Purpose
Clinical data on patients with intra-abdominal candidiasis (IAC) is still scarce.
Methods
We collected data from 13 hospitals in Italy, Spain, Brazil, and Greece over a 3-year period ...(2011–2013) including patients from ICU, medical, and surgical wards.
Results
A total of 481 patients were included in the study. Of these, 27 % were hospitalized in ICU. Mean age was 63 years and 57 % of patients were male. IAC mainly consisted of secondary peritonitis (41 %) and abdominal abscesses (30 %); 68 (14 %) cases were also candidemic and 331 (69 %) had concomitant bacterial infections. The most commonly isolated
Candida
species were
C. albicans
(
n
= 308 isolates, 64 %) and
C. glabrata
(
n
= 76, 16 %). Antifungal treatment included echinocandins (64 %), azoles (32 %), and amphotericin B (4 %). Septic shock was documented in 40.5 % of patients. Overall 30-day hospital mortality was 27 % with 38.9 % mortality in ICU. Multivariate logistic regression showed that age (OR 1.05, 95 % CI 1.03–1.07,
P
< 0.001), increments in 1-point APACHE II scores (OR 1.05, 95 % CI 1.01–1.08,
P
= 0.028), secondary peritonitis (OR 1.72, 95 % CI 1.02–2.89,
P
= 0.019), septic shock (OR 3.29, 95 % CI 1.88–5.86,
P
< 0.001), and absence of adequate abdominal source control (OR 3.35, 95 % CI 2.01–5.63,
P
< 0.001) were associated with mortality. In patients with septic shock, absence of source control correlated with mortality rates above 60 % irrespective of administration of an adequate antifungal therapy.
Conclusions
Low percentages of concomitant candidemia and high mortality rates are documented in IAC. In patients presenting with septic shock, source control is fundamental.
Invasive aspergillosis (IA) is a serious opportunistic infection, which has increasingly been recognized as an emerging disease of non-neutropenic patients. In this group of patients, the diagnosis ...of IA can be challenging owing to the lack of specificity of symptoms, the difficulty in discriminating colonization from infection, and the lower sensitivity of microbiological and radiological tests compared with immunocompromised patients. The aim of this article is to present to clinicians a critical review on the management of IA in non-neutropenic patients.
The rising incidence of bloodstream infections (BSI) due to Gram-negative bacteria (GNB) with difficult-to-treat resistance (DTR) has been recognized as a global emergency. The aim of this review is ...to provide a comprehensive assessment of the mechanisms of antibiotic resistance, epidemiology and treatment options for BSI caused by GNB with DTR, namely extended-spectrum Beta-lactamase-producing Enterobacteriales; carbapenem-resistant Enterobacteriales; DTR Pseudomonas aeruginosa; and DTR Acinetobacter baumannii.
Critically ill COVID-19 patients have pathophysiological lung features characterized by perfusion abnormalities. However, to date no study has evaluated whether the changes in the distribution of ...pulmonary gas and blood volume are associated with the severity of gas-exchange impairment and the type of respiratory support (non-invasive versus invasive) in patients with severe COVID-19 pneumonia.
This was a single-center, retrospective cohort study conducted in a tertiary care hospital in Northern Italy during the first pandemic wave. Pulmonary gas and blood distribution was assessed using a technique for quantitative analysis of dual-energy computed tomography. Lung aeration loss (reflected by percentage of normally aerated lung tissue) and the extent of gas:blood volume mismatch (percentage of non-aerated, perfused lung tissue-shunt; aerated, non-perfused dead space; and non-aerated/non-perfused regions) were evaluated in critically ill COVID-19 patients with different clinical severity as reflected by the need for non-invasive or invasive respiratory support.
Thirty-five patients admitted to the intensive care unit between February 29th and May 30th, 2020 were included. Patients requiring invasive versus non-invasive mechanical ventilation had both a lower percentage of normally aerated lung tissue (median interquartile range 33% 24-49% vs. 63% 44-68%, p < 0.001); and a larger extent of gas:blood volume mismatch (43% 30-49% vs. 25% 14-28%, p = 0.001), due to higher shunt (23% 15-32% vs. 5% 2-16%, p = 0.001) and non-aerated/non perfused regions (5% 3-10% vs. 1% 0-2%, p = 0.001). The PaO
/FiO
ratio correlated positively with normally aerated tissue (ρ = 0.730, p < 0.001) and negatively with the extent of gas-blood volume mismatch (ρ = - 0.633, p < 0.001).
In critically ill patients with severe COVID-19 pneumonia, the need for invasive mechanical ventilation and oxygenation impairment were associated with loss of aeration and the extent of gas:blood volume mismatch.
The possible negative impact of severe adult respiratory distress caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection (COVID-19) on antimicrobial stewardship and ...infection control has been postulated, but few real-life data are available. The aim of this study was to report our experience with colonization/infection of carbapenem-resistant
(CRPA), carbapenem-resistant
(CR-Kp) and
among critically ill COVID-19 patients admitted to the intensive care unit (ICU). All COVID-19 patients admitted to the ICUs at San Martino Policlinico Hospital-IRCCS in Genoa, Italy, were screened from 28 February to 31 May 2020. One-hundred and eighteen patients admitted to COVID-19 ICUs were included in the study. Among them, 12 (10.2%) became colonized/infected with CRPA, 6 (5.1%) with
and 2 (1.6%) with CR-Kp. All patients with CRPA received prior treatment with meropenem, and in 11 (91.7%) infection was not preceded by colonization. Four patients (66.7%) developed
candidemia. A significant spread of resistant pathogens was observed among critically ill COVID-19 patients. Dedicated strategies are warranted to prevent horizontal spread and maintain effective antimicrobial stewardship programs in the setting of COVID-19 care.
The primary objective of this multicenter, observational, retrospective study was to assess the incidence rate of ventilator-associated pneumonia (VAP) in coronavirus disease 2019 (COVID-19) patients ...in intensive care units (ICU). The secondary objective was to assess predictors of 30-day case-fatality of VAP. From 15 February to 15 May 2020, 586 COVID-19 patients were admitted to the participating ICU. Of them, 171 developed VAP (29%) and were included in the study. The incidence rate of VAP was of 18 events per 1000 ventilator days (95% confidence intervals CI 16-21). Deep respiratory cultures were available and positive in 77/171 patients (45%). The most frequent organisms were
(27/77, 35%) and
(18/77, 23%). The 30-day case-fatality of VAP was 46% (78/171). In multivariable analysis, septic shock at VAP onset (odds ratio OR 3.30, 95% CI 1.43-7.61,
= 0.005) and acute respiratory distress syndrome at VAP onset (OR 13.21, 95% CI 3.05-57.26,
< 0.001) were associated with fatality. In conclusion, VAP is frequent in critically ill COVID-19 patients. The related high fatality is likely the sum of the unfavorable prognostic impacts of the underlying viral and the superimposed bacterial diseases.
The incidence and the clinical presentation of neurological manifestations of coronavirus disease-2019 (COVID-19) remain unclear. No data regarding the use of neuromonitoring tools in this group of ...patients are available.
This is a retrospective study of prospectively collected data. The primary aim was to assess the incidence and the type of neurological complications in critically ill COVID-19 patients and their effect on survival as well as on hospital and intensive care unit (ICU) length of stay. The secondary aim was to describe cerebral hemodynamic changes detected by noninvasive neuromonitoring modalities such as transcranial Doppler, optic nerve sheath diameter (ONSD), and automated pupillometry.
Ninety-four patients with COVID-19 admitted to an ICU from February 28 to June 30, 2020, were included in this study. Fifty-three patients underwent noninvasive neuromonitoring. Neurological complications were detected in 50% of patients, with delirium as the most common manifestation. Patients with neurological complications, compared to those without, had longer hospital (36.8 ± 25.1 vs. 19.4 ± 16.9 days,
< 0.001) and ICU (31.5 ± 22.6 vs. 11.5±10.1 days,
< 0.001) stay. The duration of mechanical ventilation was independently associated with the risk of developing neurological complications (odds ratio 1.100, 95% CI 1.046-1.175,
= 0.001). Patients with increased intracranial pressure measured by ONSD (19% of the overall population) had longer ICU stay.
Neurological complications are common in critically ill patients with COVID-19 receiving invasive mechanical ventilation and are associated with prolonged ICU length of stay. Multimodal noninvasive neuromonitoring systems are useful tools for the early detection of variations in cerebrovascular parameters in COVID-19.
Candidemia is associated with a heavy burden of morbidity and mortality in hospitalized patients. The availability of blood culture results could require up to 48-72 h after blood draw; thus, early ...treatment decisions are made in the absence of a definite diagnosis.
In this retrospective study, we assessed the performance of different supervised machine learning algorithms for the early differential diagnosis of candidemia and bacteremia in adult patients on a large dataset automatically extracted within the AUTO-CAND project.
Overall, 12,483 episodes of candidemia (1275; 10%) or bacteremia (11,208; 90%) were included in the analysis. A random forest classifier achieved the best diagnostic performance for candidemia, with sensitivity 0.98 and specificity 0.65 on the training set (true skill statistic TSS = 0.63) and sensitivity 0.74 and specificity 0.57 on the test set (TSS = 0.31). Then, the random classifier was trained in the subgroup of patients with available serum β-D-glucan (BDG) and procalcitonin (PCT) values by exploiting the feature ranking learned in the entire dataset. Although no statistically significant differences were observed from the performance measures obtained by employing BDG and PCT alone, the performance measures of the classifier that included the features selected in the entire dataset, plus BDG and PCT, were the highest in most cases.
Random forest classifiers trained on large datasets of automatically extracted data have the potential to improve current diagnostic algorithms for candidemia. However, further development through implementation of automatically extracted clinical features may be necessary to achieve crucial improvements.
Hospitalized patients with COVID-19 can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features
In this study, we externally ...confirmed the prognostic impact of clinical phenotypes previously identified by Gutierrez-Gutierrez and colleagues in a Spanish cohort of hospitalized patients with COVID-19, and the usefulness of their simplified probabilistic model for phenotypes assignment
This could indirectly support the validity of both phenotype's development and their extrapolation to other hospitals and countries for management decisions during other possible future viral pandemics
Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis.
Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method.
Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio HR 3.10, 95% confidence interval CI 1.81-5.30, p < 0.001) and for phenotype C vs. B (HR 2.20, 95% CI 1.50-3.23, p < 0.001). A non-statistically significant trend towards higher mortality was also observed for phenotype B vs. A (HR 1.41; 95% CI 0.92-2.15, p = 0.115). By means of cluster analysis, three different phenotypes were also identified in our cohort, with an overall similar gradient in terms of prognostic impact to that observed when patients were assigned to FEN-COVID-19 phenotypes.
The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study.
is an emerging MDR pathogen raising major concerns worldwide. In Italy, it was first and only identified in July 2019 in our hospital (San Martino Hospital, Genoa), where infection or colonization ...cases have been increasingly recognized during the following months. To gain insights into the introduction, transmission dynamics, and resistance traits of this fungal pathogen, consecutive
isolates collected from July 2019 to May 2020 (
= 10) were subjected to whole-genome sequencing (WGS) and antifungal susceptibility testing (AST); patients' clinical and trace data were also collected. WGS resolved all isolates within the genetic clade I (South Asian) and showed that all but one were part of a cluster likely stemming from the index case. Phylogenetic molecular clock analyses predicted a recent introduction (May 2019) in the hospital setting and suggested that most transmissions were associated with a ward converted to a COVID-19-dedicated ICU during the pandemic. All isolates were resistant to amphotericin B, voriconazole, and fluconazole at high-level, owing to mutations in
(K143R) and
(A640V). Present data demonstrated that the introduction of MDR
in Italy was a recent event and suggested that its spread could have been facilitated by the COVID-19 pandemic. Continued efforts to implement stringent infection prevention and control strategies are warranted to limit the spread of this emerging pathogen within the healthcare system.
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