Risk Index Score for Bacteremia in Febrile Neutropenic Episodes in Children with Malignancies

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 4654-4654
Author(s):  
Maria I Spasova ◽  
Janet G. Grudeva ◽  
Stefan S. Kostyanev ◽  
Evgeni D. Genev ◽  
Angelina A. Stoyanova ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Antibiotic Therapy ◽  
Risk Group ◽  
Risk Index ◽  
Empiric Antibiotic Therapy ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Empiric Antibiotic ◽  
Risk Index Score

Abstract BACKGROUND: Nowadays febrile neutropenia is regarded as heterogeneous syndrome and adequate risk stratification of patients as a basis for tailoring empiric antibiotic therapy is attempted. We conducted this prospective study to determine risk factors for bacteremia in febrile neutropenic children that could be assessed in the first days from the onset of fever and based on logistic regression analysis to construct a risk index score for prediction of bacteremia. MATERIAL AND METHODS: We studied prospectively 199 consecutive episodes of febrile neutropenia for a 4-years period (2000 – 2004), occurring in 80 children with malignancies, treated by conventional chemotherapy. A standardized computer database with a set of variables for each febrile neutropenic episode was used. C-reactive protein was measured at the first fever and depending on its duration - on the 3-rd and 5-th day from the beginning of antibiotic therapy by immunoturbidimetric method. At the onset of fever and before initiation of antibiotic therapy blood cultures were drawn and injected directly into a culture bottle BACTEC Peds plus. RESULTS: By multivariate logistic regression analysis we determined 5 variables as independent risk factors for bacteremia: the underlying malignant disease (leukemia, NHL-gr.IV), chills, perianal cellulitis, presence of central venous catheter and degree of CRP rise ≥34.5 mg/L between the onset of fever and the 3rd day of empiric antibiotic therapy. This logistic regression model has sensitivity of 93%, specificity of 25%, negative predictive value of 89% and positive predictive value of 36% for the presence of bacteremia (Chi-square: 44, −2 log likelihood:200, Cox & Snell R square: 0.2). CONCLUSIONS: The present prospective study is characterized by prevalence of hematologic malignancies and relatively high frequency of bacteremia. We identified a low-risk group of 19.1%, comparable to the reported by other groups. Based on the statistical significance of serial measurement of C-reactive protein, which allows definite risk stratification of febrile neutropenic episodes on the 3rd day from the onset of fever, we would recommend sequential empiric antibiotic approach with switch to oral or even outpatient treatment in the low-risk group on the 3rd day.

scholarly journals Local audit of empiric antibiotic therapy in bacteremia: A retrospective cohort study

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248817
Author(s):  
Anthony D. Bai ◽  
Neal Irfan ◽  
Cheryl Main ◽  
Philippe El-Helou ◽  
Dominik Mertz
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Blood Culture ◽  
Antibiotic Therapy ◽  
Retrospective Cohort Study ◽  
Clinical Pathway ◽  
Retrospective Cohort ◽  
Negative Likelihood Ratio ◽  
Empiric Antibiotic Therapy ◽  
Empiric Antibiotic

Background It is unclear if a local audit would be useful in providing guidance on how to improve local practice of empiric antibiotic therapy. We performed an audit of antibiotic therapy in bacteremia to evaluate the proportion and risk factors for inadequate empiric antibiotic coverage. Methods This retrospective cohort study included patients with positive blood cultures across 3 hospitals in Hamilton, Ontario, Canada during October of 2019. Antibiotic therapy was considered empiric if it was administered within 24 hours after blood culture collection. Adequate coverage was defined as when the isolate from blood culture was tested to be susceptible to the empiric antibiotic. A multivariable logistic regression model was used to predict inadequate empiric coverage. Diagnostic accuracy of a clinical pathway based on patient risk factors was compared to clinician’s decision in predicting which bacteria to empirically cover. Results Of 201 bacteremia cases, empiric coverage was inadequate in 56 (27.9%) cases. Risk factors for inadequate empiric coverage included unknown source at initiation of antibiotic therapy (adjusted odds ratio (aOR) of 2.76 95% CI 1.27–6.01, P = 0.010) and prior antibiotic therapy within 90 days (aOR of 2.46 95% CI 1.30–4.74, P = 0.006). A clinical pathway that considered community-associated infection as low risk for Pseudomonas was better at ruling out Pseudomonas bacteremia with a negative likelihood ratio of 0.17 (95% CI 0.03–1.10) compared to clinician’s decision with negative likelihood ratio of 0.34 (95% CI 0.10–1.22). Conclusions An audit of antibiotic therapy in bacteremia is feasible and may provide useful feedback on how to locally improve empiric antibiotic therapy.

A high C-reactive protein/procalcitonin ratio predicts Mycoplasma pneumoniae infection

2019 ◽  
Vol 57 (10) ◽  
pp. 1638-1646 ◽  
Author(s):  
Olivia L. Neeser ◽  
Tanja Vukajlovic ◽  
Laetitia Felder ◽  
Sebastian Haubitz ◽  
Angelika Hammerer-Lercher ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Mycoplasma Pneumoniae ◽  
Viral Infections ◽  
Tertiary Care ◽  
Multivariate Logistic Regression Analysis ◽  
Empiric Antibiotic Therapy ◽  
Care Hospital ◽  
C Reactive Protein ◽  
Neutrophil Lymphocyte Ratio ◽  
Reactive Protein

Abstract Background Discriminating Mycoplasma pneumoniae (MP) from Streptococcus pneumoniae (SP) and viral etiologies of community-acquired pneumonia (CAP) is challenging but has important implications regarding empiric antibiotic therapy. We investigated patient parameters upon hospital admission to predict MP infection. Methods All patients hospitalized in a tertiary care hospital between 2013 and 2017 for CAP with a confirmed etiology were analyzed using logistic regression analyses and area under the receiver operator characteristics (ROC) curves (AUC) for associations between demographic, clinical and laboratory features and the causative pathogen. Results We analyzed 568 patients with CAP, including 47 (8%) with MP; 152 (27%) with SP and 369 (65%) with influenza or other viruses. Comparing MP and SP by multivariate logistic regression analysis, younger age (odds ration [OR] 0.56 per 10 years, 95% CI 0.42–0.73), a lower neutrophil/lymphocyte ratio (OR 0.9, 0.82–0.99) and an elevated C-reactive protein/procalcitonin (CRP/PCT) ratio (OR 15.04 [5.23–43.26] for a 400 mg/μg cut-off) independently predicted MP. With a ROC curve AUC of 0.91 (0.80 for the >400 mg/μg cutoff), the CRP/PCT ratio was the strongest predictor of MP vs. SP. The discriminatory value resulted from significantly lower PCT values (p < 0.001) for MP, while CRP was high in both groups (p = 0.057). Comparing MP and viral infections showed similar results with again the CRP/PCT ratio providing the best information (AUC 0.83; OR 5.55 for the >400 mg/μg cutoff, 2.26–13.64). Conclusions In patients hospitalized with CAP, a high admission CRP/PCT ratio predicts M. pneumoniae infection and may improve empiric management.

scholarly journals Epidemiology of Inappropriate Empiric Antibiotic Therapy for Bacteremia Based on Discordant In vitro Susceptibilities: Risk factors and Taxon-level Variation in Burden and Outcome in 156 US hospitals, 2000–2014

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S13-S14
Author(s):  
Sameer S Kadri ◽  
Yi Ling Lai ◽  
Emily Ricotta ◽  
Jeffrey Strich ◽  
Ahmed Babiker ◽  
...  
Keyword(s):  
Risk Factors ◽  
Antibiotic Therapy ◽  
Empiric Antibiotic Therapy ◽  
In Vitro Susceptibility ◽  
Gram Negative ◽  
Risk Of Death ◽  
Risk Of Mortality ◽  
Increased Risk ◽  
Empiric Antibiotic

Abstract Background Discordance between in vitro susceptibility and empiric antibiotic therapy is inextricably linked to antibiotic resistance and decreased survival in bloodstream infections (BSI). However, its prevalence, patient- and hospital-level risk factors, and impact on outcome in a large cohort and across different pathogens remain unclear. Methods We examined in vitro susceptibility interpretations for bacterial BSI and corresponding antibiotic therapy among inpatient encounters across 156 hospitals from 2000 to 2014 in the Cerner Healthfacts database. Discordance was defined as nonsusceptibility to initial therapy administered from 2 days before pathogen isolation to 1 day before final susceptibility reporting. Discordance prevalence was compared across taxa; risk factors and its association with in-hospital mortality were evaluated by logistic regression. Adjusted odds ratios (aOR) were estimated for pathogen-, patient- and facility-level factors. Results Of 33,161 unique encounters with BSIs, 4,219 (13%) at 123 hospitals met criteria for discordant antibiotic therapy, ranging from 3% for pneumococci to 55% for E. faecium. Discordance was higher in recent years (2010–2014 vs. 2005–2009) and was associated with older age, lower baseline SOFA score, urinary (vs. abdominal) source and hospital-onset BSI, as well as ≥500-bed, Midwestern, non-teaching, and rural hospitals. Discordant antibiotic therapy increased the risk of death [aOR = 1.3 [95% CI 1.1–1.4]). Among Gram-negative taxa, discordant therapy increased risk of mortality associated with Enterobacteriaceae (aOR = 1.3 [1.0–1.6]) and non-fermenters (aOR = 1.7 [1.1–2.5]). Among Gram-positive taxa, risk of mortality from discordant therapy was significantly higher for S. aureus (aOR = 1.3 [1.1–1.6]) but unchanged for streptococcal or enterococcal BSIs. Conclusion The prevalence of discordant antibiotic therapy displayed extensive taxon-level variability and was associated with patient and institutional factors. Discordance detrimentally impacted survival in Gram-negative and S. aureus BSIs. Understanding reasons behind observed differences in discordance risk and their impact on outcomes could inform stewardship efforts and guidelines for empiric therapy in sepsis. Disclosures All authors: No reported disclosures.

Nosocomial Bacterial Pneumonia in HIV-Infected Patients: Risk Factors for Adverse Outcome and Implications for Rational Empiric Antibiotic Therapy

Infection ◽  
2006 ◽  
Vol 34 (1) ◽  
pp. 9-16 ◽  
Author(s):  
F. Franzetti ◽  
A. Grassini ◽  
M. Piazza ◽  
M. Degl’Innocenti ◽  
A. Bandera ◽  
...  
Keyword(s):  
Risk Factors ◽  
Antibiotic Therapy ◽  
Bacterial Pneumonia ◽  
Adverse Outcome ◽  
Empiric Antibiotic Therapy ◽  
Empiric Antibiotic

scholarly journals Risk factors for clinical progression in patients with COVID-19: a retrospective study of electronic health record data in the United Kingdom

2020 ◽  
Author(s):  
Robert A Fletcher ◽  
Thomas Matcham ◽  
Marta Tibúrcio ◽  
Arseni Anisimovich ◽  
Stojan Jovanović ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mechanical Ventilation ◽  
Logistic Regression ◽  
Body Temperature ◽  
Blood Cell ◽  
Severe Disease ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Multivariable Logistic Regression ◽  
D Dimer

Background: The novel coronavirus disease 2019 (COVID-19) outbreak presents a significant threat to global health. A better understanding of patient clinical profiles is essential to drive efficient and timely health service strategies. In this study, we aimed to identify risk factors for a higher susceptibility to symptomatic presentation with COVID-19 and a transition to severe disease. Methods: We analysed data on 2756 patients admitted to Chelsea & Westminster Hospital NHS Foundation Trust between 1st January and 23rd April 2020. We compared differences in characteristics between patients designated positive for COVID-19 and patients designated negative on hospitalisation and derived a multivariable logistic regression model to identify risk factors for predicting risk of symptomatic COVID-19. For patients with COVID-19, we used univariable and multivariable logistic regression to identify risk factors associated with progression to severe disease defined by: 1) admission to the hospital AICU, 2) the need for mechanical ventilation, 3) in-hospital mortality, and 4) at least one measurement of elevated D-dimer (equal or superior to 1,000 ug/L) indicative of increased risk of venous thromboembolism. Results: The patient population consisted of 1148 COVID-19 positive and 1608 COVID-19 negative patients. Age, sex, self-reported ethnicity, C-reactive protein, white blood cell count, respiratory rate, body temperature, and systolic blood pressure formed the most parsimonious model for predicting risk of symptomatic COVID-19 at hospital admission. Among 1148 patients with COVID-19, 116 (10.1%) were admitted to the AICU, 71 (6.2%) required mechanical ventilation, 368 (32.1%) had at least one record of D-dimer levels ≥1,000 μg/L, and 118 patients died. In the multivariable logistic regression, age (OR = 0.953 per 1 year, 95% CI: 0.937-0.968) C-reactive protein (OR = 1.004 per 1 mg/L, 95% CI: 1.002-1.007), and white blood cell counts (OR = 1.059 per 109/L, 95% CI: 1.010-1.111) were found to be associated with admission to the AICU. Age (OR = 0.973 per 1 year, 95% CI: 0.955-0.990), C-reactive protein (OR = 1.003 per 1 mg/L, 95% CI: 1.000-1.006) and sodium (OR = 0.915 per 1 mmol/L, 0.868-0.962) were associated with mechanical ventilation. Age (OR = 1.023 per 1 year, 95% CI: 1.004-1.043), CRP (OR = 1.004 per 1 mg/L, 95% CI: 1.002-1.006), and body temperature (OR = 0.723 per 1oC, 95% CI: 0.541-0.958) were associated with elevated D-dimer. For mortality, we observed associations with age (OR = 1.060 per 1 year, 95% CI: 1.040-1.082), female sex (OR = 0.442, 95% CI: 0.442, 95% CI: 0.245-0.777), Asian ethnic background (OR = 2.237 vs White ethnic background, 95% CI: 1.111-4.510), C-reactive protein (OR = 1.004 per 1 mg/L, 95% CI: 1.001-1.006), sodium (OR = 1.038 per 1 mmol/L, 95% CI: 1.001-1.006), and respiratory rate (OR = 1.054 per 1 breath/min, 95% CI: 1.024-1.087). Conclusion: Our analysis suggests there are several demographic, clinical and laboratory findings associated with a symptomatic presentation of COVID-19. Moreover, significant associations between patient deterioration were found with age, sex and specific blood markers, chiefly C-reactive protein, and could help early identification of patients at risk of poorer prognosis. Further work is required to clarify the extent to which our observations are relevant beyond current settings.

Increased pretreatment C-reactive protein-to-albumin ratio predicts severe coronavirus disease 2019

2020 ◽  
Author(s):  
Xiaoyue Wang ◽  
Yan Xu ◽  
Huang Huang ◽  
Desheng Jiang ◽  
Chunlei Zhou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Early Warning ◽  
Warning Signs ◽  
C Reactive Protein ◽  
Albumin Ratio ◽  
Reactive Protein ◽  
Independent Risk Factors

Abstract Objective The aim of this study was to identify early warning signs for severe coronavirus disease 2019 (COVID-19). Methods We retrospectively analysed the clinical data of 90 patients with COVID-19 from Guanggu District of Hubei Women and Children Medical and Healthcare Center, comprising 60 mild cases and 30 severe cases. The demographic data, underlying diseases, clinical manifestations and laboratory blood test results were compared between the two groups. The cutoff values were determined by receiver operating characteristic curve analysis. Logistic regression analysis was performed to identify the independent risk factors for severe COVID-19. Results The patients with mild and severe COVID-19 had significant differences in terms of cancer incidence, age, pretreatment neutrophil-to-lymphocyte ratio (NLR), and pretreatment C-reactive protein-to-albumin ratio (CAR) ( P =0.000; P =0.008; P=0.000; P =0.000). The severity of COVID-19 was positively correlated with comorbid cancer, age, NLR, and CAR ( P <0.005). Multivariate logistic regression analysis showed that age, the NLR and the CAR were independent risk factors for severe COVID-19 (OR=1.086, P =0.008; OR=1.512, P =0.007; OR=17.652, P =0.001). Conclusion An increased CAR can serve as an early warning sign of severe COVID-19 in conjunction with the NLR and age.

scholarly journals C-Reactive Protein-to-Albumin Ratio Predicts Sepsis and Prognosis in Patients with Severe Burn Injury

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yaohua Yu ◽  
Weiwei Wu ◽  
Yanyan Dong ◽  
Jiliang Li
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Multivariate Logistic Regression Analysis ◽  
Severe Burn ◽  
C Reactive Protein ◽  
Multivariate Logistic Regression ◽  
Albumin Ratio ◽  
Reactive Protein ◽  
Severe Burns ◽  
Independent Risk Factors

Background. Sepsis is a leading cause of mortality among severe burns. This study was conducted to investigate the predictive role of C-reactive protein-to-albumin ratio (CAR) for sepsis and prognosis in severe burns. Methods. Patients with severe burn injuries from 2013 to 2017 were enrolled and divided into septic and nonseptic groups based on the presence of sepsis within 30 days postburn. Independent risk factors for sepsis were performed by the univariate and multivariate logistic regression analyses. The association between CAR level at admission and postburn 30-day mortality was designed via the Kaplan–Meier method. Results. Of all the 196 enrolled patients, 83 patients developed sepsis within 30 days postburn injury, with an incidence of 42.3%. TBSA percentage (OR: 1.65, 95% CI: 1.17-2.32, P = 0.014 ) and CAR at admission (OR: 2.25, 95% CI: 1.33-3.56, P = 0.009 ) were the two independent risk factors for sepsis in severe burns by the multivariate logistic regression analysis. A higher CAR level (≥1.66) at admission was associated with a lower postburn 30-day survival rate ( P = 0.005 ). Conclusions. The CAR level at admission was an independent risk factor for sepsis and prognosis in severe burns.

scholarly journals The Association of Body Composition Parameters and Laboratory Markers With The Severity of Hypertriglyceridemia-Induced Pancreatitis

2020 ◽  
Author(s):  
Lifang Chen ◽  
Yingbao Huang ◽  
Huajun Yu ◽  
Kehua Pan ◽  
Zhao Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Body Composition ◽  
Logistic Regression ◽  
Adipose Tissue ◽  
Serum Albumin ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
The Third ◽  
Laboratory Markers ◽  
Low Serum

Abstract Background: Hypertriglyceridemia has arisen as the third leading cause of acute pancreatitis. This study aimed at exploring the association between the severity of hypertriglyceridemia-induced pancreatitis (HTGP) and computed tomography (CT)-based body composition parameters and laboratory markers.Methods: Clinical parameters were collected from 242 patients with HTGP between 2017 and 2020. Severity of HTGP was evaluated by original or modified CT severity index. Body composition parameters such as area and radiodensity of muscle, subcutaneous adipose tissue and visceral adipose tissue were calculated by CT at the third lumbar vertebra level. Parameters between mild and moderately severe to severe HTGP were compared. Uni-variate and multi-variate Logistic regression analyses were employed to assess the risk factors of the severity of HTGP.Results: Seventy patients with HTGP (28.9%) were mild. Body mass index, waist circumference and all CT-based body composition parameters differed between male and female patients. None was associated with the severity of HTGP, neither in the male nor in the female. Uni-variate and multi-variate Logistic regression analysis showed that low serum albumin (<35g/L) and high C-reactive protein (>90 mg/L) were risk factors of moderately severe to severe HTGP (P<0.001, OR=4.846, 95%CI=2.122-11.068; P<0.001, OR=4.230, 95%CI=2.050-8.727, respectively). Low serum albumin was also associated with pancreatic necrosis, longer hospital stay and higher scores of APACHE II, Ranson and Marshall in HTGP patients (all P<0.05).Conclusions: Low serum albumin and high C-reactive protein upon admission are associated with the severity of HTGP. However, none of the body composition parameters is associated with the severity of HTGP.

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