Dataset Information

Culture-Negative and Culture-Positive Sepsis: A Comparison of Characteristics and Outcomes.

ABSTRACT: BACKGROUND:The primary objective of this study was to compare the characteristics of culture-positive and culture-negative status in septic patients. We also determined whether culture status is associated with mortality and whether unique variables are associated with mortality in culture-positive and culture-negative patients separately. METHODS:Utilizing patient records from intensive care units, emergency department, and general care wards in a large academic medical center, we identified adult patients with suspected infection and ?2 systemic inflammatory response syndrome criteria between January 1, 2007, and May 31, 2014. We compared the characteristics between culture-positive and culture-negative patients and used binary logistic regression to identify variables independently associated with culture status and mortality. We also did sensitivity analyses using patients with Sequential Organ Failure Assessment and quick Sequential Organ Failure Assessment criteria for sepsis. RESULTS:The study population included 9288 culture-negative patients (89%) and 1105 culture-positive patients (11%). Culture-negative patients received more antibiotics during the 48 hours preceding diagnosis but otherwise demonstrated similar characteristics as culture-positive patients. After adjusting for illness severity, a positive culture was not independently associated with mortality (odds ratio = 1.01 [95% CI, 0.81-1.26]; P = .945). The models predicting mortality separately in culture-negative and culture-positive patients demonstrated very good and excellent discrimination (C-statistic ± SD, 0.87 ± 0.01 and 0.92 ± 0.01), respectively. In the sensitivity analyses using patients with sepsis by Sequential Organ Failure Assessment and quick Sequential Organ Failure Assessment criteria, after adjustments for illness severity, positive cultures were still not associated with mortality (odds ratio = 1.13 [95% CI, 0.86-1.43]; P = .303; and odds ratio = 1.05 [95% CI, 0.83-1.33]; P = .665), respectively. In all models, physiological derangements were associated with mortality. CONCLUSIONS:While culture status is important for tailoring antibiotics, culture-negative and culture-positive patients with sepsis demonstrate similar characteristics and, after adjusting for severity of illness, similar mortality. The most important factor associated with negative cultures is receipt of antibiotics during the preceding 48 hours. The risk of death in patients suspected of having an infection is most associated with severity of illness. This is aligned with the Sepsis-3 definition using Sequential Organ Failure Assessment score to better identify those suspected of infection at highest risk of a poor outcome.

SUBMITTER: Sigakis MJG

PROVIDER: S-EPMC7577261 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Culture-Negative and Culture-Positive Sepsis: A Comparison of Characteristics and Outcomes.

Sigakis Matthew J G MJG Jewell Elizabeth E Maile Michael D MD Cinti Sandro K SK Bateman Brian T BT Engoren Milo M

Anesthesia and analgesia 20191101 5

<h4>Background</h4>The primary objective of this study was to compare the characteristics of culture-positive and culture-negative status in septic patients. We also determined whether culture status is associated with mortality and whether unique variables are associated with mortality in culture-positive and culture-negative patients separately.<h4>Methods</h4>Utilizing patient records from intensive care units, emergency department, and general care wards in a large academic medical center, w ...[more]

PMID: 30829670

Similar Datasets

Project description:BackgroundSepsis is a potentially life-threatening condition that occurs when the body's response to infection leads to widespread inflammation and tissue damage. Negative cultures can make it difficult for clinicians to make a diagnosis and may raise questions about the validity of the definition of sepsis. In addition, the clinical distinctions between burn patients with blood culture-positive and -negative sepsis are also poorly understood. Therefore, this study aimed to examine the clinical differences between blood culture-positive and -negative sepsis in burn patients in order to improve the understanding of the pathophysiology and epidemiology of sepsis in this population.MethodsThis study had a retrospective design, and the participants were adults aged ≥18 years. Patients diagnosed with sepsis were divided into two groups based on their blood culture results within 1 week of sepsis diagnosis.ResultsWe enrolled 1643 patients admitted to our institution's burn intensive care unit between January 2010 and December 2021. pH, platelet count, bicarbonate and haematocrit were significant in both the positive and negative groups. However, lymphocyte, red cell distribution width and blood urea nitrogen were significant only in the positive group, whereas lactate dehydrogenase was significant only in the negative group. Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumonia are common gram-negative bacterial species, and Staphylococcus aureus and Staphylococcus epidermidis are common gram-positive bacterial species seen in burn patients with positive blood cultures. Carbapenem resistance was found to be associated with an unfavourable prognosis in gram-negative bacteria, with the exception of P. aeruginosa.ConclusionspH, platelet count, bicarbonate and haematocrit were routine biomarkers that demonstrated statistical significance in both groups. Lactate dehydrogenase was significant in the blood-negative group, while red cell distribution width, blood urea nitrogen and lymphocyte count were significant in the positive group. Furthermore, the most common causes of sepsis are gram-negative bacteria, including A. baumannii, K. pneumoniae and P. aeruginosa. Additionally, resistance to carbapenems is associated with unfavourable outcomes.

Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. The study included seventy-two critically ill patients admitted to the intensive care unit (ICU) of Nepean Hospital, Sydney, Australia. Of these, fifty-five patients were diagnosed to have sepsis, as confirmed by microbiological culture. The remaining seventeen patients did not have sepsis and were therefore used as controls. The study was approved by the hospital ethics committee and informed consent was obtained from all patients or their relatives. Patient Samples. Whole blood was taken from each patient on admission to ICU. Neutrophils were separated from whole blood using density-gradient separation with Ficoll-PaqueP P(Amersham). Subsequent neutrophil RNA extraction was performed using guanidinium thiocyanate (Ambion). Microarray Experiment. The neutrophil RNA was converted to cDNA, fluorescently labeled and hybridized to its complimentary sequences on the microarray (Invitrogen). The fluorescent signals on each micrroarray were captured using the GenePix 4000B laser scanner (Axon Instruments). Expression level of each gene was represented by the intensity of its fluorescent signal. Data Extraction. All signal intensity values were processed using background-subtraction method. Prior to analysis, all values were log-transformed and normalized by fitting a print-tip group Lowess curve. Normalization minimizes bias due to dye chemistry, signal intensity or location of a gene on the array. It ensures the detection of genes that are truly differentially expressed, instead of those caused by experimental artifacts or variation in the hybridization process. After normalization, genes that had more than 50% of data missing were removed. We then selected genes that had at least 80% of the data showing two-fold changes from the geneâs median values. After filtering, 1617 genes were available for further analysis.

Project description:BACKGROUND:The optimal choice of antibiotics is challenging in culture-negative pyogenic spondylitis (PS). The empiric use of glycopeptides is suggested depending on various risk factors, although clinical data are sparse. This study aimed to analyze the clinical characteristics and outcomes of patients with culture-negative PS and evaluate the effect of empiric glycopeptide use on clinical outcomes in these patients. MATERIALS AND METHODS:Data on the characteristics, treatment, and outcomes of 175 patients diagnosed with PS were retrospectively obtained from the electronic database of a tertiary referral hospital from 2009 to 2016. Patients with negative culture results were grouped by the duration of glycopeptide treatment: glycopeptide therapy <28 days (Group A) and glycopeptide therapy ≥28 days (Group B). RESULTS:Of 89 patients with negative culture results, 78 were included in the analysis (Group A, n = 66; Group B, n = 12). The mean age of patients with negative culture results was 65.5 years, and 52.6% were male. The median follow-up duration was 573 (interquartile range [IQR], 83 - 1,037) days. The duration of intravenous glycopeptide therapy was 0.0 (IQR, 0.0 - 0.0) days and 55.5 (IQR, 37.0 - 75.7) days for Groups A and B, respectively. Patients who used glycopeptide longer empirically (Group B) had more commonly undergone a previous spinal procedure, including surgery (P = 0.024). The length of hospitalization, erythrocyte sedimentation rate, and C-reactive protein level were significantly higher in Group B compared with those in Group A (P <0.001, P <0.001, and P = 0.006, respectively). Regarding treatment modalities, patients in Group B underwent surgery more frequently (P = 0.017). The duration of parenteral antibiotic treatment was longer in Group B (P <0.001). Recurrence was noted in 7 patients (9.0%), and the recurrence rate was not significantly different between the 2 groups (Group A, 5/66 [7.6%]; Group B, 2/12 [16.7%]; P = 0.293). CONCLUSION:The recurrence rate among patients with culture-negative PS was not different based on the duration of empiric glycopeptide use. However, considering the small sample size and heterogeneity of our study population, we suggest that it is reasonable to administer glycopeptide antibiotics in these patients depending on clinical risk factors. Further large-scale prospective studies are needed to obtain more evidence for appropriate antibiotic treatment.

Dataset Information

Culture-Negative and Culture-Positive Sepsis: A Comparison of Characteristics and Outcomes.

Publications

Culture-Negative and Culture-Positive Sepsis: A Comparison of Characteristics and Outcomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets