Bloodstream Infections In Febrile Patients Research Articles

Diagnostic efficacy of serum cytokines and chemokines in fungal bloodstream infection in febrile patients.

BackgroundThe role of serum cytokines/chemokines in early diagnosis of fungal infections has not been clearly clarified yet. This study aims to measure the serum levels of cytokines/chemokines in cases of fungemia and to compare them with culture‐negative controls.MethodsIn total, fourteen types of serum cytokines and chemokines from 41 patients with fungemia were compared with 57 patients with negative blood culture results. The cytokine and chemokine levels were detected with multiplex platform. We then performed statistical analysis as a two‐tailed P < .05. ROC analysis was performed, and an area under the curve (AUC), and sensitivity and specificity values were calculated to determine the efficacy of various cytokines and chemokines for fungemia. Binary logistic regression was performed to further explore the combination mode of cytokines and chemokines, which could increase the diagnostic efficiency.ResultsC‐reactive protein and procalcitonin were significantly higher compared with those in negative control group, while white blood cell, percentage of neutrophil, percentage of lymphocyte, and ratio of neutrophil and lymphocyte did not differentiate between two groups. Serum levels of IFN‐γ, TNF‐α, MIP‐1β, IL‐6, IL‐8, IL‐10, IL‐12p70, and IL‐17 were significantly higher in patients with fungemia compared with the control group. Combination of MIP‐1β and IL‐17 could improve the AUC, sensitivity, and specificity for the diagnosis of fungemia.ConclusionOur study demonstrates that serum cytokines and chemokines including IFN‐γ, TNF‐α, MIP‐1β, IL‐6, IL‐8, IL‐10, IL‐12p70, and IL‐17 could be considered as diagnostic markers for fungemia. Combination of these biomarkers might improve the diagnostic efficiency of fungemia.

The Burden of Invasive Bacterial Infections in Pemba, Zanzibar

BackgroundWe conducted a surveillance study to determine the leading causes of bloodstream infection in febrile patients seeking treatment at three district hospitals in Pemba Island, Zanzibar, Tanzania, an area with low malaria transmission.MethodsAll patients above two months of age presenting to hospital with fever were screened, and blood was collected for microbiologic culture and malaria testing. Bacterial sepsis and malaria crude incidence rates were calculated for a one-year period and were adjusted for study participation and diagnostic sensitivity of blood culture.ResultsBlood culture was performed on 2,209 patients. Among them, 166 (8%) samples yielded bacterial growth; 87 (4%) were considered as likely contaminants; and 79 (4%) as pathogenic bacteria. The most frequent pathogenic bacteria isolated were Salmonella Typhi (n = 46; 58%), followed by Streptococcus pneumoniae (n = 12; 15%). The crude bacteremia rate was 6/100,000 but when adjusted for potentially missed cases the rate may be as high as 163/100,000. Crude and adjusted rates for S. Typhi infections and malaria were 4 and 110/100,000 and 4 and 47/100,000, respectively. Twenty three (51%), 22 (49%) and 22 (49%) of the S.Typhi isolates were found to be resistant toward ampicillin, chloramphenicol and cotrimoxazole, respectively. Multidrug resistance (MDR) against the three antimicrobials was detected in 42% of the isolates.ConclusionsIn the presence of very low malaria incidence we found high rates of S. Typhi and S. pneumoniae infections on Pemba Island, Zanzibar. Preventive measures such as vaccination could reduce the febrile disease burden.

The role of procalcitonin in a decision tree for prediction of bloodstream infection in febrile patients

Bloodstream infection (BSI) in febrile patients is associated with high mortality. Clinical and laboratory variables, such as procalcitonin (PCT), may predict BSI and help decision-making concerning empirical treatment. This study compared two models for prediction of BSI, and evaluated the role of PCT vs. clinical variables, collected daily in 300 consecutive febrile inpatients, for 48 h after onset of fever. Multiple logistic regression (MLR) and classification and regression tree (CART) models were compared for discriminatory power and diagnostic performance. BSI was present in 17% of cases. MLR identified the presence of intravascular devices, nadir albumin and thrombocyte counts, and peak temperature, respiratory rate and leukocyte counts, but not PCT, as independent predictors of BSI. In contrast, a peak PCT level of >2.45 ng/mL was the principal discriminator in the decision tree based on CART. The latter was more accurate (94%) than the model based on MLR (72%; p <0.01). Hence, the presence of BSI in febrile patients is predicted more accurately and by different variables, e.g., PCT, in CART analysis, as compared with MLR models. This underlines the value of PCT plus CART analysis in the diagnosis of a febrile patient.