Abstract

Objectives: Validation of SICK score for its ability to predict out come. Validation based on predominant system involved. Methods: Prospective study done at tertiary care centre in puducherry. Inclusion criteria: All children admitted in PICU between 1 month & 12 year in 6 month period. Exclusion criteria: Patients with surgical illness, congenital anomalies, non availability of consent. Physical variables of Temperature, Heart Rate, Respiratory Rate, Blood pressure, Capiallary Refill time, Oxygen saturation & sensoriurn (using AVPU scale) were recorded at the time of admission. SICK score was calculated and outcome was recorded as survived or expired. Association of patients outcome with total score was done using logistic regression analysis. The receiver operating characteristic (ROC) curve analysis was performed to decide the optimum cut off point in terms of total score that provides maximum sensitivity & specificity. Area under ROC curve (AUC) was used to compare the predictive power of total score. All analysis was carried out using SPPS software version 13.0. Results: Total of 354 Children were analyzed. For SICK score of <1 mortality was 0%, which gradually increased to 100% with a score of 7 or more. The area under the ROC curve was 93% (95%: CI: 89.8% - 97.3%) indicating good predictive ability of the score. Conclusion: SICK score has good predictive ability and uses only physical criteria. Further SICK score is not influenced by predominant system involved.

Highlights

  • Mortality in an intensive care unit depends on severity of illness and quality of care [1]

  • Many of the scoring systems depend on Manuscript received: 10th March 2017 Reviewed: 17th March 2017 Author Corrected: 24th March 2017 Accepted for Publication: 31st March 2017 both physical and laboratory variable, take 24 hrs or more for predicting outcome

  • The receiver operating characteristic (ROC) curve developed using different cut off points had 93% of area under curve, indicating good predictive ability of the score(figure 1)

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Summary

Introduction

Mortality in an intensive care unit depends on severity of illness and quality of care [1]. Severity of illness scores in pediatrics like the PRISM Score (Pediatric Risk of Mortality Score) and PIM (Pediatric Index of Mortality Score) serve the purposes of comparative audit (comparing actual with expected outcomes over different units), and research (adjusting for differences in the case mix) These scoring systems could be used as a tool to triage, prioritize care and obviate harmful delay in the management of sick children [2]. Many of the scoring systems depend on Manuscript received: 10th March 2017 Reviewed: 17th March 2017 Author Corrected: 24th March 2017 Accepted for Publication: 31st March 2017 both physical and laboratory variable, take 24 hrs or more for predicting outcome They are inappropriate for primary triage and are cost and labor intensive [1,4]. This window of opportunity of treating the child aggressively is lost by the time PRISM and PIM scores are available [5]

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