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Artif Organs ; 46(12): 2371-2381, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2279662

ABSTRACT

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) represents an advanced option for supporting refractory respiratory and/or cardiac failure. Systemic anticoagulation with unfractionated heparin (UFH) is routinely used. However, patients with bleeding risk and/or heparin-related side effects may necessitate alternative strategies: among these, nafamostat mesilate (NM) has been reported. METHODS: We conducted a systematic literature search (PubMed and EMBASE, updated 12/08/2021), including all studies reporting NM anticoagulation for ECMO. We focused on reasons for starting NM, its dose and the anticoagulation monitoring approach, the incidence of bleeding/thrombosis complications, the NM-related side effects, ECMO weaning, and mortality. RESULTS: The search revealed 11 relevant findings, all with retrospective design. Of these, three large studies reported a control group receiving UFH, the other were case series (n = 3) or case reports (n = 5). The main reason reported for NM use was an ongoing or high risk of bleeding. The NM dose varied largely as did the anticoagulation monitoring approach. The average NM dose ranged from 0.46 to 0.67 mg/kg/h, but two groups of authors reported larger doses when monitoring anticoagulation with ACT. Conflicting findings were found on bleeding and thrombosis. The only NM-related side effect was hyperkalemia (n = 2 studies) with an incidence of 15%-18% in patients anticoagulated with NM. Weaning and survival varied across studies. CONCLUSION: Anticoagulation with NM in ECMO has not been prospectively studied. While several centers have experience with this approach in high-risk patients, prospective studies are warranted to establish the optimal space of this approach in ECMO.


Subject(s)
Extracorporeal Membrane Oxygenation , Thrombosis , Humans , Extracorporeal Membrane Oxygenation/adverse effects , Heparin/adverse effects , Anticoagulants/adverse effects , Retrospective Studies , Hemorrhage/etiology , Thrombosis/etiology , Thrombosis/prevention & control , Thrombosis/drug therapy
2.
Nutr Metab Cardiovasc Dis ; 30(11): 1899-1913, 2020 10 30.
Article in English | MEDLINE | ID: covidwho-759219

ABSTRACT

BACKGROUND AND AIMS: There is poor knowledge on characteristics, comorbidities and laboratory measures associated with risk for adverse outcomes and in-hospital mortality in European Countries. We aimed at identifying baseline characteristics predisposing COVID-19 patients to in-hospital death. METHODS AND RESULTS: Retrospective observational study on 3894 patients with SARS-CoV-2 infection hospitalized from February 19th to May 23rd, 2020 and recruited in 30 clinical centres distributed throughout Italy. Machine learning (random forest)-based and Cox survival analysis. 61.7% of participants were men (median age 67 years), followed up for a median of 13 days. In-hospital mortality exhibited a geographical gradient, Northern Italian regions featuring more than twofold higher death rates as compared to Central/Southern areas (15.6% vs 6.4%, respectively). Machine learning analysis revealed that the most important features in death classification were impaired renal function, elevated C reactive protein and advanced age. These findings were confirmed by multivariable Cox survival analysis (hazard ratio (HR): 8.2; 95% confidence interval (CI) 4.6-14.7 for age ≥85 vs 18-44 y); HR = 4.7; 2.9-7.7 for estimated glomerular filtration rate levels <15 vs ≥ 90 mL/min/1.73 m2; HR = 2.3; 1.5-3.6 for C-reactive protein levels ≥10 vs ≤ 3 mg/L). No relation was found with obesity, tobacco use, cardiovascular disease and related-comorbidities. The associations between these variables and mortality were substantially homogenous across all sub-groups analyses. CONCLUSIONS: Impaired renal function, elevated C-reactive protein and advanced age were major predictors of in-hospital death in a large cohort of unselected patients with COVID-19, admitted to 30 different clinical centres all over Italy.


Subject(s)
Betacoronavirus , Cardiovascular Diseases/etiology , Coronavirus Infections/mortality , Hospital Mortality , Machine Learning , Pneumonia, Viral/mortality , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , C-Reactive Protein/analysis , COVID-19 , Female , Glomerular Filtration Rate , Humans , Male , Middle Aged , Pandemics , Retrospective Studies , Risk Factors , SARS-CoV-2 , Survival Analysis , Young Adult
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