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      Development and validation of a bedside prediction score for nosocomial sepsis in the pediatric ICU: a prospective observational cohort study

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      1 , , 1 , 1
      Critical Care
      BioMed Central
      Sepsis 2012
      14-16 November 2012

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          Abstract

          Background Diagnosis of nosocomial sepsis (NS) is a challenge in every pediatric ICU [1,2]. There are very few studies on NS prediction in children, and those existing [3-8] have studied risk factors with emphasis on admission variables. In contrast, our study attempts to simplify the decision-making process using a dynamic scoring system based on objective criteria. Methods This was a prospective study where 428 consecutive admissions, aged 1 month to 12 years, between January and October 2011 with PICU stay >48 hours, were enrolled and followed-up during their ICU stay and 72 hours thereafter. Occurrence of culture-positive nosocomial infections and relevant details were recorded. Patients with and without nosocomial sepsis were compared by chi-square test or Fisher's exact test for categorical and unpaired t test or Kruskal-Wallis for continuous variables. Significant predictors of NS (P < 0.05 on univariate analysis) were included in the binary backward stepwise logistic regression. The resultant derivation model's discrimination and calibration were assessed using the receiver operator characteristic (ROC) curve and Hosmer-Lemeshow test, respectively. The final model was transformed into a score, based on the regression coefficients. For internal validation, bootstrapping and shrinkage coefficients were used. Results Of the 428 enrolled, 17 were excluded (malignancies (14 cases), burns (one case), polytrauma (one case) and missing data (one case)). A total of 151 episodes (23.1%; 95 out of 411 children) of culture-positive NS were seen giving an incidence rate of 4.5 per 100 patient-days. Age, PRISM III score, device utilization, albumin, immunomodulator and prior antibiotic use, and intubation were significant independent predictors on multivariate analysis (Table 1). This model had an AUC-ROC of 0.87 (Figure 1). Also, the Hosmer-Lemeshow chi-square was 5.06 (P = 0.75) indicating good fit of the model. Based on the regression coefficients, a pediatric nosocomial sepsis prediction score (Pe-NoSeP) was developed. Probability cutoffs versus sensitivity and specificity plotting showed a cutoff of 0.38 corresponding to a score of 15. The sensitivity, specificity, positive predictive value, negative predictive value and positive likelihood ratio at this cutoff were 79.1%, 79.1%, 61.6%, 89.9% and 3.76, respectively. The accuracy of the model was 79.3% and reduced classification errors from 29.8% to 20.7%. All seven predictors retained their statistical significance after bootstrapping, confirming the validity of the score. Table 1 Multivariate logistic regression analysis: independent predictors and the Pediatric Nosocomial Sepsis Prediction Score (Pe-NoSeP) Serial no. Variable B Coeff. Odds ratio (OR) OR 95% CI P value Category Score 1 PRISM III score 0.06 1.06 1.02 to 1.10 0.003 5 to 15 0 16 to 26 2 27 to 37 4 38 to 48 7 49 to 59 9 2 Indwelling catheter use 1.67 5.31 2.31 to 12.23 < 0.001 No 0 Yes 6 3 Albumin transfusion 1.35 3.87 1.58 to 9.50 0.003 No 0 Yes 5 4 Age (≤5 years/>5 years) 0.90 2.45 1.22 to 4.93 0.010 >5 years 0 ≤5 years 3 5 Immunomodulator use 1.30 3.66 1.23 to 10.94 0.020 No 0 Yes 5 6 Intubation 1.70 5.48 2.53 to 11.88 < 0.001 No 0 Yes 6 7 Prior antibiotic use (<4/≥4) 0.58 1.79 1.03 to 3.11 0.040 <4 0 ≥4 2 Figure 1 Receiver operator characteristic (ROC) curve for the prediction model. Conclusion The Pe-NoSeP score is a simple, easy-to-use bedside prediction model, which estimates the probability of NS in a child on a particular day and assists clinical decision-making. This tool may have diagnostic, therapeutic and preventive utilities based on its application.

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          Risk factors for nosocomial infection in critically ill children: a prospective cohort study.

          To identify factors in pediatric intensive care unit (ICU) patients that are associated with an increased risk of nosocomial infections. A prospective, 1-yr cohort study. A 16-bed pediatric ICU in a multidisciplinary, regional referral center. All patients admitted to the pediatric ICU. None. The primary outcome variable was the development of nosocomial infection. Out of 945 consecutive admissions, 75 patients developed 96 nosocomial infections. The most frequent infection sites were the lower respiratory tract (35%), the bloodstream (21%), and the urinary tract (21%). The most common organisms isolated were Gram-negative bacteria (53%, Gram-positive bacteria (27%), and fungi (9%). Variables significantly associated with the development of nosocomial infections included age, weight, Pediatric Risk of Mortality (PRISM) score, device utilization ratio, antimicrobial therapy, histamine-2 (H2) receptor blocker use, immune status, parenteral nutrition, and length of stay. When combined in a multivariate logistic regression model, the significant variables were operative status, PRISM score, device utilization ratio, antimicrobial therapy, parenteral nutrition, and length of stay before the onset of infection. The area under the receiver operating characteristic curve was 0.868. At a probability of 0.15, the sensitivity was 66.67%, and the specificity was 87.82%. Patients at risk for developing nosocomial infection can be identified using a multivariate logistic regression model with a high degree of sensitivity and specificity. These data indicate that institutional nosocomial rates need to be adjusted for risk factors. This model could help target patients at high risk for developing nosocomial infections for preventive strategies.
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            Infection Probability Score (IPS): A method to help assess the probability of infection in critically ill patients.

            To develop a simple score to help assess the presence or absence of infection in critically ill patients using routinely available variables. Observational study of a prospective cohort of patients divided into a developmental set (n = 353) and a validation set (n = 140). Department of intensive care at an academic tertiary care center. Four hundred and ninety-three adult patients admitted to the intensive care unit for > or =24 hrs. None. The presence of infection was defined using the Centers for Disease Control definitions. Body temperature, heart rate, respiratory rate, white blood cell count, and C-reactive protein concentrations were measured, and the Sequential Organ Failure Assessment score was calculated throughout the intensive care unit stay. Infection was documented in 92 of the 353 patients (26%) in the developmental set and in 41 of the 140 patients (29%) in the validation set. Univariate logistic regression was used to select significant predictors for infection. Each continuous predictor was transformed in a categorical variable using a robust locally weighted least square regression between infection and the continuous variable of interest. When more than two categories were created, the variable was separated into iso-weighted dummy variables. A multiple logistic regression model predicting infection was calculated with all the variables coded 1 or 0 allowing for relative scoring of the different predictors. The resulting Infection Probability Score consisted of six different variables and ranged from 0 to 26 points (0-2 for temperature, 0-12 for heart rate, 0-1 for respiratory rate, 0-3 for white blood cell count, 0-6 for C-reactive protein, 0-2 for Sequential Organ Failure Assessment score). The best predictors for infection were heart rate and C-reactive protein, whereas respiratory rate was found to have the poorest predictive value. The cutoff value for the Infection Probability Score was 14 points, with a positive predictive value of 53.6% and a negative predictive value of 89.5%. Model performance was very good (Hosmer-Lemeshow statistic, p =.918), and the areas under receiver operating characteristic curves were 0.820 for the developmental set and 0.873 for the validation set. The Infection Probability Score is a simple score that can help assess the probability of infection in critically ill patients. The variables used are simple, routinely available, and familiar to clinicians. Patients with a score <14 points have only a 10% risk of infection.
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              Physicians' ability to diagnose sepsis in newborns and critically ill children.

              To elucidate physicians' ability to correctly diagnose infection in critically ill children in three different situations: 1) post hoc adjudication (e.g., ward rounds, outcome determination in surveillance studies or controlled trials), 2) when decisions must be made (e.g., sepsis workup in suspected infection), c) and applying suggested adult consensus conference definitions in children. Appraisal of two previously published studies and a data simulation model. Data of the reviewed studies were obtained from a multidisciplinary neonatal and a pediatric intensive care unit in tertiary hospitals. None. In the first study reviewed, the post hoc adjudication of 167 consecutive cases of suspected infection was carried out by a fifth-year medical student and three senior consultants. The agreement of the three experts beyond chance in the 119 episodes not classifiable unanimously by a priori defined criteria into proven sepsis or no infection was poor. In the second study reviewed, the physicians provided daily predictions of the likelihood of infection (pretest probability) in premature infants and critically ill children (2567 hospitalization days). Estimated pretest probabilities provided at the time of sepsis workup showed a remarkable predictive accuracy (area under the receiver operating characteristic curve, 0.85). In the simulation model, in which catheter-related sepsis was assumed, correct classification of patients from a central and a peripheral culture decreased to 56% when a sensitivity of 70%-80% was assumed for blood cultures and amounted to 15% only when a sensitivity of 30%-50% was imputed. Misclassification is a serious threat in post hoc adjudication of episodes or when consensus definitions rely on the application of criteria with imperfect sensitivity (e.g., the positivity of blood cultures in premature infants or children). This underscores the need to use probability-based categorizations such as probable and possible infection.
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                Author and article information

                Conference
                Crit Care
                Crit Care
                Critical Care
                BioMed Central
                1364-8535
                1466-609X
                2012
                14 November 2012
                : 16
                : Suppl 3
                : P23
                Affiliations
                [1 ]PGIMER, Chandigarh, India
                Article
                cc11710
                10.1186/cc11710
                3504824
                4ffac89e-9858-4b79-bd23-21fbca6aedc7
                Copyright ©2012 Saptharishi et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Sepsis 2012
                Paris, France
                14-16 November 2012
                History
                Categories
                Poster Presentation

                Emergency medicine & Trauma
                Emergency medicine & Trauma

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