Use of Metagenomic Next-Generation Sequencing in the Identification of Pneumocystis Jiroveci Pneumonia in a Previously Healthy Infant Diagnosed With X-Linked Hyper-IgM Syndrome.

This case describes a four-month-old male who was admitted to the pediatric intensive care unit for acute respiratory failure in the setting of a co-infection requiring increased ventilatory support. Immunodeficiency workup demonstrated poor vaccination response and low immunoglobulin titers. mNGS via Karius® test was positive for Pneumocystis jiroveci (PJP), Parvovirus, and Bocavirus. The patient was successfully treated with trimethoprim-sulfamethoxazole and prednisone. Genetic workup via Invitae panel confirmed that the patient had X-linked Hyper-IgM Syndrome. Use of mNGS can help with early identification of pathogens that conventional testing does not detect, even in patients not already identified as immunocompromised.

Use of the BIG score to predict mortality in pediatric trauma.

OBJECTIVE: The BIG score, which is comprised of admission base deficit (B), International Normalized Ratio (I), and GCS (G), is a severity of illness score that can be used to rapidly predict in-hospital mortality in pediatric patients presenting following traumatic injury. We sought to compare the mortality prediction of the pediatric trauma BIG score with other well-established pediatric trauma severity of illness scores: the pediatric logistic organ dysfunction (PELOD); the pediatric index of mortality 2 (PIM2); and the pediatric risk of mortality (PRISM III). METHODS: In this retrospective cohort study, data from 2009 to 2015 was collected using a multi-institutional database. All pediatric patients admitted following traumatic injury with a recorded initial GCS were included. BIG, PELOD, PIM2, and PRISM III scores were calculated, and Receiver Operator Characteristic curves were derived for all severity of illness scores. Mortality prediction performance for each score was compared by the area under the curve (AUC). RESULTS: A total of 29,204 patients were included in this analysis. AUC for BIG, PELOD, PIM2, and PRISM III scores were 0.97 (0.97-0.98), 0.98 (0.98-0.98), 0.98 (0.97-0.98), and 0.99 (0.98-0.99), respectively. At the optimum cut-off point of 16, the BIG score had a sensitivity of 0.937, specificity of 0.938, positive predictive value of 0.514, and negative predictive value of 0.995. CONCLUSIONS: In this massive cohort of pediatric trauma patients, the BIG score using imputation of missing variables performed similarly to the PELOD, PIM2, and PRISM III, further validating the score as a predictor of mortality.

Mortality prediction in pediatric trauma.

BACKGROUND: In trauma research, accurate estimates of mortality that can be rapidly calculated prior to enrollment are essential to ensure appropriate patient selection and adequate sample size. This study compares the accuracy of the BIG (Base Deficit, International normalized ratio and Glasgow Coma scale) score in predicting mortality in pediatric trauma patients to Pediatric Risk of Mortality III (PRISM III) score, Pediatric Index of Mortality 2 (PIM2) score and Pediatric Logistic Organ Dysfunction (PELOD) score. METHODS: Data were collected from Virtual Pediatric Systems (VPS, LLC) database for children between 2004 and 2015 from 149 PICUs. Logistic regression models were developed to evaluate mortality prediction. The Area under the Curve (AUC) of Receiver Operator Characteristic (ROC) curves were derived from these models and compared between scores. RESULTS: A total of 45,377 trauma patients were analyzed. The BIG score could only be calculated for 152 patients (0.33%). PRISM III, PIM2, and PELOD scores were calculated for 44,360, 45,377 and 14,768 patients respectively. The AUC of the BIG score was 0.94 compared to 0.96, 0.97 and 0.93 for the PRISM III, PIM2, and PELOD respectively. CONCLUSIONS: The BIG score is accurate in predicting mortality in pediatric trauma patients. LEVEL OF EVIDENCE: Level I prognosis.

Analysis of HIV testing refusal among patients aged less than 21 years in the Pediatric Emergency Department.

HIV testing in the Pediatric Emergency Department (PED) is a novel concept as adolescents, and young adults, use the PED as point of care or first point of contact with the health care system. Our objective was to study the HIV nontesting data and factors that influenced testing decision among patients receiving care in our PED. We designed a survey that inquired about testing acceptance, reasons for rejection, satisfaction with testing conditions, and understanding of the consequence of HIV test results. We approached 500 patients across all shifts in the PED; for analysis, categorical variables were created using demographic data (race, age, ethnicity, marital status, level of education). Forward conditional binary logistic regression was used to explore the effect of various independent predictors on HIV testing rejection with the strength of association measured with adjusted odds ratio (OR), and their 95% CIs. We conducted model fitting by plotting residuals, Hosmer and Lemeshow test statistic, and area under the curve completed using predicted probabilities. We used SPSS Version 25™, Microsoft Excel 2016™ for data preparation and analysis. Of the 500 patients approached, 423 (84.6%) completed the survey, median (interquartile) age of survey participants was 19 (17-20) years, 158 (37.4%) rejected HIV testing, 284 (67.1%) were older than 18 years of age, 200 (47.3%) were males, 154 (36.4%) were white, and 127 (30%) were of Hispanic origin. The most common reason for rejecting HIV was low risk perception declared by 79 (50%) respondents. In multivariate analysis, age <18 years (OR, 3.5; 95% CI, 2.3-5.5, P<0.00) and being Hispanic (OR, 2.5; 95% CI, 1.6-3.8, P<0.00) were significant predictors for respondent nontesting. Hosmer and Lemeshow test was not significant, P=0.42, and area under the curve was 0.67 (95% CI, 0.61-0.76). Respondents, <18 years were more likely to reject HIV testing because of low perception of risk. Program addressing risk perception which emphasizes safe health practices should be developed to reduce HIV transmission.