Candidemia in critically ill COVID-19 patients: Risk factors and impact on mortality.

Background: Risk factors of candidemia are well-described in intensive care units (ICUs) before the Coronavirus disease 2019 (COVID-19) pandemic. The increased rates of admission to ICUs have appeared during the pandemic. Methods: Patient characteristics and laboratory data of 80 candidemia with COVID-19, 101 candidemia without COVID-19, and 100 non-candidemia with COVID-19 patients were evaluated, in this study. Results: Systemic inflammatory response syndrome (SIRS) ≥ 2, solid malignancy, total parenteral nutrition (TPN), central venous catheterization (CVC), hypotension, fever, urea, alanine aminotransferase (ALT), D-dimer, procalcitonin, ferritin, and delta neutrophil index (DNI) was found to be associated with candidemia in COVID-19 patients. TPN, hypotension, and fever were identified as independent predictors of candidemia in COVID-19, and candidemia in COVID-19 is characterized by significantly high mortality rates. Urea, lactate, and procalcitonin were defined as independent predictors of hospital mortality in candidemia patients with COVID-19. Conclusion: The presence of candidemia increases mortality in COVID-19. TPN, fever, and hypotension werefound to be the most powerful predictors of candidemia in COVID-19. Overall, these data show that candidemia in COVID-19 is characterized by significantly high mortality rates. Determination of distinctive features can prevent candidemia and mortality.

The usefulness of hematological parameters and cerebrospinal fluid indexes in the differential diagnosis of acute bacterial from viral meningitis.

Central nervous system (CNS) infection is a medical emergency with an important cause of mortality worldwide. The 79 patients with confirmed acute CNS infection (48 bacterial and 31 viral meningitis) were evaluated. Bacterial meningitis score, cerebrospinal fluid (CSF)/serum glucose ratio, and CSF/serum albumin ratio had the highest area under the curves (0.873, 0.843, 0.810, respectively) for discriminating bacterial meningitis. Neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte ratio (PLR) and CSF lactate dehydrogenase have a good ability for the differential diagnosis of bacterial meningitis. CSF/serum glucose ratio, NLR (with a cut-off value> 8.87), large unstained cell, total protein, albumin, and procalcitonin levels were found to be predictors for mortality. NLR can be used as a biomarker to differentiate bacterial meningitis from viral meningitis and to predict the prognosis of CNS infection. CSF/serum albumin ratio and CSF lactate dehydrogenase can be used to predict bacterial meningitis as well as CSF/serum glucose ratio.

Prognostic Value of Hemogram-Derived Ratios in Patients with Crimean-Congo Hemorrhagic Fever.

Background: Crimean-Congo hemorrhagic fever (CCHF) is an emerging infectious disease that has epidemic and pandemic potential and causes mortality. Predicting the outcome of the disease is important to guide the management of patients and prevent mortality. Materials and Methods: This study aimed to investigate hemogram parameters and hemogram-derived ratios for predicting mortality in 207 patients with CCHF (survivors = 177, nonsurvivors = 30). Results: Compared with the survivor group, the nonsurvivor group had higher neutrophils, neutrophil-to-lymphocyte ratio (NLR), derived NLR (d-NLR), and aspartate aminotransferase (AST), AST-to-lymphocyte ratio index (ALRI) on admission and third day of hospitalization. Higher white blood cells (WBCs), lower platelet-to-lymphocyte ratio on admission, and lower lymphocytes, and monocytes on the third day were found in the nonsurvivor group. Evaluating the change of admission and the third day of laboratory values, a downward trend in neutrophils, NLR, d-NLR, ALRI, and an upward trend in WBCs were found statistically significant in the survivor group. These dynamic changes were not found in the nonsurvivor group. AST (third day) and ALRI (third day) had the highest area under the curve (AUC) in the receiver operating characteristic analysis (0.939 and 0.934, respectively; p-value is <0.0001 for all). The NLR on the third day than on admission had a higher AUC, the optimal cutoff value was 1.44, which resulted in a sensitivity of 93.33 and a specificity of 40.34 (AUC: 0.790, p < 0.0001). The d-NLR on the third day had a higher AUC (with a sensitivity of 81.48 and a specificity of 67.43) than on admission (0.781 and 0.669, respectively). Conclusion: CCHF is a common vector-borne disease and mortality rates are high. This study revealed that NLR, d-NLR, and ALRI can be used as biomarkers to predict mortality. Patients who survived had better improvement in hemogram parameters and ratios. Therefore, patients who do not show this improvement should be followed more closely.

Diagnostic value of ß-D-glucan alone or combined with Candida score, colonization index and C-reactive protein for candidemia.

INTRODUCTION: Candidemia causes high mortality and is occuring at increasing rate in intensive care units (ICUs). (1,3)- ß-D-glucan (BDG) testing is recommended in neutropenic patients. However the usefulness of BDG in ICUs is unclear. METHODOLOGY: This study was conducted to compare the diagnostic value of Candida score (CS), colonization index (CI), serum BDG detection, and routine laboratory parameters in ICU patients. Characteristics and laboratory data of 83 patients (15 patients with candidemia and 68 patients without candidemia) were evaluated. RESULTS: Median serum BDG was significantly higher in the candidemia group (129 pg/mL vs. 36 pg/mL, p < 0.001). BDG assay with standard cut-off value ≥ of 80 pg/mL had 93.33% sensitivity and 64.18% specificity (Areas under the ROC curve (AUC): 0.788). This study concluded that the optimal cut-off value for BDG assay was 112 pg/mL with sensitivity of 86.67% and specificity of 82.09% (AUC: 0.844). C-reactive protein (CRP) with optimal cut-off value ≥ 85 mg/L and BDG ≥ 80 pg/mL had the highest AUC (0.862, 95% CI: 0.768 - 0.928) with sensitivity 93.33% and specificity 79.1%. CONCLUSIONS: Predicting candidemia is essential in critically ill patients who are at high risk and have high mortality rates. The results of this study suggest that BDG testing is useful for predicting candidemia in ICU. However, BDG combined with CRP may be a stronger predictor for candidemia.

Are angiotensin converting enzyme (ACE1/ACE2) gene variants associated with the clinical severity of COVID-19 pneumonia? A single-center cohort study.

OBJECTIVE: The impact of the coronavirus disease 2019 (COVID-19) pandemic has been unceasingly ongoing worldwide. Recent bioinformatics analysis and epidemiologic studies have highlighted that the functional polymorphisms on the angiotensin converting enzyme (ACE) gene may have an impact on the clinical progress of COVID-19. In this study, we aimed to determine the impact of the ACE1 gene I/D polymorphism and ACE2 peptidase-2 domain variants on disease severity. METHODS: Hundred patients with confirmed COVID-19 related pneumonia [50 patients with severe disease in intensive care unit (ICU) and 50 patients not in ICU] were compared on the basis of genetic and clinical characteristics. Genomic DNA was purified from peripheral blood lymphocytes with an automated QIA symphony DSP DNA Mini-Kit. The Sanger sequencing analysis was performed. The frequencies of ACE1 gene polymorphism and ACE2 PD variants were compared in patients hospitalized in ICU and those not in ICU. The Statistical Package for Social Sciences version 22.0 was used for statistical analysis. RESULTS: The sequencing analysis of the ACE2 gene exon 1 and 2 revealed none of the polymorphisms investigated or any other variants in the present cohort. The frequencies of the ACE1 ID, DD, and II genotypes were 51%, 31%, and 18%, respectively. The frequency of the D allele was similar between the ICU and non-ICU groups (50.4% versus 49.6%). Older age and the presence of advanced stage radiologic abnormalities on admission were detected as independent predictors of ICU requirement. CONCLUSION: No effect of any ACE1 gene polymorphism on predicting ICU requirement was detected. To the best of our knowledge, this is the first study investigating the impact of ACE gene polymorphisms on clinical severity of COVID-19 in a Turkish cohort.

Assessment of Galectin-1, Galectin-3, and Prostaglandin E2 Levels in Patients with COVID-19.

It is important to determine the inflammatory biomarkers in the severity of coronavirus disease 2019 (COVID-19) with the emergence of the pandemic. Galectins and prostaglandins play important roles in the regulation of immune and inflammatory responses. Therefore, this study aimed to investigate Galectin-1 (Gal-1), Galectin-3 (Gal-3), and prostaglandin E2 (PGE2) levels in patients with COVID-19. Serum concentrations of Gal-1, Gal-3, and PGE2 were measured using enzyme-linked immunosorbent assay on 84 patients with COVID-19 (severe = 29 and nonsevere = 55) and 56 healthy controls. In this study, increased levels of Gal-1 (median, 9.86, 6.35, and 3.67 ng/mL), Gal-3 (median, 415.31, 326.33, and 243.13 pg/mL), and PGE2 (median, 193.17, 192.58, and 124.62 pg/mL) levels were found in patients with COVID-19 than in healthy controls (P < 0.001 for all). In the severe disease group, Gal-3 levels were higher, while no differences were noted in Gal-1 and PGE2 levels (P = 0.011, P = 0.263, and P = 0.921, respectively). Serum levels of Gal-1 were positively correlated with those of Gal-3 (P = 0.871 and P < 0.001). Gal-3, C-reactive protein, lymphocyte count, and age were found as independent predictors of disease severity (P = 0.002, P = 0.001, P = 0.007, and P = 0.003, respectively). With the emergence of effective drug needs in the COVID-19 pandemic, differentiation of severe disease is important. Therefore, Gal-3 could be a potential prognostic biomarker of COVID-19.

Efficacy and cost-effectivity analysis of outpatient parenteral antimicrobial therapy unit in infectious disease clinical practices: Turkey perspective.

BACKGROUND: Outpatient parenteral antimicrobial treatment (OPAT) has become a common treatment modality in developed countries. OPAT units are not widespread in Turkey, and their cost-effectivity analysis has not been studied, yet. AIMS: To analyze the clinical efficacy and cost-effectiveness of the OPAT unit, based on a 1000-bed teaching hospital. METHODS: The records of patients, who were treated between October 2013 and December 2017, in an OPAT unit of a tertiary hospital in Ankara, were obtained retrospectively. The cost that would arise if the patients were hospitalized for the same treatment period with the same diagnosis was calculated and compared with the actual treatment cost of the patients in the OPAT unit. RESULTS: A total of 594 patients who received antimicrobial treatment at the OPAT unit were enrolled. The mean age of the patients was 55.39 ± 16.37 years and 313 (52.7%) were males. Based on the end-of-treatment goals, 98.5% of the patients reached the treatment goal. An indirect cost analysis revealed that the OPAT unit was 487.625 94 TL/129.008 78 $ less costly than inpatient parenteral antibiotic treatment. In other words, OPAT cost was 75% of the equivalent inpatient costs. It was also determined that a total of 7078 bed days and 11.9 bed days per person were saved. CONCLUSIONS: OPAT units should be expanded increasingly in Turkey. The evaluation together with the health care system conditions in Turkey revealed that the OPAT program is safe, effective, and cost-efficient.

Predictive performance of CT for adverse outcomes among COVID-19 suspected patients: a two-center retrospective study.

The aim of the study was to compare the performance of various computed tomography (CT) reporting tools, including zonal CT visual score (ZCVS), the number of involved lobes, and Radiological Society of North America (RSNA) categorization in predicting adverse outcomes among patients hospitalized due to the lower respiratory symptoms during the coronavirus disease 2019 (COVID-19) pandemic. A total of 405 patients admitted with severe respiratory symptoms who underwent a chest CT were enrolled. The primary adverse outcome was intensive care unit (ICU) admission of patients. Predictive performances of reporting tools were compared using the area under the receiver operating characteristic curves (AUC ROC). Among the 405 patients, 39 (9.63%) required ICU support during their hospital stay. At least two or more observers reported a typical and indeterminate COVID-19 pneumonia CT pattern according to RSNA categorization in 70% (285/405) of patients. Among these, 63% (179/285) had a positive polymerase chain reaction (PCR test for the SARS-CoV-2 virus. The median number of lobes involved according to CT was higher in patients who required ICU support (median interquartile range [IQR], 5[3; 5] vs. 3[0; 5]). The median ZCVS score was higher among the patients that subsequently required ICU support (median [IQR], 4[0; 12] vs. 13[5.75; 24]). The bootstrap comparisons of AUC ROC showed significant differences between reporting tools, and the ZCVS was found to be superior (AUC ROC, 71-75%). The ZCVS score at the first admission showed a linear and significant association with adverse outcomes among patients with the lower respiratory tract symptoms during the COVID-19 pandemic.

Lymphocyte Subset Alteration and Monocyte CD4 Expression Reduction in Patients with Severe COVID-19.

The spectrum of coronavirus disease 2019 (COVID-19) severity, related to cellular immune functions, has not been fully clarified yet. Therefore, this study aimed to investigate the alteration of peripheral blood cells in patients with COVID-19. The flow cytometric characterization of immune cell subset was performed on 69 COVID-19 patients and 21 healthy controls. These data were evaluated based on the disease severity. A total of 69 patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were classified as asymptomatic infection (n = 14), nonsevere (n = 39), and severe (n = 16) groups. Decreased lymphocytes and increased CD14 + 4- monocytes are found in patients with severe COVID-19. Decreased CD4 expression level was observed in the monocytes of patients with severe COVID-19. The total lymphocytes, B and T lymphocytes, CD4+ cells and CD8+ cells, and natural killer (NK) and natural killer T (NKT) cells were found to be decreased in patients with severe COVID-19. The CD4+/CD8+ ratio was not significantly different between patients with COVID-19 and healthy controls. The percentage of activated T cells (CD3+HLA-DR+) and B cells (CD19+CD38+) was lower in patients with severe COVID-19. Age and CD4- monocytes were independent predictors of disease severity. The SARS-CoV-2 infection may affect lymphocyte subsets, resulting in decreased T and B cells, monocytes, and NK and NKT cells. Decreased CD4 expression level by monocytes was significantly correlated with disease severity. Further studies on the host immune response to SARS-CoV-2 infection are necessary to predict the disease severity and protect against the virus.

The role of haematological parameters in patients with COVID-19 and influenza virus infection.

SARS-CoV-2, the causative agent of coronavirus disease 19 (COVID-19), was identified in Wuhan, China. Since then, the novel coronavirus started to be compared to influenza. The haematological parameters and inflammatory indexes are associated with severe illness in COVID-19 patients. In this study, the laboratory data of 120 COVID-19 patients, 100 influenza patients and 61 healthy controls were evaluated. Lower lymphocytes, eosinophils, basophils, platelets and higher delta neutrophil index (DNI), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were found in COVID-19 and influenza groups compared to healthy controls. The eosinophils, lymphocytes and PLR made the highest contribution to differentiate COVID-19 patients from healthy controls (area under the curves (AUCs): 0.819, 0.817 and 0.716, respectively; P-value is <0.0001 for all). The NLR, the optimal cut-off value was 3.58, which resulted in a sensitivity of 30.8 and a specificity of 100 (AUC: 0.677, P < 0.0001). Higher leucocytes, neutrophils, DNI, NLR, PLR and lower lymphocytes, red blood cells, haemoglobin, haematocrit levels were found in severe patients at the end of treatment. Nonsevere patients showed an upward trend for lymphocytes, eosinophils and platelets, and a downward trend for neutrophils, DNI, NLR and PLR. However, there was an increasing trend for eosinophils, platelets and PLR in severe patients. In conclusion, NLR and PLR can be used as biomarkers to distinguish COVID-19 patients from healthy people and to predict the severity of COVID-19. The increasing value of PLR during follow-up may be more useful compared to NLR to predict the disease severity.

Clinical and laboratory features of COVID-19: Predictors of severe prognosis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) emerged first in December 2019 in Wuhan, China and quickly spread throughout the world. Clinical and laboratory data are of importance to increase the success in the management of COVID-19 patients. METHODS: Data were obtained retrospectively from medical records of 191 hospitalized patients diagnosed with COVID-19 from a tertiary single-center hospital between March and April 2020. Prognostic effects of variables on admission among patients who received intensive care unit (ICU) support and those who didn't require ICU care were compared. RESULTS: Patients required ICU care (n = 46) were older (median, 71 vs. 43 years), with more underlying comorbidities (76.1% vs. 33.1%). ICU patients had lower lymphocytes, percentage of large unstained cell (%LUC), hemoglobin, total protein, and albumin, but higher leucocytes, neutrophils, neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocytes ratio (PLR), urea, creatinine, aspartate amino transferase (AST), lactate dehydrogenase (LDH), and D-dimer when compared with non-critically ill patients (p < 0.001). A logistic regression model was created to include ferritin, %LUC, NLR, and D-dimer. %LUC decrease and D-dimer increase had the highest odds ratios (0.093 vs 5.597, respectively) to predict severe prognosis. D-dimer, CRP, and NLR had the highest AUC in the ROC analysis (0.896, 0.874, 0.861, respectively). CONCLUSIONS: The comprehensive analysis of clinical and admission laboratory parameters to identify patients with severe prognosis is important not only for the follow-up of the patients but also to identify the pathophysiology of the disease. %LUC decrease and D-dimer, NLR, and CRP increases seem to be the most powerful laboratory predictors of severe prognosis.

Virolactia in an Asymptomatic Mother with COVID-19.

Background: Limited data are available on the perinatal and postnatal transmission of novel coronavirus disease 2019 (COVID-19). The Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) recommended breastfeeding with necessary precautions to mothers with COVID-19. Case Presentation: A 20-year-old pregnant woman with no symptoms of COVID-19 presented to the hospital for delivery at 39 weeks of gestation. She was tested for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) by reverse transcriptase polymerase chain reaction (RT-PCR) because her father had been diagnosed with COVID-19. A nasopharyngeal swab RT-PCR test was positive for SARS-CoV-2. Therefore, the baby and the mother were cared for separately after delivery. Breast milk obtained after first lactation was tested by real-time RT-PCR and was positive for SARS-CoV-2. Conclusions: In this article, we aimed to report the presence of SARS-CoV-2 in breast milk. Although further studies are needed, this situation may have an impact on breastfeeding recommendations.

Does the course of laboratory parameters help us to predict the outcome of CCHF?

BACKGROUND/AIM: This study was performed to identify the characteristics distinguishing fatal and nonfatal cases of patients diagnosed with Crimean-Congo hemorrhagic fever (CCHF). MATERIALS AND METHODS: A total of 92 patients with confirmed diagnosis of CCHF in 2009-2013 were included in the study. RESULTS: A high level of urea and aPTT on the third day of hospital stay, diarrhea, somnolence, and the interval from the beginning of the symptoms to hospital admission were independently associated with fatality. Each 10-unit increase in aPTT and urea levels increased the fatality rate by 3.379-fold and 1.236-fold, respectively. Delay in hospital admission increased the fatality rate 1.453-fold for each day of delay. When comparing first and third admission-day laboratory values, the increase in leukocyte counts and the decrease in CPK, urea, creatinine, aPTT, PT, INR, and hemoglobin levels were significant in nonfatal cases. CONCLUSION: This study showed that the course of these laboratory tests helps us to predict the outcome of the disease. In a few days of hospitalization, persistence or progress of the abnormal laboratory parameters may warn us about poor prognosis.

Crimean-Congo Hemorrhagic Fever: Prognostic Factors and the Association of Leukocyte Counts with Mortality.

We aimed to determine the relationship between leukocyte counts and the survival of patients with Crimean-Congo hemorrhagic fever (CCHF), a life-threatening illness. This is the first study to do so. A total of 220 patients with CCHF were evaluated retrospectively. The mortality rate was 16.4%. Analysis of the relationship between leukocyte counts and mortality rates provided insight into the pathogenesis of CCHF. Receiving operating curve analysis revealed that leukocyte counts ≥2,950/mm(3) on the day of admission predicted mortality rate with 62.1% sensitivity. The mean hospitalization stay in patients with fatal disease was 4.3 days; therefore, leukocyte counts were compared on the day of admission and day 3 of the hospital stay. Increases in neutrophil levels and decreases in lymphocyte and monocyte levels were identified as significant risk factors for mortality (P = 0.01, 0.037, and 0.001, respectively). The mortality risk was 7-12 fold higher in patients whose levels of leukocytes (2,950 µL), lactate dehydrogenase (967.5 U/L), and alanine aminotransferase (>119.5 U/L) and activated partial thromboplastin time (42.4 s) exceeded the cut-off values; these were identified as independent predictors of mortality. Depletion of monocytes and lymphocytes and accumulation of neutrophils correlated with poor outcome. These results highlight the importance of the mononuclear immune response for the survival of patients with CCHF.

Emergence of multidrug resistant isolates and mortality predictors in patients with solid tumors or hematological malignancies.

INTRODUCTION: Infections are an important preventable cause of death in cancer patients. The aim of this study was to clarify the epidemiologic characteristics and resistance patterns of causative isolates and mortality predictors in infections of cancer patients. METHODOLOGY: Patients with sterile site infections were evaluated in a retrospective cohort study. Etiological agents, antimicrobial resistance patterns of the isolates, and possible risk factors for mortality were recorded. Survivors and non-survivors on day 30 after each infection onset were compared to identify the predictors of mortality. RESULTS: A total of 205 infection episodes of 132 patients were included in this study. Of them, 75% had hematologic malignancies and 25% had solid tumors. Febrile neutropenia was diagnosed in 61.5%. Bloodstream infections were the most frequent infection (78%). The majority of the pathogens were Enterobacteriaceae (44.3%) and nonfermentative isolates (17.6%). Multidrug-resistant (MDR) infections were responsible for 40% of the episodes. The mortality rate was 23.4%. Inadequate initial antibiotic treatment (OR = 4.04, 95% CI = 1.80-9.05, p = 0.001), prolonged neutropenia (> 7 days) before infection (OR = 3.61, 95% CI = 1.48-8.80, p = 0.005), infection due to Klebsiella species (OR = 3.75, 95% CI = 1.31-10.7, p = 0.013), and Acinetobacter baumannii (OR = 5.00, 95% CI = 1.38-18.2, p = 0.014) were independent predictors of mortality. CONCLUSIONS: Gram-negative isolates were found to be the predominant pathogens with higher mortality rates. Local epidemiological data should be taken into account when administering empirical therapy since the inadequacy of initial antibiotherapy is associated with a poor outcome.