Development and utility assessment of a machine learning bloodstream infection classifier in pediatric patients receiving cancer treatments.

BACKGROUND: Objectives were to build a machine learning algorithm to identify bloodstream infection (BSI) among pediatric patients with cancer and hematopoietic stem cell transplantation (HSCT) recipients, and to compare this approach with presence of neutropenia to identify BSI. METHODS: We included patients 0-18 years of age at cancer diagnosis or HSCT between January 2009 and November 2018. Eligible blood cultures were those with no previous blood culture (regardless of result) within 7 days. The primary outcome was BSI. Four machine learning algorithms were used: elastic net, support vector machine and two implementations of gradient boosting machine (GBM and XGBoost). Model training and evaluation were performed using temporally disjoint training (60%), validation (20%) and test (20%) sets. The best model was compared to neutropenia alone in the test set. RESULTS: Of 11,183 eligible blood cultures, 624 (5.6%) were positive. The best model in the validation set was GBM, which achieved an area-under-the-receiver-operator-curve (AUROC) of 0.74 in the test set. Among the 2236 in the test set, the number of false positives and specificity of GBM vs. neutropenia were 508 vs. 592 and 0.76 vs. 0.72 respectively. Among 139 test set BSIs, six (4.3%) non-neutropenic patients were identified by GBM. All received antibiotics prior to culture result availability. CONCLUSIONS: We developed a machine learning algorithm to classify BSI. GBM achieved an AUROC of 0.74 and identified 4.3% additional true cases in the test set. The machine learning algorithm did not perform substantially better than using presence of neutropenia alone to predict BSI.

[Acute haematogenous osteomyelitis in children : Diagnostic algorithm and treatment strategies]. / Akute hämatogene Osteomyelitis im Wachstumsalter : Diagnostischer Algorithmus und Behandlungsstrategien.

Acute haematogenous osteomyelitis (AHO) in children is a severe condition. A delay in diagnosis and insufficient treatment may result in deformities, chronicity and sepsis. Therefore a structured diagnostic workup has to be followed in order to diagnose or rule out osteomyelitis. To identify the causative agent for targeted antibiotic treatment, a bone biopsy or puncture should be performed. However, approximately 25% of cases are culture-negative even after biopsy. The knowledge of the typical age-dependent bacterial spectrum is essential for empirical antibiotic therapy. The principal causative organism is Staphylococcus aureus. Surgery is not routinely required in paediatric acute osteomyelitis but surgical intervention is indicated if an abscess is detected. Secondary septic arthritis is a serious complication which has to be treated immediately by surgical intervention. Nevertheless, complete regeneration can be expected in up to 80% of children with AHO.

Diagnosis and classification of adult Still's disease.

The cornerstone of adult onset Still's disease is the triad of daily fever, arthritis and rash. This syndrome remains enigmatic and most often a disease of exclusion. There are both musculoskeletal as well as systemic features. More importantly, reactive hemophagocytic syndrome may occur in patients. In this review we attempt to place this syndrome in perspective, including data on geoepidemiology, clinical and laboratory features.

Prediction of bacteremia in children with febrile episodes during chemotherapy for acute lymphoblastic leukemia.

The purpose was to identify risk factors for bacteremia in febrile episodes occurring during chemotherapy for acute lymphoblastic leukemia (ALL) in children, and to develop a risk score permitting risk-adapted antibiotic therapy. We reviewed a total of 172 febrile episodes occurring during chemotherapy in 31 children and adolescents with ALL. Temperature, hematological parameters, culture findings, and antibiotic therapy were recorded. Bacteremias were classified as transmucosal or CVC-dependent. Blood cultures were positive with mucosal pathogens in 15 cases (9%) and with skin/environmental bacteria in 34 (20%). CVC-dependent infections occurred throughout the treatment phases, while transmucosal primarily during induction therapy. Transmucosal bacteremia was associated with induction therapy, leukocyte count ≤0.5 × 10(9)/L, neutrophil count ≤0.1 × 10(9)/L, monocyte count ≤0.01 × 10(9)/L, and platelet count ≤50 × 10(9)/L. Based on logistic conversion of the odds ratios for the five factors, a weight of 2 was assigned to induction therapy and leukocyte count ≤0.5 × 10(9)/L, and a weight of 1 to the remaining three parameters. The weights were included in a simple additive score ranging from 0 to 7, which defined groups with 4%, 6%, 24%, and 40% risk of transmucosal bacteremia. CVC-dependent bacteremia was not associated with markers of poor bone marrow function. In conclusion, transmucosal bacteremia in children with ALL is related to infiltration or suppression of the bone marrow. A score reflecting the condition of the marrow can define low-risk and high-risk groups and may prove clinically useful.

[Taxonomic composition of metagenomic community in the larval gut of mosquito Anopheles sinensis (Diptera: Culicidae)].

OBJECTIVE: To investigate the bacteria diversity in larval gut of field-collected Anopheles sinensis. METHODS: The 16S rDNA V4 region of An. sinensis larvae collected from paddy on Jiading District of Shanghai (L1/L2) and small seeping water on Wenchang City of Hainan (AS) was sequenced by high-throughput pyrosequencing. Using Qiime and Mothur softwares, the number of sequences and operational taxonomic units (OTUs) for each sample was sorted and calculated, the species abundance and distribution, Alpha diversity index and difference times of species abundance among samples were analyzed. RESULTS: The number of sequences and OTUs for each sample were 253 724/3 930 (L1), 225 203/4 312 (L2) and 73 990/2 380 (AS). The rarefaction curves showed that adequate sampling was achieved. The number of OTUs was close to actual situation. The value of richness index was 5 942.61/6 534.88 (L1), 6 328.17/7 235.89 (L2) and 4228.66/5 651.20 (AS); diversity index was 4.63/0.03 (L1), 5.10/0.02 (L2) and 0.14/3.94 (AS). The dominant species of An. sinensis larvae gut microbiota all belonged to the phylum Proteobacteria, with a percentage of 87% (AS) and 90% (L). In addition, the dominant phyla among them were Firmicutes, Bacteroidetes and Actinobacteria. The comparison of bacterial abundance between L and AS showed that there were 18 phyla with significant difference, except the Proteobacteria and Deinococcus-Thermus; only 9 phyla were different significantly between L1 and L2. CONCLUSION: Evenness and richness of bacteria flora in the An. sinensis larvae gut collected from paddy and small seeping waters were obtained.

Classification of positive blood cultures: computer algorithms versus physicians' assessment--development of tools for surveillance of bloodstream infection prognosis using population-based laboratory databases.

BACKGROUND: Information from blood cultures is utilized for infection control, public health surveillance, and clinical outcome research. This information can be enriched by physicians' assessments of positive blood cultures, which are, however, often available from selected patient groups or pathogens only. The aim of this work was to determine whether patients with positive blood cultures can be classified effectively for outcome research in epidemiological studies by the use of administrative data and computer algorithms, taking physicians' assessments as reference. METHODS: Physicians' assessments of positive blood cultures were routinely recorded at two Danish hospitals from 2006 through 2008. The physicians' assessments classified positive blood cultures as: a) contamination or bloodstream infection; b) bloodstream infection as mono- or polymicrobial; c) bloodstream infection as community- or hospital-onset; d) community-onset bloodstream infection as healthcare-associated or not. We applied the computer algorithms to data from laboratory databases and the Danish National Patient Registry to classify the same groups and compared these with the physicians' assessments as reference episodes. For each classification, we tabulated episodes derived by the physicians' assessment and the computer algorithm and compared 30-day mortality between concordant and discrepant groups with adjustment for age, gender, and comorbidity. RESULTS: Physicians derived 9,482 reference episodes from 21,705 positive blood cultures. The agreement between computer algorithms and physicians' assessments was high for contamination vs. bloodstream infection (8,966/9,482 reference episodes [96.6%], Kappa = 0.83) and mono- vs. polymicrobial bloodstream infection (6,932/7,288 reference episodes [95.2%], Kappa = 0.76), but lower for community- vs. hospital-onset bloodstream infection (6,056/7,288 reference episodes [83.1%], Kappa = 0.57) and healthcare-association (3,032/4,740 reference episodes [64.0%], Kappa = 0.15). The 30-day mortality in the discrepant groups differed from the concordant groups as regards community- vs. hospital-onset, whereas there were no material differences within the other comparison groups. CONCLUSIONS: Using data from health administrative registries, we found high agreement between the computer algorithms and the physicians' assessments as regards contamination vs. bloodstream infection and monomicrobial vs. polymicrobial bloodstream infection, whereas there was only moderate agreement between the computer algorithms and the physicians' assessments concerning the place of onset. These results provide new information on the utility of computer algorithms derived from health administrative registries.

[Microbiological characteristics of pathogens causing bacteremia among hospitalized pediatric oncology patients with fever and neutropenia].

BACKGROUND: Bacterial infections are a major threat to pediatric oncology patients with fever and neutropenia. Current management consists of empiric broad-spectrum antibiotics and prompt medical evaluation. Local bacterial susceptibility rates were published in 2005, and the local protocol (piperacillin and amikacin) was established as an adequate empiric treatment with -100% efficiency against the common pathogens in our pediatric hemato-oncology ward. AIM: To characterize the spectrum of bacteria isolated from blood cultures at the pediatric hemato-oncology ward between 2008- 2010, and to evaluate the current protocol. METHODS: A prospective study, conducted in the pediatric hemato-oncologic ward among hospitalized children (2 months - 18 years) with fever and neutropenia. Blood cultures from peripheral blood and central lines were obtained from all patients at admission. Bacterial resistance to various antimicrobial agents was determined. RESULTS: During 2008-2010, 195 admissions (105 children) due to fever and neutropenia were recorded. Approximately 30% of all blood cultures were positive for a pathogen with -50% Gram positive bacteria mostly CONS. The most prevalent Gram negative bacteria were acinetobacter and klebsiella spp. Candida species were isolated from 7% of positive cultures. Susceptibility rates for the current empiric antimicrobial regimen were about 90%. CONS bacteremia rate increased from 4% in 2000-2002 to 29% in 2008-2010 (p < 0.01). CONCLUSIONS: The currently applied empiric antimicrobial protocol is an optimal first line regimen, considering the susceptibility of the most common pathogens. Judicious use of carbapenems for gram negative bacteria and glycopeptides or other novel antimicrobial agents in cases of CONS bacteremia is required.

Quality of traditional surveillance for public reporting of nosocomial bloodstream infection rates.

CONTEXT: Central line-associated bloodstream infection (BSI) rates, determined by infection preventionists using the Centers for Disease Control and Prevention (CDC) surveillance definitions, are increasingly published to compare the quality of patient care delivered by hospitals. However, such comparisons are valid only if surveillance is performed consistently across institutions. OBJECTIVE: To assess institutional variation in performance of traditional central line-associated BSI surveillance. DESIGN, SETTING, AND PARTICIPANTS: We performed a retrospective cohort study of 20 intensive care units among 4 medical centers (2004-2007). Unit-specific central line-associated BSI rates were calculated for 12-month periods. Infection preventionists, blinded to study participation, performed routine prospective surveillance using CDC definitions. A computer algorithm reference standard was applied retrospectively using criteria that adapted the same CDC surveillance definitions. MAIN OUTCOME MEASURES: Correlation of central line-associated BSI rates as determined by infection preventionist vs the computer algorithm reference standard. Variation in performance was assessed by testing for institution-dependent heterogeneity in a linear regression model. RESULTS: Forty-one unit-periods among 20 intensive care units were analyzed, representing 241,518 patient-days and 165,963 central line-days. The median infection preventionist and computer algorithm central line-associated BSI rates were 3.3 (interquartile range [IQR], 2.0-4.5) and 9.0 (IQR, 6.3-11.3) infections per 1000 central line-days, respectively. Overall correlation between computer algorithm and infection preventionist rates was weak (ρ = 0.34), and when stratified by medical center, point estimates for institution-specific correlations ranged widely: medical center A: 0.83; 95% confidence interval (CI), 0.05 to 0.98; P = .04; medical center B: 0.76; 95% CI, 0.32 to 0.93; P = .003; medical center C: 0.50, 95% CI, -0.11 to 0.83; P = .10; and medical center D: 0.10; 95% CI -0.53 to 0.66; P = .77. Regression modeling demonstrated significant heterogeneity among medical centers in the relationship between computer algorithm and expected infection preventionist rates (P < .001). The medical center that had the lowest rate by traditional surveillance (2.4 infections per 1000 central line-days) had the highest rate by computer algorithm (12.6 infections per 1000 central line-days). CONCLUSIONS: Institutional variability of infection preventionist rates relative to a computer algorithm reference standard suggests that there is significant variation in the application of standard central line-associated BSI surveillance definitions across medical centers. Variation in central line-associated BSI surveillance practice may complicate interinstitutional comparisons of publicly reported central line-associated BSI rates.

Administrative coding data and health care-associated infections.

Surveillance for health care-associated infections (HAIs) using administrative data has received attention from health care epidemiologists searching for efficient means to track infections in their institutions. Several states are also considering electronic surveillance that incorporates administrative data as a means to satisfy an increasing demand for mandatory public reporting of HAIs. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes have attributes that make them suitable for detecting HAIs; for example, they may facilitate automated surveillance, freeing up infection control personnel to perform other important tasks, such as staff education and outbreak investigation. However, controversy surrounds the appropriate use of ICD-9-CM data in detecting HAIs, and administrative coding data have been criticized for lacking elements necessary for surveillance. Administrative coding data are inappropriate as the sole means of HAI surveillance but may have value to the health care epidemiologist as a way to augment traditional methods.

Prevalence, intensity and identity of bacteraemia following conservative dental procedures in children.

INTRODUCTION: The aim of this study was to investigate the prevalence, intensity and microbial identity of bacteraemia following conservative dental procedures. The procedures were placement of rubber dam, use of the fast drill, use of the slow drill and placement of a matrix band and wedge. METHOD: Two hundred and five children and adolescents undergoing general anaesthesia for dental treatment at the Eastman Dental Hospital were recruited. Each subject was randomly allocated to one of the procedure groups. A baseline blood sample was taken before any dental treatment was carried out. A second blood sample was taken 30 s after a single conservative procedure. The blood samples were processed using lysis filtration. All bacterial isolates were identified using comparative 16 S ribosomal RNA gene sequencing. Oral Streptococcus spp. and coagulase-negative Staphylococcus spp. were further identified by comparative sodA gene sequencing. RESULTS: The prevalence of bacteraemia was significantly greater following placement of rubber dam (P = 0.01) and placement of matrix band and wedge, compared with baseline. The intensity of bacteraemia was significantly greater following placement of rubber dam (P = 0.001) and placement of matrix band and wedge (P = 0.0001). The most frequently isolated bacteria were Streptococcus spp. (56%), Actinomyces spp. (15%) and coagulase-negative Staphylococcus spp. (15%). CONCLUSION: Conservative dental procedures are a significant cause of bacteraemia.

Classification of bloodstream infections in patients recently discharged from acute-care facilities: Hospital acquired or healthcare-associated community onset?

Laboratory-identified bloodstream infections (LAB-ID BSIs) in recently discharged patients are likely to be classified as healthcare-associated community-onset (HCA-CO) infections, even though they may represent hospital-onset (HO) infections. A review of LAB-ID BSIs among patients discharged within 14 days revealed that 109 of 756 cases (14.4%) were HO infections. The BSI risk being misclassified as HCA CO may underestimate the hospital infection risk.

Cluster analysis to define distinct clinical phenotypes among septic patients with bloodstream infections.

Prior attempts at identifying outcome determinants associated with bloodstream infection have employed a priori determined classification schemes based on readily identifiable microbiology, infection site, and patient characteristics. We hypothesized that even amongst this heterogeneous population, clinically relevant groupings can be described that transcend old a priori classifications.We applied cluster analysis to variables from three domains: patient characteristics, acuity of illness/clinical presentation and infection characteristics. We validated our clusters based on both content validity and predictive validity.Among 3715 patients with bloodstream infections from Barnes-Jewish Hospital (2008-2015), the most stable cluster arrangement occurred with the formation of 4 clusters. This clustering arrangement resulted in an approximately uniform distribution of the population: Cluster One "Surgical Outside Hospital Transfers" (21.5%), Cluster Two "Functional Immunocompromised Patients" (27.9%), Cluster Three "Women with Skin and Urinary Tract Infection" (28.7%) and Cluster Four "Acutely Sick Pneumonia" (21.8%). Staphylococcus aureus distributed primarily to Clusters Three (40%) and Four (25%), while nonfermenting Gram-negative bacteria grouped mainly in Clusters Two and Four (31% and 30%). More than half of the pneumonia cases occurred in Cluster Four. Clusters One and Two contained 33% and 31% respectively of the individuals receiving inappropriate antibiotic administration. Mortality was greatest for Cluster Four (33.8%, 27.4%, 19.2%, 44.6%; P < .001), while Cluster One patients were most likely to be discharged to a nursing home.Our results support the potential for machine learning methods to identify homogenous groupings in infectious diseases that transcend old a priori classifications. These methods may allow new clinical phenotypes to be identified potentially improving the severity staging and development of new treatments for complex infectious diseases.

Prevalence, intensity and nature of bacteraemia after toothbrushing.

OBJECTIVE: To estimate the prevalence, intensity and microbial identity of bacteraemia associated with toothbrushing. METHODS: A total of 141 children and adolescents, aged between 3 and 17 years, having dental treatment under general anaesthesia at the Eastman Dental Hospital were recruited. Six millilitre of blood was taken before toothbrushing (baseline) with (1) Oral B 30 toothbrush or (2) Braun or (3) Sonicare electric toothbrush or (4) dental handpiece and rubber cup. A second 6-ml sample was taken 30s after toothbrushing. All blood samples were processed using lysis filtration and bacteria were identified to species level. RESULTS: There was a significantly greater prevalence of bacteraemia following the dental handpiece only (p=0.02). There was a significantly greater aerobic and anaerobic intensity of bacteraemia following brushing with both the Sonicare (p=0.03 and p=0.05) and the dental handpiece (p=0.001 and p=0.005). CONCLUSIONS: Toothbrushing causes a bacteraemia that is often statistically significantly greater than baseline. Toothbrushing is an important contributory factor in cumulative dental bacteraemia.

Machine learning for fast identification of bacteraemia in SIRS patients treated on standard care wards: a cohort study.

Bacteraemia is a life-threating condition requiring immediate diagnostic and therapeutic actions. Blood culture (BC) analyses often result in a low true positive result rate, indicating its improper usage. A predictive model might assist clinicians in deciding for whom to conduct or to avoid BC analysis in patients having a relevant bacteraemia risk. Predictive models were established by using linear and non-linear machine learning methods. To obtain proper data, a unique data set was collected prior to model estimation in a prospective cohort study, screening 3,370 standard care patients with suspected bacteraemia. Data from 466 patients fulfilling two or more systemic inflammatory response syndrome criteria (bacteraemia rate: 28.8%) were finally used. A 29 parameter panel of clinical data, cytokine expression levels and standard laboratory markers was used for model training. Model tuning was performed in a ten-fold cross validation and tuned models were validated in a test set (80:20 random split). The random forest strategy presented the best result in the test set validation (ROC-AUC: 0.729, 95%CI: 0.679-0.779). However, procalcitonin (PCT), as the best individual variable, yielded a similar ROC-AUC (0.729, 95%CI: 0.679-0.779). Thus, machine learning methods failed to improve the moderate diagnostic accuracy of PCT.

Risk factors for late-onset health care-associated bloodstream infections in patients in neonatal intensive care units.

BACKGROUND: There are few data comparing risk factors for catheter-related (CR) versus non-CR bloodstream infection (BSI) or for BSI caused by gram-positive versus gram-negative organisms. The aims of this study were to compare risk factors for CR versus non-CR BSI and to compare risk factors for BSI associated with gram-negative versus gram-positive organisms among infants hospitalized in two neonatal intensive care units (NICUs). METHODS: Data were collected prospectively over a 2-year period to assess risk factors among 2,935 neonates from two NICUs. RESULTS: Among all neonates, in addition to low birth weight and presence of a central venous catheter, hospitalization in NICU 1 (relative risk [RR]: 1.60, 95% confidence intervals [CI]: 1.14, 2.24) was a significant predictor of BSI. In neonates with a central catheter total parenteral nutrition (TPN) was a significant risk factor for BSI (RR: 4.69, 95% CI: 2.22, 9.87). Ventilator use was a significant risk factor for CR versus non-CR BSI (RR: 3.74, 95% CI: 1.87, 7.48), and significantly more CR BSI were caused by gram-positive (77.1%) than by gram-negative organisms (61.4%), P = .03. CONCLUSIONS: This study confirmed that central venous catheters and low birth weight were risk factors for neonates with late-onset healthcare-associated BSI and further elucidated the potential risks associated with TPN and ventilator use in subgroups of neonates with BSI. Additional studies are needed to examine the incremental risk of TPN among infants with central venous catheters and to understand the link between CR BSI and ventilator use. Preventive strategies for BSI in neonates in NICUs should continue to focus on limiting the use of invasive devices.

Blood culture-PCR to optimise typhoid fever diagnosis after controlled human infection identifies frequent asymptomatic cases and evidence of primary bacteraemia.

BACKGROUND: Improved diagnostics for typhoid are needed; a typhoid controlled human infection model may accelerate their development and translation. Here, we evaluated a blood culture-PCR assay for detecting infection after controlled human infection with S. Typhi and compared test performance with optimally performed blood cultures. METHODOLOGY/PRINCIPAL FINDINGS: Culture-PCR amplification of blood samples was performed alongside daily blood culture in 41 participants undergoing typhoid challenge. Study endpoints for typhoid diagnosis (TD) were fever and/or bacteraemia. Overall, 24/41 (59%) participants reached TD, of whom 21/24 (86%) had ≥1 positive blood culture (53/674, 7.9% of all cultures) or 18/24 (75%) had ≥1 positive culture-PCR assay result (57/684, 8.3%). A further five non-bacteraemic participants produced culture-PCR amplicons indicating infection; overall sensitivity/specificity of the assay compared to the study endpoints were 70%/65%. We found no significant difference between blood culture and culture-PCR methods in ability to identify cases (12 mismatching pairs, p = 0.77, binomial test). Clinical and stool culture metadata demonstrated that additional culture-PCR amplification positive individuals likely represented true cases missed by blood culture, suggesting the overall attack rate may be 30/41 (73%) rather than 24/41 (59%). Several participants had positive culture-PCR results soon after ingesting challenge providing new evidence for occurrence of an early primary bacteraemia. CONCLUSIONS/SIGNIFICANCE: Overall the culture-PCR assay performed well, identifying extra typhoid cases compared with routine blood culture alone. Despite limitations to widespread field-use, the benefits of increased diagnostic yield, reduced blood volume and faster turn-around-time, suggest that this assay could enhance laboratory typhoid diagnostics in research applications and high-incidence settings.

The daily risk of bacteremia during hospitalization and associated 30-day mortality evaluated in relation to the traditional classification of bacteremia.

BACKGROUND: We investigated the overall and daily incidence of bacteremia among hospitalized patients and evaluated the traditional classification of bacteremia (community-onset vs nosocomial based on a 48-hour time window) by means of the daily incidence and associated 30-day mortality. METHODS: In a multicenter hospital-based cohort study, we included all patients aged 15 years or older admitted to hospitals in Funen County, Denmark, during 2000-2008, and identified all first bacteremias per admission. We calculated the overall incidence of bacteremia per 1,000 admissions and 10,000 bed-days, as well as the daily incidence of bacteremia per 10,000 bed-days and associated 30-day mortality. RESULTS: We included 724,339 admissions and 10,281 bacteremias for an overall incidence of 14.2 per 1,000 admissions and 23.6 per 10,000 bed-days. The daily incidence was highest on the first 2 days of admission followed by lower incidences that were constant beyond day 12, but varied according to patient and epidemiologic characteristics. Thirty-day mortality for patients with bacteremia was 18% on day 1, 21% on day 2, and between 25% and 35% thereafter. CONCLUSIONS: Hospitalized patients were at the highest risk of bacteremia during the first 2 days followed by lower incidences that were constant beyond day 12. Thirty-day mortality was 18%-21% for patients with bacteremia on the first 2 days and 25%-35% thereafter. Our findings support the traditional classification of bacteremia.

Healthcare-associated Staphylococcus aureus bacteremia and the risk for methicillin resistance: is the Centers for Disease Control and Prevention definition for community-acquired bacteremia still appropriate?

OBJECTIVE: To evaluate a new classification for bloodstream infections that differentiates hospital acquired, healthcare associated, and community acquired in patients with blood cultures positive for Staphylococcus aureus. DESIGN: Prospective, observational study. SETTING: Three tertiary-care, university-affiliated hospitals in Dublin, Ireland, and Strasbourg, France. PATIENTS: Two hundred thirty consecutive patients older than 18 years with blood cultures positive for S. aureus. METHODS: S. aureus bacteremia (SAB) was defined as hospital acquired if the first positive blood culture was performed more than 48 hours after admission. Other SABs were classified as healthcare associated or community acquired according to the definition proposed by Friedman et al. When available, strains of methicillin-resistant Staphylococcus aureus (MRSA) were analyzed by pulsed-field gel electrophoresis (PFGE). RESULTS: Eighty-two patients were considered as having community-acquired bacteremia according to the Centers for Disease Control and Prevention (CDC) classification. Of these 82 patients, 56% (46) had healthcare-associated SAB. MRSA prevalence was similar in patients with hospital-acquired and healthcare-associated SAB (41% vs 33%; P > .05), but significantly lower in the group with community-acquired SAB (11%; P < .03). PFGE of MRSA strains showed that most community-acquired and healthcare-associated MRSA strains were similar to hospital-acquired MRSA strains. On multivariate analysis, Friedman's classification was more effective than the CDC classification for predicting MRSA. CONCLUSION: These results support the call for a new classification for community-acquired bacteremia that would account for healthcare received outside the hospital by patients with SAB.

Bacteremia and septic shock after solid-organ transplantation.

BACKGROUND: Bacteremia and septic shock remain important causes of morbidity and mortality after solid-organ transplantation. The aim of this study was to assess the characteristics and risk factors for mortality among patients with bloodstream infections and shock. METHODS: From January 1991 to December 2000, all episodes of bloodstream infection were prospectively examined, considering bacteremia or fungemia as significant according to the CDC criteria. Septic shock was diagnosed in a patient with systemic inflammatory response syndrome and persistent dysfunction of at least one organ caused by hypoperfusion despite hemodynamic support. RESULTS: There were 466 episodes of bacteremia in 382 patients, with 66 of them developing septic shock. Risk factors for developing shock were age >50 (P = .006), liver transplant (P = .029), nosocomial infection (P = .034), pulmonary focus (P = .0001), P. aeruginosa infection (P = .001), and polymicrobial etiology (P = .039). On multivariate analysis, only age, nosocomial infection, and pulmonary source were significant. Among 66 shock patients, bacteremia was due to gram-negative bacteria in 53%, gram-positive bacteria in 24%, fungal in 7.5%, and polymicrobial in 12% of patients. The most frequent source was the lung (26%). Empiric antimicrobial therapy was correctly chosen in 79%; however, 36 patients died (54%), including 27 despite correct therapy. Urinary tract infections had less mortality than other foci. CONCLUSIONS: Risk factors for developing septic shock in bacteremia were age more than 50 years, nosocomial acquisition, and pulmonary focus. Despite adequate empiric antibiotic therapy, the mortality remained high.

Predictors of bacteremia and gram-negative bacteremia in patients with sepsis. The Veterans Affairs Systemic Sepsis Cooperative Study Group.

BACKGROUND: We analyzed data from the Department of Veterans Affairs trial of steroid therapy for systemic sepsis to identify predictors of bacteremia and gram-negative bacteremia. METHODS: Of the 2568 patients screened for entry in the trial, 465 met the following criteria: presence of four of seven clinical signs of sepsis; blood cultures at the time of screening; and complete data on nine clinical parameters. The multivariate logistic regression model was used to identify predictors of bacteremia and gram-negative bacteremia. Predicted probabilities of having these types of infections were calculated using the identified predictors. Patients were then classified into groups with and without bacteremia (and gram-negative bacteremia) based on the predicted probability. Misclassification error rates were calculated for each method of categorization by comparing the true with the predicted grouping of patients. RESULTS: Three factors were independently predictive of bacteremia and gram-negative bacteremia: elevated temperature, low systolic blood pressure, and low platelet count. Using these three factors, classification methods were identified that predicted blood infection better than chance, but misclassification was also high. For predicting bacteremia, the maximum predicted positive rate was 83%, with a specificity of nearly 100% and a sensitivity of only 5%. For predicting gram-negative bacteremia, the maximum predicted positive accuracy was 100%, with a specificity also of 100% and a sensitivity of almost 0%. CONCLUSIONS: Using simple clinical parameters, we could not predict either bacteremia or gram-negative bacteremia with sufficient accuracy to be clinically meaningful; however, our approach represents a step in the direction of forecasting the bacterial organism responsible for sepsis in advance of culture results.