Serial monitoring of pancreatic stone protein for the detection of sepsis in intensive care unit patients with complicated abdominal surgery: A prospective, longitudinal cohort study.

PURPOSE: The objective of this study was to assess the performance of pancreatic stone protein (PSP) monitoring for the detection of sepsis, prediction of outcome and distinction between bacterial and fungal infections in intensive care unit (ICU) patients with complicated abdominal surgery. MATERIALS AND METHODS: In this prospective multicenter cohort study, patients with complicated abdominal surgery had serial PSP measurements during their ICU stay. Infectious episodes were classified as bacterial, fungal or mixed. PSPmax (maximal PSP value within 48 h of the diagnosis of infection) and ΔPSP (difference between PSPmax and the preceding PSP value) were used for analyses. RESULTS: PSPmax was obtained for 118 infectious episodes (68 patients). ΔPSP was available for 73 episodes (48 patients). Both PSPmax and ΔPSP were significantly higher in patients with sepsis and in patients with a fatal outcome. A PSPmax ≥124 ng/ml and a ΔPSP ≥34 ng/ml could detect sepsis with a sensitivity/specificity of 84%/54% and 69%/76%, respectively. There was no significant difference of PSPmax or ΔPSP between patients with bacterial/mixed versus fungal infections. CONCLUSIONS: Serial PSP monitoring may be an additional tool for the early detection of sepsis in patients with complicated abdominal surgery who are at high risk of severe infections.

Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study.

Purpose: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. Methods: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities. Results: In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19. Conclusions: This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive.

Increasing morbidity and mortality of candidemia over one decade in a Swiss university hospital.

BACKGROUND: The epidemiology of candidemia is evolving with raising concern about the emergence of intrinsically resistant non-albicans Candida species and acquisition of antifungal resistance. In addition to microbiological surveys, epidemiological studies including clinical data are needed to assess the impact of candidemia on morbidity and mortality. OBJECTIVES: To assess the clinical and microbiological trends of candidemia in a Swiss university hospital. PATIENTS/METHODS: This single-centre retrospective study compared the incidence of candidemia, Candida species distribution, antifungal resistance profiles, clinical characteristics and outcomes between two periods separated by one decade. RESULTS: A total of 170 candidemic episodes were included (68 from period 1, 2004-2006, and 102 from period 2, 2014-2017). Incidence of candidemia (0.85 to 0.97 episode/10,000 patient-days), species distribution (55%-57% C albicans) and antifungal susceptibilities remained unchanged. During period 2, candidemia was more frequently observed in intensive care units (ICU, 38% vs 19% in period 1, P = .01) and amongst older patients (median age 68 vs 59 years old, P < .01) with more immunosuppressive conditions (24% vs 9%, P = .01). Candidemia in period 2 was more frequently followed by septic shock (23% vs 7% in period 1, P = .01) and ICU admission (42% vs 12%, P < .01) and was associated with higher mortality (34% vs 18%, P = .03). Overall, factors associated with mortality in multivariate analyses included cirrhosis, solid malignancies and ICU stay at the time of candidemia. CONCLUSIONS: Despite stable incidence, species distribution and antifungal resistance of candidemia, an epidemiological shift of the disease towards older and more critically ill patients was observed, with higher mortality rates.

Risk factors for candidemia: a prospective matched case-control study.

BACKGROUND: Candidemia is an opportunistic infection associated with high morbidity and mortality in patients hospitalized both inside and outside intensive care units (ICUs). Identification of patients at risk is crucial to ensure prompt antifungal therapy. We sought to assess risk factors for candidemia and death, both outside and inside ICUs. METHODS: This prospective multicenter matched case-control study involved six teaching hospitals in Switzerland and France. Cases were defined by positive blood cultures for Candida sp. Controls were matched to cases using the following criteria: age, hospitalization ward, hospitalization duration, and, when applicable, type of surgery. One to three controls were enrolled by case. Risk factors were analyzed by univariate and multivariate conditional regression models, as a basis for a new scoring system to predict candidemia. RESULTS: One hundred ninety-two candidemic patients and 411 matched controls were included. Forty-four percent of included patients were hospitalized in ICUs, and 56% were hospitalized outside ICUs. Independent risk factors for candidemia in the ICU population included total parenteral nutrition, acute kidney injury, heart disease, prior septic shock, and exposure to aminoglycoside antibiotics. Independent risk factors for candidemia in the non-ICU population included central venous catheter, total parenteral nutrition, and exposure to glycopeptides and nitroimidazoles. The accuracy of the scores based on these risk factors is better in the ICU than in the non-ICU population. Independent risk factors for death in candidemic patients included septic shock, acute kidney injury, and the number of antibiotics to which patients were exposed before candidemia. DISCUSSION: While this study shows a role for known and novel risk factors for candidemia, it specifically highlights important differences in their distribution according to the hospital setting (ICU versus non-ICU). CONCLUSION: This study provides novel risk scores for candidemia accounting for the hospital setting and recent progress in patients' management strategies and fungal epidemiology.

Preventing invasive candida infections. Where could we do better?

Invasive candidiasis is associated with high mortality rates, ranging from 35% to 60%, in the range reported for septic shock. The epidemiology and pathogenesis of invasive candidiasis differ according to the patient's immune status; the majority of cases in immunocompromised hosts are candidaemia, whereas non-candidaemic systemic candidiasis accounts for the majority of cases in critically ill patients. In contrast to candidaemia, non-candidaemic systemic candidiasis is difficult to prove, especially in critically ill patients. Up to 80% of these patients are colonized, but only 5-30% develop invasive infection. The differentiation of colonization and proven infection is challenging, and evolution from the former to the latter requires seven to 10 days. This continuum from colonization of mucosal surfaces to local invasion and then invasive infection makes it difficult to identify those critically ill patients likely to benefit most from antifungal prophylaxis or early empirical antifungal treatment. Early empirical treatment of non-candidaemic systemic candidiasis currently relies on the positive predictive value of risk assessment strategies, such as the colonization index, candida score, and predictive rules based on combinations of risk factors such as candida colonization, broad-spectrum antibiotics, and abdominal surgery. Although guidelines recently scored these strategies as being supported by limited evidence, they are widely used at bedside and have substantially decreased the incidence of invasive candidiasis.