Increasing the reliability of fully automated surveillance for central line–associated bloodstream infections

OBJECTIVETo increase reliability of the algorithm used in our fully automated electronic surveillance system by adding rules to better identify bloodstream infections secondary to other hospital-acquired infections.METHODSIntensive care unit (ICU) patients with positive blood cultures were reviewed. Central line–associated bloodstream infection (CLABSI) determinations were based on 2 sources: routine surveillance by infection preventionists, and fully automated surveillance. Discrepancies between the 2 sources were evaluated to determine root causes. Secondary infection sites were identified in most discrepant cases. New rules to identify secondary sites were added to the algorithm and applied to this ICU population and a non-ICU population. Sensitivity, specificity, predictive values, and kappa were calculated for the new models.RESULTSOf 643 positive ICU blood cultures reviewed, 68 (10.6%) were identified as central line–associated bloodstream infections by fully automated electronic surveillance, whereas 38 (5.9%) were confirmed by routine surveillance. New rules were tested to identify organisms as central line–associated bloodstream infections if they did not meet one, or a combination of, the following: (I) matching organisms (by genus and species) cultured from any other site; (II) any organisms cultured from sterile site; (III) any organisms cultured from skin/wound; (IV) any organisms cultured from respiratory tract. The best-fit model included new rules I and II when applied to positive blood cultures in an ICU population. However, they didn’t improve performance of the algorithm when applied to positive blood cultures in a non-ICU population.CONCLUSIONElectronic surveillance system algorithms may need adjustment for specific populations.Infect. Control Hosp. Epidemiol. 2015;36(12):1396–1400</jats:sec

Diurnal Variation of TEC and S 4 Index During the Period of Low Geomagnetic Activity at Ile-Ife, Nigeria

Ile-Ife lies on the equatorial anomaly region where the ionospheric current is greatly influenced by the existence of the equatorial electrojet. The dual frequency SCINDA NovAtel GSV 4004B GPS receiver recently installed at Ile-Ife [on geographical latitude 7°33′N and longitude 4°33′E and geomagnetic dipole (coordinate) of latitude 9.84°N and longitude 77.25°E] is currently operational and recording data from the available global positioning system satellites. The receiver provides the data on total electron content (TEC) and the scintillation index (S[subscript 4]). This paper presents the first sets of results from this station. Data records for the month of February 2010 were analyzed using the WinTec-P software program and these were interpreted to discuss the diurnal variation of the TEC and S[subscript 4] index during the period considered, as having low geomagnetic activity. The vertical TEC in this study showed that the values vary widely from as low as 0 TECu about sunrise to about 35 TECu during the day. Depletion in TEC was also noticed about sunset and marked by the occurrence of scintillations with a maximum index value of 0.3. Results of the IRI models and the observed TEC differ considerably; hence, there is the need to improve IRI models for its adaptability to the Africa ionospheric conditions

Preoperative Narcotic Use, Impaired Ambulation Status, and Increased Intraoperative Blood Loss Are Independent Risk Factors for Complications Following Posterior Cervical Laminectomy and Fusion Surgery.

ObjectiveThis retrospective cohort study seeks to identify risk factors associated with complications following posterior cervical laminectomy and fusion (PCLF) surgery.MethodsAdults undergoing PCLF from 2012 through 2018 at a single center were identified. Demographic and radiographic data, surgical characteristics, and complication rates were compared. Multivariate logistic regression models identified independent predictors of complications following surgery.ResultsA total of 196 patients met the inclusion criteria and were included in the study. The medical, surgical, and overall complication rates were 10.2%, 23.0%, and 29.1% respectively. Risk factors associated with medical complications in multivariate analysis included impaired ambulation status (odds ratio [OR], 2.27; p=0.02) and estimated blood loss over 500 mL (OR, 3.67; p=0.02). Multivariate analysis revealed preoperative narcotic use (OR, 2.43; p=0.02) and operative time (OR, 1.005; p=0.03) as risk factors for surgical complication, whereas antidepressant use was a protective factor (OR, 0.21; p=0.01). Overall complication was associated with preoperative narcotic use (OR, 1.97; p=0.04) and higher intraoperative blood loss (OR, 1.0007; p=0.03).ConclusionPreoperative narcotic use and estimated blood loss predicted the incidence of complications following PCLF for CSM. Ambulation status was a significant predictor of the development of a medical complication specifically. These results may help surgeons in counseling patients who may be at increased risk of complication following surgery

Fluid balance and cardiac function in septic shock as predictors of hospital mortality

INTRODUCTION: Septic shock is a major cause of morbidity and mortality throughout the world. Unfortunately, the optimal fluid management of septic shock is unknown and currently is empirical. METHODS: A retrospective analysis was performed at Barnes-Jewish Hospital (St. Louis, Missouri). Consecutive patients (n = 325) hospitalized with septic shock who had echocardiographic examinations performed within 24 hours of shock onset were enrolled. RESULTS: A total of 163 (50.2%) patients with septic shock died during hospitalization. Non-survivors had a significantly larger positive net fluid balance within the 24 hour window of septic shock onset (median (IQR): 4,374 ml (1,637 ml, 7,260 ml) vs. 2,959 ml (1,639.5 ml, 4,769.5 ml), P = 0.004). The greatest quartile of positive net fluid balance at 24 hours and eight days post-shock onset respectively were found to predict hospital mortality, and the greatest quartile of positive net fluid balance at eight days post-shock onset was an independent predictor of hospital mortality (adjusted odds ratio (AOR), 1.66; 95% CI, 1.39 to 1.98; P = 0.004). Survivors were significantly more likely to have mild left ventricular dysfunction as evaluated by bedside echocardiography and non-survivors had slightly elevated left ventricular ejection fraction, which was also found to be an independent predictor of outcome. CONCLUSIONS: Our data confirms the importance of fluid balance and cardiac function as outcome predictors in patients with septic shock. A clinical trial to determine the optimal administration of intravenous fluids to patients with septic shock is needed

Development and validation of a Clostridium difficile infection risk prediction model

OBJECTIVE: The purpose of this study was to develop and validate a risk prediction model that could identify patients at high risk for Clostridium difficile infection (CDI) before they develop disease. DESIGN: Retrospective cohort. SETTING: Tertiary care medical center. PATIENTS: Patients admitted to the hospital for ≥48 hours from 1-1-2003 through 12-31-2003. METHODS: Data were collected electronically from the hospital’s Medical Informatics database and analyzed with logistic regression to determine variables that best predicted patients’ risk for development of CDI. Model discrimination and calibration were calculated. The model was bootstrapped 500 times to validate the predictive accuracy. A receiver operating characteristic (ROC) curve was calculated to evaluate potential risk cut-offs. RESULTS: 35,350 admissions with 329 CDI cases were included. Variables in the risk prediction model were age, CDI pressure, admissions in previous 60 days, modified Acute Physiology Score, days on high risk antibiotics, low albumin, admission to an ICU, and receipt of laxatives, gastric acid suppressors, or antimotility drugs. The calibration and discrimination of the model were very good to excellent (C index=0.88; Brier score 0.009). CONCLUSIONS: The CDI risk prediction model performed well. Further study is needed to determine if it could be used in a clinical setting to prevent CDI-associated outcomes and reduce costs

Multicenter evaluation of computer automated versus traditional surveillance of hospital-acquired bloodstream infections

Objective.Central line–associated bloodstream infection (BSI) rates are a key quality metric for comparing hospital quality and safety. Traditional BSI surveillance may be limited by interrater variability. We assessed whether a computer-automated method of central line–associated BSI detection can improve the validity of surveillance.Design.Retrospective cohort study.Setting.Eight medical and surgical intensive care units (ICUs) in 4 academic medical centers.Methods.Traditional surveillance (by hospital staff) and computer algorithm surveillance were each compared against a retrospective audit review using a random sample of blood culture episodes during the period 2004–2007 from which an organism was recovered. Episode-level agreement with audit review was measured with κ statistics, and differences were assessed using the test of equal κ coefficients. Linear regression was used to assess the relationship between surveillance performance (κ) and surveillance-reported BSI rates (BSIs per 1,000 central line–days).Results.We evaluated 664 blood culture episodes. Agreement with audit review was significantly lower for traditional surveillance (κ [95% confidence interval (CI)] = 0.44 [0.37–0.51]) than computer algorithm surveillance (κ [95% CI] [0.52–0.64]; P = .001). Agreement between traditional surveillance and audit review was heterogeneous across ICUs (P = .001); furthermore, traditional surveillance performed worse among ICUs reporting lower (better) BSI rates (P = .001). In contrast, computer algorithm performance was consistent across ICUs and across the range of computer-reported central line–associated BSI rates.Conclusions.Compared with traditional surveillance of bloodstream infections, computer automated surveillance improves accuracy and reliability, making interfacility performance comparisons more valid.Infect Control Hosp Epidemiol 2014;35(12):1483–1490</jats:sec