the simultaneous circulation in Lombardy of two major viral lineages, likely derived from multiple introductions, occurring since the second half of January. Seven single nucleotide polymorphisms (five of them non-synonymous) characterized the SARS-CoV-2 sequences, none of them affecting N-glycosylation sites. These two lineages, and the presence of two well defined clusters inside Lineage 1, revealed that a sustained community transmission was ongoing way before the first COVID-19 case found in Lombardy.