RESUMO
Severe COVID-19 pneumonia in which mechanical ventilation is unable to achieve adequate gas exchange can be treated with veno-venous ECMO, eliminating the need for aggressive mechanical ventilation which might promote ventilator-induced lung injury and increase mortality. In this retrospective observational study, 18 critically ill COVID-19 patients who were treated using V-V ECMO during an 11-month period in a tertiary COVID-19 hospital were analyzed. Biomarkers of inflammation and clinical features were compared between survivors and non-survivors. Survival rates were compared between patients receiving ECMO and propensity matched mechanically ventilated controls. There were 7 survivors and 11 non-survivors. The survivors were significantly younger, with a higher proportion of females, higher serum procalcitonin at ICU admission, and before initiation of ECMO they had significantly lower Murray scores, PaCO2, WBC counts, serum ferritin levels, and higher glomerular filtration rates. No significant difference in mortality was found between patients treated with ECMO compared to patients treated using conventional lung protective ventilation. Hypercapnia, leukocytosis, reduced glomerular filtration rate, and increased serum ferritin levels prior to initiation of V-V ECMO in patients with severe COVID-19 pneumonia may be early warning signs of reduced chance of survival. Further multicentric studies are needed to confirm these findings.
RESUMO
Use of mechanical circulatory support (MCS) is a part of today's standard therapy in the treatment of end-stage heart failure. In this paper we describe characteristics of Thoratec pVAD device for MCS, implantation techniques, as well as the most important advantages and complications of application of the device. We present a 41-year-old patient with dilatated cardiomyopathy, who was the first recipient ofparacorporeal left ventricular assist device (LVAD) in the Republic of Croatia due to end-stage heart failure. After heart function recovery the patient was successfully weaned from MCS after 130 days of support.
Assuntos
Insuficiência Cardíaca/terapia , Coração Auxiliar , Adulto , Cardiomiopatia Dilatada/complicações , Insuficiência Cardíaca/etiologia , Humanos , MasculinoRESUMO
OBJECTIVES: Cardiac surgery-associated acute kidney injury (AKI) is a well-known factor influencing patients' long-term morbidity and mortality. Several prediction models of AKI requiring dialysis (AKI-D) have been developed. Only a few direct comparisons of these models have been done. Recently, a new, more uniform and objective definition of AKI has been proposed [Kidney Disease: Improve Global Outcomes (KDIGO)-AKI]. The performance of these prediction models has not yet been tested. METHODS: Preoperative demographic and clinical characteristics of 1056 consecutive adult patients undergoing cardiac surgery were collected retrospectively for the period 2012-2014. Multivariable logistic regression analysis was used to determine the independent predictors of AKI-D and the KDIGO-AKI stages. Risk scores of five prediction models were calculated using corresponding subgroups of patients. The discrimination of these models was calculated by the c-statistics (area under curve, AUC) and the calibration was evaluated for the model with the highest AUC by calibration plots. RESULTS: The incidence of AKI-D was 3.5% and for KDIGO-AKI 23% (17.3% for Stage 1, 2.1% for Stage 2 and 3.6% for Stage 3). Older age, atrial fibrillation, NYHA class III or IV heart failure, previous cardiac surgery, higher preoperative serum creatinine and endocarditis were independently associated with the development of AKI-D. For KDIGO-AKI, higher body mass index, older age, female gender, chronic obstructive pulmonary disease, previous cardiac surgery, atrial fibrillation, NYHA class III or IV heart failure, higher preoperative serum creatinine and the use of cardiopulmonary bypass were independent predictors. The model by Thakar et al. showed the best performance in the prediction of AKI-D (AUC 0.837; 95% CI = 0.810-0.862) and also in the prediction of KDIGO-AKI stage 1 and higher (AUC = 0.731; 95% CI = 0.639-0.761), KDIGO-AKI stage 2 and higher (AUC = 0.811; 95% CI = 0.783-0.838) and for KDIGO-AKI stage 3 (AUC = 0.842; 95% CI = 0.816-0.867). CONCLUSIONS: The performance of known prediction models for AKI-D was found reasonably well in the prediction of KDIGO-AKI, with the model by Thakar having the highest predictive value in the discrimination of patients with risk for all KDIGO-AKI stages.
Assuntos
Injúria Renal Aguda/etiologia , Procedimentos Cirúrgicos Cardíacos/efeitos adversos , Cardiopatias/cirurgia , Complicações Pós-Operatórias , Medição de Risco , Injúria Renal Aguda/epidemiologia , Idoso , Croácia/epidemiologia , Feminino , Seguimentos , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Prognóstico , Estudos Retrospectivos , Fatores de Risco , Fatores de TempoRESUMO
AIM: Our study aimed to examine the prevalence of non-diabetic renal disease in selected patients with type 2 diabetes mellitus and to determine important risk factors for non-diabetic renal disease. METHODS: We conducted retrospective analysis of clinical, laboratory and pathohistological data of type 2 diabetes mellitus patients in whom renal biopsies were performed from January 2004 to February 2013 at Dubrava University Hospital Zagreb Croatia (n=80). RESULTS: According to renal biopsy findings, isolated diabetic nephropathy was found in 46.25%, non-diabetic renal disease superimposed on diabetic nephropathy in 17.5% and isolated non-diabetic renal disease in 36.25% of the patients. The most common non-diabetic renal diseases found were: membranous nephropathy, followed by IgA nephropathy and focal segmental glomerulosclerosis. In univariate analysis shorter duration of diabetes, independence of insulin therapy, lower levels of HbA1c and absence of diabetic retinopathy were found to be significant clinical predictors of non-diabetic renal disease. In multivariate analysis only independence of insulin therapy (OR 4.418, 95%CI=1.477-13.216) and absence of diabetic retinopathy (OR 5.579, 95%CI=1.788-17.404) were independent predictors of non-diabetic renal disease. CONCLUSIONS: This study confirmed usefulness of renal biopsy in patients with type 2 diabetes mellitus, due to the high prevalence of non-diabetic renal disease found. Since non-diabetic renal disease are potentially curable, we should consider renal biopsy in selected type 2 diabetes mellitus patients with renal involvement, especially in those with absence of diabetic retinopathy and independence of insulin therapy.