Publications by authors named "Astrid Callegari"

4 Publications

  • Page 1 of 1

Acute kidney injury and single-dose administration of aminoglycoside in the Emergency Department: a comparison through propensity score matching.

G Ital Nefrol 2021 Jun 24;38(3). Epub 2021 Jun 24.

Department of Medicine (DAME), University of Udine, Udine, Italy; Department of Anesthesia and Intensive Care Medicine, ASUFC Hospital of Udine, Udine, Italy.

According to the Surviving Sepsis Campaign, aminoglycosides (AG) can be administered together with a β-lactam in patients with septic shock. Some authors propose administering a single dose of an AG combined with a β-lactam antibiotic in septic patients to extend the spectrum of antibiotic therapy. The aim of this study has been to investigate whether a single shot of AG when septic patients present at the Emergency Department (ED) is associated with acute kidney injury (AKI). We retrospectively enrolled patients based on a 3-year internal registry of septic patients visited in the Emergency Department (ED) of Pordenone Hospital. We compared the patients treated with a single dose of gentamicin (in addition to the β-lactam) and those who had not been treated to verify AKI incidence. 355 patients were enrolled. The median age was 71 years (IQR 60-78). Less than 1% of the patients had a chronic renal disease. The most frequent infection source was the urinary tract (31%), followed by intra-abdominal and lower respiratory tract infections (15% for both). 131 patients received gentamicin. Unmatched data showed a significant difference between the two groups in AKI (79/131, 60.3% versus 102/224, 45.5%; p=0.010) and in infectious disease specialist's consultation (77/131, 59% versus 93/224, 41.5%; p=0.002). However, after propensity score matching, no significant difference was found. Our experience shows that a single-shot administration of gentamicin upon admission to the ED does not determine an increased incidence of AKI in septic patients.
View Article and Find Full Text PDF

Download full-text PDF

June 2021

Artificial neural network model from a case series of COVID-19 patients: a prognostic analysis.

Acta Biomed 2021 05 12;92(2):e2021202. Epub 2021 May 12.

Department of Medicine, University of Udine, Udine, Italy; Department of Anesthesia and Intensive Care, ASUFC Santa Maria della Misericordia University Hospital of Udine, Udine, Italy.

Background And Aim: There is a need to determine which clinical variables predict the severity of COVID-19. We analyzed a series of critically ill COVID-19 patients to see if any of our dataset's clinical variables were associated with patient outcomes.

Methods: We retrospectively analyzed the data of COVID-19 patients admitted to the ICU of the Hospital in Pordenone from March 11, 2020, to April 17, 2020. Patients' characteristics of survivors and deceased groups were compared. The variables with a different distribution between the two groups were implemented in a generalized linear regression model (LM) and in an Artificial Neural Network (NN) model to verify the "robustness" of the association with mortality.

Results: In the considered period, we reviewed the data of 22 consecutive patients: 8 died. The causes of death were a severe respiratory failure (3), multi-organ failure (1), septic shock (1), pulmonary thromboembolism (2), severe hemorrhage (1). Lymphocyte and the platelet count were significantly lower in the group of deceased patients (p-value 0.043 and 0.020, respectively; cut-off values: 660/mm3; 280,000/mm3, respectively). Prothrombin time showed a statistically significant trend (p-value= 0.065; cut-off point: 16.8/sec). The LM model (AIC= 19.032), compared to the NN model (Mean Absolute Error, MAE = 0.02), was substantially alike (MSE 0.159 vs. 0.136).

Conclusions: In the context of critically ill COVID-19 patients admitted to ICU, lymphocytopenia, thrombocytopenia, and lengthening of prothrombin time were strictly correlated with higher mortality. Additional clinical data are needed to be able to validate this prognostic score.
View Article and Find Full Text PDF

Download full-text PDF

Source Listing
May 2021

Classification and analysis of outcome predictors in non-critically ill COVID-19 patients.

Intern Med J 2021 04 9;51(4):506-514. Epub 2021 Apr 9.

Department of Medicine, University of Udine, Udine, Italy.

Background: Early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients who could develop a severe form of COVID-19 must be considered of great importance to carry out adequate care and optimise the use of limited resources.

Aims: To use several machine learning classification models to analyse a series of non-critically ill COVID-19 patients admitted to a general medicine ward to verify if any clinical variables recorded could predict the clinical outcome.

Methods: We retrospectively analysed non-critically ill patients with COVID-19 admitted to the general ward of the hospital in Pordenone from 1 March 2020 to 30 April 2020. Patients' characteristics were compared based on clinical outcomes. Through several machine learning classification models, some predictors for clinical outcome were detected.

Results: In the considered period, we analysed 176 consecutive patients admitted: 119 (67.6%) were discharged, 35 (19.9%) dead and 22 (12.5%) were transferred to intensive care unit. The most accurate models were a random forest model (M2) and a conditional inference tree model (M5) (accuracy = 0.79; 95% confidence interval 0.64-0.90, for both). For M2, glomerular filtration rate and creatinine were the most accurate predictors for the outcome, followed by age and fraction-inspired oxygen. For M5, serum sodium, body temperature and arterial pressure of oxygen and inspiratory fraction of oxygen ratio were the most reliable predictors.

Conclusions: In non-critically ill COVID-19 patients admitted to a medical ward, glomerular filtration rate, creatinine and serum sodium were promising predictors for the clinical outcome. Some factors not determined by COVID-19, such as age or dementia, influence clinical outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source Listing
April 2021

Clinical and therapeutic aspects of candidemia: a five year single centre study.

PLoS One 2015 26;10(5):e0127534. Epub 2015 May 26.

Infectious Diseases Division, Santa Maria Misericordia University Hospital, Udine, Italy.

Background: Candida is an important cause of bloodstream infections (BSI) in nosocomial settings causing significant mortality and morbidity. This study was performed to evaluate contemporary epidemiology, species distribution, antifungal susceptibility and outcome of candida BSI in an Italian hospital.

Methods: All consecutive patients who developed candidemia at Santa Maria della Misericordia University Hospital (Italy) between January 2009 and June 2014 were enrolled in the study.

Results: A total of 204 episodes of candidemia were identified during the study period with an incidence of 0.79 episodes/1000 admissions. C. albicans was isolated in 60.3% of cases, followed by C. parapsilosis (16.7%), C. glabrata (11.8%) and C. tropicalis (6.4%). Of all Candida BSI, 124 (60.8 %) occurred in patients admitted to IMW, 31/204 (15.2 %) in ICUs, 33/204 (16.2%) in surgical units and 16/204 (7.8%) in Hematology/Oncology wards. Overall, 47% of patients died within 30 days from the onset of candidemia. C. parapsilosis and C. glabrata candidemia were associated with the lowest mortality rate (36%), while patients with C. tropicalis BSI had the highest mortality rate (58.3%). Lower mortality rates were detected in patients receiving therapy within 48 hours from the time of execution of the blood cultures (57,1% vs 38,9%, P < 0.05). At multivariate analysis, steroids treatment (OR = 0.27, p = 0.005) and CVC removal (OR = 3.77, p = 0.014) were independently associated with lower and higher survival probability, respectively. Candidemia in patients with peripherally inserted central catheters (PICC) showed to be associated with higher mortality in comparison with central venous catheters (CVC, Short catheters and Portacath) and no CVC use. For each point increase of APACHE III score, survival probability decreased of 2%. Caspofungin (OR = 3.45, p = 0.015) and Amphothericin B lipid formulation (OR = 15.26, p = 0.033) were independently associated with higher survival probability compared with no treatment.
View Article and Find Full Text PDF

Download full-text PDF

April 2016