Association of uric acid with length of stay and mortality in pediatric hospitalized population.

PURPOSE: Elevated uric acid (UA) levels have been associated with acute and chronic diseases, which could affect the prognosis of pediatric hospitalized patients. However, the association of UA levels with length of hospital stay (LOS) and mortality in hospitalized children and adolescents remains unknown. Therefore, the aim of this study was to evaluate the association of serum UA levels with in-hospital mortality and prolonged LOS in hospitalized children and adolescents. METHODS: A retrospective cohort study was conducted, involving 128 patients under 18 years of age, admitted to a tertiary-care hospital between January 2014 and December 2018. UA levels were assessed with an average of 3 days before the in-hospital outcome (discharge or death). Logistic regression was used to determine the association of UA with prolonged LOS (defined as over 30 days of hospitalization), while Cox regression multivariate analysis was employed to assess UA as a predictor of in-hospital mortality. RESULTS: UA levels showed an inverse association with prolonged LOS. Specifically, for every 1 mg/dL increase in UA level, the odds of experiencing prolonged LOS decreased by 31% (OR = 0.69; 95% CI: 0.50-0.95). Additionally, individuals with elevated UA levels had lower odds of prolonged LOS (OR = 0.23; 95% CI: 0.08-0.66). However, UA levels were not associated with in-hospital mortality (HR = 1.63; 95% CI: 0.94-2.82). CONCLUSION: Serum UA was inversely associated with LOS among children and adolescents, but no association was observed with in-hospital mortality.

Validation of the HOSPITAL score as predictor of 30-day potentially avoidable readmissions in pediatric hospitalized population: retrospective cohort study.

Potentially avoidable pediatric readmissions are a burden to patients and their families. Identifying patients with higher risk of readmission could help minimize hospital costs and facilitate the targeting of care interventions. HOSPITAL score is a tool developed and widely used to predict adult patient's readmissions; however its predictive capacity for pediatric readmissions has not yet been evaluated. The aim of the study was to validate the HOSPITAL score application to predict 30-day potentially avoidable readmissions in a pediatric hospitalized population. This is a retrospective cohort study with patients under 18 years old admitted to a tertiary university hospital (n = 6,344). The HOSPITAL score was estimated for each admission. Subsequently, we classified the patients as low (0-4), intermediate (5-6), and high (7-12) risk groups. In order to estimate the discrimination power, the sensitivity, specificity, and accuracy were determined by the receiver operating characteristics (ROC) and the calibration by the Hosmer-Lemeshow goodness-of-fit. The 30-day hospital readmission was 11.70% (745). The accuracy was 0.80 (CI 95%, 0.77, 0.83), with a sensitivity of 70.96% and specificity of 78.29%, and a good calibration (p = 0.34).    Conclusion: HOSPITAL score showed a good discrimination and can be used to predict 30-day potentially avoidable readmission in a large pediatric population with different medical diagnoses. Our study validates and expands the usefulness of the HOSPITAL score as a tool to predict avoidable hospital readmissions for pediatric population. What is Known: •   Pediatric readmissions burden patients, the family network, and the health system. In addition, it influences negatively child development. •   The HOSPITAL score is one of the tools developed and widely used to identify patients at high risk of hospital readmission, but its predictive capacity for pediatric readmissions has not been yet assessed. What is New: • The HOSPITAL score showed good ability to identify a risk of 30-day potentially avoidable readmission in a pediatric population in different clinical contexts and diagnoses. • Our study expands the usefulness of the HOSPITAL score as a tool for predicting hospital readmissions for children and adolescents.

Combination of red blood cell distribution width and body mass index (COR-BMI) predicts in-hospital mortality in patients with different diagnoses?

BACKGROUND: The combination of red blood cell distribution width and body mass index (COR-BMI) is indicated as a new prognostic index of survival in patients with laryngeal cancer. However, the ability of this prediction in other types of cancer or whether its use can be expanded to non-oncological patients is unknown. The aim of this study was to investigate the prediction of prognosis of in-hospital mortality of the COR-BMI in oncological and non-oncological patients. METHODS: A retrospective study was performed with all hospitalized patients between 2014 and 2016, totaling 2930 patients, 262 oncological and 2668 non-oncological. The COR-BMI was divided into three classes: 0, RDW ≤ 13.1% and BMI ≥ 25 kg/m2; 1, RDW ≤ 13.1% and BMI < 18.5 or ≥ 18.5 but < 25 kg/m2 and RDW > 13.1% and BMI ≥ 18.5 but < 25 or BMI ≥ 25 kg/m2; and 2, RDW > 13.1% and BMI < 18.5 kg/m2. In order to analyze the relationship between COR-BMI and in-hospital mortality in the studied population, the Cox Proportional Hazards Model was used in a multivariate analysis based on a conceptual model. RESULTS: The COR-BMI was an independent predictor of in-hospital mortality in non-oncological patients (1 versus 0: HR = 3.34; CI = 1.60-6.96, p = 0.001; 2 versus 0: HR = 3.38; CI = 1.22-9.39, p = 0.019). The survival rate of these patients was lower among those with the highest scores on the COR-BMI. This prediction was not found in oncological patients. CONCLUSION: The present study suggests that the COR-BMI may have its practical use expanded to non-oncological patients as an independent predictor of in-hospital mortality.