Predicting bloodstream infection via systemic inflammatory response syndrome or biochemistry

A clinical decision rule to rule out bloodstream infection in the emergency department: retrospective multicentric observational cohort study

BACKGROUND

We aimed to identify patients at low risk of bloodstream infection (BSI) in the ED.

METHODS

We derived and validated a prediction model to rule out BSI in the ED without the need for laboratory testing by determining variables associated with a positive blood culture (BC) and assigned points according to regression coefficients. This retrospective study included adult patients suspected of having BSI (defined by at least one BC collection) from two European ED between 1 January 2017 and 31 December 2019. The primary end point was the BSI rate in the validation cohort for patients with a negative Bacteremia Rule Out Criteria (BAROC) score. The effect of adding laboratory variables to the model was evaluated as a second step in a two-step diagnostic strategy.

RESULTS

We analysed 2580 patients with a mean age of 64 years±21, of whom 46.1% were women. The derived BAROC score comprises 12 categorical clinical variables. In the validation cohort, it safely ruled out BSI without BCs in 9% (58/648) of patients with a sensitivity of 100% (95% CI 95% to 100%), a specificity of 10% (95% CI 8% to 13%) and a negative predictive value of 100% (95% CI 94% to 100%). Adding laboratory variables (creatinine ≥177 µmol/L (2.0 mg/dL), platelet count ≤150 000/mm3 and neutrophil count ≥12 000/mm3) to the model, ruled out BSI in 10.2% (58/570) of remaining patients who had been positive on the BAROC score. The BAROC score with laboratory results had a sensitivity of 100% (95% CI 94% to 100%), specificity of 11% (95% CI 9% to 14%) and negative predictive value of 100% (95% CI 94 to 100%). In the validation cohort, there was no evidence of a difference in discrimination between the area under the receiver operating characteristic for BAROC score with versus without laboratory testing (p=0.6).

CONCLUSION

The BAROC score safely identified patients at low risk of BSI and may reduce BC collection in the ED without the need for laboratory testing.

Association of Systemic Inflammatory Response Syndrome with Bacteremia in Patients with Sepsis

The aim of this study was to evaluate the usability of systemic inflammatory response syndrome (SIRS) and commonly used biochemical parameters as predictors for positive blood culture in patients with sepsis. The study included 313 patients aged ≥18 years with severe sepsis and septic shock consecutively admitted in the Intensive Care Unit (ICU) of the University Clinic for Infectious Diseases in Skopje, Republic of North Macedonia. The study took place from January 1, 2011 to December 31, 2017. We recorded demographic variables, common laboratory tests, SIRS parameters, site of infection, comorbidities and Sequential Organ Failure Assessment (SOFA) score. Blood cultures were positive in 65 (20.8%) patients with sepsis. Gram-positive bacteria were isolated from 35 (53.8%) patients. From the evaluated variables in this study, only the presence of four SIRS parameters was associated with bacteremia, finding that will help to predict bacteremia and initiate early appropriate therapy in septic patients.

Systemic inflammatory response syndrome is more associated with bacteremia in elderly patients with suspected sepsis in emergency departments

Early diagnosis of bacteremia for patients with suspected sepsis is 1 way to improve prognosis of sepsis. Systemic inflammatory response syndrome (SIRS) has long been utilized as a screening tool to detect bacteremia by front-line healthcare providers. The value of SIRS to predict bacteremia in elderly patients (≥65 years) with suspected sepsis has not yet been examined in emergency departments (EDs).We aimed to evaluate the performance of SIRS components in predicting bacteremia among elderly patients in EDs.We retrospectively evaluated patients with suspected sepsis and 2 sets of blood culture collected within 4 hours after admitting to ED in a tertiary teaching hospital between 2010 and 2012. Patients were categorized into 3-year age groups: young (18-64 years), young-old (65-74 years), and old patients (≥75 years). Vital signs and Glasgow Coma Scale with verbal response obtained at the triage, comorbidities, sites of infection, blood cultures, and laboratory results were retrieved via the electronic medical records.A total of 20,192 patients were included in our study. Among them, 9862 (48.9%) were the elderly patients (young-old and old patients), 2656 (13.2%) developed bacteremia. Among patients with bacteremia, we found the elderly patients had higher SIRS performance (adjusted odds ratio [aOR]: 2.40, 95% confidence interval [CI]: 1.90-3.03 in the young-old and aOR: 2.66, 95% CI: 2.19-3.23 in the old). Fever at the triage was most predictive of bacteremia, especially in the elderly patients (aOR: 2.19, 95% CI: 1.81-2.65 in the young-old and aOR: 2.27, 95% CI: 1.95-2.63 in the old), and tachypnea was not predictive of bacteremia among the elderly patients (all P > 0.2).The performance of SIRS to predict bacteremia was more suitable for elderly patients in EDs observed in this study. The elderly patients presented with more fever and less tachypnea when they had bacteremia.

How do bacteraemic patients present to the emergency department and what is the diagnostic validity of the clinical parameters; temperature, C-reactive protein and systemic inflammatory response syndrome?

Objective

Although blood cultures are often ordered based on the presence of fever, it is a clinical challenge to identify patients eligible for blood cultures. Our aim was to evaluate the diagnostic value of temperature, C-reactive-protein (CRP), and Systemic Inflammatory Response Syndrome (SIRS) to identify bacteraemic patients in the Medical Emergency Department (MED).

Methods

A population-based cohort study including all adult patients at the MED at Odense University Hospital between August 1st 2009 - August 31st 2011.

Results

11,988 patients were admitted to the MED within the study period. Blood cultures were performed on 5,499 (45.9%) patients within 2 days of arrival, of which 418 (7.6%) patients were diagnosed with bacteraemia. This corresponded to 3.5% of all patients. 34.1% of the bacteraemic patients had a normal rectal temperature (36.0°–38.0°C) recorded at arrival, 32.6% had a CRP < 100 mg/L and 28.0% did not fulfil the SIRS criteria.

For a temperature cut-point of >38.0°C sensitivity was 0.64 (95% CI 0.59–0.69) and specificity was 0.81 (0.80–0.82) to identify bacteraemic patients.

Conclusion

One third of the acute medical bacteraemic patients had a normal temperature at arrival to the MED. A normal temperature combined with a CRP < 100 mg/L and no SIRS criteria, ruled out bacteraemia.

Dynamics of hospitalizations in hemodialysis patients: results from a large US provider

BACKGROUND AND OBJECTIVES

In chronic hemodialysis (HD), patients' hospitalizations result in significant costs and affect the quality of life. We aimed at understanding hospitalization rates before death and to identify patterns in clinical and laboratory parameters that precede the first hospitalization.

DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS

We conducted two separate analyses in patients treated in the 51 US Renal Research Institute HD facilities. The first analysis involved hospitalizations before death in all HD patients who died between 1 January 2007 and 31 December 2011. In the second analysis, we studied the evolution of laboratory and treatment parameters before hospitalization in all patients with, at least, one hospital admission between 1 January 2007 and 31 December 2011. Patients were followed from up to 6 months prior to their first hospital admission. For comparison, we selected non-hospitalized patients and observed the evolution of their laboratory and treatment parameters.

RESULTS

We studied 6262 patients in total. The first analysis encompassed 2058 deaths. In these patients, hospitalization increased from 0.32 admissions per patient-month 4 months before death to 1.85 in the month of death. In the second analysis, we studied the first hospitalizations in 4204 patients. Irrespective of the cause of hospitalization, all hospitalizations were preceded by an increase in the neutrophil-to-lymphocyte ratio, a decline in hemoglobin and a reduction in effective treatment time and inter-dialytic weight gain. We noted no comparable trends in non-hospitalized patients.

CONCLUSIONS

Hospitalization rates increase sharply before death. Months before the first hospitalization changes in clinical and laboratory parameters ensued. These results suggest that models aiming at predicting hospitalization should include indicators capturing the dynamics of relevant parameters.