Routine laboratory biomarkers used to predict Gram-positive or Gram-negative bacteria involved in bloodstream infections.
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ABSTRACT:
SUBMITTER: Dambroso-Altafini D
PROVIDER: S-EPMC9474441 | biostudies-literature | 2022 Sep
REPOSITORIES: biostudies-literature
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Routine laboratory biomarkers used to predict Gram-positive or Gram-negative bacteria involved in bloodstream infections.
Dambroso-Altafini Daniela D Menegucci Thatiany C TC Costa Bruno B BB Moreira Rafael R B RRB Nishiyama Sheila A B SAB Mazucheli Josmar J Tognim Maria C B MCB
Scientific reports 20220914 1
This study evaluated routine laboratory biomarkers (RLB) to predict the infectious bacterial group, Gram-positive (GP) or Gram-negative (GN) associated with bloodstream infection (BSI) before the result of blood culture (BC). A total of 13,574 BC of 6787 patients (217 BSI-GP and 238 BSI-GN) and 68 different RLB from these were analyzed. The logistic regression model was built considering BSI-GP or BSI-GN as response variable and RLB as covariates. After four filters applied total of 320 patients ...[more]
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Project description:BackgroundBacterial bloodstream infection is responsible for the majority of cases of sepsis and septic shock. Early recognition of the causative pathogen is pivotal for administration of adequate empiric antibiotic therapy and for the survival of the patients. In this study, we developed a feasible machine learning (ML) model to predict gram-positive and gram-negative bacteremia based on routine laboratory parameters.MethodsData for 2118 patients with bacteremia were obtained from the Medical Information Mart for Intensive Care dataset. Patients were randomly split into the training set and test set by stratified sampling, and 374 routine laboratory blood test variables were retrieved. Variables with missing values in more than 40% of the patients were excluded. Pearson correlation test was employed to eliminate redundant features. Five ML algorithms were used to build the model based on the selected features. Additionally, 132 patients with bacteremia who were treated at Qilu Hospital of Shandong University were included in an independent test cohort to evaluate the model.ResultsAfter feature selection, 32 variables remained. All the five ML algorithms performed well in terms of discriminating between gram-positive and gram-negative bacteremia, but the performance of convolutional neural network (CNN) and random forest (RF) were better than other three algorithms. Consider of the interpretability of models, RF was chosen for further test (ROC-AUC = 0.768; 95%CI = 0.715-0.798, with a sensitivity of 75.20% and a specificity of 63.79%). To expand the application of the model, a decision tree (DT) was built utilizing the major variables, and it achieved an AUC of 0.679 (95%CI = 0.632-0.723), a sensitivity of 66%, and a specificity of 67.82% in the test cohort. When tested in the Qilu Hospital cohort, the ROC-AUC of the RF and DT models were 0.666 (95%CI = 0.579-0.746) and 0.615 (95%CI = 0.526-0.698), respectively. Finally, a software was developed to make the RF- and DT-based prediction models easily accessible.ConclusionThe present ML-based models could effectively discriminate between gram-positive and gram-negative bacteremia based on routine laboratory blood test results. This simple model would be beneficial in terms of guiding timely antibiotic selection and administration in critically ill patients with bacteremia before their pathogen test results are available.
| S-EPMC10566101 | biostudies-literature
Project description:BackgroundOritavancin, a long-acting lipoglycopeptide approved for use in acute bacterial skin and skin structure infections, has limited data evaluating use in serious infections due to Gram-positive organisms. We aimed to assess the effectiveness and safety of oritavancin for consolidative treatment of Gram-positive bloodstream infections (BSI), including infective endocarditis (IE).MethodsWe conducted a retrospective cohort study evaluating adult patients admitted to University of Colorado Hospital from March 2016 to January 2022 who received ≥ 1 oritavancin dose for treatment of Gram-positive BSI. Patients were excluded if the index culture was drawn at an outside facility or were > 89 years of age. The primary outcome was a 90-day composite failure (clinical or microbiological failure) in those with 90-day follow-up. Secondary outcomes included individual components of the primary outcome, acute kidney injury (AKI), infusion-related reactions (IRR), and institutional cost avoidance.ResultsOverall, 72 patients were included. Mean ± SD age was 54 ± 16 years, 61% were male, and 10% had IE. Organisms most commonly causing BSI were Staphylococcus aureus (68%, 17% methicillin-resistant), followed by Streptococcus spp. (26%), and Enterococcus spp. (10%). Patients received standard-of-care antibiotics before oritavancin for a median (IQR) of 11 (5-17) days. Composite failure in the clinically evaluable population (n = 64) at 90-days occurred in 14% and was composed of clinical and microbiological failure, which occurred in 14% and 5% of patients, respectively. Three patients (4%) experienced AKI after oritavancin, and two (3%) experienced an IRR. Oritavancin utilization resulted in earlier discharge for 94% of patients corresponding to an institutional cost-avoidance of $3,055,804 (mean $44,938/patient) from 1,102 hospital days saved (mean 16 days/patient).ConclusionsThe use of oritavancin may be an effective sequential therapy for Gram-positive BSI to facilitate early discharge resulting in institutional cost avoidance.
| S-EPMC10807122 | biostudies-literature
Project description:Bloodstream infections due to bacteria are a highly consequential nosocomial occurrences and the organisms responsible for them are usually multidrug-resistant. The aims of this study were to describe the incidence of bacteremia caused by Gram-negative ESKAPE bacilli during the COVID-19 pandemic and characterize the clinical and microbiological findings including antimicrobial resistance. A total of 115 Gram-negative ESKAPE isolates were collected from patients with nosocomial bacteremia (18% of the total bacteremias) in a tertiary care center in Mexico City from February 2020 to January 2021. These isolates were more frequently derived from the Respiratory Diseases Ward (27), followed by the Neurosurgery (12), Intensive Care Unit (11), Internal Medicine (11), and Infectious Diseases Unit (7). The most frequently isolated bacteria were Acinetobacter baumannii (34%), followed by Klebsiella pneumoniae (28%), Pseudomonas aeruginosa (23%) and Enterobacter spp (16%). A. baumannii showed the highest levels of multidrug-resistance (100%), followed by K. pneumoniae (87%), Enterobacter spp (34%) and P. aeruginosa (20%). The bla CTX-M-15 and bla TEM-1 genes were identified in all beta-lactam-resistant K. pneumoniae (27), while bla TEM-1 was found in 84.6% (33/39) of A. baumannii isolates. The carbapenemase gene bla OXA-398 was predominant among carbapenem-resistant A. baumannii (74%, 29/39) and bla OXA-24was detected in four isolates. One P. aeruginosa isolate was bla VIM-2 gene carrier, while two K. pneumoniae and one Enterobacter spp were bla NDM gene carriers. Among colistin-resistant isolates mcr-1 gene was not detected. Clonal diversity was observed in K. pneumoniae, P. aeruginosa and Enterobacter spp. Two outbreaks caused by A. baumannii ST208 and ST369 were detected, both belonging to the clonal complex CC92 and IC2. A. baumannii was associated with a death rate of 72% (28/32), most of them (86%, 24/28) extensively drug-resistant or pandrug-resistant isolates, mainly in patients with COVID-19 (86%, 24/28) in the Respiratory Diseases Ward. A. baumannii isolates had a higher mortality rate (72%), which was higher in patients with COVID-19. There was no statistically significant association between the multidrug-resistant profile in Gram-negative ESKAPE bacilli and COVID-19 disease. The results point to the important role of multidrug-resistant Gram-negative ESKAPE bacteria causing bacteremia in nosocomial settings before and during the COVID-19 epidemic. Additionally, we were unable to identify a local impact of the COVID-19 pandemic on antimicrobial resistance rates, at least in the short term.
| S-EPMC10066687 | biostudies-literature
Project description:BackgroundHemogram parameters and procalcitonin (PCT) play auxiliary roles in the diagnosis and outcome of sepsis. However, it is not clear whether these indicators can quickly distinguish bacterial classification or guide the choice of empirical antibiotics.MethodsWe retrospectively enrolled 381 patients with bloodstream infections (BSI), divided into Gram-positive bloodstream infections (GP-BSI) and Gram-negative bloodstream infections (GN-BSI). Demographic parameters, hemogram parameters, and PCT were recorded and compared between the two groups.ResultsThe mean platelet volume (MPV), platelet distribution width (PDW), and PCT in the GN-BSI group were significantly higher than those in the GP-BSI group, while the platelet count (PLT), plateletcrit, platelet count-to-white blood cell count ratio (PWR), platelet count-to-neutrophil count ratio (PNR), platelet count-to-PCT ratio (PLT/PCT), and mean platelet volume-to-PCT ratio (MPV/PCT) were significantly lower in the GN-BSI group. Multivariate stepwise logistic regression analysis revealed that the independent predictors of GN-BSI were MPV, PWR, and PCT. The areas under the curve (AUC) for this prediction model was 0.79, with sensitivity =0.75 and specificity =0.71.ConclusionsThere were significant differences in terms of PCT, platelet parameters, and platelet-related index-PCT ratio between GN-BSI and GP-BSI. Combined PCT and hemogram parameters are more conducive to the early differential diagnosis of bacterial classification of BSI.
| S-EPMC8418508 | biostudies-literature
Project description:BackgroundBloodstream infections (BSI) are associated with high morbidity and mortality. This scenario worsens with the emergence of drug-resistant pathogens, resulting in infections which are difficult to treat or even untreatable with conventional antimicrobials. The aim of this study is to describe the epidemiological aspects of BSI caused by multiresistant gram-negative bacilli (MDR-GNB).MethodsWe conducted a laboratory-based surveillance for gram-negative bacteremia over a 1-year period. The bacterial isolates were identified by MALDI-TOF/MS and the antimicrobial susceptibility testing was performed by VITEK®2. Resistance genes were identified through PCR assays.ResultsOf the 143 patients, 28.7% had infections caused by MDR-GNB. The risk factors for MDR bacteremia were male sex, age ≥ 60, previous antimicrobial use, liver disease and bacteremia caused by K. pneumoniae. K. pneumoniae was the most frequently observed causative agent and had the highest resistance level. Regarding the resistance determinants, SHV, TEM, OXA-1-like and CTX-M-gp1 were predominant enzymatic variants, whereas CTX-M-gp9, CTX-M-gp2, KPC, VIM, GES, OXA-48-like, NDM and OXA-23-like were considered emerging enzymes.ConclusionsHere we demonstrate that clinically relevant antibiotic resistance genes are prevalent in this setting. We hope our findings support the development of intervention measures by policy makers and healthcare professionals to face antibiotic resistance.
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Project description:Adequate early empiric antibiotic therapy is pivotal for the outcome of patients with bloodstream infections. In clinical practice the use of surrogate laboratory parameters is frequently proposed to predict underlying bacterial pathogens; however there is no clear evidence for this assumption. In this study, we investigated the discriminatory capacity of predictive models consisting of routinely available laboratory parameters to predict the presence of Gram-positive or Gram-negative bacteremia. Major machine learning algorithms were screened for their capacity to maximize the area under the receiver operating characteristic curve (ROC-AUC) for discriminating between Gram-positive and Gram-negative cases. Data from 23,765 patients with clinically suspected bacteremia were screened and 1,180 bacteremic patients were included in the study. A relative predominance of Gram-negative bacteremia (54.0%), which was more pronounced in females (59.1%), was observed. The final model achieved 0.675 ROC-AUC resulting in 44.57% sensitivity and 79.75% specificity. Various parameters presented a significant difference between both genders. In gender-specific models, the discriminatory potency was slightly improved. The results of this study do not support the use of surrogate laboratory parameters for predicting classes of causative pathogens. In this patient cohort, gender-specific differences in various laboratory parameters were observed, indicating differences in the host response between genders.
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Project description:BackgroundClusters of bloodstream infections caused by Burkholderia cepacia and Stenotrophomonas maltophilia are uncommon, but have been previously identified in hemodialysis centers that reprocessed dialyzers for reuse on patients. We investigated an outbreak of bloodstream infections caused by B cepacia and S maltophilia among hemodialysis patients in clinics of a dialysis organization.Study designOutbreak investigation, including matched case-control study.Setting & participantsHemodialysis patients treated in multiple outpatient clinics owned by a dialysis organization.PredictorsMain predictors were dialyzer reuse, dialyzer model, and dialyzer reprocessing practice.OutcomesCase patients had a bloodstream infection caused by B cepacia or S maltophilia; controls were patients without infection dialyzed at the same clinic on the same day as a case; results of environmental cultures and organism typing.Results17 cases (9 B cepacia and 8 S maltophilia bloodstream infections) occurred in 5 clinics owned by the same dialysis organization. Case patients were more likely to have received hemodialysis with a dialyzer that had been used more than 6 times (matched OR, 7.03; 95% CI, 1.38-69.76) and to have been dialyzed with a specific reusable dialyzer (Model R) with sealed ends (OR, 22.87; 95% CI, 4.49-∞). No major lapses during dialyzer reprocessing were identified that could explain the outbreak. B cepacia was isolated from samples collected from a dialyzer header-cleaning machine from a clinic with cases and was indistinguishable from a patient isolate collected from the same clinic, by pulsed-field gel electrophoresis. Gram-negative bacteria were isolated from 2 reused Model R dialyzers that had undergone the facility's reprocessing procedure.LimitationsLimited statistical power and overmatching; few patient isolates and dialyzers available for testing.ConclusionsThis outbreak was likely caused by contamination during reprocessing of reused dialyzers. Results of this and previous investigations demonstrate that exposing patients to reused dialyzers increases the risk for bloodstream infections. To reduce infection risk, providers should consider implementing single dialyzer use whenever possible.
| S-EPMC5441929 | biostudies-literature
Project description:BackgroundGram-negative organisms are common causes of bloodstream infection (BSI) during the neonatal period and early childhood. Whilst several large studies have characterised these isolates in adults, equivalent data (particularly incorporating whole genome sequencing) is lacking in the paediatric population.MethodsWe perform an epidemiological and sequencing based analysis of Gram-negative bloodstream infections (327 isolates (296 successfully sequenced) from 287 patients) in children <18 years old between 2008 and 2018 in Oxfordshire, UK.ResultsHere we show that the burden of infection lies predominantly in neonates and that most infections are caused by Escherichia coli, Klebsiella spp. and Enterobacter hormaechei. There is no evidence in our setting that the proportion of antimicrobial resistant isolates is increasing in the paediatric population although we identify some evidence of sub-breakpoint increases in gentamicin resistance. The population structure of E. coli BSI isolates in neonates and children mirrors that in adults with a predominance of STs 131/95/73/69 and the same proportions of O-antigen serotypes. In most cases in our setting there is no evidence of transmission/point-source acquisition and we demonstrate the utility of whole genome sequencing to refute a previously suspected outbreak.ConclusionsOur findings support continued use of current empirical treatment guidelines and suggest that O-antigen targeted vaccines may have a role in reducing the incidence of neonatal sepsis.
| S-EPMC9372158 | biostudies-literature
Project description:BackgroundAntimicrobial resistance (AMR) in Gram-negative bacteria-causing bloodstream infections (BSIs), such as Klebsiella pneumoniae and non-typhoidal Salmonella (NTS), is a major public health concern. Nonetheless, AMR surveillance remains scarce in sub-Saharan Africa, where BSI treatment is largely empirical. The aim of the study was to determine the distribution and AMR patterns of BSI-causing NTS, K. pneumoniae, and other Gram-negative bacteria in Ghana.MethodsA cross-sectional study was conducted between April and December 2021 at eleven sentinel health facilities across Ghana as part of a pilot study on the feasibility and implementation of the human sector AMR surveillance harmonized protocol in sub-Saharan Africa. Gram-negative bacteria recovered from blood specimens of febrile patients were identified using MALDI-TOF and evaluated for antimicrobial resistance using the BD Phoenix M50 analyzer and Kirby-Bauer disc diffusion. The Department of Medical Microbiology at the University of Ghana served as the reference laboratory.ResultsOut of 334 Gram-negative blood isolates, there were 18 (5.4%) NTS, 85 (25.5%) K. pneumoniae, 88 (26.4%) Escherichia coli, 40 (12.0%) Acinetobacter baumannii, 25 (7.5%) Pseudomonas aeruginosa, and 77 (23.1%) other Gram-negative bacteria. As a composite, the isolates displayed high resistance to the antibiotics tested-amoxicillin (89.3%), tetracycline (76.1%), trimethoprim-sulfamethoxazole (71.5%), and chloramphenicol (59.7%). Resistance to third-generation cephalosporins [ceftriaxone (73.7%), cefotaxime (77.8%), and ceftazidime (56.3%)] and fluoroquinolones [ciprofloxacin (55.3%)] was also high; 88% of the isolates were multidrug resistant, and the rate of extended-spectrum beta-lactamase (ESBL) production was 44.6%. Antibiotic resistance in K. pneumoniae followed the pattern of all Gram-negative isolates. Antibiotic resistance was lower in NTS blood isolates, ranging between 16.7-38.9% resistance to the tested antibiotics. Resistance rates of 38.9%, 22.2%, and 27.8% were found for cefotaxime, ceftriaxone, and ceftazidime, respectively, and 27.8% and 23.8% for ciprofloxacin and azithromycin, respectively, which are used in the treatment of invasive NTS. The prevalence of multidrug resistance in NTS isolates was 38.9%.ConclusionsMulticenter AMR surveillance of Gram-negative blood isolates from febrile patients was well-received in Ghana, and the implementation of a harmonized protocol was feasible. High resistance and multidrug resistance to first- or second-choice antibiotics, including penicillins, third-generation cephalosporins, and fluoroquinolones, were found, implying that these antibiotics might have limited effectiveness in BSI treatment in the country. Continuation of AMR surveillance in Gram-negative blood isolates is essential for a better understanding of the extent of AMR in these pathogens and to guide clinical practice and policymaking.
| S-EPMC9951917 | biostudies-literature
Project description:BackgroundAlteration in the etiology of pediatric bloodstream infections (BSIs) and antimicrobial resistance (AMR) is not well known during the Coronavirus disease 2019 (COVID-19) pandemic. This study aimed to investigate the impact of the COVID-19 pandemic on pediatric BSIs and alteration in antimicrobial resistance phenotypes in Gram-positive bacteria.MethodsThe frequency of BSIs among children under 18 years old was retrospectively recorded in a tertiary children's hospital in Tehran, Iran from February 2020 to December 2022. The status of COVID-19 infection using reverse transcription polymerase chain reaction, bacteremia/fungemia according to BACTEC 9120 Culture System results, characterization of bacteria using biochemical tests, and antimicrobial susceptibility patterns for Gram-positive bacterial isolates using disk diffusion method were determined. Statistical analysis was done to measure the correlation of COVID-19 infection with BSIs and AMR.ResultsOut of 13,345 COVID-19 tests and 4,194 BACTEC blood culture requests, bacteremia/fungemia were confirmed in 10.37% (435/4,194) of the patients who requested both tests simultaneously. The COVID-19 infection was confirmed in 25.3% (110/435) of the patients with bacteremia/fungemia. The infection with characterized Gram-positive bacteria (GPB) and fungi was detected in 32.3% (140/433) and 8.31% (36/433) of the cases, respectively. Coagulase-negative Staphylococcus (CNS, 72, 16.62%), S. aureus (36, 8.3%), and Enterococcus spp. (22, 5%) were among the common isolates. Candida spp. and non-Candida yeasts were detected in 6.7% and 13.4% of the cases, respectively. A positive correlation was shown between the CNS bacteremia and COVID-19 infection (p-value = 0.019). Antibiotic susceptibility testing results showed the highest frequency of resistance to azithromycin among CNS, azithromycin and tetracycline among S. aureus and tetracycline among Enterococcus spp. Methicillin-resistance phenotype in the S. aureus (MRSA) and coagulase-negative Staphylococcus spp. (MR-CNS) was detected in 40% and 61.5% of the strains, respectively and the Enterococci were resistant to vancomycin in 33.3% of the isolates.ConclusionA decline in the trend of BSIs by GPB and an increase in AMR was shown in children during the COVID-19 pandemic. Increasing antibiotic resistance is a concern; however, chloramphenicol, linezolid, and vancomycin remain active against common causes of GPB-BSIs.
| S-EPMC11487802 | biostudies-literature