Gram-Negative Bloodstream Infections in Healthcare: The Relationship Between Antibiotic Resistance, Mortality, and Novel Serological Biomarker.

BACKGROUND: Bloodstream infections caused by Gram-negative bacteria are highly mortal. In this study, we aimed to investigate the relationship between antimicrobial resistance profile and novel serological biomarkers and mortality in bloodstream infections (BSIs) caused by Gram-negative bacteria in intensive care units (ICUs). METHODS: 366 Patients diagnosed with healthcare-associated Gram-negative bloodstream infection in the ICUs of our hospital between February 2015 and December 2021 were included in the study. Demographic variables (age, gender, comorbidities), causative microorganisms and antimicrobial susceptibilities, time to first positive blood culture after hospitalization, length of stay in hospital, surgical procedures, laboratory data (hemograms, C-reactive protein (CRP) levels, albumin), and survival data were collected. Novel serological biomarkers were calculated. RESULTS: Mortality in Gram-negative bloodstream infection was found to be associated with age and novel serological biomarkers, but not with carbapenems and colistin minimum inhibitory concentration (MIC) values. Mortality rates increased with age (p˂0.001). Patients who died had higher C-reactive protein/albumin ratio (CAR) (p<0.001) and neutrophil/lymphocyte ratio (NLR) (p=0.009) and lower prognostic nutritional index (PNI) (p<0.001). CONCLUSION: The study emphasizes that resistance to colistin and carbapenems is not associated with mortality in BSIs caused by Gram-negative bacteria. Novel serological biomarkers may be useful in predicting mortality. These results support the need for further studies to elucidate the true impact of infections caused by resistant bacteria.

Comparative Analysis of Demographic and Clinical Findings in Spontaneous, Peritoneal Dialysis-Related, and Secondary Bacterial Peritonitis.

Background This study aims to contribute to peritonitis management strategies by comparing the demographic, clinical, and laboratory characteristics of patients diagnosed with spontaneous bacterial peritonitis (SBP), peritoneal dialysis-related peritonitis (PDrP), and secondary peritonitis. Methods This study included 86 patients diagnosed with peritonitis between 2016 and 2022. Patients were categorized and compared as SBP, PDrP, and secondary peritonitis. Results SBP was diagnosed in 36% of patients, secondary peritonitis in 36% and PDrP in 28%. The mean age of patients with PDrP is 43.71 ± 14.74, which is significantly lower compared to those with SBP and secondary peritonitis (p<0.001). Patients with hypertension (HT), chronic kidney disease (CKD), and those undergoing dialysis most commonly have PDrP whereas those without HT, without CKD, and not undergoing dialysis are most often diagnosed with secondary peritonitis (p=0.002, p<0.001, p<0.001). In peritoneal fluid cultures, the growth of Gram-positive bacteria was most commonly identified in patients with PDrP, while the growth of Gram-negative bacteria was most frequently seen in patients with secondary peritonitis (p=0.018). CRP levels and sedimentation rates were found to be higher in patients with secondary peritonitis (p<0.001, p=0.003). Conclusion The distinct characteristics observed across different types of peritonitis underscore the importance of tailored approaches to diagnosis and treatment. Parameters such as CRP levels, sedimentation rates, and patient age could serve as valuable indicators in discerning between various types of peritonitis. When selecting empirical antibiotic therapy, it's crucial to consider coverage for Gram-positive pathogens in cases of PDrP and Gram-negative pathogens in secondary peritonitis.

Change in Hepatitis B Surface Antibody Titers After Chemotherapy in Patients With Hematological Malignancies.

Background The change in hepatitis B surface antibody (anti-HBs) titers after chemotherapy (CT) in patients with hematological malignancy, affecting factors, and its clinical implications have not been sufficiently understood. Therefore, we aim to evaluate the change in anti-HBs titers and hepatitis B virus reactivation (HBVr) after CT. Methods This retrospective study enrolled patients with hematological malignancies who received CT between 2013 and 2021. All patients were followed up for HBVr and a change in anti-HBs titers for one year. Results Overall, 192 patients were included. In total, 33.9% of the patients were anti-HBs (+) and 26% of the patients were anti-HBc (+) ± anti-HBs (+). Hepatitis B virus (HBV) prophylaxis was given to 35 (70%) of 50 Anti-HBc (+) patients. Tenofovir disoproxil fumarate and entecavir prophylaxis were initiated in 25 (71.4%) and 10 (28.6%) patients, respectively. A significant decrease was found in anti-HBs titers of all patients (p=0.017). A significant decrease was also found in anti-HBs titers of HBc IgG (+) patients and those who received four or more courses of CT (p=0.025; p=0.041). HBVr was not diagnosed in any of the patients. Conclusion Chemotherapeutic agents administered for hematological malignancy have serious immunosuppression effects. In these patients, anti-HBs titers may decrease or become negative one year after CT. Anti-HBs titer before CT or its change after CT may not constitute a risk for HBVr patients who received HBV prophylaxis in line with current guidelines and these recommendations.

Evaluation of TyG index and TG/HDL-C ratio in HBeAg negative chronic hepatitis B infected patients.

Patients with hepatitis B e antigen (HBeAg) negative chronic HBV infection are regularly followed up. This study investigates the presence of insulin resistance and the relationship between hepatosteatosis and insulin resistance in patients with HBeAg negative chronic HBV infection using the TyG index and TG/HDL-C ratio. Patients with HBeAg negative chronic HBV infection who applied to the Infectious Diseases and Clinical Microbiology outpatient clinic between January 2019 and December 2020 were included in the study. Glucose, lipid panel, alanine amino transferase (ALT), acetyl amino transferase (AST), body mass index (BMI), TyG index, TG/HDL-C and hepatobiliary ultrasonography (USG) results were evaluated. The data were compared with the control group consisting of 308 HBsAg negative individuals. The study included 132 patients with a median age of 52 years. There was no significant difference between the patient and control groups regarding age, gender and BMI. Glucose, total cholesterol, TG, LDL, AST, ALT, TyG index and TG/HDL-C ratio were significantly higher in patient than in the control group. At the same time, the HDL value was significantly lower in the patients. There was a strong positive correlation between the TG and BMI, and a strong negative correlation between HDL levels and both TyG index and TG/HDL-C ratio. Our findings showed that the TyG index and TG/HDL-C ratio are helpful in the diagnosis of insulin resistance and hepatosteatosis in patients with HBeAg negative chronic HBV infection.

Prognostic nutritional index: Is it associated with the prognosis of Crimean Congo hemorrhagic fever.

INTRODUCTION: The prognostic nutritional index (PNI) is calculated using total serum lymphocyte counts and albumin levels. We aimed to analyze the role of PNI in predicting intensive care unit (ICU) referral and mortality in patients with Crimean Congo hemorrhagic fever (CCHF). MATERIALS AND METHODS: Our target population was adult (age >18) patients who presented between March 2015 and October 2021 within 5 days of symptom emergence and were diagnosed with CCHF. The predictive value of PNI was analyzed by the receiver operating curve analysis. The patients were categorized based on the severity grading scores (SGS) as mild, moderate, and severe. The relationship between PNI and ICU referral and mortality was analyzed by logistic regression analysis. RESULTS: Overall, 115 patients with the diagnosis of CCHF were included. 13.9% (n = 16) of the patients were referred to ICU while 11.3% (n = 13) died. A comparison of the patients with different SGS grades revealed that they were significantly different regarding PNI (p < 0.001). There was a significant negative correlation between PNI and SGS (r = -0.662; p < 0.001). PNI had a PV regarding ICU referral and mortality ([area under the curve [AUC] = 0.723, 95% confidence interval [CI]: 0.609-0.836, p = 0.004 [AUC = 0.738, 95% CI: 0.613-0.863, p = 0.005]). The PNI threshold was 36.1 for ICU referral and mortality. The rates of female patients, hospitalization periods longer than 1 week, platelet apheresis replacement, diabetes mellitus, bleeding history, ICU admission, and mortality were significantly higher in patients with a PNI of lower than 36.1 (p < 0.05). CONCLUSION: PNI can predict ICU referral and mortality in patients admitted due to CCHF.

Antibiotic use and Influencing Factors Among Hospitalized Patients with COVID-19: A Multicenter Point-Prevalence Study from Turkey

Background: Broad-spectrum empirical antimicrobials are frequently prescribed for patients with coronavirus disease 2019 (COVID-19) despite the lack of evidence for bacterial coinfection. Aims: We aimed to cross-sectionally determine the frequency of antibiotics use, type of antibiotics prescribed, and the factors influencing antibiotics use in hospitalized patients with COVID-19 confirmed by polymerase chain reaction. Study Design: The study was a national, multicenter, retrospective, and single-day point prevalence study. Methods: This was a national, multicenter, retrospective, and single-day point-prevalence study, conducted in the 24-h period between 00:00 and 24:00 on November 18, 2020, during the start of the second COVID-19 peak in Turkey. Results: A total of 1500 patients hospitalized with a diagnosis of COVID-19 were included in the study. The mean age ± standard deviation of the patients was 65.0 ± 15.5, and 56.2% (n = 843) of these patients were men. Of these hospitalized patients, 11.9% (n = 178) were undergoing invasive mechanical ventilation or ECMO. It was observed that 1118 (74.5%) patients were receiving antibiotics, of which 416 (37.2%) were prescribed a combination of antibiotics. In total, 71.2% of the patients had neither a clinical diagnosis nor microbiological evidence for prescribing antibiotics. In the multivariate logistic regression analysis, hospitalization in a state hospital (p < 0.001), requiring any supplemental oxygen (p = 0.005), presence of moderate/diffuse lung involvement (p < 0.001), C-reactive protein > 10 ULT coefficient (p < 0.001), lymphocyte count < 800 (p = 0.007), and clinical diagnosis and/or confirmation by culture (p < 0.001) were found to be independent factors associated with increased antibiotic use. Conclusion: The necessity of empirical antibiotics use in patients with COVID-19 should be reconsidered according to their clinical, imaging, and laboratory findings.