Culture if spikes? Indications and yield of blood cultures in hospitalized medical patients

Pathophysiological Responses to Bloodstream Infection in Critically Ill Transplant Recipients Compared With Non-Transplant Recipients

BACKGROUND

Identification of bloodstream infection (BSI) in transplant recipients may be difficult due to immunosuppression. Accordingly, we aimed to compare responses to BSI in critically ill transplant and non-transplant recipients and to modify systemic inflammatory response syndrome (SIRS) criteria for transplant recipients.

METHODS

We analyzed univariate risks and developed multivariable models of BSI with 27 clinical variables from adult intensive care unit (ICU) patients at the University of Virginia (UVA) and at the University of Pittsburgh (Pitt). We used Bayesian inference to adjust SIRS criteria for transplant recipients.

RESULTS

We analyzed 38.7 million hourly measurements from 41 725 patients at UVA, including 1897 transplant recipients with 193 episodes of BSI and 53 608 patients at Pitt, including 1614 transplant recipients with 768 episodes of BSI. The univariate responses to BSI were comparable in transplant and non-transplant recipients. The area under the receiver operating characteristic curve (AUC) was 0.82 (95% confidence interval [CI], .80-.83) for the model using all UVA patient data and 0.80 (95% CI, .76-.83) when using only transplant recipient data. The UVA all-patient model had an AUC of 0.77 (95% CI, .76-.79) in non-transplant recipients and 0.75 (95% CI, .71-.79) in transplant recipients at Pitt. The relative importance of the 27 predictors was similar in transplant and non-transplant models. An upper temperature of 37.5°C in SIRS criteria improved reclassification performance in transplant recipients.

CONCLUSIONS

Critically ill transplant and non-transplant recipients had similar responses to BSI. An upper temperature of 37.5°C in SIRS criteria improved BSI screening in transplant recipients.

Implementation of a diagnostic stewardship intervention to improve blood-culture utilization in 2 surgical ICUs: Time for a blood-culture change

OBJECTIVE

We compared the number of blood-culture events before and after the introduction of a blood-culture algorithm and provider feedback. Secondary objectives were the comparison of blood-culture positivity and negative safety signals before and after the intervention.

DESIGN

Prospective cohort design.

SETTING

Two surgical intensive care units (ICUs): general and trauma surgery and cardiothoracic surgery.

PATIENTS

Patients aged ≥18 years and admitted to the ICU at the time of the blood-culture event.

METHODS

We used an interrupted time series to compare rates of blood-culture events (ie, blood-culture events per 1,000 patient days) before and after the algorithm implementation with weekly provider feedback.

RESULTS

The blood-culture event rate decreased from 100 to 55 blood-culture events per 1,000 patient days in the general surgery and trauma ICU (72% reduction; incidence rate ratio [IRR], 0.38; 95% confidence interval [CI], 0.32-0.46; P < .01) and from 102 to 77 blood-culture events per 1,000 patient days in the cardiothoracic surgery ICU (55% reduction; IRR, 0.45; 95% CI, 0.39-0.52; P < .01). We did not observe any differences in average monthly antibiotic days of therapy, mortality, or readmissions between the pre- and postintervention periods.

CONCLUSIONS

We implemented a blood-culture algorithm with data feedback in 2 surgical ICUs, and we observed significant decreases in the rates of blood-culture events without an increase in negative safety signals, including ICU length of stay, mortality, antibiotic use, or readmissions.

Relationship Between Oral Temperature and Bacteremia in Hospitalized Patients

BACKGROUND

Early recognition and treatment of bacteremia can be lifesaving. Fever is a well-known marker of bacteremia, but the predictive value of temperature has not been fully explored.

OBJECTIVE

To describe temperature as a predictor of bacteremia and other infections.

DESIGN

Retrospective review of electronic health record data.

SETTING

A single healthcare system comprising 13 hospitals in the United States.

PATIENTS

Adult medical patients admitted in 2017 or 2018 without malignancy or immunosuppression.

MAIN MEASURES

Maximum temperature, bacteremia, influenza and skin and soft tissue (SSTI) infections based on blood cultures and ICD-10 coding.

KEY RESULTS

Of 97,174 patients, 1,518 (1.6%) had bacteremia, 1,392 (1.4%) had influenza, and 3,280 (3.3%) had an SSTI. There was no identifiable temperature threshold that provided adequate sensitivity and specificity for bacteremia. Only 45% of patients with bacteremia had a maximum temperature ≥ 100.4˚F (38˚C). Temperature showed a U-shaped relationship with bacteremia with highest risk above 103˚F (39.4˚C). Positive likelihood ratios for influenza and SSTI also increased with temperature but showed a threshold effect at ≥ 101.0 ˚F (38.3˚C). The effect of temperature was similar but blunted for patients aged ≥ 65 years, who frequently lacked fever despite bacteremia.

CONCLUSIONS

The majority of bacteremic patients had maximum temperatures below 100.4 ˚F (38.0˚C) and positive likelihood ratios for bacteremia increased with high temperatures above the traditional definition of fever. Efforts to predict bacteremia should incorporate temperature as a continuous variable.

Machine learning pipeline for blood culture outcome prediction using Sysmex XN-2000 blood sample results in Western Australia

BACKGROUND

Bloodstream infections (BSIs) are a significant burden on the global population and represent a key area of focus in the hospital environment. Blood culture (BC) testing is the standard diagnostic test utilised to confirm the presence of a BSI. However, current BC testing practices result in low positive yields and overuse of the diagnostic test. Diagnostic stewardship research regarding BC testing is increasing, and becoming more important to reduce unnecessary resource expenditure and antimicrobial use, especially as antimicrobial resistance continues to rise. This study aims to establish a machine learning (ML) pipeline for BC outcome prediction using data obtained from routinely analysed blood samples, including complete blood count (CBC), white blood cell differential (DIFF), and cell population data (CPD) produced by Sysmex XN-2000 analysers.

METHODS

ML models were trained using retrospective data produced between 2018 and 2019, from patients at Sir Charles Gairdner hospital, Nedlands, Western Australia, and processed at Pathwest Laboratory Medicine, Nedlands. Trained ML models were evaluated using stratified 10-fold cross validation.

RESULTS

Two ML models, an XGBoost model using CBC/DIFF/CPD features with boruta feature selection (BFS) , and a random forest model trained using CBC/DIFF features with BFS were selected for further validation after obtaining AUC scores of [Formula: see text] and [Formula: see text] respectively using stratified 10-fold cross validation. The XGBoost model obtained an AUC score of 0.76 on a internal validation set. The random forest model obtained AUC scores of 0.82 and 0.76 on internal and external validation datasets respectively.

CONCLUSIONS

We have demonstrated the utility of using an ML pipeline combined with CBC/DIFF, and CBC/DIFF/CPD feature spaces for BC outcome prediction. This builds on the growing body of research in the area of BC outcome prediction, and provides opportunity for further research.

Assessing a standardized decision-making algorithm for blood culture collection in the intensive care unit

PURPOSE

Blood cultures are commonly ordered for patients with low risk of bacteremia. Indications for obtaining blood cultures are often broad and ill defined, and decision algorithms for appropriate blood cultures have not been comprehensively evaluated in critically-ill populations.

METHODS

We conducted a retrospective analysis to assess the frequency of inappropriate blood cultures in the ICUs at Montefiore Medical Center based on an evidence-based guidance algorithm. Blood cultures were reviewed against this algorithm to determine their appropriateness. We calculated the prevalence of inappropriate blood culture and explored the reasons for these collected cultures.

RESULTS

300 patients were randomly selected from an initial cohort of 3370 patients. 294 patients were included and of these, 167 patients had at least 1 blood culture drawn. 125 patients had one or more inappropriate blood culture. 61.4% of blood cultures drawn were assessed to be inappropriate. The most common reason for inappropriate cultures was a culture drawn as a result of isolated fever or leukocytosis.

CONCLUSION

In a cohort of critically-ill patients, inappropriate blood cultures were common. The indications for blood cultures are often not evidence-based, and evidence-based algorithms to guide the collection of blood cultures may offer a way to decrease inappropriate culture orders.

Bacteremia Prediction With Prognostic Scores and a Causal Probabilistic Network - A Cohort Study of Emergency Department Patients

BACKGROUND

Physicians tend to overestimate patients' pretest probability of having bacteremia. The low yield of blood cultures and contaminants is associated with significant financial cost, as well as increased length of stay and unnecessary antibiotic treatment.

OBJECTIVE

This study examined the abilities of the National Early Warning Score (NEWS), the Quick Sequential Organ Failure Assessment (qSOFA), the Modified Sequential Organ Failure Assessment (mSOFA), and two versions of the causal probabilistic network, SepsisFinder™ (SF) to predict bacteremia in adult emergency department (ED) patients.

METHODS

This cohort study included adult ED patients from a large urban, academic tertiary hospital, with blood cultures obtained within 24 h of admission between 2016 and 2017. The outcome measure was true bacteremia. NEWS, qSOFA, mSOFA, and the two versions of SF score were calculated for all patients based on the first available full set of vital signs within 2 h and laboratory values within 6 h after drawing the blood cultures. Area under the receiver operating characteristic curve (AUROC) was calculated for each scoring system.

RESULTS

The study included 3106 ED patients, of which 199 (6.4%) patients had true bacteremia. The AUROCs for prediction of bacteremia were: NEWS = 0.65, qSOFA = 0.60, SF I = 0.65, mSOFA = 0.71, and SF II = 0.80.

CONCLUSIONS

Scoring systems using only vital signs, NEWS, and SF I showed moderate abilities in predicting bacteremia, whereas qSOFA performed poorly. Scoring systems using both vital signs and laboratory values, mSOFA and especially SF II, showed good abilities in predicting bacteremia.

Blood culture utilization practices among febrile and/or hypothermic inpatients

Background

Predictors associated with the decision of blood culture ordering among hospitalized patients with abnormal body temperature are still underexplored, particularly non-clinical factors. In this study, we evaluated the factors affecting blood culture ordering in febrile and hypothermic inpatients.

Methods

We performed a retrospective study of 15,788 adult inpatients with fever (≥ 38.3℃) or hypothermia (< 36.0℃) from January 2016 to December 2017. We evaluated the proportion of febrile and hypothermic episodes with an associated blood culture performed within 24h. Generalized Estimating Equations were used to determine independent predictors associated with blood culture ordering among febrile and hypothermic inpatients.

Results

We identified 21,383 abnormal body temperature episodes among 15,788 inpatients (13,093 febrile and 8,290 hypothermic episodes). Blood cultures were performed in 36.7% (7,850/ 21,383) of these episodes. Predictors for blood culture ordering among inpatients with abnormal body temperature included fever ≥ 39℃ (adjusted odd ratio [aOR] 4.17, 95% confident interval [CI] 3.91–4.46), fever (aOR 3.48, 95% CI 3.27–3.69), presence of a central venous catheter (aOR 1.36, 95% CI 1.30–1.43), systemic inflammatory response (SIRS) plus hypotension (aOR 1.33, 95% CI 1.26–1.40), SIRS (aOR 1.26, 95% CI 1.20–1.31), admission to stem cell transplant / medical oncology services (aOR 1.09, 95% CI 1.04–1.14), and detection of abnormal body temperature during night shift (aOR 1.06, 95% CI 1.03–1.09) or on the weekend (aOR 1.05, 95% CI 1.01–1.08).

Conclusion

Blood culture ordering for hospitalized patients with fever or hypothermia is multifactorial; both clinical and non-clinical factors. These wide variations and gaps in practices suggest opportunities to improve utilization patterns.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07748-x.

Blood Culture Utilization in the Hospital Setting: a Call for Diagnostic Stewardship

There has been significant progress in detection of bloodstream pathogens in recent decades with the development of more sensitive automated blood culture detection systems and the availability of rapid molecular tests for faster organism identification and detection of resistance genes. However, most blood cultures in clinical practice do not grow organisms, suggesting that suboptimal blood culture collection practices (e.g., suboptimal blood volume) or suboptimal selection of patients to culture (i.e., blood cultures ordered for patients with low likelihood of bacteremia) may be occurring. A national blood culture utilization benchmark does not exist, nor do specific guidelines on when blood cultures are appropriate or when blood cultures are of low value and waste resources. Studies evaluating the potential harm associated with excessive blood cultures have focused on blood culture contamination, which has been associated with significant increases in health care costs and negative consequences for patients related to exposure to unnecessary antibiotics and additional testing. Optimizing blood culture performance is important to ensure bloodstream infections (BSIs) are diagnosed while minimizing adverse events from overuse. In this review, we discuss key factors that influence blood culture performance, with a focus on the preanalytical phase, including technical aspects of the blood culture collection process and blood culture indications. We highlight areas for improvement and make recommendations to improve current blood culture practices among hospitalized patients.

Impact of an Anti-Microbial Stewardship Program on Targeted Antimicrobial Therapy in a Tertiary Care Health Care Institute in Central India

Introduction Antimicrobial resistance (AMR) has become a global pandemic. In order to identify this menace, World Health Organisation (WHO) has developed the Global Action Plan on AMR (GAP AMR). Antimicrobial stewardship programs (AMSP) have been identified as a decisive tool for combating AMR. One of the most efficient measures of these programs has been the implementation of point prevalence surveys (PPS) of antibiotic usage and subsequent audit feedback. The present study was undertaken to identify the impact of AMSP on curtailing of empirical usage of antibiotics and the augmentation of targeted therapy.  Methods It is an observational, cross-sectional study comprising 1396 patients. The microbiology culture details and anti-microbial-sensitivity results were recorded. Antibiotic prescriptions were recorded in each patient during their hospital stay. Result Out of 1396 patients treated over four quarters (Q1-Q4), 711 (50.9%) patients were on antibiotics, and among them, only 415 patients were subjected to any microbiological cultures with an overall bacterial culture rate (BCR) of 58.3%, and 296 patients (41.6%) were treated with antibiotics empirically without sending any samples for bacterial culture. There was a statistically significant rise in BCR from 47.3% in the first quarter to 77.6% in the fourth quarter. Sending specimens for blood culture increased significantly from 29.2% in Q1 to 37.6% in Q4. After receiving culture reports, 72.3% of cases continued with the same antibiotic, the antibiotic was changed in 19.9% of cases, and the antibiotic was stopped in 7.8% of cases. Conclusion There was a strong positive impact of AMSP in curtailment of empirical usage of antibiotics and augmenting targeted therapy as evidenced by the significant rise in BCR over Q1-Q4 PPS as well as a significant rise in ordering for blood culture over the same time period.

A Rare Case of Ralstonia pickettii Infection in a Patient Undergoing Thyroid Surgery

Introduction: The incidence of infection by Ralstonia is increasing. Several reports describing infection by these bacteria in immunocompromised patients have been published. In this study, we reported a case of Ralstonia pickettii infection in a patient with normal immunity. Case Presentation: A woman presented with fever after thyroid surgery. We identified R. pickettii in her blood culture using 16S rRNA gene sequencing. The patient’s condition improved clinically upon treatment with levofloxacin. Conclusions: Our report highlights the potential of Ralstonia to cause sepsis in patients with normal immunity and emphasizes the importance of blood culture testing when a hospitalized patient has an unexplained high fever.

Fever and hypothermia represent two populations of sepsis patients and are associated with outside temperature

Background

Fever and hypothermia have been observed in septic patients. Their influence on prognosis is subject to ongoing debates.

Methods

We did a secondary analysis of a large clinical dataset from a quality improvement trial. A binary logistic regression model was calculated to assess the association of the thermal response with outcome and a multinomial regression model to assess factors associated with fever or hypothermia.

Results

With 6542 analyzable cases we observed a bimodal temperature response characterized by fever or hypothermia, normothermia was rare. Hypothermia and high fever were both associated with higher lactate values. Hypothermia was associated with higher mortality, but this association was reduced after adjustment for other risk factors. Age, community-acquired sepsis, lower BMI and lower outside temperatures were associated with hypothermia while bacteremia and higher procalcitonin values were associated with high fever.

Conclusions

Septic patients show either a hypothermic or a fever response. Whether hypothermia is a maladaptive response, as indicated by the higher mortality in hypothermic patients, or an adaptive response in patients with limited metabolic reserves under colder environmental conditions, remains an open question.

Trial registration The original trial whose dataset was analyzed was registered at ClinicalTrials.gov (NCT01187134) on August 23, 2010, the first patient was included on July 1, 2011.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03776-2.

Diagnosing hospital bacteraemia in the framework of predictive, preventive and personalised medicine using electronic health records and machine learning classifiers

Background

The bacteraemia prediction is relevant because sepsis is one of the most important causes of morbidity and mortality. Bacteraemia prognosis primarily depends on a rapid diagnosis. The bacteraemia prediction would shorten up to 6 days the diagnosis, and, in conjunction with individual patient variables, should be considered to start the early administration of personalised antibiotic treatment and medical services, the election of specific diagnostic techniques and the determination of additional treatments, such as surgery, that would prevent subsequent complications. Machine learning techniques could help physicians make these informed decisions by predicting bacteraemia using the data already available in electronic hospital records.

Objective

This study presents the application of machine learning techniques to these records to predict the blood culture's outcome, which would reduce the lag in starting a personalised antibiotic treatment and the medical costs associated with erroneous treatments due to conservative assumptions about blood culture outcomes.

Methods

Six supervised classifiers were created using three machine learning techniques, Support Vector Machine, Random Forest and K-Nearest Neighbours, on the electronic health records of hospital patients. The best approach to handle missing data was chosen and, for each machine learning technique, two classification models were created: the first uses the features known at the time of blood extraction, whereas the second uses four extra features revealed during the blood culture.

Results

The six classifiers were trained and tested using a dataset of 4357 patients with 117 features per patient. The models obtain predictions that, for the best case, are up to a state-of-the-art accuracy of 85.9%, a sensitivity of 87.4% and an AUC of 0.93.

Conclusions

Our results provide cutting-edge metrics of interest in predictive medical models with values that exceed the medical practice threshold and previous results in the literature using classical modelling techniques in specific types of bacteraemia. Additionally, the consistency of results is reasserted because the three classifiers' importance ranking shows similar features that coincide with those that physicians use in their manual heuristics. Therefore, the efficacy of these machine learning techniques confirms their viability to assist in the aims of predictive and personalised medicine once the disease presents bacteraemia-compatible symptoms and to assist in improving the healthcare economy.

Culture Ordering for Patients with New-onset Fever: A Survey of Pediatric Intensive Care Unit Clinician Practices

INTRODUCTION

Accurate assessment of infection in critically ill patients is vital to their care. Both indiscretion and under-utilization of diagnostic microbiology testing can contribute to inappropriate antibiotic administration or delays in diagnosis. However, indiscretion in diagnostic microbiology cultures may also lead to unnecessary tests that, if false-positive, would incur additional costs and unhelpful evaluations. This quality improvement project objective was to assess pediatric intensive care unit (PICU) clinicians' attitudes and practices around the microbiology work-up for patients with new-onset fever.

METHODS

We developed and conducted a self-administered electronic survey of PICU clinicians at a single institution. The survey included 7 common clinical vignettes of PICU patients with new-onset fever and asked participants whether they would obtain central line blood cultures, peripheral blood cultures, respiratory aspirate cultures, cerebrospinal fluid cultures, urine cultures, and/or urinalyses.

RESULTS

Forty-seven of 54 clinicians (87%) completed the survey. Diagnostic specimen ordering practices were notably heterogeneous. Respondents unanimously favored a decision-support algorithm to guide culture specimen ordering practices for PICU patients with fever (100%, N = 47). A majority (91.5%, N = 43) indicated that a decision-support algorithm would be a means to align PICU and consulting care teams when ordering culture specimens for patients with fever.

CONCLUSION

This survey revealed variability of diagnostic specimen ordering practices for patients with new fever, supporting an opportunity to standardize practices. Clinicians favored a decision-support tool and thought that it would help align patient management between clinical team members. The results will be used to inform future diagnostic stewardship efforts.

Bacteraemia, antimicrobial susceptibility and treatment among Campylobacter-associated hospitalisations in the Australian Capital Territory: a review

BACKGROUND

Campylobacter spp. cause mostly self-limiting enterocolitis, although a significant proportion of cases require hospitalisation highlighting potential for severe disease. Among people admitted, blood culture specimens are frequently collected and antibiotic treatment is initiated. We sought to understand clinical and host factors associated with bacteraemia, antibiotic treatment and isolate non-susceptibility among Campylobacter-associated hospitalisations.

METHODS

Using linked hospital microbiology and administrative data we identified and reviewed Campylobacter-associated hospitalisations between 2004 and 2013. We calculated population-level incidence for Campylobacter bacteraemia and used logistic regression to examine factors associated with bacteraemia, antibiotic treatment and isolate non-susceptibility among Campylobacter-associated hospitalisations.

RESULTS

Among 685 Campylobacter-associated hospitalisations, we identified 25 admissions for bacteraemia, an estimated incidence of 0.71 cases per 100,000 population per year. Around half of hospitalisations (333/685) had blood culturing performed. Factors associated with bacteraemia included underlying liver disease (aOR 48.89, 95% CI 7.03-340.22, p < 0.001), Haematology unit admission (aOR 14.67, 95% CI 2.99-72.07, p = 0.001) and age 70-79 years (aOR 4.93, 95% CI 1.57-15.49). Approximately one-third (219/685) of admissions received antibiotics with treatment rates increasing significantly over time (p < 0.05). Factors associated with antibiotic treatment included Gastroenterology unit admission (aOR 3.75, 95% CI 1.95-7.20, p < 0.001), having blood cultures taken (aOR 2.76, 95% CI 1.79-4.26, p < 0.001) and age 40-49 years (aOR 2.34, 95% CI 1.14-4.79, p = 0.02). Non-susceptibility of isolates to standard antimicrobials increased significantly over time (p = 0.01) and was associated with overseas travel (aOR 11.80 95% CI 3.18-43.83, p < 0.001) and negatively associated with tachycardia (aOR 0.48, 95%CI 0.26-0.88, p = 0.02), suggesting a healthy traveller effect.

CONCLUSIONS

Campylobacter infections result in considerable hospital burden. Among those admitted to hospital, an interplay of factors involving clinical presentation, presence of underlying comorbidities, complications and increasing age influence how a case is investigated and managed.

Does This Patient Need Blood Cultures? A Scoping Review of Indications for Blood Cultures in Adult Nonneutropenic Inpatients

Guidance regarding indications for initial or follow-up blood cultures is limited. We conducted a scoping review of articles published between January 2004 and June 2019 that reported the yield of blood cultures and/or their impact in the clinical management of fever and common infectious syndromes in nonneutropenic adult inpatients. A total of 2893 articles were screened; 50 were included. Based on the reported incidence of bacteremia, syndromes were categorized into low, moderate, and high pretest probability of bacteremia. Routine blood cultures are recommended in syndromes with a high likelihood of bacteremia (eg, endovascular infections) and those with moderate likelihood when cultures from the primary source of infection are unavailable or when prompt initiation of antibiotics is needed prior to obtaining primary source cultures. In syndromes where blood cultures are low-yield, blood cultures can be considered for patients at risk of adverse events if a bacteremia is missed (eg, patient with pacemaker and severe purulent cellulitis). If a patient has adequate source control and risk factors or concern for endovascular infection are not present, most streptococci or Enterobacterales bacteremias do not require routine follow-up blood cultures.

Developing Machine-Learning Prediction Algorithm for Bacteremia in Admitted Patients

Purpose

Bloodstream infection among hospitalized patients is associated with serious adverse outcomes. Blood culture is routinely ordered in patients with suspected infections, although 90% of blood cultures do not show any growth of organisms. The evidence regarding the prediction of bacteremia is scarce.

Patients And Methods

A retrospective review of blood cultures requested for a cohort of admitted patients between 2017 and 2019 was undertaken. Several machine-learning models were used to identify the best prediction model. Additionally, univariate and multivariable logistic regression was used to determine the predictive factors for bacteremia.

Results

A total of 36,405 blood cultures of 7157 patients were done. There were 2413 (6.62%) positive blood cultures. The best prediction was by using NN with the high specificity of 88% but low sensitivity. There was a statistical difference in the following factors: longer admission days before the blood culture, presence of a central line, and higher lactic acid—more than 2 mmol/L.

Conclusion

Despite the low positive rate of blood culture, machine learning could predict positive blood culture with high specificity but minimum sensitivity. Yet, the SIRS score, qSOFA score, and other known factors were not good prognostic factors. Further improvement and training would possibly enhance machine-learning performance.

The Diagnostic Performance of Interleukin-6 and C-Reactive Protein for Early Identification of Neonatal Sepsis

Interleukin-6 (IL-6) and C-reactive protein (CRP) are being used for diagnosis of sepsis. However, studies have reported varying cut-off levels and diagnostic performance. This study aims to investigate the optimal cut-off levels and performance of IL-6 and CRP for the diagnosis of neonatal sepsis. The study was conducted at the University Hospital of Leipzig, Germany from November 2012 to June 2020. A total of 899 neonates: 104 culture proven sepsis, 160 clinical sepsis, and 625 controls were included. Blood culture was performed using BacT/ALERT 3D system. IL-6 and CRP were analyzed by electrochemiluminescent immunoassay and immunoturbidimetric assay, respectively. Data were analyzed using SPSS 20 statistical software. Among neonates with proven sepsis, the optimal cut-off value of IL-6 was 313.5 pg/mL. The optimal cut-off values for CRP in 5 days serial measurements (CRP1, CRP2, CRP3, CRP4, and CRP5) were 2.15 mg/L, 8.01 mg/L, 6.80 mg/L, 5.25 mg/L, and 3.72 mg/L, respectively. IL-6 showed 73.1% sensitivity, 80.2% specificity, 37.6% PPV, and 94.8% NPV. The highest performance of CRP was observed in the second day with 89.4% sensitivity, 97.3% specificity, 94.5% PPV, and 98.3% NPV. The combination of IL-6 and CRP showed increase in sensitivity with decrease in specificity. In conclusion, this study defines the optimal cut-off values for IL-6 and CRP. The combination of IL-6 and CRP demonstrated increased sensitivity. The CRP 2 at cut-off 8.01 mg/L showed the highest diagnostic performance for identification of culture negative clinical sepsis cases. We recommend the combination of IL-6 (≥313.5 pg/mL) and CRP1 (≥2.15 mg/L) or IL-6 (≥313.5 pg/mL) and CRP2 (≥8.01 mg/L) for early and accurate diagnosis of neonatal sepsis. The recommendation is based on increased sensitivity, that is, to minimize the risk of any missing cases of sepsis. The CRP2 alone at cut-off 8.01 mg/L might be used to identify clinical sepsis cases among culture negative sepsis suspected neonates in hospital settings.

Limited Clinical Utility of Follow-up Blood Cultures in Patients With Streptococcal Bacteremia: An Opportunity for Blood Culture Stewardship

Background

The value of positive follow-up blood cultures (FUBCs) in streptococcal bacteremia has not been well defined. Therefore, we explored the frequency of and risk factors for positive FUBC in a retrospective cohort of patients with streptococcal bacteremia.

Methods

Adults ≥18 years of age, admitted with at least 1 positive blood culture for Streptococcus spp between 2013 and 2018 followed by at least 1 FUBC, were potentially eligible. Positive FUBCs were defined as cultures positive for the same streptococcal species drawn >24 hours after the index culture. We excluded patients with polymicrobial bacteremia. We compared the characteristics of patients with and without a positive FUBC.

Results

In our single-center cohort, we identified 590 patients with streptococcal bacteremia, and 314 patients met inclusion criteria. Ten patients had FUBC with Streptococcus spp (3.2%), 4 (1.3%) had a contaminant identified, and 3 (1.0%) had a new pathogen isolated. Endocarditis (5 of 10 [50.0%] vs 35 of 304 [11.5%]), epidural abscess (2 of 10 [20%] vs 4 of 304 [1.3%]), and discitis or vertebral osteomyelitis (3 of 10 [30.0%] vs 14 of 304 [4.6%]) were associated with positive FUBC. Patients with positive FUBC had a longer median length of stay (12.9 vs 7.1 days, P = .004) and longer duration of antibiotic treatment (14.9 vs 43.2 days, P = .03).

Conclusions

Follow-up blood cultures among patients with streptococcal BSI are rarely positive. Clinicians could consider limiting follow-up blood cultures in patients at low risk for deep-seated streptococcal infections, persistent bacteremia, or endovascular infection.

Pathophysiologic Signatures of Bloodstream Infection in Critically Ill Adults

Supplemental Digital Content is available in the text.

Objectives:

Bloodstream infection is associated with high mortality rates in critically ill patients but is difficult to identify clinically. This results in frequent blood culture testing, exposing patients to additional costs as well as the potential harms of unnecessary antibiotics. The purpose of this study was to assess whether the analysis of bedside physiologic monitoring data could accurately describe a pathophysiologic signature of bloodstream infection in patients admitted to the ICU.

Design:

Development of a statistical model using physiologic data from a retrospective observational cohort.

Setting:

University of Virginia Medical Center (Charlottesville, VA), a tertiary-care academic medical center.

Patients:

Critically ill patients consecutively admitted to either the medical or surgical/trauma ICUs with available physiologic monitoring data between February 2011 and June 2015.

Interventions:

None.

Measurements and Main Results:

We analyzed 9,954 ICU admissions with 144 patient-years of vital sign and electrocardiography waveform data, totaling 1.3 million hourly measurements. There were 15,577 blood culture instances, with 1,184 instances of bloodstream infection (8%). The multivariate pathophysiologic signature of bloodstream infection was characterized by abnormalities in 15 different physiologic features. The cross-validated area under the receiver operating characteristic curve was 0.78 (95% CI, 0.69–0.85). We also identified distinct signatures of Gram-negative and fungal bloodstream infections, but not Gram-positive bloodstream infection.

Conclusions:

Signatures of bloodstream infection can be identified in the routine physiologic monitoring data of critically ill adults. This may assist in identifying infected patients, maximizing diagnostic stewardship, and measuring the effect of new therapeutic modalities for sepsis.

A Diagnostic Stewardship Intervention To Improve Blood Culture Use among Adult Nonneutropenic Inpatients: the DISTRIBUTE Study

Interventions to optimize blood culture (BCx) practices in adult inpatients are limited. We conducted a before-after study evaluating the impact of a diagnostic stewardship program that aimed to optimize BCx use in a medical intensive care unit (MICU) and five medicine units at a large academic center. The program included implementation of an evidence-based algorithm detailing indications for BCx use and education and feedback to providers about BCx rates and indication inappropriateness. Neutropenic patients were excluded. BCx rates from contemporary control units were obtained for comparison. The primary outcome was the change in BCxs ordered with the intervention. Secondary outcomes included proportion of inappropriate BCx, solitary BCx, and positive BCx. Balancing metrics included compliance with the Centers for Medicare and Medicaid Services (CMS) SEP-1 BCx component, 30-day readmission, and all-cause in-hospital and 30-day mortality. After the intervention, BCx rates decreased from 27.7 to 22.8 BCx/100 patient-days (PDs) in the MICU (P = 0.001) and from 10.9 to 7.7 BCx/100 PD for the 5 medicine units combined (P < 0.001). BCx rates in the control units did not decrease significantly (surgical intensive care unit [ICU], P = 0.06; surgical units, P = 0.15). The proportion of inappropriate BCxs did not significantly change with the intervention (30% in the MICU and 50% in medicine units). BCx positivity increased in the MICU (from 8% to 11%, P < 0.001). Solitary BCxs decreased by 21% in the medicine units (P < 0.001). Balancing metrics were similar before and after the intervention. BCx use can be optimized with clinician education and practice guidance without affecting sepsis quality metrics or mortality.

Risk Factors for Positive Follow-Up Blood Cultures in Gram-Negative Bacilli Bacteremia: Implications for Selecting Who Needs Follow-Up Blood Cultures

Background

The value of follow-up blood cultures (FUBCs) to document clearance of bacteremia due to Gram-negative bacilli (GNB) has not been well established. Although previous studies suggested that the yield of FUBCs for GNB bacteremia is low, it remains to be elucidated for whom FUBC may be beneficial and for whom it is unnecessary.

Methods

A retrospective cohort study was performed at 4 acute care hospitals to identify risk factors for positive FUBCs with GNB bacteremia and to better guide clinicians’ decisions as to which patients may or may not benefit from FUBCs. Participants included adult patients with GNB bacteremia who had FUBCs and were admitted between January 2017 and December 2018. The primary outcomes were the factors associated with positive FUBCs and the yield of FUBCs with and without the factors.

Results

Of 306 patients with GNB bacteremia who had FUBCs, 9.2% (95% confidence interval, 6.2%–13.0%) had the same GNB in FUBCs. In the multivariate logistic regression analysis, end-stage renal disease on hemodialysis, intravascular device, and bacteremia due to extended-spectrum β-lactamase or carbapenemase-producing organism were identified as independent predictors of positive FUBCs with GNB bacteremia. Approximately 7 FUBCs and 30 FUBCs were needed for patients with ≥1 or no risk factors, respectively, to yield 1 positive result.

SummaryThis multi-site retrospective cohort study found that among patients with gram-negative bacilli (GNB) bacteremia, having ESRD on hemodialysis, intravascular devices, or bacteremia due to multi-drug resistant GNB were each independently associated with having a positive follow-up blood culture.

Conclusions

Follow-up blood culture may not be necessary for all patients with GNB bacteremia and has the highest yield in patients with 1 or more risk factors.

Strategies for increasing diagnostic yield of community-onset bacteraemia within the emergency department: A retrospective study

Bloodstream infections (BSI) are associated with high mortality. Therefore, reliable methods of detection are of paramount importance. Efficient strategies to improve diagnostic yield of bacteraemia within the emergency department (ED) are needed. We conducted a retrospective analysis of all ED encounters in a high-volume, city-centre university hospital within Germany during a five-year study period from October 2013 to September 2018. A time-series analysis was conducted for all ED encounters in which blood cultures (BCs) were collected. BC detection rates and diagnostic yield of community-onset bacteraemia were compared during the study period (which included 45 months prior to the start of a new diagnostic Antibiotic Stewardship (ABS) bundle and 15 months following its implementation). BCs were obtained from 5,191 out of 66,879 ED admissions (7.8%). Bacteraemia was detected in 1,013 encounters (19.5% of encounters where BCs were obtained). The overall yield of true bacteraemia (defined as yielding clinically relevant pathogens) was 14.4%. The new ABS-related diagnostic protocol resulted in an increased number of hospitalised patients with BCs collected in the ED (18% compared to 12.3%) and a significant increase in patients with two or more BC sets taken (59% compared to 25.4%), which resulted in an improved detection rate of true bacteraemia (2.5% versus 1.8% of hospital admissions) without any decrease in diagnostic yield. This simultaneous increase in BC rates without degradation of yield was a valuable finding that indicated success of this strategy. Thus, implementation of the new diagnostic ABS bundle within the ED, which included the presence of a skilled infectious disease (ID) team focused on obtaining BCs, appeared to be a valuable tool for the accurate and timely detection of community-onset bacteraemia.

Internal medicine residents' evaluation of fevers overnight

Background Scant data exists to guide the work-up for fever in hospitalized patients, and little is known about what diagnostic tests medicine residents order for such patients. We sought to analyze how cross-covering medicine residents address fever and how sign-out systems affect their response. Methods We conducted a prospective cohort study to evaluate febrile episodes that residents responded to overnight. Primary outcomes included diagnostic tests ordered, if an in-person evaluation occurred, and the effect of sign-out instructions that advised a "full fever work-up" (FFWU). Results Investigators reviewed 253 fevers in 155 patients; sign-out instructions were available for 204 fevers. Residents evaluated the patient in person in 29 (11%) episodes. The most common tests ordered were: blood cultures (48%), urinalysis (UA) with reflex culture (34%), and chest X-ray (30%). If the sign-out advised an FFWU, residents were more likely to order blood cultures [odds ratio (OR) 14.75, 95% confidence interval (CI) 7.52-28.90], UA with reflex culture (OR 12.07, 95% CI 5.56-23.23), chest X-ray (OR 16.55, 95% CI 7.03-39.94), lactate (OR 3.33, 95% CI 1.47-7.55), and complete blood count (CBC) (OR 3.16, 95% CI 1.17-8.51). In a multivariable regression, predictors of the number of tests ordered included hospital location, resident training level, timing of previous blood culture, in-person evaluation, escalation to a higher level of care, and sign-out instructions. Conclusions Sign-out instructions and a few patient factors significantly impacted cross-cover resident diagnostic test ordering for overnight fevers. This practice can be targeted in resident education to improve diagnostic reasoning and stewardship.

Evaluation of blood culture epidemiology and efficiency in a large European teaching hospital

Background

Blood cultures remain the gold standard for detecting bacteremia despite their limitations. The current practice of blood culture collection is still inefficient with low yields. Limited focus has been given to the association between timing of specimen collection at different time points during admission and their yield.

Methods

We carried out a retrospective observational study by analyzing all 3,890 sets of cultures collected from the 1,962 admitted patients over the seven-month period of this study. We compared the blood culture yield between the early group (≤24 hours after admission) and the late group (> 24 hours of admission). We also investigated the effect of prehospital oral antibiotics and pre-analytical time on the first cultures in the emergency department. Epidemiology and efficiency of blood cultures were studied for each medical specialty.

Results

In total, 3,349(86.1%) blood cultures were negative and 541(13.9%) were positive for one or more microorganisms. After correcting for contamination, the overall yield was 290 (7.5%). The early group (n = 1,490) yielded significantly more true-positive cultures (10.1% versus 5.8%, P<0.001) than the late group (n = 2,400). The emergency department had a significantly higher yield than general wards, 11.2% versus 5.7% (p<0.001). Prehospital oral antibiotic use and pre-analytical time did not affect the yield of first cultures at the emergency department (p = 0.735 and 0.816 respectively). The number of tests needed to obtain one true-positive culture varied between departments, ranging from 7 to 45.

Conclusion

This study showed that blood cultures are inefficient in detecting bacteremia. Cultures collected during 24 hours after admission yielded more positive results than those collected later. Significant variations in blood culture epidemiology and efficiency per specialty suggest that guidelines should be reevaluated. Future studies should aim at improving blood culture yield, implementing educational programs to reduce contamination and cost-effective application of modern molecular diagnostic technologies.

Preventability of hospital onset bacteremia and fungemia: A pilot study of a potential healthcare-associated infection outcome measure

Hospital-onset bacteremia and fungemia (HOB), a potential measure of healthcare-associated infections, was evaluated in a pilot study among 60 patients across 3 hospitals. Two-thirds of all HOB events and half of nonskin commensal HOB events were judged as potentially preventable. Follow-up studies are needed to further develop this measure.

Choosing Wisely Overnight? Residents' Approach to Fever

We surveyed internal medicine residents regarding how they approach febrile patients in cross-cover settings. Residents frequently use the term “full fever work-up,” and rely on this for sign-out. Despite this, residents felt fever work-ups were not evidenced-based, and definitions of when and how to respond to a fever varied.