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Background: Non-invasive mechanical ventilation (NIV) is effective for symptom relief and respiratory support in patients with respiratory insufficiency, severe comorbidities and no indication to intubation. Experience with NIV as the ceiling of treatment in severely compromised novel coronavirus disease (COVID-19) patients is lacking. Methods: We evaluated 159 patients with COVID-19-related acute respiratory syndrome (ARDS), 38 of whom with NIV as the ceiling of treatment, admitted to an ordinary ward and treated with continuous positive airway pressure (CPAP) and respiratory physiotherapy. Treatment failure and death were correlated with clinical and laboratory parameters in the whole cohort and in patients with NIV as the ceiling of treatment. Results: Patients who had NIV as the ceiling of treatment were elderly, with a low BMI and a high burden of comorbidities, showed clinical and laboratory signs of multi-organ insufficiency on admission and of rapidly deteriorating vital signs during the first week of treatment. NIV failure occurred overall in 77 (48%) patients, and 27/38 patients with NIV as the ceiling of treatment died. Congestive heart failure, chronic benign haematological diseases and inability/refusal to receive respiratory physiotherapy were independently associated to NIV failure and mortality. Need for increased positive end-expiratory pressures and low platelets were associated with NIV failure. Death was associated to cerebrovascular disease, need for CPAP cycles longer than 12h and, in the subgroup of patients with NIV as the ceiling of treatment, was heralded by vital sign deterioration within 48 h. Conclusions: NIV and physiotherapy are a viable treatment option for patients with severe COVID-19 and severe comorbidities.

ObjectivesTo assess the safety and efficacy of interleukin (IL)−6 blockade with sarilumab in patients with severe COVID-19 pneumonia and systemic hyperinflammation.MethodsWe conducted an open-label study of sarilumab in severe COVID-19 pneumonia (PaO2/FiO2 ResultsTwenty-eight patients were treated with sarilumab and 28 contemporary patients receiving standard of care alone were used as controls. At day 28 of follow-up, 61% of patients treated with sarilumab experienced clinical improvement and 7% died. These findings were not significantly different from the comparison group (clinical improvement 64%, mortality 18%; p=NS). Baseline PaO2/FiO2 ratio >100 mm Hg and lung consolidation ConclusionsAt day 28, overall clinical improvement and mortality in patients with severe COVID-19 were not significantly different between sarilumab and standard of care. Sarilumab was associated with faster recovery in a subset of patients showing minor lung consolidation at baseline.

Objectives The aim of our study was to describe the incidence and predictive factors of secondary infections in patients with coronavirus disease 2019 (COVID-19). Methods This was a cohort study of patients hospitalized with COVID-19 at IRCCS San Raffaele Hospital between 25th February and 6th April 2020 (NCT04318366). We considered secondary bloodstream infections (BSIs) or possible lower respiratory tract infections (pLRTIs) occurring 48 hours after hospital admission until death or discharge. We calculated multivariable Fine–Gray models to assess factors associated with risk of secondary infections. Results Among 731 patients, a secondary infection was diagnosed in 68 patients (9.3%); 58/731 patients (7.9%) had at least one BSI and 22/731 patients (3.0%) at least one pLRTI. The overall 28-day cumulative incidence was 16.4% (95%CI 12.4–21.0%). Most of the BSIs were due to Gram-positive pathogens (76/106 isolates, 71.7%), specifically coagulase-negative staphylococci (53/76, 69.7%), while among Gram-negatives (23/106, 21.7%) Acinetobacter baumanii (7/23, 30.4%) and Escherichia coli (5/23, 21.7%) predominated. pLRTIs were caused mainly by Gram-negative pathogens (14/26, 53.8%). Eleven patients were diagnosed with putative invasive aspergillosis. At multivariable analysis, factors associated with secondary infections were low baseline lymphocyte count (≤0.7 versus >0.7 per 109/L, subdistribution hazard ratios (sdHRs) 1.93, 95%CI 1.11–3.35), baseline PaO2/FiO2 (per 100 points lower: sdHRs 1.56, 95%CI 1.21–2.04), and intensive-care unit (ICU) admission in the first 48 hours (sdHR 2.51, 95%CI 1.04–6.05). Conclusions Patients hospitalized with COVID-19 had a high incidence of secondary infections. At multivariable analysis, early need for ICU, respiratory failure, and severe lymphopenia were identified as risk factors for secondary infections.

AIMS: To study whether insulin resistance accelerates the development and/or the progression of pancreatic adenocarcinoma (PDAC), we hypothesized that patients with insulin resistance, compared with those without insulin resistance, show: (1) a younger age and more advanced PDAC stage at diagnosis and (2) a shorter disease-free and overall survival after PDAC diagnosis. METHODS: Prospective observational study of patients admitted to a referral center for pancreatic disease. Insulin resistance was defined as a HOMA-IR value greater than the 66th percentile value of the patients included in this study. Survival was estimated according to Kaplan-Meier and by Cox regression. RESULTS: Of 296 patients with PDAC, 99 (33 %) met criteria for being classified as insulin resistant at diagnosis. Median follow-up time after diagnosis was 5.27 ± 0.23 years. Patients with insulin resistance received a diagnosis of PDAC at a similar age compared to patients without insulin resistance (67.1 ± 9 vs. 66.8 ± 10 years, p = 0.68), but were more likely to have a cancer stage ≥3 (23.2 vs. 14.2 %, p = 0.053) and a residual disease after surgery (R1 56.4 vs. 38 %; p = 0.007). The median overall survival was 1.3 ± 0.14 and 1.79 ± 0.11 years for the patients with and without insulin resistance, respectively (p = 0.016). Results did not change when patients with diabetes at PDAC diagnosis were excluded from the analysis. Multivariate analysis showed that insulin resistance was independently associated with overall survival. CONCLUSIONS: Insulin resistance is associated with the aggressiveness of PDAC.

Aim To investigate the effect of diabetes mellitus (DM) on disease-free and overall post-resection survival of patients with pancreatic ductal adenocarcinoma (PDAC) Methods Prospective observational study on patients admitted for pancreatic disease from January 2008 to October 2012. DM was classified as recent-onset (

Background Identification of a specific diabetes signature associated to pancreatic ductal carcinoma (PDAC) could be a key to detect asymptomatic, early stage tumors. We aim to characterize the clinical signature and the pathogenetic factors of the different types of diabetes associated with PDAC, based on the time between diabetes and cancer diagnosis. Methods Prospective observational study on 364 PDAC patients admitted to a referral center for pancreatic disease. Hospital and/or outpatient medical records were reviewed. Blood biochemical values including fasting blood glucose, insulin and/or C-peptide, glycosylated hemoglobin and anti-islet antibodies were determined. Diabetes onset was assessed after surgery and during follow-up. Results The prevalence of diabetes in patients was 67%. Considering 174 patients (47.8%) already having diabetes when diagnosed with PDAC (long duration, short duration, concomitant), the clinical and biochemical profile was similar to that of patients with type 2 diabetes (T2D). Diabetes was associated with known risk factors (i.e., age, sex, family history for diabetes and increased BMI) and both beta-cell dysfunction and insulin resistance were present. Considering 70 patients (19.2%) with onset of diabetes after PDAC diagnosis (early and late onset), the strongest predictor was the loss of beta-cell mass following pancreatectomy in patients with risk factors for T2D. Conclusion Different types of diabetes according to the time between diabetes and PDAC diagnosis are clinical entities widely overlapping with T2D. Therefore, the success of a strategy considering diabetes onset as a marker of asymptomatic PDAC will largely depend on our ability to identify new diabetes-unrelated biomarkers of PDAC.

Purpose: We aimed to assess the safety and efficacy of metformin for treating patients with metastatic pancreatic cancer and to identify endocrine and metabolic phenotypic features or tumor molecular markers associated with sensitivity to metformin antineoplastic action. Experimental Design: We designed an open-label, randomized, phase II trial to assess the efficacy of adding metformin to a standard systemic therapy with cisplatin, epirubicin, capecitabine, and gemcitabine (PEXG) in patients with metastatic pancreatic cancer. Patients ages 18 years or older with metastatic pancreatic cancer were randomly assigned (1:1) to receive PEXG every 4 weeks in combination or not with 2 g oral metformin daily. The primary endpoint was 6-months progression-free survival (PFS-6) in the intention-to-treat population. Results: Between August 2010 and January 2014, we randomly assigned 60 patients to receive PEXG with (n = 31) or without metformin (n = 29). At the preplanned interim analysis, the study was ended for futility. PFS-6 was 52% [95% confidence interval (CI), 33–69] in the control group and 42% (95% CI, 24–59) in the metformin group (P = 0.61). Furthermore, there was no difference in disease-free survival and overall survival between groups. Despite endocrine metabolic modifications induced by metformin, there was no correlation with the outcome. Single-nucleotide polymorphism rs11212617 predicted glycemic response, but not tumor response to metformin. Gene expression on tumor tissue did not predict tumor response to metformin. Conclusions: Addition of metformin at the dose commonly used in diabetes did not improve outcome in patients with metastatic pancreatic cancer treated with standard systemic therapy. Clin Cancer Res; 22(5); 1076–85. ©2015 AACR. See related commentary by Yang and Rustgi, p. 1031

In the developed world, pancreatic surgery is becoming more common, with an increasing number of patients developing diabetes because of either partial or total pancreatectomy, with a significant impact on quality of life and survival. Although these patients are expected to consume increasing health care resources in the near future, many aspects of diabetes after pancreatectomy are still not well defined. The treatment of diabetes in these patients takes advantage of the therapies used in type 1 and 2 diabetes; however, no specific guidelines for its management, both immediately after pancreatic surgery or in the long term, have been developed. In this article, on the basis of both the literature and our clinical experience, we address the open issues and discuss the most appropriate therapeutic options for patients with diabetes after pancreatectomy.